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} | 2.34375 | stackv2 | # coding=utf-8
from __future__ import division
from __future__ import absolute_import
from __future__ import print_function
import subprocess
from collections import defaultdict
from acsp.com.common import *
from acsp.com.utils import *
class EvaluationResult(object):
"""An object that stores the results output by trec_eval."""
eval_fields = {
"num_q": int,
"num_ret": int,
"num_rel": int,
"num_rel_ret": int,
"map": float,
"Rprec": float,
"bpref": float,
"recip_rank": float,
"P_10": float,
"P_30": float,
"P_100": float}
def __init__(self, rc):
"""Initializes from a file which contains the output from trec_eval."""
self.runid = ""
self.results = {}
self.queries = {}
# with open(filepath, 'r') acsp f:
for line in rc.split('\n'):
if line.strip() == '':
continue
(field, query, value) = line.split()
if query == "all": # accumulated results over all queries
if field == "runid":
self.runid = value
else:
self.parse_field(field, value, self.results)
else: # query is a number
if query not in self.queries:
self.queries[query] = {}
self.parse_field(field, value, self.queries[query])
def parse_field(self, field, value, target):
"""Parses the value of a field and puts it in target[field]."""
field_types = self.__class__.eval_fields
if field in field_types:
target[field] = field_types[field](value) # convert str type to target type
else:
pass
def get_total_measure_score(self, field):
"""Get average measure for all queries."""
return self.results[field]
def get_measure_score_by_query(self, field, query):
"""
Get measure by query.
"""
if query in self.queries.keys():
return self.queries[query].get(field, 0)
else:
return 0
class TrecEval(object):
"""Wrapper of trec_eval."""
def __init__(self, trec_name):
self.dict_answer = self.calculate_metrics(trec_name=trec_name)
@staticmethod
def trec_eval(path_qrels_file, path_query_rt_file, path_trec_eval=TREC_EVAL_EXCUTE):
"""Call trec_eval via subprocess."""
# call trec_eval in command
pipe = subprocess.Popen([path_trec_eval, '-q', path_qrels_file, path_query_rt_file], stdout=subprocess.PIPE)
try:
stdout, stderr = pipe.communicate()
except subprocess.CalledProcessError as e:
raise e
# format result
rc_str = stdout.decode()
eval_result = EvaluationResult(rc_str)
return eval_result
def calculate_metrics(self, trec_name):
"""Calculate rel doc, rel doc, total doc, ap, rp, p30, rr, rbp, bpref."""
# qrel
rel_dir = os.path.join(DATA_DIR, trec_name, DICT_TREC_TYPE[trec_name][1])
path_qrels_file = os.path.join(rel_dir, get_file_ids(rel_dir)[0])
# system run
sysrun_dir = os.path.join(DATA_DIR, trec_name, DICT_TREC_TYPE[trec_name][0])
file_ids = get_file_ids(sysrun_dir)
# get (r, ap, rp) for all topics and system runs
dict_answer = defaultdict(dict)
for run_id in file_ids:
path_query_rt_file = os.path.join(sysrun_dir, run_id)
eval_result = self.trec_eval(path_qrels_file=path_qrels_file, path_query_rt_file=path_query_rt_file)
# per topic
for topic_id in eval_result.queries.keys():
r = eval_result.get_measure_score_by_query('num_rel', topic_id)
t = eval_result.get_measure_score_by_query('num_ret', topic_id)
ap = eval_result.get_measure_score_by_query('map', topic_id)
rp = eval_result.get_measure_score_by_query('Rprec', topic_id)
p30 = eval_result.get_measure_score_by_query('P_30', topic_id)
dcg = 0 # stub
rr = eval_result.get_measure_score_by_query('recip_rank', topic_id)
bpref = eval_result.get_measure_score_by_query('bpref', topic_id)
dict_answer[run_id.strip()][topic_id.strip()] = (r, r, t, ap, rp, p30, dcg, rr, 0, bpref)
# all
total_r = eval_result.get_total_measure_score('num_rel')
total_t = eval_result.get_total_measure_score('num_ret')
total_ap = eval_result.get_total_measure_score('map')
total_rp = eval_result.get_total_measure_score('Rprec')
total_p30 = eval_result.get_total_measure_score('P_30')
total_dcg = 0 # stub
total_rr = eval_result.get_total_measure_score('recip_rank')
total_bpref = eval_result.get_total_measure_score('bpref')
dict_answer[run_id.strip()]['all_topics'] = (total_r, total_r, total_t, total_ap, total_rp, total_p30, total_dcg,
total_rr, total_bpref)
return dict_answer
def get_answer(self, topic_id, list_sysrun_name):
"""Test. The result can be compared with that of Preprocess."""
list_answer = []
for run_id in list_sysrun_name:
list_answer.append(self.dict_answer[run_id.strip()][topic_id.strip()])
return list_answer
def get_system_answer(self):
"""Test. The result can be compared with the published results in TREC overview papers."""
print('system (R, AP, RP) ')
for key in self.dict_answer.keys():
print('{} {} '.format(key, self.dict_answer[key]['all_topics']))
return
if __name__ == '__main__':
pass
| 169 | 33.55 | 125 | 17 | 1,361 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_cc5d4134f5a31f6f_bc0fff64", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 90, "line_end": 90, "column_start": 16, "column_end": 117, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmprvd6_wj2/cc5d4134f5a31f6f.py", "start": {"line": 90, "col": 16, "offset": 2506}, "end": {"line": 90, "col": 117, "offset": 2607}, "extra": {"message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
90
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90
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16
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117
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"A01:2017 - Injection"
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"Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | trec_eval.py | /acsp/pre/trec_eval.py | mdmustafizurrahman/activesampling | MIT | |
2024-11-18T20:31:22.109371+00:00 | 1,686,028,601,000 | b4c99ac535b7af97f2b23aa02895128c857403ed | 3 | {
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} | 2.625 | stackv2 | import cma as cm
from lppls.lppls import LPPLS
# import multiprocessing as mp
import numpy as np
from scipy.stats import chisquare
class LPPLSCMAES(LPPLS):
def __init__(self, observations):
super().__init__(observations)
self.observations = observations
def fun_restricted(self, x, obs):
"""
Define the objective function for the CMA-ES optimizer
Args:
x (List): objective variable
obs (): blah
Returns:
float: error of the objective function
"""
tc, m, w = x
try:
rM = super().matrix_equation(obs, tc, m, w)
a, b, c1, c2 = rM[:, 0].tolist()
except Exception as e:
a, b, c1, c2 = 0, 0, 0, 0
print(e)
t = obs[0, :]
res = super().lppls(t, tc, m, w, a, b, c1, c2)
# make nan or inf to zero
res[np.isnan(res)] = 0.
res[np.isinf(res)] = 0.
# calculate the chi square
error, _ = chisquare(f_obs=res, f_exp=obs[1, :])
return error
def fit(self, max_iteration=1000, factor_sigma=0.1, pop_size=1, obs=None):
"""
Runs the optimazation loop
Args:
max_iteration (int, optional): maximum number of iterations. Defaults to 2500.
factor_sigma (float, optiona): factor to multiplying the range of the bounded values
pop_size (int, optional): population size for CMA ES
cores (int, optional): number of parallel runs
obs ():
Returns:
[List]: all optimized and calculated values for tc, m, w, a, b, c, c1, c2
"""
if obs is None:
obs = self.observations
# best guess of the starting values
m = 0.5
w = 9.
# INFO: so far as I've understand the tc time this cannot be smaller als the max time of the time series
tc = np.max(obs[0, :])
# define options for CMAES
opts = cm.CMAOptions()
# here we define the initial search steps for CMAES usually I use to calculate the range of the
# max and min bounds of the value and then apply a factor for sigma
opts.set('CMA_stds', [factor_sigma * tc, factor_sigma * (0.9 - 0.1), factor_sigma * (13. - 6.)])
opts.set('bounds', [(tc, 0.1, 6.), (np.inf, 0.9, 13.)])
opts.set('popsize', 10 * 2 ** pop_size)
es = cm.CMAEvolutionStrategy(x0=[tc, m, w], sigma0=1., inopts=opts)
# here we go
while not es.stop() and es.countiter <= max_iteration:
solutions = es.ask()
solution = [self.fun_restricted(s, obs) for s in solutions]
es.tell(solutions, solution)
es.logger.add() # write data to disc to be plotted
es.disp()
# after while loop print infos and plot the final
# es.result_pretty()
# cm.plot()
# plt.savefig('cmaes.png', dpi=300)
# get best results
t1 = obs[0, 0]
t2 = obs[0, -1]
if es.result.xbest is not None:
tc, m, w = es.result.xbest
try:
rM = super().matrix_equation(obs, tc, m, w)
a, b, c1, c2 = rM[:, 0].tolist()
except Exception as e:
a, b, c1, c2 = 0, 0, 0, 0
print(e)
c = self.get_c(c1, c2)
# Use sklearn format for storing fit params -> original code from lppls package
for coef in ['tc', 'm', 'w', 'a', 'b', 'c', 'c1', 'c2']:
self.coef_[coef] = eval(coef)
O = self.get_oscillations(w, tc, t1, t2)
D = self.get_damping(m, w, b, c)
return tc, m, w, a, b, c, c1, c2, O, D
else:
return 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
| 115 | 31.96 | 112 | 16 | 1,088 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_d95149cdc75c43c9_1d20d8b8", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 108, "line_end": 108, "column_start": 36, "column_end": 46, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmprvd6_wj2/d95149cdc75c43c9.py", "start": {"line": 108, "col": 36, "offset": 3566}, "end": {"line": 108, "col": 46, "offset": 3576}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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"security"
] | [
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] | [
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] | [
5
] | [
"LOW"
] | [
"HIGH"
] | lppls_cmaes.py | /lppls/lppls_cmaes.py | Boulder-Investment-Technologies/lppls | MIT | |
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} | 2.390625 | stackv2 | #Copyright 2015 Daniel Gusenleitner, Stefano Monti
#Licensed under the Apache License, Version 2.0 (the "License");
#you may not use this file except in compliance with the License.
#You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#Unless required by applicable law or agreed to in writing, software
#distributed under the License is distributed on an "AS IS" BASIS,
#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#See the License for the specific language governing permissions and
#limitations under the License.
"""Star module
This module contains functions for initializing all tophat specific variables and
a wrapper that that runs tophat using those parameters on a single sample.
"""
import subprocess
import os
import sys
from hydra_pkg import module_helper as MODULE_HELPER
def init(param):
"""Initialization function that checks the all relevant tophat parameters
:Parameter param: dictionary that contains all general RNASeq pipeline parameters
"""
MODULE_HELPER.check_parameter(param, key='star_exec', dtype=str)
MODULE_HELPER.check_parameter(param, key='star_index', dtype=str, checkfile=True)
MODULE_HELPER.check_parameter(param, key='outFilterType', dtype=str)
MODULE_HELPER.check_parameter(param, key='outFilterMultimapNmax', dtype=str)
MODULE_HELPER.check_parameter(param, key='alignSJoverhangMin', dtype=str)
MODULE_HELPER.check_parameter(param, key='alignSJDBoverhangMin', dtype=str)
MODULE_HELPER.check_parameter(param, key='outFilterMismatchNmax', dtype=str)
MODULE_HELPER.check_parameter(param, key='outFilterMismatchNoverLmax', dtype=str)
MODULE_HELPER.check_parameter(param, key='alignIntronMin', dtype=str)
MODULE_HELPER.check_parameter(param, key='alignIntronMax', dtype=str)
MODULE_HELPER.check_parameter(param, key='alignMatesGapMax', dtype=str)
MODULE_HELPER.check_parameter(param,
key='outputSAMtype',
allowed=['BAM_SortedByCoordinate',
'BAM_unsorted'],
dtype=str)
def main():
"""Main function that is run on each samples, which in turn calls runs
star on a sample.
"""
param = MODULE_HELPER.initialize_module()
#run create output directory
outdir = param['module_dir']+param['outstub']+'/'
if not os.path.exists(outdir):
os.makedirs(outdir)
#build tophat call:
call = [param['star_exec']]
#add the directory where we built the star index
call.append('--genomeDir')
call.append(param['star_index'])
#add the number of processors to use
call.append('runThreadN')
call.append(param['num_processors'])
#add all the optional parameters
call.append('--outFilterType')
call.append(param['outFilterType'])
call.append('--outFilterMultimapNmax')
call.append(param['outFilterMultimapNmax'])
call.append('--alignSJoverhangMin')
call.append(param['alignSJoverhangMin'])
call.append('--alignSJDBoverhangMin')
call.append(param['alignSJDBoverhangMin'])
call.append('--outFilterMismatchNmax')
call.append(param['outFilterMismatchNmax'])
call.append('--outFilterMismatchNoverLmax')
call.append(param['outFilterMismatchNoverLmax'])
call.append('--alignIntronMin')
call.append(param['alignIntronMin'])
call.append('--alignIntronMax')
call.append(param['alignIntronMax'])
call.append('--alignMatesGapMax')
call.append(param['alignMatesGapMax'])
if (param['outputSAMtype'] == 'BAM_SortedByCoordinate'):
call.append('--outSAMtype')
call.append('BAM')
call.append('SortedByCoordinate')
outfile = 'Aligned.sortedByCoord.out.bam'
elif (param['outputSAMtype'] == 'BAM_unsorted'):
call.append('--outSAMtype')
call.append('BAM')
call.append('Unsorted')
outfile = 'Aligned.out.bam'
else:
outfile = 'Aligned.out.sam'
#add the proper output directories
call.append('--outFileNamePrefix')
call.append(outdir)
#specify whether the fastq files are zipped
if param['zipped_fastq']:
call.append('--readFilesCommand')
call.append('gunzip')
call.append('-c')
#adding the files we want to work on
call.append('--readFilesIn')
call.append(param['working_file'])
#if paired add second working file
if param['paired']:
call.append(param['working_file2'])
param['file_handle'].write('CALL: '+' '.join(call)+'\n')
output, error = subprocess.Popen(call,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE).communicate()
param['file_handle'].write(error)
param['file_handle'].write(output)
#check if the run was successful
if not os.path.exists(outdir+'SJ.out.tab'):
param['file_handle'].write('Star did not run successfully...')
sys.exit(0)
#wrap up and return the current workingfile
MODULE_HELPER.wrapup_module(param,
[outdir+outfile],
remove_intermediate=True)
| 137 | 37.16 | 85 | 12 | 1,158 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_6261fd10505a932f_6cf27600", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 118, "line_end": 120, "column_start": 21, "column_end": 61, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmprvd6_wj2/6261fd10505a932f.py", "start": {"line": 118, "col": 21, "offset": 4614}, "end": {"line": 120, "col": 61, "offset": 4758}, "extra": {"message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
118
] | [
120
] | [
21
] | [
61
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | star.py | /build/lib/hydra_pkg/star.py | tetomonti/Hydra | Apache-2.0 | |
2024-11-18T20:31:23.163522+00:00 | 1,520,533,770,000 | 6d1f8ebe4cd288a0c0f33a60f17c7f08cdac28d6 | 2 | {
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"visit_date": "2021-09-08T08:32:45.392875"
} | 2.5 | stackv2 | import json
import os.path
import pickle
from pythiam.lib.iam_manager import IAMManager
from pythiam.lib.utils import file_age
class UserRecordManager(object):
def __init__(self, *args, **kwargs):
self._client = None
self._filename = kwargs.get('filename') or 'data.db'
self._iam = None
self._records = {}
def with_file(self, filename):
self._filename = filename
self.load_data()
return self
def with_iam(self, iam):
self._iam = iam
return self
@property
def filename(self):
return self._filename
@property
def iam(self):
if self._iam is None:
self._iam = IAMManager()
return self._iam
@property
def records(self):
return self._records
@records.setter
def records(self, value):
self._records = value
def create_user_record(self, user_name, data):
record = UserRecord(user_name)
self._set_iam_data(record, data)
self._set_user_access_keys(record)
self._set_user_groups(record)
self._set_login_profile(record)
self._set_inline_policies(record)
self._set_attached_policies(record)
self._set_mfa_devices(record)
self.records[user_name] = record
self.write_record_to_disk(record)
return record
def delete_user_record(self, user_name):
new_records = dict(self.records)
del new_records[user_name]
self.records = new_records
self.write_all_records_to_disk()
def get_user_record(self, user_name):
record = self._records.get(user_name)
if record is None:
print("User account {} not found in data file".format(user_name))
print("Looking up account in IAM")
user_data = self.iam.get_user(user_name)
if not user_data:
print("... not found in IAM")
else:
record = self.create_user_record(user_name, user_data)
return record
def load_data(self):
if not os.path.exists(self.filename):
print("User record data file not found. Creating new file: {}".format(self.filename))
with open(self.filename, 'wb') as f:
for u in self.iam.list_users():
n = u.get('UserName')
print("Processing record: {}".format(n))
r = self.create_user_record(n, u)
self.write_record_to_disk(r)
if file_age(self.filename) > 2:
print("Data file is more than 2 days old, consider refreshing.")
with open(self.filename, 'rb') as f:
while True:
try:
r = pickle.load(f)
assert isinstance(r, UserRecord)
self.records[r.user_name] = r
except EOFError:
break
def write_all_records_to_disk(self):
# replace data file with contents of new_records
with open(self.filename, 'wb') as f:
f.truncate()
with open(self.filename, 'ab') as f:
for k in self.records.keys():
pickle.dump(self.records[k], f)
def write_record_to_disk(self, record):
with open(self.filename, 'ab') as f:
pickle.dump(record, f)
@staticmethod
def _set_iam_data(record, data):
"""
{
Path: /,
UserName: str,
UserId: str,
Arn: str,
CreateDate: datetime,
PasswordLastUsed: datetime
}
"""
record.iam_data = data
def _set_login_profile(self, record):
record.login_profile = self.iam.get_login_profile(record.user_name)
def _set_attached_policies(self, record):
for p in self.iam.list_attached_policies(record.user_name):
record.attached_policies.append(p.get('PolicyArn'))
def _set_inline_policies(self, record):
for p in self.iam.list_user_policies(record.user_name):
record.inline_policies.append(p)
def _set_user_access_keys(self, record):
for k in self.iam.list_access_keys(record.user_name):
key_id = k.get('AccessKeyId')
record.access_keys[key_id] = self.iam.get_access_key_last_used(key_id)
def _set_user_groups(self, record):
for g in self.iam.list_groups_for_user(record.user_name):
record.groups.append(g.get('GroupName'))
def _set_mfa_devices(self, record):
for m in self.iam.list_mfa_devices(record.user_name):
record.mfa_devices.append(m.get('SerialNumber'))
class UserRecord(object):
def __init__(self, user_name):
self._access_keys = {}
self._attached_policies = []
self._groups = []
self._iam_data = {}
self._inline_policies = []
self._login_profile = {}
self._mfa_devices = []
self._user_name = user_name
def __repr__(self):
return json.dumps(self.__dict__, default=str)
@property
def access_keys(self):
return self._access_keys
@property
def arn(self):
return self._iam_data.get('Arn')
@property
def attached_policies(self):
return self._attached_policies
@property
def creation_date(self):
return self._iam_data.get('CreateDate')
@property
def groups(self):
return self._groups
@property
def iam_data(self):
return self._iam_data
@iam_data.setter
def iam_data(self, value):
self._iam_data = value
@property
def inline_policies(self):
return self._inline_policies
@property
def login_profile(self):
return self._login_profile
@login_profile.setter
def login_profile(self, value):
self._login_profile = value
@property
def mfa_devices(self):
return self._mfa_devices
@property
def password_last_used(self):
return self._iam_data.get('PasswordLastUsed')
@property
def user_groups(self):
return self._groups
@property
def user_id(self):
return self._iam_data.get('UserId')
@property
def user_name(self):
return self._user_name
@property
def last_activity(self):
events = list()
# add account creation date
events.append(self.iam_data.get('CreateDate'))
# last password usage
d = self.password_last_used
if d:
events.append(self.password_last_used)
# last access key usage
for k in self.access_keys:
d = self.access_keys.get(k).get('LastUsedDate')
if d:
events.append(d)
# return most recent
events = sorted(events, reverse=True)
return events[0]
| 240 | 27.49 | 97 | 18 | 1,502 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_46578dda894ca21b_89cdebfc", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. 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"MEDIUM",
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] | user_record.py | /pythiam/lib/user_record.py | rsutton/pythiam | Apache-2.0 | |
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} | 2.78125 | stackv2 | import csv
import psycopg2
import secrets
def parse(filename, tableName):
conn = psycopg2.connect("dbname=gardnly2 user=cqlanus password=" + secrets.password)
cur = conn.cursor()
with open(filename, 'rt') as csvfile:
rows = csv.reader(csvfile, delimiter=' ')
for row in rows:
rowStr = ', '.join(row)
formattedRow = rowStr.replace(' ,', '').split(', ')
stationId = formattedRow[0]
wpan = stationId[6:];
onlyTemps = formattedRow[2:]
tempNums = list(map(parseTemp, onlyTemps))
month = int(formattedRow[1])
data = {'stationId': formattedRow[0], 'month': int(formattedRow[1]), 'days': tempNums}
print(data)
cur.execute("INSERT INTO " + tableName + " (station_id, wpan, month, days) VALUES (%s, %s, %s, %s)",
(stationId, wpan, month, tempNums))
conn.commit()
cur.close()
conn.close()
def parseTemp(temp):
if len(temp) == 4:
return float(temp[0:2] + '.' + temp[2])
elif len(temp) == 5 and temp[0].isdigit():
return float(temp[0:3] + '.' + temp[3])
parse('../data/dly-tmax-normal.csv','daily_max_temps')
parse('../data/dly-tmin-normal.csv', 'daily_min_temps')
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"CWE-89"
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"rules.python.lang.security.audit.sqli.psycopg-sqli",
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query"
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"security"
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"LOW"
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"MEDIUM",
"HIGH"
] | [
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22
] | [
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23
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13
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5,
7.5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | temp_parsing.py | /src/temp_parsing.py | cqlanus/weather_parsing | MIT | |
2024-11-18T20:31:34.655620+00:00 | 1,572,898,414,000 | 6884ba0c104fd259454a6aa728cef1775f03dccc | 3 | {
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"visit_date": "2020-04-28T06:31:33.907456"
} | 2.78125 | stackv2 | from optparse import OptionParser
import os
def getOptions():
parser = OptionParser()
parser.add_option("--f", dest = "infile",
help = "Input GTF file of genomic transcripts", metavar = "FILE", type = "string")
parser.add_option("--e", dest = "exons",
help = "Input BED file of final exons", metavar = "FILE", type = "string")
parser.add_option("--p", dest = "prefix", help = "Prefix for intermediate files",
metavar = "FILE", type = "string")
(options, args) = parser.parse_args()
return options
def main():
options = getOptions()
infile = options.infile
exons = options.exons
bed = options.prefix + "genomic.bed"
# Get genomic transcripts in BED format
cmd = """awk -v OFS='\t' '{if($3 == "transcript") print $1,$4-1,$5,".",".",$7}' """ + infile + " > " + bed
os.system(cmd)
# Bedtools intersect it
btools_out = options.prefix + "nGenomic_intersect_lastExons.bed"
bedtools_cmd = """bedtools intersect -a %s \
-b %s \
-u \
-s | wc -l > %s""" % (bed, exons, btools_out)
os.system(bedtools_cmd)
# Now, collect the results for output
with open(btools_out) as f:
overlap_size = int(f.readline().strip())
total_genomic = sum(1 for line in open(bed))
percent_overlap = round(overlap_size*100./total_genomic)
print("\t".join([options.prefix, str(overlap_size), str(total_genomic), str(percent_overlap) + "%"]))
if __name__ == '__main__':
main()
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"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-system-call-audit",
"rules.python.lang.security.audit.dangerous-system-call-audit"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | [
26,
34
] | [
26,
34
] | [
5,
5
] | [
19,
28
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"A01:2017 - Injection"
] | [
"Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.",
"Found dynamic conte... | [
7.5,
7.5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | print_genomic_in_final_exons.py | /genomic_transcripts/last_exons/print_genomic_in_final_exons.py | dewyman/TALON-paper-2019 | MIT | |
2024-11-18T20:31:34.760539+00:00 | 1,632,480,663,000 | 25b301235480ca549e84db76d06f96130eb476a9 | 2 | {
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} | 2.375 | stackv2 | # -*- coding: utf-8 -*-
"""
:author: Cao YongChao
:mail: cyckun@aliyun.com
:copyright: © 2020 Cao YongChao
:license: MIT, see LICENSE for more details.
"""
from __future__ import print_function
import pyopenabe
from xmlrpc.server import SimpleXMLRPCServer
# 调用函数
def respon_string(str):
return "get string:%s"%str
class cpabe():
def __init__(self):
self.openabe = pyopenabe.PyOpenABE()
self.cpabe = self.openabe.CreateABEContext("CP-ABE")
self.cpabe.generateParams()
def enc(self, message, policy):
print("enc service is called.")
ct = self.cpabe.encrypt(policy, message.data)
return ct
def dec(self, ct, username):
key_path = "./keys/" + username + "_sk.txt"
with open(key_path, "rb") as f:
sk = f.read()
f.close()
self.cpabe.importUserKey(username, sk)
print("ddkdk, ", type(ct), type(username))
try:
pt = self.cpabe.decrypt(username, ct.data) # 解析返回错误，高优
print("service dec pt =", pt)
if pt == 0 or len(pt) < 2:
return b"DEC FAIL"
return pt
except Exception as e:
print(e)
return b"DEC FAIL0"
def generate_userkey(self, username, userattri):
try:
self.cpabe.keygen(userattri, username)
except:
return "GENKEY FAIL"
uk = self.cpabe.exportUserKey(username)
# should write to db;
filepath = "./keys/" + username + "_sk.txt"
with open(filepath, 'wb') as f:
f.write(uk)
f.close()
return uk
if __name__ == '__main__':
server = SimpleXMLRPCServer(('localhost', 8888)) # 初始化
server.register_function(respon_string, "get_string") # 注册函数
alg = cpabe()
server.register_function(alg.enc, "cpabe_enc_cli")
server.register_function(alg.dec, "cpabe_dec_cli")
server.register_function(alg.generate_userkey, "cpabe_usrkey")
print ("Listening for Client")
server.serve_forever() # 保持等待调用状态
| 71 | 28.14 | 68 | 13 | 546 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xmlrpc_261ae6209b3c3457_c9e8a458", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xmlrpc", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected use of xmlrpc. xmlrpc is not inherently safe from vulnerabilities. Use defusedxml.xmlrpc instead.", "remediation": "", "location": {"file_path": "unknown", "line_start": 11, "line_end": 11, "column_start": 1, "column_end": 45, "code_snippet": "requires login"}, "cwe_id": "CWE-776: Improper Restriction of Recursive Entity References in DTDs ('XML Entity Expansion')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A04:2017 - XML External Entities (XXE)", "references": [{"url": "https://pypi.org/project/defusedxml/", "title": null}, {"url": "https://docs.python.org/3/library/xml.html#xml-vulnerabilities", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.use-defused-xmlrpc", "path": "/tmp/tmprvd6_wj2/261ae6209b3c3457.py", "start": {"line": 11, "col": 1, "offset": 229}, "end": {"line": 11, "col": 45, "offset": 273}, "extra": {"message": "Detected use of xmlrpc. xmlrpc is not inherently safe from vulnerabilities. Use defusedxml.xmlrpc instead.", "metadata": {"cwe": ["CWE-776: Improper Restriction of Recursive Entity References in DTDs ('XML Entity Expansion')"], "owasp": ["A04:2017 - XML External Entities (XXE)", "A05:2021 - Security Misconfiguration", "A02:2025 - Security Misconfiguration"], "source-rule-url": "https://github.com/PyCQA/bandit/blob/07f84cb5f5e7c1055e6feaa0fe93afa471de0ac3/bandit/blacklists/imports.py#L160", "references": ["https://pypi.org/project/defusedxml/", "https://docs.python.org/3/library/xml.html#xml-vulnerabilities"], "category": "security", "technology": ["python"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-776"
] | [
"rules.python.lang.security.use-defused-xmlrpc"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
11
] | [
11
] | [
1
] | [
45
] | [
"A04:2017 - XML External Entities (XXE)"
] | [
"Detected use of xmlrpc. xmlrpc is not inherently safe from vulnerabilities. Use defusedxml.xmlrpc instead."
] | [
7.5
] | [
"LOW"
] | [
"MEDIUM"
] | rpc_server.py | /rpc_server.py | cyckun/abe_enc_server | MIT | |
2024-11-18T20:31:34.967467+00:00 | 1,589,080,113,000 | ed759e5a170ed24f2716df3e22862840ea335725 | 3 | {
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"visit_date": "2021-04-20T07:05:06.037395"
} | 2.640625 | stackv2 | import glob
import tensorflow as tf
import sys
import os
import pandas as pd
import shutil
import xml.etree.ElementTree as ET
FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_string('dir1', None, 'first folder')
tf.app.flags.DEFINE_string('dir2', None, '2nd folder')
tf.app.flags.DEFINE_string('annotation_out', 'annotation_out', 'Merged Annotation output folder')
def main(unused_argv):
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.DEBUG)
dir1 = FLAGS.dir1
dir2 = FLAGS.dir2
dest_dir = FLAGS.annotation_out
if dir1 is None or dir2 is None:
tf.compat.v1.logging.warn('Please provides 2 folders for merging. Output folder is annotation_out by default.')
tf.compat.v1.logging.warn('--dir1=dir1 --dir2=dir2')
sys.exit(0)
dir1_files = glob.glob(os.path.join(dir1,'**', '*.xml'), recursive=True)
dir2_files = glob.glob(os.path.join(dir2, '**', '*.xml'), recursive=True)
## copying no matching files to annotation dir first
dir1_set = build_set(dir1_files, dir1)
dir2_set = build_set(dir2_files, dir2)
os.makedirs(dest_dir, exist_ok=True)
copy_files_no_matching(dir1_set, dir2_set, dir1, dest_dir )
copy_files_no_matching(dir2_set, dir1_set, dir2, dest_dir )
matched_set = dir1_set.intersection(dir2_set)
for f in matched_set:
tree = ET.parse(dir2+f)
objects = tree.findall('object')
first_tree = ET.parse(dir1+f)
for o in objects:
first_tree.getroot().append(o)
first_tree.write(dest_dir+f)
tf.logging.debug('Merged to %s', dest_dir+f)
tf.logging.debug(' == END ==')
def copy_files_no_matching(dir1_set, dir2_set, dir, dest_dir):
files_excluded = dir1_set.difference(dir2_set)
for f in files_excluded:
tf.logging.debug('copied to %s',dest_dir+f)
shutil.copyfile(dir+f, dest_dir+f)
def build_set(dir1_files, dir1):
df = pd.DataFrame(dir1_files, columns=['name'])
df['name']=df['name'].str.replace(dir1,'')
name_set = set(df['name'])
return name_set
if __name__ == '__main__':
main(sys.argv)
| 78 | 26.26 | 119 | 13 | 554 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_da98e211732432a8_4080c3a0", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "remediation": "", "location": {"file_path": "unknown", "line_start": 7, "line_end": 7, "column_start": 1, "column_end": 35, "code_snippet": "requires login"}, "cwe_id": "CWE-611: Improper Restriction of XML External Entity Reference", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A04:2017 - XML External Entities (XXE)", "references": [{"url": "https://docs.python.org/3/library/xml.html", "title": null}, {"url": "https://github.com/tiran/defusedxml", "title": null}, {"url": "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.use-defused-xml", "path": "/tmp/tmprvd6_wj2/da98e211732432a8.py", "start": {"line": 7, "col": 1, "offset": 91}, "end": {"line": 7, "col": 35, "offset": 125}, "extra": {"message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. 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These attacks can leak confidential data and \"XML bombs\" can cause denial of service. Do not use this library to parse untrusted input. 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"CWE-611",
"CWE-611",
"CWE-611"
] | [
"rules.python.lang.security.use-defused-xml",
"rules.python.lang.security.use-defused-xml-parse",
"rules.python.lang.security.use-defused-xml-parse"
] | [
"security",
"security",
"security"
] | [
"LOW",
"MEDIUM",
"MEDIUM"
] | [
"HIGH",
"HIGH",
"HIGH"
] | [
7,
50,
53
] | [
7,
50,
53
] | [
1,
16,
22
] | [
35,
32,
38
] | [
"A04:2017 - XML External Entities (XXE)",
"A04:2017 - XML External Entities (XXE)",
"A04:2017 - XML External Entities (XXE)"
] | [
"The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.",
"The native Python `xml` library is vulnerable to XML Exter... | [
7.5,
7.5,
7.5
] | [
"LOW",
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM",
"MEDIUM"
] | safety_merge_annotations.py | /research/object_detection/dataset_tools/safety_merge_annotations.py | tealeeseng/models | Apache-2.0 | |
2024-11-18T20:31:37.551815+00:00 | 1,535,791,374,000 | b0f18afde1a0cec1f4c7614e4dbb302189895c4e | 3 | {
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"src_encoding": "UTF-8",
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"visit_date": "2020-03-27T19:20:09.514263"
} | 2.796875 | stackv2 | # coding:utf8
"""
下载器模块
1.根据请求对象，发送请求，获取相应数据，封装为Reponse对象返回
"""
import requests
from ..http.response import Response
class DownLoader(object):
def get_response(self, request):
if request.method.upper() == "GET":
res = requests.get(request.url,headers=request.headers,params=request.params,cookies=request.cookies)
elif request.method.upper() == "POST":
res = requests.post(request.url,headers=request.headers, cookies=request.cookies)
else:
raise Exception('暂时只支持GET和POST请求')
return Response(res.url,res.status_code,res.headers, res.content)
| 25 | 23.92 | 113 | 15 | 138 | python | [{"finding_id": "semgrep_rules.python.django.security.injection.ssrf.ssrf-injection-requests_b23c93ef9acb2344_7775a4a0", "tool_name": "semgrep", "rule_id": "rules.python.django.security.injection.ssrf.ssrf-injection-requests", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Data from request object is passed to a new server-side request. This could lead to a server-side request forgery (SSRF). To mitigate, ensure that schemes and hosts are validated against an allowlist, do not forward the response to the user, and ensure proper authentication and transport-layer security in the proxied request. 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See https://owasp.org/www-community/attacks/Server_Side_Request_Forgery to learn more about SSRF vulnerabilities.", "metadata": {"cwe": ["CWE-918: Server-Side Request Forgery (SSRF)"], "owasp": ["A10:2021 - Server-Side Request Forgery (SSRF)", "A01:2025 - Broken Access Control"], "references": ["https://owasp.org/www-community/attacks/Server_Side_Request_Forgery"], "category": "security", "technology": ["django"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["vuln"], "likelihood": "MEDIUM", "impact": "HIGH", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.requests.best-practice.use-raise-for-status_b23c93ef9acb2344_06f91c73", "tool_name": "semgrep", "rule_id": "rules.python.requests.best-practice.use-raise-for-status", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "There's an HTTP request made with requests, but the raise_for_status() utility method isn't used. 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This can result in request errors going unnoticed and your code behaving in unexpected ways, such as if your authorization API returns a 500 error while you're only checking for a 401.", "metadata": {"references": ["https://requests.readthedocs.io/en/master/api/#requests.Response.raise_for_status"], "category": "best-practice", "technology": ["requests"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.requests.best-practice.use-timeout_b23c93ef9acb2344_8b7a6e32", "tool_name": "semgrep", "rule_id": "rules.python.requests.best-practice.use-timeout", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Detected a 'requests' call without a timeout set. By default, 'requests' calls wait until the connection is closed. This means a 'requests' call without a timeout will hang the program if a response is never received. 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See https://owasp.org/www-community/attacks/Server_Side_Request_Forgery to learn more about SSRF vulnerabilities.", "metadata": {"cwe": ["CWE-918: Server-Side Request Forgery (SSRF)"], "owasp": ["A10:2021 - Server-Side Request Forgery (SSRF)", "A01:2025 - Broken Access Control"], "references": ["https://owasp.org/www-community/attacks/Server_Side_Request_Forgery"], "category": "security", "technology": ["django"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["vuln"], "likelihood": "MEDIUM", "impact": "HIGH", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.django.security.injection.ssrf.ssrf-injection-requests_b23c93ef9acb2344_e587b4a8", "tool_name": "semgrep", "rule_id": "rules.python.django.security.injection.ssrf.ssrf-injection-requests", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Data from request object is passed to a new server-side request. 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See https://owasp.org/www-community/attacks/Server_Side_Request_Forgery to learn more about SSRF vulnerabilities.", "remediation": "", "location": {"file_path": "unknown", "line_start": 16, "line_end": 16, "column_start": 19, "column_end": 94, "code_snippet": "requires login"}, "cwe_id": "CWE-918: Server-Side Request Forgery (SSRF)", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A10:2021 - Server-Side Request Forgery (SSRF)", "references": [{"url": "https://owasp.org/www-community/attacks/Server_Side_Request_Forgery", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.django.security.injection.ssrf.ssrf-injection-requests", "path": "/tmp/tmprvd6_wj2/b23c93ef9acb2344.py", "start": {"line": 16, "col": 19, "offset": 468}, "end": {"line": 16, "col": 94, "offset": 543}, "extra": {"message": "Data from request object is passed to a new server-side request. 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"CWE-918",
"CWE-918",
"CWE-918",
"CWE-918"
] | [
"rules.python.django.security.injection.ssrf.ssrf-injection-requests",
"rules.python.django.security.injection.ssrf.ssrf-injection-requests",
"rules.python.django.security.injection.ssrf.ssrf-injection-requests",
"rules.python.django.security.injection.ssrf.ssrf-injection-requests"
] | [
"security",
"security",
"security",
"security"
] | [
"MEDIUM",
"MEDIUM",
"MEDIUM",
"MEDIUM"
] | [
"HIGH",
"HIGH",
"HIGH",
"HIGH"
] | [
14,
14,
16,
16
] | [
14,
14,
16,
16
] | [
13,
19,
13,
19
] | [
114,
114,
94,
94
] | [
"A10:2021 - Server-Side Request Forgery (SSRF)",
"A10:2021 - Server-Side Request Forgery (SSRF)",
"A10:2021 - Server-Side Request Forgery (SSRF)",
"A10:2021 - Server-Side Request Forgery (SSRF)"
] | [
"Data from request object is passed to a new server-side request. This could lead to a server-side request forgery (SSRF). To mitigate, ensure that schemes and hosts are validated against an allowlist, do not forward the response to the user, and ensure proper authentication and transport-layer security in the prox... | [
7.5,
7.5,
7.5,
7.5
] | [
"MEDIUM",
"MEDIUM",
"MEDIUM",
"MEDIUM"
] | [
"HIGH",
"HIGH",
"HIGH",
"HIGH"
] | downloader.py | /framework/scrapy_plus/core/downloader.py | Danny2024/scrapy-3.3.3 | MIT | |
2024-11-18T20:43:21.487861+00:00 | 1,431,563,839,000 | 3ae45d7291df1dd0328eefe08e6485532fab7cce | 2 | {
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} | 2.390625 | stackv2 | '''
Copyright (C) 2014 Parrot SA
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in
the documentation and/or other materials provided with the
distribution.
* Neither the name of Parrot nor the names
of its contributors may be used to endorse or promote products
derived from this software without specific prior written
permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
SUCH DAMAGE.
'''
import sys
import subprocess
import os
import inspect
import shutil
import re
# Print a message
def ARPrint(msg, noNewLine=False):
sys.stdout.write(msg)
if not noNewLine:
sys.stdout.write('\n')
# Exit the script with an optional error code
def EXIT(code):
if code != 0:
ARPrint('-- ABORTING --')
sys.exit(code)
# Class to handle 'cd' and 'cd -'
class Chdir:
def __init__(self, newPath, create=True, verbose=True):
self.savedPath = os.getcwd()
if not os.path.exists(newPath) and create:
os.makedirs(newPath)
os.chdir(newPath)
self.verbose = verbose
if verbose:
try:
ARLog('Entering <%(newPath)s>' % locals())
except:
pass
def exit(self):
os.chdir(self.savedPath)
if self.verbose:
try:
ARLog('Returning to <'+self.savedPath+'>')
except:
pass
# Execute a bash command
def ARExecute(cmdline, isShell=True, failOnError=False, printErrorMessage=True):
try:
if printErrorMessage:
ARLog('Running <%(cmdline)s>' % locals())
subprocess.check_call(cmdline, shell=isShell)
return True
except subprocess.CalledProcessError as e:
if printErrorMessage:
ARPrint('Error while running <%(cmdline)s>' % locals())
if failOnError:
EXIT(e.returncode)
else:
return False
# Execute a bash command, and return the stdout output
def ARExecuteGetStdout(args, isShell=False, failOnError=True, printErrorMessage=True):
if printErrorMessage:
ARLog('Running <' + ARListAsBashArg(args) + '>')
p = subprocess.Popen(args, shell=isShell, stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
out, err = p.communicate()
ret = p.wait()
if ret:
if printErrorMessage:
ARLog('Error while running <' + ARListAsBashArg(args) + '>')
if failOnError:
EXIT(ret)
return ''
return out.strip()
# Checks if a given commands exists in path
def ARExistsInPath(program, isShell=True):
try:
subprocess.check_call('which %(program)s 2>/dev/null 1>/dev/null' % locals(), shell=isShell)
return True
except subprocess.CalledProcessError as e:
return False
# Set an environment variable
def ARSetEnv(var, val):
os.environ[var] = val
# Set an environment variable if not currenly defined
# return True if the variable was added
def ARSetEnvIfEmpty(var, val):
if os.environ.get(var) is None:
os.environ[var] = val
return True
return False
# Unset an environment variable
def ARUnsetEnv(var):
if var in os.environ:
os.environ.pop(var)
# Set an environment variable to 'ideal' if it exists in path, else to 'fallback'
def ARSetEnvIfExists(var, ideal, fallback, args=''):
if ARExistsInPath(ideal):
ARSetEnv(var, ideal + ' ' + args)
else:
ARSetEnv(var, fallback + ' ' + args)
# Append a message to a file
def ARAppendToFile(filename, message, doPrint=True):
arfile = open(filename, 'a')
arfile.write(message + '\n')
arfile.close()
if doPrint:
ARPrint(message)
# Log a message(append to the default logfile + output to console)
def ARLog(message):
LOGFILE = os.environ.get('ARLOGF')
if not LOGFILE:
LOGFILE = ARPathFromHere('build.log')
ARAppendToFile(LOGFILE, message)
# Init the default log file
def ARInitLogFile():
LOGFILE = ARPathFromHere('build.log')
ARSetEnv('ARLOGF', LOGFILE)
ARDeleteIfExists(LOGFILE)
# Get the absolute path from a relative path
def ARPathFromHere(path):
MYDIR=os.path.abspath(os.path.dirname(sys.argv[0]))
if '' == MYDIR:
MYDIR=os.getcwd()
return '%(MYDIR)s/%(path)s' % locals()
# Get the absolute path from a relative path
def ARPathFromPwd(path):
MYDIR=os.getcwd()
return '%(MYDIR)s/%(path)s' % locals()
# Transform a python list to a bash args list
def ARListAsBashArg(lst):
return ' '.join(lst)
# Checks if file A is newer than file B
def ARFileIsNewerThan(fileA, fileB):
if not os.path.exists(fileA):
return False
if not os.path.exists(fileB):
return True
return os.stat(fileA).st_mtime > os.stat(fileB).st_mtime
# Called at the beginning of a function to log its start with all its arguments
def StartDumpArgs(**kwargs):
CallerName = inspect.stack()[1][3]
if len(kwargs) > 0:
ARLog('Start running %(CallerName)s with args:' % locals())
else:
ARLog('Start running %(CallerName)s' % locals())
for key, value in kwargs.items():
ARLog(' -- %(key)s -> %(value)s' % locals())
# Called at the end of a function to log its return status and all its arguments
# (use 'return EndDumpArgs(res=True/False, args)')
def EndDumpArgs(res, **kwargs):
CallerName = inspect.stack()[1][3]
START_MSG = 'Finished'
if not res:
START_MSG = 'Error while'
if len(kwargs) > 0:
ARLog('%(START_MSG)s running %(CallerName)s with args:' % locals())
else:
ARLog('%(START_MSG)s running %(CallerName)s' % locals())
for key, value in kwargs.items():
ARLog(' -- %(key)s -> %(value)s' % locals())
return res
# Copy and replace a file
def ARCopyAndReplaceFile(SrcFile, DstFile):
if not os.path.exists(SrcFile):
raise Exception('%(SrcFile)s does not exist' % locals())
if not os.path.exists(os.path.dirname(DstFile)):
os.makedirs(os.path.dirname(DstFile))
shutil.copy2(SrcFile, DstFile)
# Recursive copy and replace of a directory.
# Can optionnaly delete the previous content of the destination directory
# instead of merging
def ARCopyAndReplace(SrcRootDir, DstRootDir, deletePrevious=False):
if not os.path.exists(SrcRootDir):
raise Exception('%(SrcRootDir)s does not exist' % locals())
if deletePrevious:
ARDeleteIfExists(DstRootDir)
shutil.copytree(SrcRootDir, DstRootDir, symlinks=True)
else:
if not os.path.exists(DstRootDir):
os.makedirs(DstRootDir)
for SrcDir, directories, files in os.walk(SrcRootDir):
DstDir = SrcDir.replace(SrcRootDir, DstRootDir)
if not os.path.exists(DstDir):
os.mkdir(DstDir)
for _file in files:
SrcFile = os.path.join(SrcDir, _file)
DstFile = os.path.join(DstDir, _file)
ARDeleteIfExists(DstFile)
shutil.copy2(SrcFile, DstFile)
# Delete one or multiple files/directories
# Do not throw an error if the file/directory does not exists
def ARDeleteIfExists(*args):
for fileOrDir in args:
if os.path.exists(fileOrDir):
if os.path.isdir(fileOrDir):
shutil.rmtree(fileOrDir)
else:
os.remove(fileOrDir)
# Gets the number of available CPUs
# If the real number can not be determined, return 1
def ARGetNumberOfCpus():
try:
import multiprocessing
return multiprocessing.cpu_count()
except (ImportError, NotImplementedError):
pass
return 1
def ARReplaceEnvVars(source):
envMatches = re.findall(r'%\{.*?\}%', source)
for _match in envMatches:
Match = _match.replace('%{', '').replace('}%', '')
try:
EnvMatch = os.environ[Match]
source = source.replace(_match, EnvMatch)
except (KeyError):
ARLog('Environment variable %(Match)s is not set !' % locals())
return None
return source
| 267 | 33.25 | 100 | 16 | 2,185 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_6487f0d636e8e6a5_fe82dd64", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 135, "line_end": 135, "column_start": 14, "column_end": 33, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmprvd6_wj2/6487f0d636e8e6a5.py", "start": {"line": 135, "col": 14, "offset": 4678}, "end": {"line": 135, "col": 33, "offset": 4697}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 4 | true | [
"CWE-78",
"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security",
"security",
"security"
] | [
"LOW",
"LOW",
"LOW"
] | [
"HIGH",
"HIGH",
"HIGH"
] | [
76,
90,
104
] | [
76,
90,
104
] | [
9,
9,
9
] | [
54,
96,
101
] | [
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.",
"Detected subprocess ... | [
7.5,
7.5,
7.5
] | [
"LOW",
"LOW",
"LOW"
] | [
"HIGH",
"HIGH",
"HIGH"
] | ARFuncs.py | /ARDroneSDK3/ARSDKBuildUtils-master/Utils/Python/ARFuncs.py | nericCU/QuadcopterProject | BSD-3-Clause | |
2024-11-18T20:43:23.483418+00:00 | 1,632,633,716,000 | a8a045266aa386a14eafdf0d91a299f0bdb8f843 | 3 | {
"blob_id": "a8a045266aa386a14eafdf0d91a299f0bdb8f843",
"branch_name": "refs/heads/master",
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"detected_licenses": [
"MIT"
],
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"extension": "py",
"filename": "run.py",
"fork_events_count": 1,
"gha_created_at": 1624255416000,
"gha_event_created_at": 1629347153000,
"gha_language": "C++",
"gha_license_id": "MIT",
"github_id": 378823531,
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1750,
"license": "MIT",
"license_type": "permissive",
"path": "/benchmarks/run.py",
"provenance": "stack-edu-0054.json.gz:575222",
"repo_name": "ljcc0930/taichi",
"revision_date": 1632633716000,
"revision_id": "c9b8166d7b019734438232d9b247eb3555e0d6f0",
"snapshot_id": "cfcd0d8b043afe1148022fc56474462d474507e9",
"src_encoding": "UTF-8",
"star_events_count": 2,
"url": "https://raw.githubusercontent.com/ljcc0930/taichi/c9b8166d7b019734438232d9b247eb3555e0d6f0/benchmarks/run.py",
"visit_date": "2023-08-16T21:58:14.811036"
} | 2.5625 | stackv2 | import os
import taichi as ti
def get_benchmark_dir():
return os.path.join(ti.core.get_repo_dir(), 'benchmarks')
class Case:
def __init__(self, name, func):
self.name = name
self.func = func
self.records = {}
def __lt__(self, other):
return self.name < other.name
def __eq__(self, other):
return self.name == other.name
def run(self):
print(f'==> {self.name}:')
os.environ['TI_CURRENT_BENCHMARK'] = self.name
self.func()
class Suite:
def __init__(self, filename):
self.cases = []
print(filename)
self.name = filename[:-3]
loc = {}
exec(f'import {self.name} as suite', {}, loc)
suite = loc['suite']
case_keys = list(
sorted(filter(lambda x: x.startswith('benchmark_'), dir(suite))))
self.cases = [Case(k, getattr(suite, k)) for k in case_keys]
def run(self):
print(f'{self.name}:')
for case in sorted(self.cases):
case.run()
class TaichiBenchmark:
def __init__(self):
self.suites = []
benchmark_dir = get_benchmark_dir()
for f in map(os.path.basename, sorted(os.listdir(benchmark_dir))):
if f != 'run.py' and f.endswith('.py') and f[0] != '_':
self.suites.append(Suite(f))
def run(self):
output_dir = os.environ.get('TI_BENCHMARK_OUTPUT_DIR', '.')
filename = f'{output_dir}/benchmark.yml'
try:
with open(filename, 'r+') as f:
f.truncate() # clear the previous result
except FileNotFoundError:
pass
print("Running...")
for s in self.suites:
s.run()
b = TaichiBenchmark()
b.run()
| 68 | 24.74 | 77 | 18 | 418 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.exec-detected_bfc3723add3e6562_a9b6ec54", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.exec-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 34, "line_end": 34, "column_start": 9, "column_end": 54, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.exec-detected", "path": "/tmp/tmprvd6_wj2/bfc3723add3e6562.py", "start": {"line": 34, "col": 9, "offset": 669}, "end": {"line": 34, "col": 54, "offset": 714}, "extra": {"message": "Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. 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This will cause a runtime error.", "remediation": "", "location": {"file_path": "unknown", "line_start": 37, "line_end": 37, "column_start": 37, "column_end": 63, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.return-in-init", "path": "/tmp/tmprvd6_wj2/bfc3723add3e6562.py", "start": {"line": 37, "col": 37, "offset": 806}, "end": {"line": 37, "col": 63, "offset": 832}, "extra": {"message": "`return` should never appear inside a class __init__ function. This will cause a runtime error.", "metadata": {"category": "correctness", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_bfc3723add3e6562_220a6465", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 58, "line_end": 58, "column_start": 18, "column_end": 38, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmprvd6_wj2/bfc3723add3e6562.py", "start": {"line": 58, "col": 18, "offset": 1504}, "end": {"line": 58, "col": 38, "offset": 1524}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 3 | true | [
"CWE-95"
] | [
"rules.python.lang.security.audit.exec-detected"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
34
] | [
34
] | [
9
] | [
54
] | [
"A03:2021 - Injection"
] | [
"Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources."
] | [
5
] | [
"LOW"
] | [
"HIGH"
] | run.py | /benchmarks/run.py | ljcc0930/taichi | MIT | |
2024-11-18T20:43:27.169363+00:00 | 1,654,066,172,000 | 9cca9498a338bb3cd64b6ddce626016d915791b6 | 3 | {
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"language": "Python",
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"license": "MIT",
"license_type": "permissive",
"path": "/docs/client/http/samples/python/GetTintriDashboard.py",
"provenance": "stack-edu-0054.json.gz:575271",
"repo_name": "Tintri/tintri-rest-api",
"revision_date": 1654066172000,
"revision_id": "b2918838f318e434730b8dedf865a58aefdb7a60",
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"url": "https://raw.githubusercontent.com/Tintri/tintri-rest-api/b2918838f318e434730b8dedf865a58aefdb7a60/docs/client/http/samples/python/GetTintriDashboard.py",
"visit_date": "2022-06-13T22:31:53.477698"
} | 2.703125 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# The code example provided here is for reference only to illustrate
# sample workflows and may not be appropriate for use in actual operating
# environments.
# Support will be provided by Tintri for the Tintri APIs, but theses
# examples are for illustrative purposes only and are not supported.
# Tintri is not responsible for any outcome resulting from the use
# of these scripts.
#
from datetime import date, datetime
import requests
import json
import sys
import time
from prettytable import PrettyTable
"""
This Python script is responsible for getting the Dashboard information (Appliance info and Datastore stats) for
VMstore and showing it on console.
A user can make changes in the configuration section to change the configurations like debug_mode
if debug_mode is set to False; then JSON response won't be printed on console
Command usage: GetTintriDashboard <serverName> <userName> <password>
"""
##### ************** Configurations to be done by end user ************** ########
# For exhaustive messages on console, make it to True; otherwise keep it False
debug_mode = False
##### ************** End of Configuration Section ************** ########
debug_prefix = "[DEBUG] : "
info_prefix = "[INFO] : "
error_prefix = "[ERROR] : "
if len(sys.argv) < 4:
print(error_prefix+"Insufficient parameters passed for getting VMstore Dashboard info.")
print(info_prefix+"COMMAND USAGE : GetTintriDashboard serverName userName password")
sys.exit(-5)
header = "********************************* Tintri Ic. *********************************"
sub_heading = " ------- Get VMstore Dashboard info. ------- "
serverName = sys.argv[1]
userName = sys.argv[2]
password = sys.argv[3]
if debug_mode:
print()
print("Arguments fetched from commandline")
print(debug_prefix+"ServerName fetched : "+serverName)
print(debug_prefix+"UserName fetched : "+userName)
print(debug_prefix+"Password fetched : ********")
print()
# Login to VMstore
#Payload, header and URL for login call
payload = {"newPassword": None, "username": userName, "roles": None, "password": password, "typeId": "com.tintri.api.rest.vcommon.dto.rbac.RestApiCredentials"}
headers = {'content-type': 'application/json'}
urlLogin = 'https://'+serverName+'/api/v310/session/login'
print()
print(header)
print()
print(sub_heading)
print()
print("SERVER NAME : "+serverName)
print()
print("STEP 1: Login to VMstore")
# Debug Logs to console
if debug_mode:
print("\t"+debug_prefix+"Going to make the Login call to server : "+serverName)
print("\t"+debug_prefix+"The URL being used for login is : "+urlLogin)
try:
r = requests.post(urlLogin, json.dumps(payload), headers=headers, verify=False)
except requests.ConnectionError:
print("\t"+error_prefix+"API Connection error occurred")
sys.exit(-1)
except requests.HTTPError:
print("\t"+error_prefix+"HTTP error occurred")
sys.exit(-2)
except requests.Timeout:
print("\t"+error_prefix+"Request timed out")
sys.exit(-3)
except Exception:
print("\t"+error_prefix+"An unexpected error occurred")
sys.exit(-4)
if debug_mode:
print("\t"+debug_prefix+"The HTTP Status code for login call to the server "+serverName + " is: "+str(r.status_code))
# if Http Response is not 200 then raise an exception
if r.status_code is not 200:
print("\t"+error_prefix+"The HTTP response for login call to the server "+serverName+" is not 200")
sys.exit(-6)
# Debug Logs to console
if debug_mode:
print("\t"+debug_prefix+"The Json response of login call to the server "+serverName+" is: "+r.text)
# Fetch SessionId from Cookie
session_id = r.cookies['JSESSIONID']
# Fetch Appliance info from VMStore
print()
print("STEP 2: Fetch and display Appliance info from VMStore")
#Header and URL for getApplianceInfo call
headers = {'content-type': 'application/json','cookie': 'JSESSIONID='+session_id}
urlGetApplianceInfo = 'https://'+serverName+'/api/v310/appliance/default/info'
print("\t"+info_prefix+"Fetching appliance info. by REST request: GET " + urlGetApplianceInfo)
r=requests.get(urlGetApplianceInfo,headers=headers, verify=False)
if debug_mode:
print("\t"+debug_prefix+"The HTTP Status code for getApplianceInfo call to the server "+serverName + " is: "+str(r.status_code))
# if Http Response is not 200 then raise an exception
if r.status_code is not 200:
print("\t"+error_prefix+"The HTTP response for getApplianceInfo call to the server "+serverName+" is not 200")
sys.exit(-6)
if debug_mode:
print("\t"+debug_prefix+"The Json response of getApplianceInfo call to the server "+serverName+" is: "+r.text)
#loads the appliance info result
applianceInfo_result = json.loads(r.text)
print()
#Printing appliance info. in tabular format
header = ['Serial No.', 'Model Name', 'Tintri OS version']
print("\t"+info_prefix+"---------- Appliance Information ----------")
x = PrettyTable(header)
row = [applianceInfo_result["serialNumber"], applianceInfo_result["modelName"], applianceInfo_result["osVersion"]]
x.add_row(row)
print(x)
print()
print("STEP 3: Fetch and display datastore stat from VMstore")
#Header and URL for getDatastoreInfo call
headers = {'content-type': 'application/json','cookie': 'JSESSIONID='+session_id}
urlDatastoreStat = 'https://'+serverName+'/api/v310/datastore/default/statsRealtime'
print("\t"+info_prefix+"Fetching Datastore stat by REST request: GET " + urlDatastoreStat)
r=requests.get(urlDatastoreStat,headers=headers, verify=False)
if debug_mode:
print("\t"+debug_prefix+"The HTTP Status code for getDatastoreStat call to the server "+serverName + " is: "+str(r.status_code))
# if Http Response is not 200 then raise an exception
if r.status_code is not 200:
print("\t"+error_prefix+"The HTTP response for getDatastoreStat call to the server "+serverName+" is not 200")
sys.exit(-6)
if debug_mode:
print("\t"+debug_prefix+"The Json response of getDatastoreStat call to the server "+serverName+" is: "+r.text)
#loads the paginated result for datastore stats
datastoreStat_result = json.loads(r.text)
# get the filteredtotal number of datastore stats
number_of_dsStats=int(datastoreStat_result['filteredTotal'])
print()
#Printing datastore stat in tabular format
if number_of_dsStats > 0:
print()
header = ['Flash hit Ratio (%)', 'Network latency (ms)', 'Storage latency (ms)',
'Disk latency (ms)', 'Host latency (ms)', 'Total latency (ms)',
'Perf. Reserves allocated', 'Space used live Physical (GiB)', 'Space used other (GiB)',
'Read IOPS', 'Write IOPS', 'Throughput Read (MBps)', 'Throughput Write (MBps)']
stats = datastoreStat_result["items"][0]["sortedStats"]
print("\t"+info_prefix+"---------- Datastore stats ----------")
x = PrettyTable()
x.add_column("Attributes", header)
x.add_column("Values", [stats[0]["flashHitPercent"], stats[0]["latencyNetworkMs"],
stats[0]["latencyStorageMs"], stats[0]["latencyDiskMs"],
stats[0]["latencyHostMs"], stats[0]["latencyTotalMs"],
stats[0]["performanceReserveAutoAllocated"],
stats[0]["spaceUsedLivePhysicalGiB"],
stats[0]["spaceUsedOtherGiB"],
stats[0]["operationsReadIops"], stats[0]["operationsWriteIops"],
stats[0]["throughputReadMBps"], stats[0]["throughputWriteMBps"]
]
)
print(x)
print()
# Logout of VMStore
print()
print("STEP 4: Logout from VMstore")
#Header and URL for logout call
headers = {'content-type': 'application/json','cookie': 'JSESSIONID='+session_id}
url_VMStore_logout = 'https://'+serverName+'/api/v310/session/logout'
if debug_mode:
print("\t"+debug_prefix+"The URL being used for logout is : "+url_VMStore_logout)
r = requests.get(url_VMStore_logout,headers=headers, verify=False)
if debug_mode:
print("\t"+debug_prefix+"The HTTP Status code for logout call to the server "+serverName + " is: "+str(r.status_code))
# if Http Response is not 204 then raise an exception
if r.status_code is not 204:
print("\t"+error_prefix+"The HTTP response for logout call to the server "+serverName+" is not 204")
sys.exit(-6)
print()
print("**********End of Get VMstore Dashboard Sample Client Script**********")
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By default, 'requests' calls wait until the connection is closed. This means a 'requests' call without a timeout will hang the program if a response is never received. Consider setting a timeout for all 'requests'.", "fix": "requests.get(urlDatastoreStat,headers=headers, verify=False, timeout=30)", "metadata": {"category": "best-practice", "references": ["https://docs.python-requests.org/en/latest/user/advanced/?highlight=timeout#timeouts", "https://requests.readthedocs.io/en/latest/user/quickstart/#timeouts"], "technology": ["requests"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.requests.security.disabled-cert-validation_48c378697b6cf346_5968a219", "tool_name": "semgrep", "rule_id": "rules.python.requests.security.disabled-cert-validation", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Certificate verification has been explicitly disabled. This permits insecure connections to insecure servers. Re-enable certification validation.", "remediation": "requests.get(urlDatastoreStat,headers=headers, verify=True)", "location": {"file_path": "unknown", "line_start": 153, "line_end": 153, "column_start": 3, "column_end": 63, "code_snippet": "requires login"}, "cwe_id": "CWE-295: Improper Certificate Validation", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A03:2017 - Sensitive Data Exposure", "references": [{"url": "https://stackoverflow.com/questions/41740361/is-it-safe-to-disable-ssl-certificate-verification-in-pythonss-requests-lib", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.requests.security.disabled-cert-validation", "path": "/tmp/tmprvd6_wj2/48c378697b6cf346.py", "start": {"line": 153, "col": 3, "offset": 5477}, "end": {"line": 153, "col": 63, "offset": 5537}, "extra": {"message": "Certificate verification has been explicitly disabled. This permits insecure connections to insecure servers. Re-enable certification validation.", "fix": "requests.get(urlDatastoreStat,headers=headers, verify=True)", "metadata": {"cwe": ["CWE-295: Improper Certificate Validation"], "owasp": ["A03:2017 - Sensitive Data Exposure", "A07:2021 - Identification and Authentication Failures", "A07:2025 - Authentication Failures"], "references": ["https://stackoverflow.com/questions/41740361/is-it-safe-to-disable-ssl-certificate-verification-in-pythonss-requests-lib"], "category": "security", "technology": ["requests"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "LOW", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.requests.best-practice.python.requests.best-practice.use-response-json-shortcut_48c378697b6cf346_9c90c990", "tool_name": "semgrep", "rule_id": "rules.python.requests.best-practice.python.requests.best-practice.use-response-json-shortcut", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "The requests library has a convenient shortcut for reading JSON responses, which lets you stop worrying about deserializing the response yourself.", "remediation": "r.json()", "location": {"file_path": "unknown", "line_start": 168, "line_end": 168, "column_start": 24, "column_end": 42, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://requests.readthedocs.io/en/stable/user/quickstart/#json-response-content", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.requests.best-practice.python.requests.best-practice.use-response-json-shortcut", "path": "/tmp/tmprvd6_wj2/48c378697b6cf346.py", "start": {"line": 168, "col": 24, "offset": 6107}, "end": {"line": 168, "col": 42, "offset": 6125}, "extra": {"message": "The requests library has a convenient shortcut for reading JSON responses, which lets you stop worrying about deserializing the response yourself.", "fix": "r.json()", "metadata": {"references": ["https://requests.readthedocs.io/en/stable/user/quickstart/#json-response-content"], "category": "best-practice", "technology": ["requests"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.requests.best-practice.use-raise-for-status_48c378697b6cf346_aafa4fe6", "tool_name": "semgrep", "rule_id": "rules.python.requests.best-practice.use-raise-for-status", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "There's an HTTP request made with requests, but the raise_for_status() utility method isn't used. This can result in request errors going unnoticed and your code behaving in unexpected ways, such as if your authorization API returns a 500 error while you're only checking for a 401.", "remediation": "", "location": {"file_path": "unknown", "line_start": 210, "line_end": 210, "column_start": 5, "column_end": 67, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://requests.readthedocs.io/en/master/api/#requests.Response.raise_for_status", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.requests.best-practice.use-raise-for-status", "path": "/tmp/tmprvd6_wj2/48c378697b6cf346.py", "start": {"line": 210, "col": 5, "offset": 7930}, "end": {"line": 210, "col": 67, "offset": 7992}, "extra": {"message": "There's an HTTP request made with requests, but the raise_for_status() utility method isn't used. This can result in request errors going unnoticed and your code behaving in unexpected ways, such as if your authorization API returns a 500 error while you're only checking for a 401.", "metadata": {"references": ["https://requests.readthedocs.io/en/master/api/#requests.Response.raise_for_status"], "category": "best-practice", "technology": ["requests"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.requests.best-practice.use-timeout_48c378697b6cf346_9302d694", "tool_name": "semgrep", "rule_id": "rules.python.requests.best-practice.use-timeout", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Detected a 'requests' call without a timeout set. By default, 'requests' calls wait until the connection is closed. This means a 'requests' call without a timeout will hang the program if a response is never received. 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Consider setting a timeout for all 'requests'.", "fix": "requests.get(url_VMStore_logout,headers=headers, verify=False, timeout=30)", "metadata": {"category": "best-practice", "references": ["https://docs.python-requests.org/en/latest/user/advanced/?highlight=timeout#timeouts", "https://requests.readthedocs.io/en/latest/user/quickstart/#timeouts"], "technology": ["requests"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.requests.security.disabled-cert-validation_48c378697b6cf346_6bd83b5f", "tool_name": "semgrep", "rule_id": "rules.python.requests.security.disabled-cert-validation", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Certificate verification has been explicitly disabled. This permits insecure connections to insecure servers. Re-enable certification validation.", "remediation": "requests.get(url_VMStore_logout,headers=headers, verify=True)", "location": {"file_path": "unknown", "line_start": 210, "line_end": 210, "column_start": 5, "column_end": 67, "code_snippet": "requires login"}, "cwe_id": "CWE-295: Improper Certificate Validation", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A03:2017 - Sensitive Data Exposure", "references": [{"url": "https://stackoverflow.com/questions/41740361/is-it-safe-to-disable-ssl-certificate-verification-in-pythonss-requests-lib", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.requests.security.disabled-cert-validation", "path": "/tmp/tmprvd6_wj2/48c378697b6cf346.py", "start": {"line": 210, "col": 5, "offset": 7930}, "end": {"line": 210, "col": 67, "offset": 7992}, "extra": {"message": "Certificate verification has been explicitly disabled. This permits insecure connections to insecure servers. Re-enable certification validation.", "fix": "requests.get(url_VMStore_logout,headers=headers, verify=True)", "metadata": {"cwe": ["CWE-295: Improper Certificate Validation"], "owasp": ["A03:2017 - Sensitive Data Exposure", "A07:2021 - Identification and Authentication Failures", "A07:2025 - Authentication Failures"], "references": ["https://stackoverflow.com/questions/41740361/is-it-safe-to-disable-ssl-certificate-verification-in-pythonss-requests-lib"], "category": "security", "technology": ["requests"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "LOW", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 14 | true | [
"CWE-295",
"CWE-295",
"CWE-295",
"CWE-295"
] | [
"rules.python.requests.security.disabled-cert-validation",
"rules.python.requests.security.disabled-cert-validation",
"rules.python.requests.security.disabled-cert-validation",
"rules.python.requests.security.disabled-cert-validation"
] | [
"security",
"security",
"security",
"security"
] | [
"LOW",
"LOW",
"LOW",
"LOW"
] | [
"HIGH",
"HIGH",
"HIGH",
"HIGH"
] | [
81,
119,
153,
210
] | [
81,
119,
153,
210
] | [
9,
3,
3,
5
] | [
84,
66,
63,
67
] | [
"A03:2017 - Sensitive Data Exposure",
"A03:2017 - Sensitive Data Exposure",
"A03:2017 - Sensitive Data Exposure",
"A03:2017 - Sensitive Data Exposure"
] | [
"Certificate verification has been explicitly disabled. This permits insecure connections to insecure servers. Re-enable certification validation.",
"Certificate verification has been explicitly disabled. This permits insecure connections to insecure servers. Re-enable certification validation.",
"Certificate v... | [
7.5,
7.5,
7.5,
7.5
] | [
"LOW",
"LOW",
"LOW",
"LOW"
] | [
"LOW",
"LOW",
"LOW",
"LOW"
] | GetTintriDashboard.py | /docs/client/http/samples/python/GetTintriDashboard.py | Tintri/tintri-rest-api | MIT | |
2024-11-18T20:43:35.376435+00:00 | 1,635,315,024,000 | 18c810361ce85b5d4a2bd5c5d6a3893d256d3c93 | 3 | {
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"visit_date": "2021-11-04T03:08:13.578408"
} | 2.6875 | stackv2 | import sys
import logging
import subprocess
from pid import PidFile
from configparser import ConfigParser
from http.server import BaseHTTPRequestHandler,HTTPServer
#This class will handles any incoming request from
#the browser
class HealthCheckHandler(BaseHTTPRequestHandler):
def check_status(self):
global command
p = subprocess.Popen('bash -c \''+command+"'", shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
p.communicate()[0]
print(p.returncode)
return p.returncode==0
def do_healthcheck(self):
if self.check_status():
self.send_response(200)
self.send_header('Content-type','text/html')
self.end_headers()
self.wfile.write(bytes("OK", "utf-8"))
else:
self.send_response(503)
self.send_header('Content-type','text/html')
self.end_headers()
self.wfile.write(bytes("ERROR", "utf-8"))
#Handler for the GET requests
def do_GET(self):
self.do_healthcheck()
return
#Handler for the HEAD requests
def do_HEAD(self):
self.do_healthcheck()
return
if __name__ == "__main__":
try:
configfile = sys.argv[1]
except IndexError:
configfile = '/etc/healthcheckd.config'
try:
config = ConfigParser()
config.read(configfile)
try:
pidfile = config.get('healthcheckd', 'pidfile').strip('"').strip("'").strip()
except:
pidfile = 'healthcheckd'
try:
piddir = config.get('healthcheckd', 'piddir').strip('"').strip("'").strip()
except:
piddir = '/tmp'
try:
port_number = int(config.get('healthcheckd', 'port').strip('"').strip("'").strip())
except:
port_number = 17
try:
command = config.get('healthcheckd', 'command').strip('"').strip("'").strip()
except Exception as e:
command = '/bin/true'
print('INFO: setting default command: '+command)
with PidFile(piddir=piddir, pidname=pidfile) as pidfile:
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
try:
#Create a web server and define the handler to manage the
#incoming request
server = HTTPServer(('', port_number), HealthCheckHandler)
print('Started httpserver on port '+str(port_number))
#Wait forever for incoming htto requests
server.serve_forever()
except KeyboardInterrupt:
logging.info('shutting down healthcheckd')
server.socket.close()
sys.exit()
except Exception as e:
msg = 'Global ERROR: '+str(e)
logging.error(msg)
sys.exit(msg+'\n')
| 93 | 30.57 | 114 | 21 | 633 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_3bb3e621d1f2bc4e_13bdd5ea", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_3bb3e621d1f2bc4e_b91ea5fa", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'Popen' with 'shell=True'. 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This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. 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"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.subprocess-shell-true"
] | [
"security",
"security"
] | [
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH"
] | [
15,
15
] | [
15,
15
] | [
13,
62
] | [
115,
66
] | [
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.",
"Found 'subprocess' functi... | [
7.5,
7.5
] | [
"LOW",
"HIGH"
] | [
"HIGH",
"LOW"
] | healthcheckd.py | /healthcheckd.py | jordiprats/python-healthcheckd | Apache-2.0 | |
2024-11-18T20:43:40.741314+00:00 | 1,513,539,361,000 | ac11dd9c1ec5ed8972d07414db7e484b608a6f49 | 3 | {
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} | 2.734375 | stackv2 | #server
# TCP Server Code
from Crypto.Cipher import AES
from Crypto.Cipher import DES
from Crypto.Cipher import DES3
from Crypto.Cipher import Blowfish
from Crypto.Cipher import ChaCha20
import hashlib
from hashlib import blake2s
import pickle
import random
import sys
import Crypto
from ecc import getcurvebyname
from array import array
import socket
from socket import *
import time
import argparse
host="127.0.0.1"
port=4446
#port=12345
parser = argparse.ArgumentParser()
parser.add_argument("e", type=int, choices=[0, 1, 2, 3, 4],
help="symmetric encryption algorithm [ 0 - AES, 1 - DES, 2 - 3DES, 3 - Blowfish, 4 - ChaCha20]")
parser.add_argument("-d", "--hash", type=int, choices=[0, 1, 2],
help="hash function [0 - md5, 1 - blake2s, 2 - SHA256 ]")
args = parser.parse_args()
def decryptData( secret, msg):
"Decrypts the data based on the used cipher"
msg_nonce = msg[:8]
ciphertext = msg[8:]
cipher = ChaCha20.new(key=secret, nonce=msg_nonce)
decryptedData = cipher.decrypt(ciphertext)
return decryptedData
def getCipher( key ):
"This returns the Cipher based on the preffered algorithm -AES, DES, 3DES"
if args.e == 0:
tempCipher = AES.new(key, AES.MODE_ECB)
elif args.e == 1:
tempCipher = DES.new(key, DES.MODE_ECB)
elif args.e == 2:
tempCipher = DES3.new(key, DES3.MODE_ECB)
elif args.e == 3:
tempCipher = Blowfish.new(key, Blowfish.MODE_ECB)
elif args.e == 4:
tempCipher = ChaCha20.new(key=key)
return tempCipher
def getKey( strValue ):
"Returns the key based on the chosen symmetric function"
if args.e == 0:
#AES
if args.hash == 0:
tempKey=hashlib.md5()
elif args.hash == 1:
tempKey=hashlib.blake2s(digest_size=16)
else:
tempKey=hashlib.md5()
elif args.e == 1:
tempKey=hashlib.blake2s(digest_size=8) #DES
elif args.e == 2:
tempKey=hashlib.blake2s(digest_size=16) #3DES
elif args.e == 3:
tempKey=hashlib.blake2s() #Blowfish
elif args.e == 4:
tempKey=hashlib.blake2s(digest_size=32) #ChaCha20
tempKey.update(strValue)
tempKey=tempKey.digest()
return tempKey
def readFromClient():
c=random.randint(0,1)
curve=getcurvebyname("ed25519")
g=curve.G
b=random.randint(1,2**255-19)
Alice=pickle.loads(q.recv(4096))
if (c==0):
Bob=(g.__mul__(b))
else:
Bob=(Alice.__mul__(c)).__add__(g.__mul__(b))
q.send(pickle.dumps(Bob,pickle.HIGHEST_PROTOCOL))
k = getKey(str(Alice.__mul__(b)).encode())
cipher1 = getCipher(k)
message=[1]*2
for i in range (2):
en=q.recv(1024)
if args.e == 4:
message[i] = decryptData(k, en)
else:
message[i]=cipher1.decrypt(en)
print ('Message [',i,']',message[i].decode('iso-8859-15'))
print('#########################################################')
return;
s=socket(AF_INET, SOCK_STREAM)
s.bind((host,port))
s.listen(1)
print ("Listening for connections.. ")
if args.e == 0:
print ("AES encryption")
elif args.e == 1:
print ("DES encryption")
elif args.e == 2:
print ("3DES encryption")
elif args.e == 3:
print ("Blowfish encryption")
elif args.e == 4:
print ("ChaCha20 encryption")
q,addr=s.accept()
start_time = time.time()
for i in range (10):
start_time = time.time()
readFromClient()
print("----- %s seconds ----" %(time.time() - start_time))
s.close() # Closes the socket
# End of code
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] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | server.py | /server.py | FMI-VT/Simplest-OT-Python-Implementation | MIT | |
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"visit_date": "2023-05-23T19:34:52.967311"
} | 2.578125 | stackv2 | import os
import numpy as np
import streamlit as st
from gensim import corpora, models
def lda_basic(list_of_list_of_tokens, num_topics):
dictionary_LDA = corpora.Dictionary(list_of_list_of_tokens)
dictionary_LDA.filter_extremes(no_below=2)
corpus = [
dictionary_LDA.doc2bow(list_of_tokens)
for list_of_tokens in list_of_list_of_tokens
]
lda_model = models.LdaModel(
corpus,
num_topics=num_topics,
id2word=dictionary_LDA,
passes=20,
alpha="auto",
eta="auto",
random_state=42,
)
cm = models.CoherenceModel(model=lda_model, corpus=corpus, coherence="u_mass")
coherence = cm.get_coherence() # get coherence value
return corpus, lda_model, coherence
@st.cache(persist=eval(os.getenv("PERSISTENT")))
def extract_topics_lda(text_file_paths, num_topics=0, num_words=10):
list_of_list_of_tokens = []
for text_file_path in text_file_paths:
with open(text_file_path, "r") as f:
text = f.read()
doc_words = text.replace("\n", " ").split(" ")
list_of_list_of_tokens.append(doc_words)
if num_topics == 0:
coherence_scores = []
range_of_topics = list(range(5, 31))
for num_topics_in_lst in range_of_topics:
_, lda_model, coherence = lda_basic(
list_of_list_of_tokens, num_topics_in_lst
)
coherence_scores.append(abs(coherence))
num_topics = 3 + np.argmin(coherence_scores)
corpus, lda_model, _ = lda_basic(list_of_list_of_tokens, num_topics)
year_wise_topics = []
for i, list_of_tokens in enumerate(list_of_list_of_tokens):
year_wise_topics.append(lda_model[corpus[i]])
return year_wise_topics, lda_model.show_topics(
formatted=True, num_topics=num_topics, num_words=num_words
)
| 58 | 31.09 | 82 | 17 | 450 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_65e48e4b1d5007d4_ebd8b384", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 31, "line_end": 31, "column_start": 19, "column_end": 48, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmprvd6_wj2/65e48e4b1d5007d4.py", "start": {"line": 31, "col": 19, "offset": 780}, "end": {"line": 31, "col": 48, "offset": 809}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_65e48e4b1d5007d4_2140dffb", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 35, "line_end": 35, "column_start": 14, "column_end": 39, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmprvd6_wj2/65e48e4b1d5007d4.py", "start": {"line": 35, "col": 14, "offset": 968}, "end": {"line": 35, "col": 39, "offset": 993}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"CWE-95"
] | [
"rules.python.lang.security.audit.eval-detected"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
31
] | [
31
] | [
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48
] | [
"A03:2021 - Injection"
] | [
"Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources."
] | [
5
] | [
"LOW"
] | [
"HIGH"
] | topic_extraction_lda.py | /src/analysis/topic_extraction_lda.py | rajaswa/DRIFT | MIT | |
2024-11-18T20:43:49.966903+00:00 | 1,573,216,143,000 | 182a1c07177697f88b529d603fd730dde5edbd0c | 2 | {
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"visit_date": "2020-09-06T14:54:56.006251"
} | 2.3125 | stackv2 | #!/usr/bin/python
import subprocess
import sys
from SystemConfiguration import (
SCDynamicStoreCreate, SCDynamicStoreCopyValue, SCDynamicStoreCopyConsoleUser)
sys.path.insert(0, '/usr/local/munki')
from munkilib import FoundationPlist
sys.path.insert(0, '/usr/local/sal')
import macmodelshelf
import utils
MEMORY_EXPONENTS = {'KB': 0, 'MB': 1, 'GB': 2, 'TB': 3}
__version__ = '1.0.0'
def main():
machine_results = {'facts': {'checkin_module_version': __version__}}
extras = {}
extras['hostname'] = get_hostname()
extras['os_family'] = 'Darwin'
extras['console_user'] = get_console_user()[0]
extras.update(process_system_profile())
machine_results['extra_data'] = extras
utils.set_checkin_results('Machine', machine_results)
def process_system_profile():
machine_results = {}
system_profile = get_sys_profile()
if not system_profile:
# We can't continue if system_profiler dies.
return machine_results
machine_results['serial'] = system_profile['SPHardwareDataType'][0]['serial_number']
os_version = system_profile['SPSoftwareDataType'][0]['os_version'].split()[1]
if os_version == 'X':
os_version = system_profile['SPSoftwareDataType'][0]['os_version'].split()[2]
machine_results['operating_system'] = os_version
machine_results['machine_model'] = system_profile['SPHardwareDataType'][0]['machine_model']
friendly_model = get_friendly_model(machine_results['serial'])
if friendly_model:
machine_results['machine_model_friendly'] = friendly_model
machine_results['cpu_type'] = system_profile['SPHardwareDataType'][0].get('cpu_type', '')
machine_results['cpu_speed'] = (
system_profile['SPHardwareDataType'][0]['current_processor_speed'])
machine_results['memory'] = system_profile['SPHardwareDataType'][0]['physical_memory']
machine_results['memory_kb'] = process_memory(machine_results['memory'])
for device in system_profile['SPStorageDataType']:
if device['mount_point'] == '/':
# div by 1000.0 to
# a) Convert to Apple base 10 kilobytes
# b) Cast to python floats
machine_results['hd_space'] = device['free_space_in_bytes']
machine_results['hd_total'] = device['size_in_bytes']
# We want the % used, not of free space, so invert.
machine_results['hd_percent'] = '{:.2f}'.format(
abs(float(machine_results['hd_space']) / machine_results['hd_total'] - 1) * 100)
return machine_results
def get_hostname():
_, name_type, _ = utils.get_server_prefs()
net_config = SCDynamicStoreCreate(None, "net", None, None)
return get_machine_name(net_config, name_type)
def get_machine_name(net_config, nametype):
"""Return the ComputerName of this Mac."""
sys_info = SCDynamicStoreCopyValue(net_config, "Setup:/System")
if sys_info:
return sys_info.get(nametype)
return subprocess.check_output(['/usr/sbin/scutil', '--get', 'ComputerName'])
def get_friendly_model(serial):
"""Return friendly model name"""
model_code = macmodelshelf.model_code(serial)
model_name = macmodelshelf.model(model_code)
return model_name
def process_memory(amount):
"""Convert the amount of memory like '4 GB' to the size in kb as int"""
try:
memkb = int(amount[:-3]) * 1024 ** MEMORY_EXPONENTS[amount[-2:]]
except ValueError:
memkb = int(float(amount[:-3])) * 1024 ** MEMORY_EXPONENTS[amount[-2:]]
return memkb
def get_sys_profile():
"""Get sysprofiler info.
Returns:
System Profiler report for networking, drives, and hardware as a
plist dict, or an empty dict.
"""
command = [
'/usr/sbin/system_profiler', '-xml', 'SPHardwareDataType', 'SPStorageDataType',
'SPSoftwareDataType']
try:
output = subprocess.check_output(command)
except subprocess.CalledProcessError:
return {}
try:
system_profile = FoundationPlist.readPlistFromString(output)
except FoundationPlist.FoundationPlistException:
system_profile = {}
# sytem_profiler gives us back an array; convert to a dict with just
# the data we care about.
results = {}
for data_type in system_profile:
key = data_type['_dataType']
results[key] = data_type['_items']
return results
def get_console_user():
"""Get informatino about the console user
Returns:
3-Tuple of (str) username, (int) uid, (int) gid
"""
return SCDynamicStoreCopyConsoleUser(None, None, None)
if __name__ == "__main__":
main()
| 139 | 32.35 | 96 | 21 | 1,106 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_e28dceb7eb1889d2_8f4a082e", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 110, "line_end": 110, "column_start": 18, "column_end": 50, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmprvd6_wj2/e28dceb7eb1889d2.py", "start": {"line": 110, "col": 18, "offset": 3876}, "end": {"line": 110, "col": 50, "offset": 3908}, "extra": {"message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
110
] | [
110
] | [
18
] | [
50
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | machine_checkin.py | /payload/usr/local/sal/checkin_modules/machine_checkin.py | asemak/sal-scripts | Apache-2.0 | |
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} | 2.984375 | stackv2 | #Interface with SQL Database
import sqlite3
#Pickle objects
import pickle
#CV to train
import cv2
#Base64 encode images
import base64
#For exit
import sys
#For numpy arrays
import numpy as np
#For file system interaction
import os
#If you decide to train based on the file system, this code is from the same location as the code in
#OpenCV-Face-Recognition-Python
def prepare_training_data(data_folder_path):
#------STEP-1--------
#get the directories (one directory for each subject) in data folder
dirs = os.listdir(data_folder_path)
#list to hold all subject faces
faces = []
#list to hold labels for all subjects
labels = []
#let's go through each directory and read images within it
for dir_name in dirs:
#our subject directories start with letter 's' so
#ignore any non-relevant directories if any
if not dir_name.startswith("s"):
continue;
#------STEP-2--------
#extract label number of subject from dir_name
#format of dir name = slabel
#, so removing letter 's' from dir_name will give us label
label = int(dir_name.replace("s", ""))
#build path of directory containin images for current subject subject
#sample subject_dir_path = "training-data/s1"
subject_dir_path = data_folder_path + "/" + dir_name
#get the images names that are inside the given subject directory
subject_images_names = os.listdir(subject_dir_path)
#------STEP-3--------
#go through each image name, read image,
#detect face and add face to list of faces
for image_name in subject_images_names:
#ignore system files like .DS_Store
if image_name.startswith("."):
continue;
#build image path
#sample image path = training-data/s1/1.pgm
image_path = subject_dir_path + "/" + image_name
#read image
image = cv2.imread(image_path)
#display an image window to show the image
#cv2.imshow("Training on image...", cv2.resize(image, (400, 500)))
#cv2.waitKey(100)
#detect face
face, rect = detect_face(image)
#------STEP-4--------
#for the purpose of this tutorial
#we will ignore faces that are not detected
if face is not None:
#add face to list of faces
faces.append(face)
#add label for this face
labels.append(label)
#cv2.destroyAllWindows()
#cv2.waitKey(1)
#cv2.destroyAllWindows()
return faces, labels
#function to detect face using OpenCV
def detect_face(img):
#convert the test image to gray image as opencv face detector expects gray images
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#cv2.imshow("Training on image...", cv2.resize(gray, (400, 500)))
#cv2.waitKey(100)
#load OpenCV face detector, I am using LBP which is fast
#there is also a more accurate but slow Haar classifier
face_cascade = cv2.CascadeClassifier('opencv-files/lbpcascade_frontalface.xml')
#let's detect multiscale (some images may be closer to camera than others) images
#result is a list of faces
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5);
#if no faces are detected then return original img
if (len(faces) == 0):
return None, None
#under the assumption that there will be only one face,
#extract the face area
(x, y, w, h) = faces[0]
#return only the face part of the image
return gray[y:y+w, x:x+h], faces[0]
#Connect to the database
conn = sqlite3.connect('targets.db')
c = conn.cursor()
labels = []
names = []
faces = []
label = 1
#Read all face/labels into lists
#LAST FIRST, I0, ..., LAST_UPDATED
for row in c.execute('SELECT * FROM images'):
name = row[0] + " " + row[1]
for i in range(2,8):
buff = base64.b64decode(row[i])
arr = np.asarray(bytearray(buff), dtype=np.uint8)
frame = cv2.imdecode(arr, cv2.IMREAD_COLOR)
if frame is None:
c.close()
conn.close()
sys.exit()
face, rect = detect_face(frame)
if face is not None:
#If a face is detected, add to the training set
labels.append(label)
faces.append(face)
if labels[-1] != label:
print("Unable to get good face of " + name)
c.close()
conn.close()
sys.exit()
names.append(name)
label = label + 1
#Finish the connection
c.close()
conn.close()
#create our LBPH face recognizer
face_recognizer = cv2.face.LBPHFaceRecognizer_create()
#face_recognizer = cv2.face.createLBPHFaceRecognizer()
#or use EigenFaceRecognizer by replacing above line with
#face_recognizer = cv2.face.EigenFaceRecognizer_create()
#or use FisherFaceRecognizer by replacing above line with
#face_recognizer = cv2.face.FisherFaceRecognizer_create()
#train our face recognizer of our training faces
face_recognizer.train(faces, np.array(labels))
face_recognizer.save("tmp")
#Read in result of the dump and remove the dump
buf = open("tmp").read()
os.remove("tmp")
result = {'model': buf, 'names': names}
#Give result to standard out
print(base64.b64encode(pickle.dumps(result)))
| 179 | 29.64 | 100 | 13 | 1,313 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_d12298c669655447_72f50c6b", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 173, "line_end": 173, "column_start": 7, "column_end": 18, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmprvd6_wj2/d12298c669655447.py", "start": {"line": 173, "col": 7, "offset": 5332}, "end": {"line": 173, "col": 18, "offset": 5343}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_d12298c669655447_e207cc94", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 179, "line_end": 179, "column_start": 24, "column_end": 44, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmprvd6_wj2/d12298c669655447.py", "start": {"line": 179, "col": 24, "offset": 5462}, "end": {"line": 179, "col": 44, "offset": 5482}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
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"LOW"
] | [
"MEDIUM"
] | trainer.py | /Node/trainer.py | TechMatt1337/Bastion | BSD-3-Clause | |
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} | 3.28125 | stackv2 | """
Benchmark SamplesLoss in 3D
=====================================
Let's compare the performances of our losses and backends
as the number of samples grows from 100 to 1,000,000.
"""
##############################################
# Setup
# ---------------------
import numpy as np
import time
from matplotlib import pyplot as plt
import importlib
import torch
use_cuda = torch.cuda.is_available()
from geomloss import SamplesLoss
MAXTIME = 10 if use_cuda else 1 # Max number of seconds before we break the loop
REDTIME = (
2 if use_cuda else 0.2
) # Decrease the number of runs if computations take longer than 2s...
D = 3 # Let's do this in 3D
# Number of samples that we'll loop upon
NS = [
100,
200,
500,
1000,
2000,
5000,
10000,
20000,
50000,
100000,
200000,
500000,
1000000,
]
##############################################
# Synthetic dataset. Feel free to use
# a Stanford Bunny, or whatever!
def generate_samples(N, device):
"""Create point clouds sampled non-uniformly on a sphere of diameter 1."""
x = torch.randn(N, D, device=device)
x[:, 0] += 1
x = x / (2 * x.norm(dim=1, keepdim=True))
y = torch.randn(N, D, device=device)
y[:, 1] += 2
y = y / (2 * y.norm(dim=1, keepdim=True))
x.requires_grad = True
# Draw random weights:
a = torch.randn(N, device=device)
b = torch.randn(N, device=device)
# And normalize them:
a = a.abs()
b = b.abs()
a = a / a.sum()
b = b / b.sum()
return a, x, b, y
##############################################
# Benchmarking loops.
def benchmark(Loss, dev, N, loops=10):
"""Times a loss computation+gradient on an N-by-N problem."""
importlib.reload(torch) # In case we had a memory overflow just before...
device = torch.device(dev)
a, x, b, y = generate_samples(N, device)
# We simply benchmark a Loss + gradien wrt. x
code = "L = Loss( a, x, b, y ) ; L.backward()"
Loss.verbose = True
exec(code, locals()) # Warmup run, to compile and load everything
Loss.verbose = False
t_0 = time.perf_counter() # Actual benchmark --------------------
if use_cuda:
torch.cuda.synchronize()
for i in range(loops):
exec(code, locals())
if use_cuda:
torch.cuda.synchronize()
elapsed = time.perf_counter() - t_0 # ---------------------------
print(
"{:3} NxN loss, with N ={:7}: {:3}x{:3.6f}s".format(
loops, N, loops, elapsed / loops
)
)
return elapsed / loops
def bench_config(Loss, dev):
"""Times a loss computation+gradient for an increasing number of samples."""
print("Backend : {}, Device : {} -------------".format(Loss.backend, dev))
times = []
def run_bench():
try:
Nloops = [100, 10, 1]
nloops = Nloops.pop(0)
for n in NS:
elapsed = benchmark(Loss, dev, n, loops=nloops)
times.append(elapsed)
if (nloops * elapsed > MAXTIME) or (
nloops * elapsed > REDTIME and len(Nloops) > 0
):
nloops = Nloops.pop(0)
except IndexError:
print("**\nToo slow !")
try:
run_bench()
except RuntimeError as err:
if str(err)[:4] == "CUDA":
print("**\nMemory overflow !")
else:
# CUDA memory overflows semi-break the internal
# torch state and may cause some strange bugs.
# In this case, best option is simply to re-launch
# the benchmark.
run_bench()
return times + (len(NS) - len(times)) * [np.nan]
def full_bench(loss, *args, **kwargs):
"""Benchmarks the varied backends of a geometric loss function."""
print("Benchmarking : ===============================")
lines = [NS]
backends = ["tensorized", "online", "multiscale"]
for backend in backends:
Loss = SamplesLoss(*args, **kwargs, backend=backend)
lines.append(bench_config(Loss, "cuda" if use_cuda else "cpu"))
benches = np.array(lines).T
# Creates a pyplot figure:
plt.figure()
linestyles = ["o-", "s-", "^-"]
for i, backend in enumerate(backends):
plt.plot(
benches[:, 0],
benches[:, i + 1],
linestyles[i],
linewidth=2,
label='backend="{}"'.format(backend),
)
plt.title('Runtime for SamplesLoss("{}") in dimension {}'.format(Loss.loss, D))
plt.xlabel("Number of samples per measure")
plt.ylabel("Seconds")
plt.yscale("log")
plt.xscale("log")
plt.legend(loc="upper left")
plt.grid(True, which="major", linestyle="-")
plt.grid(True, which="minor", linestyle="dotted")
plt.axis([NS[0], NS[-1], 1e-3, MAXTIME])
plt.tight_layout()
# Save as a .csv to put a nice Tikz figure in the papers:
header = "Npoints " + " ".join(backends)
np.savetxt(
"output/benchmark_" + Loss.loss + "_3D.csv",
benches,
fmt="%-9.5f",
header=header,
comments="",
)
##############################################
# Gaussian MMD, with a small blur
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
full_bench(SamplesLoss, "gaussian", blur=0.1, truncate=3)
##############################################
# Energy Distance MMD
# ~~~~~~~~~~~~~~~~~~~~~~
#
full_bench(SamplesLoss, "energy")
##############################################
# Sinkhorn divergence
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# With a medium blurring scale, at one twentieth of the
# configuration's diameter:
full_bench(SamplesLoss, "sinkhorn", p=2, blur=0.05, diameter=1)
##############################################
# With a small blurring scale, at one hundredth of the
# configuration's diameter:
full_bench(SamplesLoss, "sinkhorn", p=2, blur=0.01, diameter=1)
plt.show()
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"CWE-95",
"CWE-95"
] | [
"rules.python.lang.security.audit.exec-detected",
"rules.python.lang.security.audit.exec-detected"
] | [
"security",
"security"
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"LOW"
] | [
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"MEDIUM"
] | [
94,
101
] | [
94,
101
] | [
5,
9
] | [
25,
29
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"A03:2021 - Injection"
] | [
"Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.",
"Detected the use of exec(). exec() can be dangerous if used... | [
5,
5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | plot_benchmarks_samplesloss_3D.py | /geomloss/examples/performances/plot_benchmarks_samplesloss_3D.py | jeanfeydy/geomloss | MIT | |
2024-11-18T20:44:07.584358+00:00 | 1,485,810,103,000 | 62977f7ee225ee575a2f3813c47ecbc391c84558 | 3 | {
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"repo_name": "Adel-B/simple-site-crawler",
"revision_date": 1485810103000,
"revision_id": "ddb2db60308cb091e09732d0f0527145fb346c75",
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"visit_date": "2021-01-08T10:45:52.664015"
} | 3.140625 | stackv2 | """
Test `simple_site_crawler.site_crawler` file
"""
import xml.etree.cElementTree as ET
from xml.dom import minidom
def generate_sitemap_xml(urls, filename='sitemap.xml'):
"""
Generate 'sitemap.xml' file based on passed urls
:param urls: list of URLs
:type urls: list of str
:param filename: output file name
:type filename: str
"""
urlset = ET.Element(
'urlset',
xmlns='http://www.sitemaps.org/schemas/sitemap/0.9',
)
for webpage_url in urls:
url = ET.SubElement(urlset, 'url')
ET.SubElement(url, 'loc').text = webpage_url
pretty_xml = minidom.parseString(
ET.tostring(urlset),
).toprettyxml(
encoding='UTF-8',
)
with open(filename, 'wb') as f:
f.write(pretty_xml)
def render_children(children, prefix='│ ├── ', last_item_prefix='│ └── '):
"""
Simple helper for rendering element children
:param children: children container
:type children: iterable object
:param prefix: string that will prefix the child element
:type prefix: str
:param last_item_prefix: string that will prefix the last child elemment
:return: rendered children string
:rtype: str
"""
s = ''
for item in children[:-1]:
s += '{}{}\n'.format(prefix, item)
s += '{}{}'.format(last_item_prefix, children[-1])
return s
| 55 | 24.05 | 78 | 12 | 351 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_cde5800f545af206_08ae678a", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "remediation": "", "location": {"file_path": "unknown", "line_start": 4, "line_end": 4, "column_start": 1, "column_end": 36, "code_snippet": "requires login"}, "cwe_id": "CWE-611: Improper Restriction of XML External Entity Reference", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A04:2017 - XML External Entities (XXE)", "references": [{"url": "https://docs.python.org/3/library/xml.html", "title": null}, {"url": "https://github.com/tiran/defusedxml", "title": null}, {"url": "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.use-defused-xml", "path": "/tmp/tmpr7mo7ysm/cde5800f545af206.py", "start": {"line": 4, "col": 1, "offset": 53}, "end": {"line": 4, "col": 36, "offset": 88}, "extra": {"message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "metadata": {"owasp": ["A04:2017 - XML External Entities (XXE)", "A05:2021 - Security Misconfiguration", "A02:2025 - Security Misconfiguration"], "cwe": ["CWE-611: Improper Restriction of XML External Entity Reference"], "references": ["https://docs.python.org/3/library/xml.html", "https://github.com/tiran/defusedxml", "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_cde5800f545af206_a1921ac7", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "remediation": "", "location": {"file_path": "unknown", "line_start": 5, "line_end": 5, "column_start": 1, "column_end": 28, "code_snippet": "requires login"}, "cwe_id": "CWE-611: Improper Restriction of XML External Entity Reference", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A04:2017 - XML External Entities (XXE)", "references": [{"url": "https://docs.python.org/3/library/xml.html", "title": null}, {"url": "https://github.com/tiran/defusedxml", "title": null}, {"url": "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.use-defused-xml", "path": "/tmp/tmpr7mo7ysm/cde5800f545af206.py", "start": {"line": 5, "col": 1, "offset": 89}, "end": {"line": 5, "col": 28, "offset": 116}, "extra": {"message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.", "metadata": {"owasp": ["A04:2017 - XML External Entities (XXE)", "A05:2021 - Security Misconfiguration", "A02:2025 - Security Misconfiguration"], "cwe": ["CWE-611: Improper Restriction of XML External Entity Reference"], "references": ["https://docs.python.org/3/library/xml.html", "https://github.com/tiran/defusedxml", "https://owasp.org/www-community/vulnerabilities/XML_External_Entity_(XXE)_Processing"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
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"The Python documentation recommends using `defusedxml` ins... | [
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] | [
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] | utils.py | /simple_site_crawler/utils.py | Adel-B/simple-site-crawler | MIT | |
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} | 2.671875 | stackv2 | "flask-mustache Flask plugin"
from jinja2 import Template
import pystache
from flask import current_app, Blueprint
__all__ = ('FlaskMustache',)
mustache_app = Blueprint('mustache', __name__, template_folder='templates', static_folder='static')
class FlaskMustache(object):
"Wrapper to inject Mustache stuff into Flask"
def __init__(self, app=None):
self.app = app
if app is not None:
self.init_app(app)
def init_app(self, app):
"Wrapper around the app so that we can instantiate it from different places"
self.app = app
# XXX: this url_prefix is due to a bug in Blueprints where the
# static assets aren't available until they have a `url_prefix`
app.register_blueprint(mustache_app, url_prefix='/_mustache')
# set up global `mustache` function
app.jinja_env.globals['mustache'] = mustache
# attach context processor with template content
app.context_processor(mustache_templates)
@staticmethod
def attach(app):
"This is written so it can work like WSGI middleware"
# noop
_ = FlaskMustache(app)
return app
def get_template(name):
# throw away everything except the file content
template, _, _ = current_app.jinja_env.loader.get_source(current_app.jinja_env, name)
return template
# context processor
def mustache_templates():
"Returns the content of all Mustache templates in the Jinja environment"
# TODO: add a config option to load mustache templates into the
# global context
# get all the templates this env knows about
all_templates = current_app.jinja_env.loader.list_templates()
ctx_mustache_templates = {}
for template_name in all_templates:
# TODO: make this configurable
# we only want a specific extension
if template_name.endswith('mustache'):
ctx_mustache_templates[template_name] = get_template(template_name)
# prepare context for Jinja
context = {
'mustache_templates': ctx_mustache_templates
}
# returns the full HTML, ready to use in JavaScript
template = current_app.jinja_env.get_template('_template_script_block.jinja')
return {'mustache_templates': template.render(context)}
# template helper function
def mustache(template, partials=None, **kwargs):
"""Usage:
{{ mustache('path/to/whatever.mustache', key=value, key1=value1.. keyn=valuen) }}
or, with partials
{{ mustache('path/to/whatever.mustache', partials={'partial_name': 'path/to/partial.mustache'}, \
key1=value1.. keyn=valuen) }}
This uses the regular Jinja2 loader to find the templates, so your
*.mustache files will need to be available in that path.
"""
# TODO: cache loaded templates
template = get_template(template)
_partials = None
if partials:
_partials = dict((name, get_template(path)) for name, path in partials.iteritems())
renderer = pystache.Renderer(partials=_partials)
return renderer.render(template, kwargs, encoding='utf-8')
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] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | __init__.py | /flask_mustache/__init__.py | bradwright/flask-mustachejs | BSD-3-Clause | |
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} | 2.484375 | stackv2 | import torch
import hydra
from ..base.constants import MODEL_MVTCAE
from ..base.base_model import BaseModelVAE
from ..base.representations import ProductOfExperts
class mvtCAE(BaseModelVAE):
r"""
Multi-View Total Correlation Auto-Encoder (MVTCAE).
Code is based on: https://github.com/gr8joo/MVTCAE
NOTE: This implementation currently only caters for a PoE posterior distribution. MoE and MoPoE posteriors will be included in further work.
Args:
cfg (str): Path to configuration file. Model specific parameters in addition to default parameters:
- model.beta (int, float): KL divergence weighting term.
- model.alpha (int, float): Log likelihood, Conditional VIB and VIB weighting term.
- encoder.default._target_ (multiviewae.architectures.mlp.VariationalEncoder): Type of encoder class to use.
- encoder.default.enc_dist._target_ (multiviewae.base.distributions.Normal, multiviewae.base.distributions.MultivariateNormal): Encoding distribution.
- decoder.default._target_ (multiviewae.architectures.mlp.VariationalDecoder): Type of decoder class to use.
- decoder.default.init_logvar(int, float): Initial value for log variance of decoder.
- decoder.default.dec_dist._target_ (multiviewae.base.distributions.Normal, multiviewae.base.distributions.MultivariateNormal): Decoding distribution.
input_dim (list): Dimensionality of the input data.
z_dim (int): Number of latent dimensions.
References
----------
Hwang, HyeongJoo and Kim, Geon-Hyeong and Hong, Seunghoon and Kim, Kee-Eung. Multi-View Representation Learning via Total Correlation Objective. 2021. NeurIPS
"""
def __init__(
self,
cfg = None,
input_dim = None,
z_dim = None
):
super().__init__(model_name=MODEL_MVTCAE,
cfg=cfg,
input_dim=input_dim,
z_dim=z_dim)
def encode(self, x):
r"""Forward pass through encoder networks.
Args:
x (list): list of input data of type torch.Tensor.
Returns:
Returns either the joint or separate encoding distributions depending on whether the model is in the training stage:
qz_xs (list): list containing separate encoding distributions.
qz_x (list): Single element list containing PoE joint encoding distribution.
"""
if self._training:
qz_xs = []
for i in range(self.n_views):
mu, logvar = self.encoders[i](x[i])
qz_x = hydra.utils.instantiate(
eval(f"self.cfg.encoder.enc{i}.enc_dist"), loc=mu, scale=logvar.exp().pow(0.5)
)
qz_xs.append(qz_x)
return qz_xs
else:
mu = []
logvar = []
for i in range(self.n_views):
mu_, logvar_ = self.encoders[i](x[i])
mu.append(mu_)
logvar.append(logvar_)
mu = torch.stack(mu)
logvar = torch.stack(logvar)
mu, logvar = ProductOfExperts()(mu, logvar)
qz_x = hydra.utils.instantiate(
self.cfg.encoder.default.enc_dist, loc=mu, scale=logvar.exp().pow(0.5)
)
qz_x = [qz_x]
return qz_x
def decode(self, qz_xs):
r"""Forward pass of joint latent dimensions through decoder networks.
Args:
x (list): list of input data of type torch.Tensor.
Returns:
(list): A nested list of decoding distributions, px_zs. The outer list has a single element indicating the shared latent dimensions.
The inner list is a n_view element list with the position in the list indicating the decoder index.
"""
if self._training:
mu = [qz_x.loc for qz_x in qz_xs]
var = [qz_x.variance for qz_x in qz_xs]
mu = torch.stack(mu)
var = torch.stack(var)
mu, logvar = ProductOfExperts()(mu, torch.log(var))
px_zs = []
for i in range(self.n_views):
px_z = self.decoders[i](
hydra.utils.instantiate(
self.cfg.encoder.default.enc_dist, loc=mu, scale=logvar.exp().pow(0.5)
).rsample()
)
px_zs.append(px_z)
return [px_zs]
else:
px_zs = []
for i in range(self.n_views):
px_z = self.decoders[i](qz_xs[0].loc)
px_zs.append(px_z)
return [px_zs]
def forward(self, x):
r"""Apply encode and decode methods to input data to generate the joint latent dimensions and data reconstructions.
Args:
x (list): list of input data of type torch.Tensor.
Returns:
fwd_rtn (dict): dictionary containing encoding and decoding distributions.
"""
qz_xs = self.encode(x)
px_zs = self.decode(qz_xs)
fwd_rtn = {"px_zs": px_zs, "qz_xs": qz_xs}
return fwd_rtn
def loss_function(self, x, fwd_rtn):
r"""Calculate MVTCAE loss.
Args:
x (list): list of input data of type torch.Tensor.
fwd_rtn (dict): dictionary containing encoding and decoding distributions.
Returns:
losses (dict): dictionary containing each element of the MVTCAE loss.
"""
px_zs = fwd_rtn["px_zs"]
qz_xs = fwd_rtn["qz_xs"]
rec_weight = (self.n_views - self.alpha) / self.n_views
cvib_weight = self.alpha / self.n_views
vib_weight = 1 - self.alpha
grp_kl = self.calc_kl_groupwise(qz_xs)
cvib_kl = self.calc_kl_cvib(qz_xs)
ll = self.calc_ll(x, px_zs)
kld_weighted = cvib_weight * cvib_kl + vib_weight * grp_kl
total = -rec_weight * ll + self.beta * kld_weighted
losses = {"loss": total, "kl_cvib": cvib_kl, "kl_grp": grp_kl, "ll": ll}
return losses
def calc_kl_cvib(self, qz_xs):
r"""Calculate KL-divergence between PoE joint encoding distribution and the encoding distribution for each view.
Args:
qz_xs (list): list of encoding distributions of each view.
Returns:
kl (torch.Tensor): KL-divergence loss.
"""
mu = [qz_x.loc for qz_x in qz_xs]
var = [qz_x.variance for qz_x in qz_xs]
mu = torch.stack(mu)
var = torch.stack(var)
mu, logvar = ProductOfExperts()(mu, torch.log(var))
kl = 0
for i in range(self.n_views):
kl += (
hydra.utils.instantiate(
eval(f"self.cfg.encoder.enc{i}.enc_dist"), loc=mu, scale=logvar.exp().pow(0.5)
)
.kl_divergence(qz_xs[i]).sum(1, keepdims=True).mean(0)
)
return kl
def calc_kl_groupwise(self, qz_xs):
r"""Calculate KL-divergence between the encoding distribution for each view and the prior distribution.
Args:
qz_xs (list): list of encoding distributions of each view.
Returns:
kl (torch.Tensor): KL-divergence loss.
"""
mu = [qz_x.loc for qz_x in qz_xs]
var = [qz_x.variance for qz_x in qz_xs]
mu = torch.stack(mu)
var = torch.stack(var)
mu, logvar = ProductOfExperts()(mu, torch.log(var))
return (
hydra.utils.instantiate(
self.cfg.encoder.default.enc_dist, loc=mu, scale=logvar.exp().pow(0.5)
)
.kl_divergence(self.prior).sum(1, keepdims=True).mean(0)
)
def calc_ll(self, x, px_zs):
r"""Calculate log-likelihood loss.
Args:
x (list): list of input data of type torch.Tensor.
px_zs (list): list of decoding distributions.
Returns:
ll (torch.Tensor): Log-likelihood loss.
"""
ll = 0
for i in range(self.n_views):
ll += px_zs[0][i].log_likelihood(x[i]).mean(0).sum() #first index is latent, second index is view
return ll
| 217 | 36.97 | 162 | 24 | 1,972 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_ef488c1853069b67_1cc85e11", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 65, "line_end": 65, "column_start": 21, "column_end": 62, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpr7mo7ysm/ef488c1853069b67.py", "start": {"line": 65, "col": 21, "offset": 2711}, "end": {"line": 65, "col": 62, "offset": 2752}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_ef488c1853069b67_26c9881c", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 177, "line_end": 177, "column_start": 21, "column_end": 62, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpr7mo7ysm/ef488c1853069b67.py", "start": {"line": 177, "col": 21, "offset": 6800}, "end": {"line": 177, "col": 62, "offset": 6841}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"CWE-95",
"CWE-95"
] | [
"rules.python.lang.security.audit.eval-detected",
"rules.python.lang.security.audit.eval-detected"
] | [
"security",
"security"
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"LOW",
"LOW"
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"MEDIUM",
"MEDIUM"
] | [
65,
177
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65,
177
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21,
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"Detected the use of eval(). eval() can be dangerous if used... | [
5,
5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | mvtcae.py | /multiviewae/models/mvtcae.py | alawryaguila/multi-view-AE | MIT | |
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} | 3.0625 | stackv2 | #!/usr/bin/env python
"""Measure performance for 3 cases:
1. dict has key at the start of list
2. dict has key at the end of list
3. dict has no key in a list
See http://stackoverflow.com/questions/1737778/dict-has-key-from-list
"""
from functools import wraps
from itertools import imap
def to_compare(function):
"""Decorator to add `function` to global comparison registry.
NOTE: It changes interface of the `function` in order to use make-figure.py
"""
if not hasattr(to_compare, 'functions'):
to_compare.functions = []
@wraps(function)
def wrapper(args): # transform interface for make-figure.py
return function(args[0], args[1])
to_compare.functions.append(wrapper)
return wrapper
@to_compare
def mgag_loop(myDict, myList):
for i in myList:
if i in myDict:
return True
return False
@to_compare
def ronny_any(myDict, myList):
return any(x in myDict for x in myList)
@to_compare
def ronny_set(myDict, myList):
return set(myDict) & set(myList)
@to_compare
def pablo_len(myDict, myList):
return len([x for x in myList if x in myDict]) > 0
@to_compare
def jfs_map(my_dict, my_list):
return any(map(my_dict.__contains__, my_list))
@to_compare
def jfs_imap(my_dict, my_list):
return any(imap(my_dict.__contains__, my_list))
def args_key_at_start(n):
'Make args for comparison functions "key at start" case.'
d, lst = args_no_key(n)
lst.insert(0, n//2)
assert (n//2) in d and lst[0] == (n//2)
return (d, lst)
def args_key_at_end(n):
'Make args for comparison functions "key at end" case.'
d, lst = args_no_key(n)
lst.append(n//2)
assert (n//2) in d and lst[-1] == (n//2)
return (d, lst)
def args_no_key(n):
'Make args for comparison functions "no key" case.'
d = dict.fromkeys(xrange(n))
lst = range(n, 2*n+1)
assert not any(x in d for x in lst)
return (d, lst)
if __name__ == '__main__':
from subprocess import check_call
import sys
# check that all function produce expected result
assert all(f(make_args(5))
for f in to_compare.functions
for make_args in [args_key_at_start, args_key_at_end])
assert not any(f(make_args(5))
for f in to_compare.functions
for make_args in [args_no_key])
# measure performance and plot it
check_call(
["python", "make-figures.py"] +
["--sort-function=main." + f.__name__ for f in to_compare.functions] +
["--sequence-creator=main." + f.__name__
for f in (args_key_at_start, args_key_at_end, args_no_key)] +
sys.argv[1:])
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"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
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] | [
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96
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5
] | [
22
] | [
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] | [
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] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | snippet.py | /all-gists/235395/snippet.py | gistable/gistable | MIT | |
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} | 2.421875 | stackv2 | #!/usr/bin/python
# import cgitb
# cgitb.enable()
import sys; import os
sys.path.insert(0, os.path.abspath('..'))
sys.path.insert(0, os.path.abspath('.'))
import psycopg2
import re
from Utils.Globals import *
class DataSource:
def __init__(self):
"""
Create a DataSource object
:return: None
"""
db = database
try:
# create a connection to event_detection database
conn = psycopg2.connect(user='root', database=db)
conn.autocommit = True
except:
print("Error: cannot connect to event_detection database")
sys.exit()
try:
self.cursor = conn.cursor()
except:
print("Error: cannot create cursor")
sys.exit()
def get_unprocessed_queries(self):
"""
Gets all queries from the database that are not yet marked as processed
:return: all unprocessed queries
"""
self.cursor.execute("SELECT q.id, q.subject, q.verb, q.direct_obj, q.indirect_obj, q.loc \
FROM queries q \
WHERE q.processed = false")
return self.cursor.fetchall()
def get_unprocessed_query_article_pairs(self):
"""
Gets all query-article pairs that are not marked as processed
:return: all unprocessed query-article pairs
"""
self.cursor.execute("SELECT qa.query, qa.article FROM query_articles qa\
WHERE qa.processed = false")
return self.cursor.fetchall()
def get_query_synonyms(self, query_id):
"""
Gets information about a query
:param query_id: the query to retrieve synonyms for
:return: word, pos, sense and synonyms for the query
"""
self.cursor.execute("SELECT word, pos, sense, synonyms FROM query_words WHERE query=%s", (query_id,))
return self.cursor.fetchall()
def get_article_keywords(self, article_id):
"""
Gets keywords for an article
:param article_id: the id to retrieve keywords for
:return: the keywords for the article
"""
self.cursor.execute("SELECT keywords FROM articles WHERE id=%s", (article_id, ))
words = self.cursor.fetchone()
return words
def get_all_article_keywords(self):
"""
Gets keywords for all articles
:return: the keywords for all articles
"""
self.cursor.execute("SELECT keywords FROM articles WHERE keywords IS NOT null;")
return self.cursor.fetchall()
def get_all_titles_and_keywords(self):
"""
Gets titles and keywords for all articles
Does not retrieve these if the keywords are null (article unprocessed)
:return: titles and keywords for all articles
"""
self.cursor.execute("SELECT title, keywords FROM articles WHERE keywords IS NOT null;")
return self.cursor.fetchall()
def get_all_article_ids_and_keywords(self):
"""
Gets ids and keywords for all articles
Does not retrieve these if the keywords are null (article unprocessed)
:return: ids and keywords for all articles
"""
self.cursor.execute("SELECT id, keywords FROM articles WHERE keywords IS NOT null;")
return self.cursor.fetchall()
def get_articles(self):
"""
Gets all article ids
:return: ids for all articles
"""
self.cursor.execute("SELECT id FROM articles")
return self.cursor.fetchall()
def get_all_article_ids_and_filenames(self):
"""
Gets ids and filenames for all articles
:return: ids and filenames for all articles
"""
self.cursor.execute("SELECT id, filename FROM articles;")
return self.cursor.fetchall()
def get_article_ids_titles_filenames(self):
"""
Gets ids, titles and filenames for all articles
:return: ids, titles and filenames for all articles
"""
self.cursor.execute("SELECT id, title, filename FROM articles;")
return self.cursor.fetchall()
def insert_query_word_synonym(self, query_id, query_word, pos_group, synonyms):
"""
Inserts information about a query into query words
:param query_id: the id of the query
:param query_word: the word from the query
:param pos_group: to POS for the query word
:param synonyms: the synonyms for the query word
:return: None
"""
self.cursor.execute("INSERT INTO query_words (query, word, pos, sense, synonyms) VALUES (%s, %s ,%s, '',%s)", \
(query_id, query_word, pos_group, synonyms))
def post_validator_update(self, matching_prob, query_id, article_id):
"""
Updates query articles after the validator is run
:param matching_prob: the probability of the match
:param query_id: the query id
:param article_id: the article id
:return: None
"""
self.cursor.execute("UPDATE query_articles SET processed=true, accuracy=%s WHERE query=%s AND article=%s",\
(matching_prob, query_id, article_id))
def post_query_processor_update(self, query_id):
"""
Sets a query to processed in the database
This involves setting it to processed in the queries table and adding a row with it and all articles
in the query_articles table
:param query_id: the query id
:return: None
"""
self.cursor.execute("UPDATE queries SET processed=true WHERE id=%s", (query_id, ))
for article_id in self.get_articles():
self.cursor.execute("INSERT INTO query_articles (query, article) VALUES (%s, %s) ON CONFLICT DO NOTHING", (query_id, article_id))
def get_query_elements(self, query_id):
"""
Gets the subject, verb, direct object, indirect object and location for a query
:param query_id: the query id
:return: the subject, verb, direct object, indirect object and location
"""
self.cursor.execute("SELECT subject, verb, direct_obj, indirect_obj, loc FROM queries WHERE id=%s", (query_id, ))
elements = self.cursor.fetchone()
elements = [element for element in elements if element is not None or element is not ""]
return elements
def get_article_url(self, article_id):
"""
Gets the URL for an article
:param article_id: the article id
:return: the article URL
"""
self.cursor.execute("SELECT url FROM articles WHERE id=%s", (article_id, ))
return str(self.cursor.fetchone()[0])
def get_article_title(self, article_id):
"""
Gets the title for an article
:param article_id: the article id
:return: the article title
"""
self.cursor.execute("SELECT title FROM articles WHERE id=%s", (article_id, ))
return str(self.cursor.fetchone()[0])
def get_email_and_phone(self, query_id):
"""
Gets the article and phone number associated to a query
:param query_id: the query id
:return: the phone number and email
"""
self.cursor.execute("SELECT userid FROM queries WHERE id="+str(query_id))
user_id = self.cursor.fetchone()[0]
self.cursor.execute("SELECT phone FROM users WHERE id="+str(user_id))
phone = str(self.cursor.fetchone()[0])
if phone is not None:
phone = re.sub(r'-', '', phone)
phone = "+1" + phone
self.cursor.execute("SELECT email FROM users WHERE id="+str(user_id))
email = str(self.cursor.fetchone()[0])
return phone, email
def get_unprocessed_articles(self):
"""
Gets all unprocessed articles that need keyword extraction to be performed
:return: id, title, filename, url and source for all unprocessed articles
"""
self.cursor.execute("SELECT id, title, filename, url, source FROM articles WHERE keywords is null;")
return self.cursor.fetchall()
def add_keywords_to_article(self, article_id, keyword_string):
"""
Adds keyword JSON string to an article
:param article_id: the article id
:param keyword_string: the JSON string of keywords
:return: None
"""
self.cursor.execute("UPDATE articles SET keywords = %s WHERE id = %s", (keyword_string, article_id))
def article_processed(self, article_id):
"""
Checks if an article has been processed
:param article_id: the id of the article
:return: True if the article has been processed, False otherwise
"""
self.cursor.execute("SELECT keywords FROM articles WHERE id = %s;", (article_id, ))
return self.cursor.fetchone()[0] is not None
def query_route(self, query_id):
"""
Gets a query for web app with validating article counts
:param query_id: the id of the query
:return: the query
"""
self.cursor.execute("SELECT a.title, s.source_name as source, a.url \
FROM queries q \
INNER JOIN query_articles qa on q.id = qa.query \
INNER JOIN articles a on qa.article = a.id \
INNER JOIN sources s on s.id = a.source \
WHERE q.id = %s and qa.notification_sent = true;", (query_id,))
articles = self.cursor.fetchall()
self.cursor.execute("SELECT id, subject, verb, direct_obj, indirect_obj, loc FROM queries where id = %s;", (query_id,))
query = self.cursor.fetchone()
return articles, query
def queries_route(self):
"""
Gets all queries for web app with validating article counts
:return: all queries
"""
self.cursor.execute("SELECT q.id, q.subject, q.verb, q.direct_obj, q.indirect_obj, \
q.loc, count(qa.article) as article_count \
FROM queries q \
LEFT JOIN query_articles qa on q.id = qa.query and qa.notification_sent = true \
GROUP BY(q.id);")
return self.cursor.fetchall()
def new_query(self, email, phone, subject, verb, direct_obj, indirect_obj, loc):
"""
Add a query to the database for a user
:param email: the user's email
:param phone: the user's phone number
:param subject: the query subject
:param verb: the query verb
:param direct_obj: the query direct object
:param indirect_obj: the query indirect object
:param loc: the query location
:return: True if no error
"""
self.cursor.execute("SELECT id from users where email = %s and phone = %s", (email, phone))
# use existing user if it exists
user_id = self.cursor.fetchone()
if user_id:
user_id = user_id[0]
else:
self.cursor.execute("INSERT INTO users (email, phone) VALUES (%s, %s) RETURNING id;", (email, phone))
user_id = self.cursor.fetchone()[0]
try:
self.cursor.execute("INSERT INTO queries (subject, verb, direct_obj, indirect_obj, loc, userid) \
VALUES (%s, %s, %s, %s, %s, %s);", (subject, verb, direct_obj, indirect_obj, loc, user_id))
except psycopg2.IntegrityError:
return False
return True
def add_article_to_query_articles(self, article_id):
self.cursor.execute("SELECT id FROM queries;")
query_ids = self.cursor.fetchall()
for query_id in query_ids:
self.cursor.execute("INSERT INTO query_articles (query, article) VALUES (%s, %s) ON CONFLICT DO NOTHING", (query_id, article_id))
# query | article | accuracy | processed
def articles_route(self):
"""
Gets all queries for web app with source name strings
:return: the article titles, source names and URLs
"""
self.cursor.execute("SELECT title, s.source_name as source, url FROM articles a \
INNER JOIN sources s on s.id = a.source;")
return self.cursor.fetchall()
| 301 | 39.76 | 142 | 15 | 2,565 | python | [{"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_a7fb2255c31a2634_4d602ae4", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "remediation": "", "location": {"file_path": "unknown", "line_start": 192, "line_end": 192, "column_start": 9, "column_end": 82, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "title": null}, {"url": "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "title": null}, {"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "path": "/tmp/tmpr7mo7ysm/a7fb2255c31a2634.py", "start": {"line": 192, "col": 9, "offset": 7277}, "end": {"line": 192, "col": 82, "offset": 7350}, "extra": {"message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. 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In most cases, SQLAlchemy ORM will be a better option.", "metadata": {"cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column"], "category": "security", "technology": ["sqlalchemy"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_a7fb2255c31a2634_60cdbc08", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "remediation": "", "location": {"file_path": "unknown", "line_start": 194, "line_end": 194, "column_start": 9, "column_end": 78, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "title": null}, {"url": "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "title": null}, {"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "path": "/tmp/tmpr7mo7ysm/a7fb2255c31a2634.py", "start": {"line": 194, "col": 9, "offset": 7403}, "end": {"line": 194, "col": 78, "offset": 7472}, "extra": {"message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "metadata": {"cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column"], "category": "security", "technology": ["sqlalchemy"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_a7fb2255c31a2634_61aa5639", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "remediation": "", "location": {"file_path": "unknown", "line_start": 199, "line_end": 199, "column_start": 9, "column_end": 78, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "title": null}, {"url": "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "title": null}, {"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "path": "/tmp/tmpr7mo7ysm/a7fb2255c31a2634.py", "start": {"line": 199, "col": 9, "offset": 7635}, "end": {"line": 199, "col": 78, "offset": 7704}, "extra": {"message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "metadata": {"cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column"], "category": "security", "technology": ["sqlalchemy"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 3 | true | [
"CWE-89",
"CWE-89",
"CWE-89"
] | [
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query",
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query",
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query"
] | [
"security",
"security",
"security"
] | [
"LOW",
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] | [
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"HIGH"
] | [
192,
194,
199
] | [
192,
194,
199
] | [
9,
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78,
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"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expre... | [
7.5,
7.5,
7.5
] | [
"LOW",
"LOW",
"LOW"
] | [
"HIGH",
"HIGH",
"HIGH"
] | DataSource.py | /event-detection-master/Utils/DataSource.py | a-raina/Event-Detection-using-NLP | MIT | |
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} | 2.421875 | stackv2 | import copy
import json
import logging
import os
import uuid
import subprocess
from omniscient.structure.query_graph import QueryGraph
from omniscient.structure.stage import Stage
from omniscient.structure.sentence import Sentence
from omniscient.structure.mention import Mention
from omniscient.structure import constant
try:
from omniscient.kg.tdb_query import TDBQuery
except:
pass
TMP_DIR = "sparql_tmp"
LOGGER = logging.getLogger("QueryGraphUtils")
LOGGER.setLevel(logging.INFO)
def reverse_direction(direction):
if direction == constant.P_FORWARD:
return constant.P_BACKWARD
if direction == constant.P_BACKWARD:
return constant.P_FORWARD
raise ValueError("Error argument on {}".format(direction))
class QueryGraphUtils(object):
def __init__(
self,
use_tdb_query=False,
kb_type=None,
kb_index_path=None):
self.use_tdb_query = use_tdb_query
self.kb_type = kb_type
self.kb_index_path = kb_index_path
self.query_client = None
if use_tdb_query and kb_type and kb_index_path:
self.query_client = TDBQuery(path=self.kb_index_path)
def sparql_to_json(self, sparql):
"""
Args:
sparql:
Returns:
"""
if not os.path.exists(TMP_DIR):
os.mkdir(TMP_DIR)
tmp_file_path = os.path.join(TMP_DIR, str(uuid.uuid4()))
with open(tmp_file_path, "w") as query_fout:
refined_sparql = "PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>\n{}\n".format(
sparql.strip().replace(" OR ", " || "))
query_fout.write(refined_sparql)
json_string = subprocess.check_output(
'sparql-to-json {}'.format(tmp_file_path), shell=True).decode("utf-8")
json_dict = json.loads(json_string)
os.remove(tmp_file_path)
return json_dict, refined_sparql
def json_to_graph(self, json_dict, sparql=None):
"""
This function is to convert the json dict into
`QueryGraph`
Args:
json_dict (dict): the output of sparql2json
Returns: QueryGraph
"""
query_graph = QueryGraph(sparql)
for where_args in json_dict["where"]:
if where_args["type"] == "bgp":
for triple in where_args["triples"]:
query_graph.add_edge((triple["subject"], triple["predicate"], triple["object"]))
return query_graph
def sparql_to_graph(self, sparql, is_grounding=False, grounded_results=None):
"""
This function is to convert full sparql query into
`QueryGraph`
Args:
sparql (str): sparql query
Returns: Tuple(json_dict, `QueryGraph`)
"""
sparql_parse_json, refined_sparql = self.sparql_to_json(sparql=sparql)
graph = self.json_to_graph(json_dict=sparql_parse_json, sparql=refined_sparql)
if is_grounding:
if grounded_results:
graph.grounding(grounded_results=grounded_results)
elif self.query_client:
results = self.query_client.query(refined_sparql.replace(
"DISTINCT ?x", "DISTINCT *").encode("utf-8"))
if results:
graph.grounding(grounded_results=results)
else:
LOGGER.info("grounding failed with \n{}\n".format(refined_sparql))
else:
raise ValueError("Grounded results are needed or the query client should be initialized")
return sparql_parse_json, graph
def batch_grounding(self, graphs):
"""
Args:
graphs: Batching all graphs for parallel grounding
Returns:
"""
raise NotImplementedError
def apply_action(self, query_graph, action):
"""
Apply the action on a graph.
We use the value of standpoint(Vertex), predicate(Edge) and target(Vertex) build
the query graph step by step.
We will not reuse the Vertex and Edge object because the `id` might be different
from the original graph
Args:
query_graph (:obj:QueryGraph): Partial query graph
action (:obj:Action): The action would be applied to the query graph
Returns: QueryGraph
"""
query_graph_new = copy.deepcopy(query_graph)
if action.p_direction == constant.P_FORWARD:
query_graph_new.add_edge((
action.standpoint.value,
action.predicate.value,
action.target.value))
elif action.p_direction == constant.P_BACKWARD:
query_graph_new.add_edge((
action.target.value,
action.predicate.value,
action.standpoint.value))
return query_graph_new
def query_graph_stage_generation(self, sentence, query_graph):
"""
This function is to convert the `query_graph` (using the actions)
into list of `stages`.
Args:
sentence (str)
query_graph (QueryGraph)
Returns: List[Stage]
"""
actions = query_graph.graph_to_actions()
query_graph = QueryGraph()
stages = []
variable_pool = []
sent = Sentence(sentence)
black_predicate_dict = {}
for action in actions:
# TODO: fix the mention here
if action.standpoint.type == constant.URI:
mention = None
else:
mention = None
query_graph_new = self.apply_action(query_graph, action)
black_predicate_dict_ = copy.deepcopy(black_predicate_dict)
stage = Stage(
sentence=sent,
query_graph=query_graph_new,
standpoint=action.standpoint,
variable_pool=copy.deepcopy(variable_pool),
mention=mention,
gold_predicate=action.predicate,
action=action,
black_predicate_dict=black_predicate_dict_)
if action.standpoint.value not in black_predicate_dict:
black_predicate_dict[action.standpoint.value] = []
black_predicate_dict[action.standpoint.value].append((action.predicate.value, action.p_direction))
if action.target.value not in black_predicate_dict:
black_predicate_dict[action.target.value] = []
black_predicate_dict[action.target.value].append((action.predicate.value, reverse_direction(action.p_direction)))
stages.append(stage)
if action == constant.GEN_VAR:
variable_pool.append(len(variable_pool))
"""Update the variable pool"""
query_graph = query_graph_new
return stages
def retrieve_neighbourhood_with_batch_graph(self, graphs, output_path):
"""
Because of the problem of parallel TDBQuery, this will stage
all the results in memory.
Args:
graphs:
output_path:
Returns:
"""
raise NotImplementedError
def retrieve_forward_neighbourhood_with_entity(self, entity):
forward_result = self.query_client.query(
constant.FORWARD_QUERY_TEMPLATE.format("<{}>".format(entity)).encode("utf-8"))
return forward_result
def retrieve_backward_neighbourhood_with_entity(self, entity):
backward_result = self.query_client.query(
constant.BACKWARD_QUERY_TEMPLATE.format("<{}>".format(entity)).encode("utf-8"))
return backward_result
def retrieve_neighbourhood_with_entity_list(self, entity_list, output_path=None, num_threads=30):
batch_forward_queries = []
batch_backward_queries = []
for entity in entity_list:
batch_forward_queries.append(
constant.FORWARD_QUERY_TEMPLATE.format("<{}>".format(entity)).encode("utf-8"))
batch_backward_queries.append(
constant.BACKWARD_QUERY_TEMPLATE.format("<{}>".format(entity)).encode("utf-8"))
if self.query_client:
forward_results = self.query_client.parallel_query(batch_forward_queries, num_threads=num_threads)
backward_results = self.query_client.parallel_query(batch_backward_queries, num_threads=num_threads)
else:
raise ValueError("The query client is not initialized")
if output_path:
with open(output_path, "w") as fout:
for entity, forward_result, backward_result in zip(entity_list, forward_results, backward_results):
fout.write(json.dumps({
entity: {
"forward_result": forward_result,
"backward_result": backward_result }}) + "\n")
else:
return forward_results, backward_results
def is_valid_predicate(self, predicate):
if (predicate.startswith("http://rdf.freebase.com/ns/common") or
predicate.startswith("http://rdf.freebase.com/ns/type") or
predicate.startswith("http://rdf.freebase.com/key")):
return False
return True
if __name__ == "__main__":
utils = QueryGraphUtils()
query_graph = QueryGraph()
query_graph.add_edge((
"?c",
"http://rdf.freebase.com/ns/location.country.administrative_divisions",
"http://rdf.freebase.com/ns/m.010vz"))
query_graph.add_edge((
"?c",
"http://rdf.freebase.com/ns/government.governmental_jurisdiction.governing_officials",
"?y"))
query_graph.add_edge((
"?y",
"http://rdf.freebase.com/ns/government.government_position_held.office_holder",
"?x"))
query_graph.add_edge((
"?y",
"http://rdf.freebase.com/ns/government.government_position_held.basic_title",
"http://rdf.freebase.com/ns/m.060c4"))
query_graph_stages = utils.query_graph_stage_generation(
sentence="Who was the president in 1980 of the country that has Azad Kashmir?",
query_graph=query_graph)
pair = False
for stage in query_graph_stages:
if pair:
stage_examples = stage.to_training_example()
else:
stage_examples = stage.to_testing_example()
print(stage_examples) | 271 | 33.18 | 119 | 23 | 2,103 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_b4772ae019a32771_44ecac82", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 54, "line_end": 54, "column_start": 10, "column_end": 34, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/b4772ae019a32771.py", "start": {"line": 54, "col": 10, "offset": 1335}, "end": {"line": 54, "col": 34, "offset": 1359}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_b4772ae019a32771_3fc48c28", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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"CWE-78"
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] | [
"security",
"security"
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"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH"
] | [
58,
59
] | [
59,
59
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19,
56
] | [
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60
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"Found 'subprocess'... | [
7.5,
7.5
] | [
"LOW",
"HIGH"
] | [
"HIGH",
"LOW"
] | query_graph_utils.py | /omniscient/utils/query_graph_utils.py | Impavidity/Omniscient | Apache-2.0 | |
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} | 2.328125 | stackv2 | import pickle
from datetime import datetime
import numpy as np
import pandas as pd
import xarray as xr
import yaml
from vmodel.util.util import clean_attrs
def generate_filename(args):
# Construct output file name
time_str = datetime.now().strftime('%Y-%m-%d-%H-%M-%S')
fnamedict = {
'agents': args.num_agents,
'runs': args.num_runs,
'times': args.num_timesteps,
'dist': args.ref_distance,
'perc': args.perception_radius,
'topo': args.max_agents,
'rngstd': args.range_std,
}
formatexts = {'netcdf': 'nc', 'pickle': 'pkl'}
args_str = '_'.join(f'{k}_{v}' for k, v in fnamedict.items())
return f'{time_str}_{args_str}.states.{formatexts[args.format]}'
def create_dataset(datas, args):
ds = xr.Dataset()
# Clean up attrs dict to be compatible with YAML and NETCDF
ds.attrs = clean_attrs(vars(args))
time = np.array(datas[0].time)
pos = np.array([d.pos for d in datas])
vel = np.array([d.vel for d in datas])
coord_run = np.arange(args.num_runs, dtype=int) + 1
coord_time = pd.to_timedelta(time, unit='s')
coord_agent = np.arange(args.num_agents, dtype=int) + 1
coord_space = np.array(['x', 'y'])
coords_rtas = {
'run': coord_run,
'time': coord_time,
'agent': coord_agent,
'space': coord_space
}
dapos = xr.DataArray(pos, dims=coords_rtas.keys(), coords=coords_rtas)
dapos.attrs['units'] = 'meters'
dapos.attrs['long_name'] = 'position'
ds['position'] = dapos
davel = xr.DataArray(vel, dims=coords_rtas.keys(), coords=coords_rtas)
davel.attrs['units'] = 'meters/second'
davel.attrs['long_name'] = 'velocity'
ds['velocity'] = davel
ds = ds.transpose('run', 'agent', 'space', 'time')
# Return only state (position and velocity)
if args.no_save_precomputed:
return ds
coords_rtaa = {
'run': coord_run,
'time': coord_time,
'agent': coord_agent,
'agent2': coord_agent
}
vis = np.array([d.vis for d in datas])
davis = xr.DataArray(vis, dims=coords_rtaa.keys(), coords=coords_rtaa)
davis.attrs['units'] = 'boolean'
davis.attrs['long_name'] = 'visibility'
ds['visibility'] = davis
# Tranpose to match data generated from Gazebo
ds = ds.transpose('run', 'agent', 'agent2', 'space', 'time')
return ds
def save_dataset(ds, fname, args):
if args.format == 'pickle':
with open(fname, 'wb') as f:
pickle.dump(ds, f, protocol=pickle.HIGHEST_PROTOCOL)
elif args.format == 'netcdf':
comp = dict(zlib=True, complevel=5)
encoding = None if args.no_compress else {v: comp for v in ds.data_vars}
ds.to_netcdf(fname, encoding=encoding)
with open(f'{fname}.yaml', 'w') as f:
yaml.dump(ds.attrs, f)
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] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | dataset.py | /vmodel/dataset.py | lis-epfl/vmodel | MIT | |
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} | 2.359375 | stackv2 | #!/usr/bin/env python
#
# Wrapper on pyinotify for running commands
# (c) 2009 Peter Bengtsson, peter@fry-it.com
#
# TODO: Ok, now it does not start a command while another is runnnig
# But! then what if you actually wanted to test a modification you
# saved while running another test
# Yes, we could stop the running command and replace it by the new test
# But! django tests will complain that a test db is already here
import argparse
import os
from subprocess import Popen
from threading import Lock, Thread
__version__='1.6'
class SettingsClass(object):
VERBOSE = False
settings = SettingsClass()
try:
from pyinotify import WatchManager, Notifier, ThreadedNotifier, ProcessEvent, EventsCodes
except ImportError:
print "pyinotify not installed. Try: easy_install pyinotify"
raise
def _find_command(path):
# path is a file
assert os.path.isfile(path)
# in dictionary lookup have keys as files and directories.
# if this path exists in there, it's a simple match
try:
return lookup[path]
except KeyError:
pass
# is the parent directory in there?
while path != '/':
path = os.path.dirname(path)
try:
return lookup[path]
except KeyError:
pass
def _ignore_file(path):
if path.endswith('.pyc'):
return True
if path.endswith('~'):
return True
basename = os.path.basename(path)
if basename.startswith('.#'):
return True
if basename.startswith('#') and basename.endswith('#'):
return True
if '.' in os.path.basename(path) and \
basename.split('.')[-1] in settings.IGNORE_EXTENSIONS:
return True
if os.path.split(os.path.dirname(path))[-1] in settings.IGNORE_DIRECTORIES:
return True
if not os.path.isfile(path):
return True
class PTmp(ProcessEvent):
def __init__(self):
super(PTmp, self).__init__()
self.lock = Lock()
def process_IN_CREATE(self, event):
if os.path.basename(event.pathname).startswith('.#'):
# backup file
return
print "Creating:", event.pathname
command = _find_command(event.pathname)
#def process_IN_DELETE(self, event):
# print "Removing:", event.pathname
# command = _find_command(event.pathname)
def process_IN_MODIFY(self, event):
if _ignore_file(event.pathname):
return
def execute_command(event, lock):
# By default trying to acquire a lock is blocking
# In this case it will create a queue of commands to run
#
# If you try to acquire the lock in the locked state non-blocking
# style, it will immediatly returns False and you know that a
# command is already running, and in this case we don't want to run
# this command at all.
block = settings.RUN_ON_EVERY_EVENT
if not lock.acquire(block):
# in this case we just want to not execute the command
return
print "Modifying:", event.pathname
command = _find_command(event.pathname)
if command:
if settings.VERBOSE:
print "Command: ",
print command
p = Popen(command, shell=True)
sts = os.waitpid(p.pid, 0)
lock.release()
command_thread = Thread(target=execute_command, args=[event, self.lock])
command_thread.start()
def start(actual_directories):
wm = WatchManager()
flags = EventsCodes.ALL_FLAGS
mask = flags['IN_MODIFY'] #| flags['IN_CREATE']
p = PTmp()
notifier = Notifier(wm, p)
for actual_directory in actual_directories:
print "DIRECTORY", actual_directory
wdd = wm.add_watch(actual_directory, mask, rec=True)
# notifier = Notifier(wm, p, timeout=10)
try:
print "Waiting for stuff to happen..."
notifier.loop()
except KeyboardInterrupt:
pass
return 0
lookup = {}
def configure_more(directories):
actual_directories = set()
#print "directories", directories
# Tune the configured directories a bit
for i, (path, cmd) in enumerate(directories):
if isinstance(path, (list, tuple)):
actual_directories.update(configure_more(
[(x, cmd) for x in path]))
continue
if not path.startswith('/'):
path = os.path.join(os.path.abspath(os.path.dirname('.')), path)
if not (os.path.isfile(path) or os.path.isdir(path)):
raise OSError, "%s neither a file or a directory" % path
path = os.path.normpath(path)
if os.path.isdir(path):
if path.endswith('/'):
# tidy things up
path = path[:-1]
if path == '.':
path = ''
actual_directories.add(path)
else:
# because we can't tell pyinotify to monitor files,
# when a file is configured, add it's directory
actual_directories.add(os.path.dirname(path))
lookup[path] = cmd
return actual_directories
def get_settings_file():
"""Return a setting file path or exit if not passed in and no
defaults settings files are found.
"""
parser = argparse.ArgumentParser(description="Gorun")
path_files = [os.path.expanduser('~/.gorun_settings.py'),
os.path.expanduser('~/.gorunsettings.py')]
parser.add_argument('-c', '--conf', help='Full path to the configuration file')
ns = parser.parse_args()
settings_file = None
if ns.conf:
settings_file = ns.conf
else:
for path in path_files:
if os.path.isfile(path):
settings_file = path
print("Using configuration file %s" % settings_file)
break
if settings_file is None:
parser.print_help()
sys.exit(1)
return settings_file
if __name__ == '__main__':
import sys
import imp
settings_file = get_settings_file()
sys.path.append(os.path.abspath(os.curdir))
x = imp.load_source('gorun_settings', settings_file)
settings.DIRECTORIES = x.DIRECTORIES
settings.VERBOSE = getattr(x, 'VERBOSE', settings.VERBOSE)
settings.IGNORE_EXTENSIONS = getattr(x, 'IGNORE_EXTENSIONS', tuple())
settings.IGNORE_DIRECTORIES = getattr(x, 'IGNORE_DIRECTORIES', tuple())
settings.RUN_ON_EVERY_EVENT = getattr(x, 'RUN_ON_EVERY_EVENT', False)
actual_directories = configure_more(settings.DIRECTORIES)
sys.exit(start(actual_directories))
| 213 | 30.44 | 93 | 17 | 1,461 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_7fb489c6284f572d_2320a828", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 106, "line_end": 106, "column_start": 21, "column_end": 47, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/7fb489c6284f572d.py", "start": {"line": 106, "col": 21, "offset": 3350}, "end": {"line": 106, "col": 47, "offset": 3376}, "extra": {"message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
106
] | [
106
] | [
21
] | [
47
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | gorun.py | /gorun.py | AndreaCrotti/python-gorun | Python-2.0 | |
2024-11-18T20:57:33.584756+00:00 | 1,579,511,800,000 | e0989b47c11bccf0129df1d9fdccf909c0b12db9 | 3 | {
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"is_vendor": false,
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"license_type": "permissive",
"path": "/vicorrect/model/add_accents.py",
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"repo_name": "lvhanh270597/correct_vietnamese_sentence",
"revision_date": 1579511800000,
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"visit_date": "2020-05-07T06:05:03.715647"
} | 2.828125 | stackv2 | import pickle
from vicorrect.machine_learning.hmm import HiddenMarkovModel
class CorrectVietnameseSentence():
def __init__(self, listNgrams=[2, 3, 4], eta=0.000001, verbose=True):
self.__listNgrams = listNgrams
self.__eta = eta
self.__loaded = False
self.__verbose = verbose
def load(self, filePath):
try:
self.__model = pickle.load(open(filePath, 'rb'))
self.__loaded = True
print("OK!")
except Exception as E:
print("Error: %s" % E)
return None
def __initModel(self):
self.__model = HiddenMarkovModel(self.__listNgrams, self.__eta, self.__verbose)
def fit(self, data):
if self.__loaded:
print("Done!")
return
self.__initModel()
self.__model.setData(data)
self.__model.fit()
def predict(self, testcase, lim_per_index=[5], output_size=1):
return self.__model.fastPredict(testcase, lim_per_index, output_size)
def score(self, inp_list, label_list, list_of_indices=[5]):
return self.__model.score(inp_list, label_list, list_of_indices) | 35 | 27.51 | 81 | 15 | 278 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_78b95b93216200ec_aeb07195", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 13, "line_end": 13, "column_start": 19, "column_end": 52, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpr7mo7ysm/78b95b93216200ec.py", "start": {"line": 13, "col": 19, "offset": 338}, "end": {"line": 13, "col": 52, "offset": 371}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-502"
] | [
"rules.python.lang.security.deserialization.avoid-pickle"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
13
] | [
13
] | [
19
] | [
52
] | [
"A08:2017 - Insecure Deserialization"
] | [
"Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format."
] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | add_accents.py | /vicorrect/model/add_accents.py | lvhanh270597/correct_vietnamese_sentence | MIT | |
2024-11-18T20:57:34.271453+00:00 | 1,551,126,716,000 | 0913054b93ba0bb0e92294cb0b3721da80836989 | 2 | {
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"visit_date": "2020-04-22T18:57:51.490287"
} | 2.328125 | stackv2 | import os
import json
import subprocess
def ffprobe(fin, fout):
ffp_in = subprocess.check_output(['ffprobe', '-v', 'warning',
'-print_format', 'json',
'-show_streams',
'-show_format',
fin])
ffp_out = subprocess.check_output(['ffprobe', '-v', 'warning',
'-print_format', 'json',
'-show_streams',
'-show_format',
fout])
ffp_in = json.loads(ffp_in)
ffp_out = json.loads(ffp_out)
duration_in = int(ffp_in['format']['duration'].split('.')[0])
duration_out = int(ffp_out['format']['duration'].split('.')[0])
if duration_in == duration_out:
return True
else:
return False
def encode_c480(fin, fout):
if os.path.exists(fout):
os.remove(fout)
output = ""
cmd = ['ffmpeg',
'-i', fin,
'-r', '30',
'-s', 'hd480',
'-b:v', '1024k',
'-loglevel', 'quiet',
fout]
try:
subprocess.check_call(cmd)
except OSError:
output += "cmd ffmpeg not found. please install ffmpeg first."
return False, output
except subprocess.CalledProcessError as e:
output += "error converting. msg: {}".format(e)
return False, output
succeed = ffprobe(fin, fout)
if succeed:
output += "finished(480p)"
return True, output
else:
output += "failed(480p)"
return False, output
def encode_c720(fin, fout):
if os.path.exists(fout):
os.remove(fout)
output = ""
cmd = ['ffmpeg',
'-i', fin,
'-r', '30',
'-s', 'hd720',
'-b:v', '2048k',
'-loglevel', 'quiet',
fout]
try:
subprocess.check_call(cmd)
except OSError:
output += "cmd ffmpeg not found. please install ffmpeg first."
return False, output
except subprocess.CalledProcessError as e:
output += "error converting. msg: {}".format(e)
return False, output
succeed = ffprobe(fin, fout)
if succeed:
output += "finished(720p)"
return True, output
else:
output += "failed(480p)"
return False, output | 88 | 23.81 | 67 | 14 | 536 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_6dfa583feb614630_a83db6b9", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | [
43,
74
] | [
43,
74
] | [
3,
3
] | [
29,
29
] | [
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.",
"Detected subprocess ... | [
7.5,
7.5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | encode.py | /encode.py | ec500-software-engineering/exercise-2-ffmpeg-BrefCool | MIT | |
2024-11-18T20:57:34.958615+00:00 | 1,580,165,283,000 | 5626835ccc8b27583b60ffe1b08306d2d999e9c6 | 3 | {
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"src_encoding": "UTF-8",
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"url": "https://raw.githubusercontent.com/ahmed081/EgyBest-Downloader/271ef483e19ec5299f55b6ff8b4e4f3e55ee9424/egybest.py",
"visit_date": "2020-12-31T11:04:47.506470"
} | 2.609375 | stackv2 | import os
import sys
import requests
from bs4 import BeautifulSoup
from pySmartDL import SmartDL
from selenium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
class EgyBest:
search_base_url = "https://nero.egybest.site/explore/?q="
chrome_driver = None
def __init__(self):
self.search_url = None
self.content_url = None
self.content_type = None
self.content_name = None
self.chosen_seasons_numbers_list = []
self.chosen_seasons_url_list = []
self.chosen_episodes_number_list = []
self.chosen_episodes_url_list = []
self.downloadable_episodes_url_list = []
def reset(self):
self.__init__()
def get_search_url(self):
try:
self.search_url = self.search_base_url + \
self.get_string_input("What are you searching for ? :")
# print(self.search_url)
except:
exit("search url")
# function to get the download content
def get_content_url(self):
print("Searching for results !!!")
res = self.get_bs4_result(self.search_url, "a", "movie")
# Displaying the fitched linked
for i, link in enumerate(res, 1):
content_type = None
try:
content_type = self.get_url_type(link['href']).upper()
print(i, " ->", link.contents[4].text, ", Type : ", content_type, ",", "IMDB Rating :",
link.contents[0].i.i.text,'\n')
except:
print(i, " ->", link.contents[2].text,
", Type : ", content_type)
# looking for user choice
while res:
try:
self.content_url = res[self.get_int_input(
"Enter link number :") - 1]['href']
break
except:
retry = self.get_string_input(
"Non valid input ,retry ? (y/n) :")
if retry != "y":
self.content_type = None
return
if not res:
print("Didn't found a thing")
elif self.content_url:
self.content_type = self.get_url_type(self.content_url)
# initializing chrome drivers
def init_chrome_driver(self):
if not self.chrome_driver:
print("Initializing chrome driver")
try:
caps = DesiredCapabilities().CHROME
caps["pageLoadStrategy"] = "eager"
chrome_options = webdriver.ChromeOptions()
chrome_options.add_argument('--log-level=3')
chrome_options.add_argument('--disable-logging')
chrome_options.add_argument('--headless')
self.chrome_driver = webdriver.Chrome(executable_path="./Driver/chromedriver.exe",
options=chrome_options)
except:
print("Couldn't init chrome drivers")
self.exit("init_chrome")
# closing and destroying chrome driver instant
def destroy_chrome_driver(self):
try:
if self.chrome_driver is not None:
self.chrome_driver.close()
print("Driver Closed")
else:
print("Driver already closed")
except Exception as e:
print(e)
def gather_download_link(self):
self.init_chrome_driver()
print("Accessing EgyBest page")
self.chrome_driver.get(self.chosen_episodes_url_list[-1])
self.chose_quality()
print("Accessing the download page")
self.chrome_driver.close()
self.chrome_driver.switch_to.window(
self.chrome_driver.window_handles[0])
while 1:
try:
target_button = self.chrome_driver.find_element_by_xpath(
"/html/body/div[1]/div/p[2]/a[1]")
if not target_button.get_attribute("href"):
print("Closing ads tab")
target_button.click()
self.chrome_driver.switch_to.window(
self.chrome_driver.window_handles[1])
self.chrome_driver.close()
self.chrome_driver.switch_to.window(
self.chrome_driver.window_handles[0])
else:
print("Obtaining the download link")
url = target_button.get_attribute("href")
if url:
self.downloadable_episodes_url_list.append(url)
return
except Exception as e:
print(e)
self.chrome_driver.switch_to.window(
self.chrome_driver.window_handles[0])
def download_seasons(self, url=None):
if url is None:
url = self.content_url
res = self.get_bs4_result(url, "div", "movies_small")[0]
seasons_list = res.find_all("a")
number_of_seasons = len(seasons_list)
all_eps = False
while number_of_seasons:
print(F"There're {number_of_seasons} seasons ")
choice = self.get_string_input(
"Do you want to download all seasons or specific ones, type['all' or 'spec']:")
if choice == 'all':
all_eps = True
self.chosen_seasons_numbers_list = [
i for i in range(1, number_of_seasons + 1)]
break
elif choice == 'spec':
while 1:
chosen_number_seasons = self.get_int_input(
"Choose how many seasons :")
try:
if number_of_seasons >= chosen_number_seasons > 0:
break
except:
pass
print("Add the seasons you want to download")
for i in range(1, chosen_number_seasons + 1):
while 1:
choice = self.get_int_input(
F"{i} --> Choose a season from 1 to {number_of_seasons}:") if not None else 0
try:
if number_of_seasons >= choice >= 1:
print(F"Season {choice} Added")
self.chosen_seasons_numbers_list.append(choice)
break
else:
print("Non valid option")
except:
pass
break
print("Non valid option")
self.chosen_seasons_numbers_list.sort()
for i in self.chosen_seasons_numbers_list:
self.chosen_seasons_url_list.append(seasons_list[-i]['href'])
print("Gathering episodes Urls")
# print("chosen_seasons_url_list", self.chosen_seasons_url_list)
for url in self.chosen_seasons_url_list:
res = self.get_bs4_result(url, "div", "movies_small")[0]
episodes_list = res.find_all("a")
number_of_eps = len(episodes_list)
if number_of_eps:
print(F"There're {number_of_eps} episodes in {' '.join(url.split('/')[-2].split('-')[1:])}")
if all_eps:
choice = 'all'
else:
choice = self.get_string_input(
"Do you want to download all episodes or specific ones, type['all' or 'spec']:")
if choice == 'all':
self.chosen_episodes_number_list = [
i for i in range(1, number_of_eps + 1)]
elif choice == 'spec':
while 1:
chosen_number_episodes = self.get_int_input(
"Choose how many episodes :")
try:
if number_of_eps >= chosen_number_episodes > 0:
break
except:
pass
print("Add the episodes you want to download")
for i in range(1, chosen_number_episodes + 1):
while 1:
choice = self.get_int_input(
F"{i} --> Choose an episode from 1 to {number_of_eps}:")
try:
if number_of_eps >= choice >= 1:
print(F"Episode {choice} Added")
self.chosen_episodes_number_list.append(
choice)
break
else:
print("Non valid option")
except:
pass
# print("chosen_episodes_number_list",
# self.chosen_episodes_number_list)
# print("episodes_list", episodes_list)
self.chosen_episodes_number_list.sort()
for i in self.chosen_episodes_number_list:
self.chosen_episodes_url_list.append(episodes_list[-i]["href"])
self.gather_download_link()
# print(self.downloadable_episodes_url_list)
# print(self.chosen_episodes_url_list)
return True
def start(self, link=None):
# Check if link provided is valid
valid_link = False
if link:
self.content_type = self.get_url_type(link)
if self.content_type:
valid_link = True
# if it's valid it wont enter the loop
while not self.content_type:
# shows that the link is trash
if link:
print("None valid link")
# getting user input
self.get_search_url()
self.get_content_url()
self.content_name = self.get_content_name(self.content_url if not valid_link else link)
if self.content_type == "series":
self.download_seasons()
elif self.content_type == "movie":
self.chosen_episodes_url_list.append(self.content_url if not valid_link else link)
# print(self.chosen_episodes_url_list)
self.gather_download_link()
self.save_links_to_file()
self.get_user_download_choice()
@staticmethod
def get_int_input(output_msg):
try:
return int(input(output_msg))
except:
return None
@staticmethod
def get_string_input(output_msg):
try:
return str(input(output_msg)).lower()
except:
exit("strig input")
@staticmethod
def get_bs4_result(url, html_tag, class_name):
print("Requesting link !")
r = requests.get(url)
soup = BeautifulSoup(r.text, "html.parser")
return soup.find_all(html_tag, class_=class_name)
@staticmethod
def get_url_type(url):
# print(url)
try:
return url.split("/")[3]
except:
print("None valid link in get_url_type")
return None
@staticmethod
def get_content_name(url):
# print(url)
try:
return url.split("/")[4]
except:
print("None valid link in get_content_name")
return None
def exit(self, code):
self.destroy_chrome_driver()
sys.exit("\n Exited " + code)
def chose_quality(self):
target_button = self.chrome_driver.find_elements_by_class_name(
'btn.g.dl.nop._open_window')[0]
target_button.click()
def get_user_download_choice(self):
while 1:
choice = self.get_string_input(
"---> Links saved to file , Do you want to start [d]ownloading ,[a]ppend to IDM or [q]uit?,"
"chose: (d/a/q)")
if choice == "d":
self.start_downloading()
break
if choice == "a":
self.append_to_idm()
break
if choice == "q":
break
print("None valid option !")
def start_downloading(self):
print("Note : if your're using pycharm console, it won't show you progress bar !")
if not self.downloadable_episodes_url_list:
print("Array is empty")
for i, ep_link in enumerate(self.downloadable_episodes_url_list):
print("Starting to download :", ep_link)
obj = SmartDL(ep_link, "./Downloads" + os.sep)
obj.start()
print("Download location :" + obj.get_dest())
def append_to_idm(self):
for i, ep_link in enumerate(self.downloadable_episodes_url_list):
try:
os.system(
F'"C:\\Program Files (x86)\\Internet Download Manager\\IDMan.exe" /d {ep_link} /n /a')
print("+1 :", ep_link)
except Exception as excep:
print(F"Couldn't add {self.chosen_episodes_url_list[i]} \nException :{excep}")
print("Saving them to a file !")
def save_links_to_file(self):
base_dic = "LinkSaves/"
os.makedirs(os.path.dirname(base_dic), exist_ok=True)
# print(self.downloadable_episodes_url_list)
with open(F"{base_dic}/{self.content_type}-{self.content_name}.txt", "w+") as f:
for ep in self.downloadable_episodes_url_list:
f.write(F"{ep}\n")
def reset_chrome_driver(self):
self.destroy_chrome_driver()
self.init_chrome_driver()
if __name__ == "__main__":
egy = EgyBest()
link = "https://nero.egybest.site/movie/joker-2019/"
try:
while 1:
egy.start()
try:
choice = egy.get_int_input("Do you want to restart ? : (1/0)")
if choice == 0:
break
egy.reset()
except:
break
except Exception as e:
egy.reset_chrome_driver()
print(e)
finally:
egy.destroy_chrome_driver()
| 365 | 37.98 | 108 | 26 | 2,780 | python | [{"finding_id": "semgrep_rules.python.lang.correctness.use-sys-exit_da06b18664d193a7_46aa0de5", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.use-sys-exit", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "Detected use of `exit`. 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Use `sys.exit` over the python shell `exit` built-in. `exit` is a helper for the interactive shell and may not be available on all Python implementations.", "remediation": "sys.exit(\"strig input\")", "location": {"file_path": "unknown", "line_start": 263, "line_end": 263, "column_start": 13, "column_end": 32, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://stackoverflow.com/questions/6501121/difference-between-exit-and-sys-exit-in-python", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.use-sys-exit", "path": "/tmp/tmpr7mo7ysm/da06b18664d193a7.py", "start": {"line": 263, "col": 13, "offset": 10816}, "end": {"line": 263, "col": 32, "offset": 10835}, "extra": {"message": "Detected use of `exit`. Use `sys.exit` over the python shell `exit` built-in. `exit` is a helper for the interactive shell and may not be available on all Python implementations.", "fix": "sys.exit(\"strig input\")", "metadata": {"category": "correctness", "technology": ["python"], "references": ["https://stackoverflow.com/questions/6501121/difference-between-exit-and-sys-exit-in-python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.requests.best-practice.use-raise-for-status_da06b18664d193a7_ff621342", "tool_name": "semgrep", "rule_id": "rules.python.requests.best-practice.use-raise-for-status", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "There's an HTTP request made with requests, but the raise_for_status() utility method isn't used. 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Consider setting a timeout for all 'requests'.", "remediation": "requests.get(url, timeout=30)", "location": {"file_path": "unknown", "line_start": 268, "line_end": 268, "column_start": 13, "column_end": 30, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python-requests.org/en/latest/user/advanced/?highlight=timeout#timeouts", "title": null}, {"url": "https://requests.readthedocs.io/en/latest/user/quickstart/#timeouts", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.requests.best-practice.use-timeout", "path": "/tmp/tmpr7mo7ysm/da06b18664d193a7.py", "start": {"line": 268, "col": 13, "offset": 10953}, "end": {"line": 268, "col": 30, "offset": 10970}, "extra": {"message": "Detected a 'requests' call without a timeout set. By default, 'requests' calls wait until the connection is closed. 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This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b605_start_process_with_a_shell.html", "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_da06b18664d193a7_6f42826d", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 6 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-system-call-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
328
] | [
329
] | [
17
] | [
107
] | [
"A01:2017 - Injection"
] | [
"Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | egybest.py | /egybest.py | ahmed081/EgyBest-Downloader | MIT | |
2024-11-18T20:57:52.820940+00:00 | 1,505,503,412,000 | a9bd3d5686b67a0c78b7060194ac3103e352eb56 | 2 | {
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"path": "/validation/validators/wfs.py",
"provenance": "stack-edu-0054.json.gz:575985",
"repo_name": "usgin/ContentModelCMS",
"revision_date": 1505503412000,
"revision_id": "ac9a7824d5e79014d873fb84803788474d40b6ce",
"snapshot_id": "d6f3fb9874595b7e418866f5bf43d5c28f66540b",
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"visit_date": "2021-01-13T14:20:25.101532"
} | 2.375 | stackv2 | from contentmodels.models import ContentModel, ModelVersion
from WfsCapabilities import WfsCapabilities
from WfsGetFeature import WfsGetFeature
from django import forms
from django.http import HttpResponseNotAllowed
from django.shortcuts import render
#--------------------------------------------------------------------------------------
# A Form to gather user's input: Just the WFS URL
# Also validates that the URL returns a GetCapabilities doc and that the WFS
# provides some FeatureTypes
#--------------------------------------------------------------------------------------
class WfsSelectionForm(forms.Form):
wfs_get_capabilities_url = forms.URLField(
widget=forms.TextInput(attrs={'class':'span10', 'placeholder':'Enter a WFS GetCapabilities URL'})
) # Just one field in this form: the WFS GetCapabilities URL
# Function to validate the wfs_get_capabilites_url
def clean_wfs_get_capabilities_url(self):
# Get the URL that the user provided
url = self.cleaned_data['wfs_get_capabilities_url']
# Check the validity of the given URL
capabilities = WfsCapabilities(url)
if not capabilities.url_is_valid:
raise forms.ValidationError('The URL given is invalid')
# Check that the WFS provides some FeatureTypes
if len(capabilities.feature_types) is 0:
raise forms.ValidationError('The WFS you specified does not provide any FeatureTypes')
#--------------------------------------------------------------------------------------
# A Form to gather user's input required to validate a WFS against some ModelVersion
# Note that the constructor for the form requires a URL
#--------------------------------------------------------------------------------------
class WfsValidationParametersForm(forms.Form):
# Redefine the constructor for this form to accomodate an input URL
def __init__(self, url, *args, **kwargs):
super(forms.Form, self).__init__(*args, **kwargs)
# Set the feature_type field's choices to the available WFS FeatureTypes
self.capabilities = WfsCapabilities(url)
self.fields['feature_type'].choices = [ (typename, typename) for typename in self.capabilities.feature_types ]
# Set the initial URL
self.fields['url'].initial = url
# Define form fields
url = forms.URLField(widget=forms.HiddenInput)
content_model = forms.ModelChoiceField(queryset=ContentModel.objects.all(),
widget=forms.Select(attrs={'class':'span4'})
)
version = forms.ModelChoiceField(queryset=ModelVersion.objects.all(),
widget=forms.Select(attrs={'class':'span4'})
)
feature_type = forms.ChoiceField(choices=[],
widget=forms.Select(attrs={'class':'span4'})
)
number_of_features = forms.IntegerField(
widget=forms.Select(
attrs={'class':'span1'},
choices=((1,1), (10,10), (50, 50))
)
)
#--------------------------------------------------------------------------------------
# Here is the actual view function for /validate/wfs
#--------------------------------------------------------------------------------------
def validate_wfs_form(req):
# Insure that HTTP requests are of the proper type
allowed = [ 'GET', 'POST' ]
if req.method not in allowed:
return HttpResponseNotAllowed(allowed)
# When a data is passed in during a POST request...
if req.method == 'POST':
# ... determine if the req.POST contains WfsSelectionForm or WfsValidationParametersForm
# This is a WfsValidationParametersForm
if 'version' in req.POST:
form = WfsValidationParametersForm(req.POST['url'], req.POST)
# Check the form's validity
if form.is_valid():
# Perform WFS Validation
feature_type = form.cleaned_data['feature_type']
number_of_features = form.cleaned_data['number_of_features']
modelversion = form.cleaned_data['version']
get_feature_validator = WfsGetFeature(form.capabilities, feature_type, number_of_features)
result = get_feature_validator.validate(modelversion)
# Setup hash table for results rendering
context = {
"valid": result.valid,
"valid_elements": result.valid_count(),
"url": get_feature_validator.url,
"errors": result.errors,
"modelversion": modelversion,
"feature_type": feature_type,
"number_of_features": number_of_features,
"wfs_base_url": get_feature_validator.url.split('?')[0]
}
# Render the results as HTML
return render(req, 'wfs-results-bootstrap.html', context)
# Otherwise it is treated as a WfsSelectionForm
else:
form = WfsSelectionForm(req.POST)
# Check the form's validity
if form.is_valid():
# We need to send back a WfsValidationParametersForm, which takes a URL as input
url = form.data['wfs_get_capabilities_url']
second_form = WfsValidationParametersForm(url)
return render(req, 'wfs-form-bootstrap.html', { 'form': second_form, 'url': url })
# A GET request should just a data-free WfsSelectionForm
else:
form = WfsSelectionForm()
# You'll get here if it was a GET request, or if form validation failed
return render(req, 'wfs-form-bootstrap.html', { 'form': form }) | 123 | 42.26 | 114 | 18 | 1,109 | python | [{"finding_id": "semgrep_rules.python.django.security.audit.xss.direct-use-of-httpresponse_71c11ff15b183e13_f8d6879f", "tool_name": "semgrep", "rule_id": "rules.python.django.security.audit.xss.direct-use-of-httpresponse", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected data rendered directly to the end user via 'HttpResponse' or a similar object. This bypasses Django's built-in cross-site scripting (XSS) defenses and could result in an XSS vulnerability. Use Django's template engine to safely render HTML.", "remediation": "", "location": {"file_path": "unknown", "line_start": 73, "line_end": 73, "column_start": 12, "column_end": 43, "code_snippet": "requires login"}, "cwe_id": "CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A07:2017 - Cross-Site Scripting (XSS)", "references": [{"url": "https://docs.djangoproject.com/en/3.1/intro/tutorial03/#a-shortcut-render", "title": null}, {"url": "https://docs.djangoproject.com/en/3.1/topics/http/shortcuts/#render", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.django.security.audit.xss.direct-use-of-httpresponse", "path": "/tmp/tmpr7mo7ysm/71c11ff15b183e13.py", "start": {"line": 73, "col": 12, "offset": 3234}, "end": {"line": 73, "col": 43, "offset": 3265}, "extra": {"message": "Detected data rendered directly to the end user via 'HttpResponse' or a similar object. This bypasses Django's built-in cross-site scripting (XSS) defenses and could result in an XSS vulnerability. Use Django's template engine to safely render HTML.", "metadata": {"cwe": ["CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')"], "owasp": ["A07:2017 - Cross-Site Scripting (XSS)", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://docs.djangoproject.com/en/3.1/intro/tutorial03/#a-shortcut-render", "https://docs.djangoproject.com/en/3.1/topics/http/shortcuts/#render"], "category": "security", "technology": ["django"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-79"
] | [
"rules.python.django.security.audit.xss.direct-use-of-httpresponse"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
73
] | [
73
] | [
12
] | [
43
] | [
"A07:2017 - Cross-Site Scripting (XSS)"
] | [
"Detected data rendered directly to the end user via 'HttpResponse' or a similar object. This bypasses Django's built-in cross-site scripting (XSS) defenses and could result in an XSS vulnerability. Use Django's template engine to safely render HTML."
] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | wfs.py | /validation/validators/wfs.py | usgin/ContentModelCMS | BSD-2-Clause | |
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"license_type": "permissive",
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"repo_name": "zentrum-lexikographie/IMSnPars",
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"visit_date": "2023-01-19T17:28:10.501774"
} | 2.703125 | stackv2 | '''
Created on Jun 29, 2018
@author: falensaa
'''
import dynet
import logging
import abc
import pickle
import random
class TokenReprBuilder(object):
__metaclass__ = abc.ABCMeta
##
# word2i dictionaries operations
@abc.abstractmethod
def addToken(self, token):
pass
@abc.abstractmethod
def save(self, pickleOut):
pass
@abc.abstractmethod
def load(self, pickleIn):
pass
@abc.abstractmethod
def getFeatInfo(self):
pass
##
# instance operations
@abc.abstractmethod
def initializeParameters(self, model):
pass
@abc.abstractmethod
def buildInstance(self, token):
pass
##
# vector operations
@abc.abstractmethod
def getDim(self):
pass
@abc.abstractmethod
def getTokenVector(self, tokInstance, isTraining):
pass
@abc.abstractmethod
def getRootVector(self):
pass
################################################################
# TokenReprBuilders
################################################################
class WordReprBuilder(TokenReprBuilder):
def __init__(self, dim, wordDropout):
self.__dim = dim
self.__vocab = { }
self.__wordsFreq = { }
self.__wordDropout = wordDropout
self.__logger = logging.getLogger(self.__class__.__name__)
# additional entries - root, unknown
self.__addEntries = 2
self.__lookup = None
##
# word2i operations
def addToken(self, token):
norm = token.getNorm()
wId = self.__vocab.get(norm, None)
if wId == None:
wId = len(self.__vocab)
self.__vocab[norm] = wId
if self.__wordDropout:
if wId not in self.__wordsFreq:
self.__wordsFreq[wId] = 1
else:
self.__wordsFreq[wId] += 1
def save(self, pickleOut):
pickle.dump((self.__vocab, self.__wordsFreq), pickleOut)
def load(self, pickleIn):
self.__vocab, self.__wordsFreq = pickle.load(pickleIn)
def getFeatInfo(self):
return "Words: %i" % len(self.__vocab)
##
# instance opeations
def initializeParameters(self, model):
self.__lookup = model.add_lookup_parameters((len(self.__vocab) + self.__addEntries, self.__dim))
def buildInstance(self, token):
return self.__vocab.get(token.getNorm())
##
# vector operations
def getDim(self):
return self.__dim
def getTokenVector(self, wordId, isTraining):
if isTraining:
wordId = self.__wordIdWithDropout(wordId)
if wordId == None:
return self.__getUnknVector()
else:
return self.__lookup[wordId]
def getRootVector(self):
return self.__lookup[len(self.__vocab) + 1]
def __getUnknVector(self):
return self.__lookup[len(self.__vocab)]
def __wordIdWithDropout(self, wordId):
if self.__wordDropout == None or wordId == None:
return wordId
dropProb = self.__wordDropout / ( self.__wordDropout + self.__wordsFreq.get(wordId))
if random.random() < dropProb:
return None
return wordId
class POSReprBuilder(TokenReprBuilder):
def __init__(self, dim):
self.__logger = logging.getLogger(self.__class__.__name__)
self.__dim = dim
self.__pos = { }
# additional entries - root, unknown
self.__addEntries = 2
self.__lookup = None
##
# word2i operations
def addToken(self, token):
posId = self.__pos.get(token.pos, None)
if posId == None:
posId = len(self.__pos)
self.__pos[token.pos] = posId
def save(self, pickleOut):
pickle.dump(self.__pos, pickleOut)
def load(self, pickleIn):
self.__pos = pickle.load(pickleIn)
def getFeatInfo(self):
return "POS: %i" % len(self.__pos)
##
# instance opeations
def initializeParameters(self, model):
self.__lookup = model.add_lookup_parameters((len(self.__pos) + self.__addEntries, self.__dim))
def buildInstance(self, token):
return self.__pos.get(token.pos)
##
# vector operations
def getDim(self):
return self.__dim
def getTokenVector(self, posId, _):
if posId == None:
return self.__getUnknVector()
else:
return self.__lookup[posId]
def getRootVector(self):
return self.__lookup[len(self.__pos) + 1]
def __getUnknVector(self):
return self.__lookup[len(self.__pos)]
class MorphReprBuilder(TokenReprBuilder):
def __init__(self, dim):
self.__dim = dim
self.__morph = { }
# additional entries - root, unknown
self.__addEntries = 2
self.__lookup = None
##
# word2i operations
def addToken(self, token):
morphId = self.__morph.get(token.morph, None)
if morphId == None:
morphId = len(self.__morph)
self.__morph[token.morph] = morphId
def save(self, pickleOut):
pickle.dump(self.__morph, pickleOut)
def load(self, pickleIn):
self.__morph = pickle.load(pickleIn)
def getFeatInfo(self):
return "Morph: %i" % len(self.__morph)
##
# instance opeations
def initializeParameters(self, model):
self.__lookup = model.add_lookup_parameters((len(self.__morph) + self.__addEntries, self.__dim))
def buildInstance(self, token):
return self.__morph.get(token.morph)
##
# vector operations
def getDim(self):
return self.__dim
def getTokenVector(self, morphId, _):
if morphId == None:
return self.__getUnknVector()
else:
return self.__lookup[morphId]
def getRootVector(self):
return self.__lookup[len(self.__morph) + 1]
def __getUnknVector(self):
return self.__lookup[len(self.__morph)]
class CharLstmReprBuilder(TokenReprBuilder):
def __init__(self, dim, lstmDim, charDropout=None, lstmDropout=None):
self.__dim = dim
self.__lstmDim = lstmDim
self.__chars = { }
self.__charFreq = { }
# additional entries - unknown, <w>, </w>
self.__addEntries = 3
self.__lookup = None
self.__forwardLstm = None
self.__backwardLstm = None
self.__rootVec = None
self.__dropout = lstmDropout
self.__charDropout = charDropout
##
# word2i operations
def addToken(self, token):
for c in token.orth:
if c not in self.__chars:
cId = len(self.__chars)
self.__chars[c] = cId
else:
cId = self.__chars[c]
if self.__charDropout:
if cId not in self.__charFreq:
self.__charFreq[cId] = 1
else:
self.__charFreq[cId] += 1
def save(self, pickleOut):
pickle.dump((self.__chars, self.__charFreq), pickleOut)
def load(self, pickleIn):
self.__chars, self.__charFreq = pickle.load(pickleIn)
def getFeatInfo(self):
return "Chars [BiLSTM]: %i" % len(self.__chars)
##
# instance opeations
def initializeParameters(self, model):
self.__lookup = model.add_lookup_parameters((len(self.__chars) + self.__addEntries, self.__dim))
self.__rootVec = model.add_parameters((self.getDim()))
self.__forwardLstm = dynet.VanillaLSTMBuilder(1, self.__dim, self.__lstmDim, model)
self.__backwardLstm = dynet.VanillaLSTMBuilder(1, self.__dim, self.__lstmDim, model)
def buildInstance(self, token):
return [ self.__chars.get(c) for c in token.orth ]
##
# vector operations
def getDim(self):
return 2 * self.__lstmDim
def getTokenVector(self, charIds, isTraining):
self.__setDropout(isTraining)
if isTraining and self.__charDropout:
charIds = [ self.__charIdWithDropout(cId) for cId in charIds ]
charVecs = [ self.__getBegVector() ]
charVecs += [ self.__lookup[cId] if cId != None else self.__getUnknCVector() for cId in charIds ]
charVecs.append( self.__getEndVector() )
forwardInit = self.__forwardLstm.initial_state()
backwardInit = self.__backwardLstm.initial_state()
result = [ ]
result.append(forwardInit.add_inputs(charVecs)[-1].output())
result.append(backwardInit.add_inputs(reversed(charVecs))[-1].output())
return dynet.concatenate(result)
def getRootVector(self):
return self.__rootVec.expr()
def __getBegVector(self):
return self.__lookup[len(self.__chars)]
def __getEndVector(self):
return self.__lookup[len(self.__chars) + 1]
def __getUnknCVector(self):
return self.__lookup[len(self.__chars) + 2]
def __setDropout(self, isTraining):
if not self.__dropout:
return
if isTraining:
self.__forwardLstm.set_dropout(self.__dropout)
self.__backwardLstm.set_dropout(self.__dropout)
else:
self.__forwardLstm.disable_dropout()
self.__backwardLstm.disable_dropout()
def __charIdWithDropout(self, cId):
if self.__charDropout == None or cId == None:
return cId
dropProb = self.__charDropout / ( self.__charDropout + self.__charFreq.get(cId))
if random.random() < dropProb:
return None
return cId
| 366 | 26.21 | 106 | 17 | 2,390 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_8c86cbec026d3307_c85cfdd4", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. 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} | 3.15625 | stackv2 | #!/usr/bin/env python3
"""Kicad script to create a BOM according to the Seeed Studio Fusion PCBA."""
import csv
import sys
import xml.etree.ElementTree as ET
# Natural key sorting for orders like:
# C1, C5, C10, C12 ... (instead of C1, C10, C12, C5...)
# http://stackoverflow.com/a/5967539
import re
def atoi(text):
"""Atoi."""
return int(text) if text.isdigit() else text
def natural_keys(text):
"""
alist.sort(key=natural_keys) sorts in human order.
http://nedbatchelder.com/blog/200712/human_sorting.html
(See Toothy's implementation in the comments)
"""
return [atoi(c) for c in re.split('(\d+)', text)]
def parse_kicad_xml(input_file):
"""
Kicad XML parser.
Parse the KiCad XML file and look for the part designators
as done in the case of the official KiCad Open Parts Library:
* OPL parts are designated with "SKU" (preferred)
* other parts are designated with "MPN"
"""
components = {}
parts = {}
missing = []
dnm_components = []
tree = ET.parse(input_file)
root = tree.getroot()
for f in root.findall('./components/'):
name = f.attrib['ref']
info = {}
fields = f.find('fields')
opl, mpn, dnm = None, None, False
if fields is not None:
dnm = False
for x in fields:
if x.attrib['name'].upper() == 'DNM':
dnm = True
if x.attrib['name'].upper() == 'SKU':
opl = x.text
elif x.attrib['name'].upper() == 'MPN':
mpn = x.text
if not dnm:
if opl:
components[name] = opl
elif mpn:
components[name] = mpn
else:
missing += [name]
continue
else:
dnm_components += [name]
continue
if components[name] not in parts:
parts[components[name]] = []
parts[components[name]] += [name]
return components, missing, dnm_components
def write_bom_seeed(output_file_slug, components):
"""
Write the BOM according to the Seeed Studio Fusion PCBA.
Template available at:
https://statics3.seeedstudio.com/assets/file/fusion/bom_template_2016-08-18.csv
```
Ref,MPN/SKU,Qtd
C1,RHA,1
"D1,D2",CC0603KRX7R9BB102,2
```
The output is a CSV file at the `output_file_slug`.csv location.
"""
parts = {}
for c in components:
if components[c] not in parts:
parts[components[c]] = []
parts[components[c]] += [c]
field_names = ['Ref', 'MPN/SKU', 'Qtd']
with open("{}.csv".format(output_file_slug), 'w') as csvfile:
bomwriter = csv.DictWriter(
csvfile, fieldnames=field_names,
delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
bomwriter.writeheader()
for p in sorted(parts.keys()):
pieces = sorted(parts[p], key=natural_keys)
designators = ",".join(pieces)
bomwriter.writerow({'Ref': designators,
'MPN/SKU': p,
'Qtd': len(pieces)})
if __name__ == "__main__":
input_file = sys.argv[1]
output_file = sys.argv[2]
components, missing, dnm_components = parse_kicad_xml(input_file)
write_bom_seeed(output_file, components)
if len(dnm_components) > 0:
print("\n** Info **:parts with do not mount (DNM) atributte were not included")
print(dnm_components)
if len(missing) > 0:
print("\n** Warning **: there were parts with missing SKU/MFP")
print(missing)
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"CWE-611",
"CWE-611"
] | [
"rules.python.lang.security.use-defused-xml",
"rules.python.lang.security.use-defused-xml-parse"
] | [
"security",
"security"
] | [
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH"
] | [
6,
41
] | [
6,
41
] | [
1,
12
] | [
35,
32
] | [
"A04:2017 - XML External Entities (XXE)",
"A04:2017 - XML External Entities (XXE)"
] | [
"The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.",
"The native Python `xml` library is vulnerable to XML Exter... | [
7.5,
7.5
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | kicad_bom_seeedstudio.py | /kicad_bom_seeedstudio.py | leoheck/kicad-bom-seeedstudio | Apache-2.0 | |
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"visit_date": "2023-08-13T21:27:19.709156"
} | 2.3125 | stackv2 | # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0
import datetime
import boto3
import json
events_client = boto3.client("events")
sagemaker_client = boto3.client("sagemaker")
ssm_client = boto3.client("ssm")
class Metric:
_iam_permissions = [
{
"Action": ["events:PutEvents"],
"Resource": "arn:aws:events:**REGION**:**ACCOUNT_ID**:event-bus/default",
}
]
def __init__(self, metric_name, project_name, metadata, environment):
"""Class constructor. child classes should not need to implement this.
Args:
metric_name (str): the name of this metric
project_name (str): the project the metric belongs to
metadata (dict): the metadata
"""
self.metric_name = metric_name
self.project_name = project_name
self.metadata = metadata
self.environment = environment
def get_iam_permissions(self, region, account_id):
replaced_list = []
for p in self._iam_permissions:
p = (
str(p)
.replace("**REGION**", region)
.replace("**ACCOUNT_ID**", account_id)
)
replaced_list.append(eval(p))
return replaced_list
def extract(self):
"""The method that calculates the value of the metric and formats the output. child classes should not need to implement this."""
return {
"MetricName": self.metric_name,
"MetricValue": self._compute_value(),
"ExtractionDate": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f"),
"Metadata": self.metadata,
"Environment": self.environment,
"ProjectName": self.project_name,
}
def emit_event(self, payload):
"""emit an event with a given payload. child classes should not need to implement this.
Args:
payload (dict): the payload of the event to be emitted
"""
response = events_client.put_events(
Entries=[
{
"Source": "metric_extractor",
"Resources": [],
"DetailType": "metric_extractor",
"Detail": json.dumps(payload),
}
]
)
def _compute_value(self):
"""This is where the actual calculation happens. Child classes MUST implement this"""
raise NotImplementedError
class TotalCompletedTrainingJobs(Metric):
_iam_permissions = Metric._iam_permissions + [
{"Action": ["sagemaker:ListTrainingJobs"], "Resource": "*"}
]
def _compute_value(self):
jobs = sagemaker_client.list_training_jobs(
StatusEquals="Completed",
)["TrainingJobSummaries"]
return len(jobs)
class CompletedTrainingJobs24h(Metric):
_iam_permissions = Metric._iam_permissions + [
{"Action": ["sagemaker:ListTrainingJobs"], "Resource": "*"}
]
def _compute_value(self):
today = datetime.datetime.now()
yesterday = today - datetime.timedelta(days=1)
jobs = sagemaker_client.list_training_jobs(
StatusEquals="Completed",
LastModifiedTimeAfter=yesterday,
LastModifiedTimeBefore=today,
)["TrainingJobSummaries"]
return len(jobs)
class NumberEndPointsInService(Metric):
_iam_permissions = Metric._iam_permissions + [
{"Action": "sagemaker:ListEndpoints", "Resource": "*"}
]
def _compute_value(self):
eps = sagemaker_client.list_endpoints(
StatusEquals="InService",
)["Endpoints"]
return len(eps)
class SSMParamStoreValueMyName(Metric):
_iam_permissions = Metric._iam_permissions + [
{
"Action": "ssm:GetParameter",
"Resource": "arn:aws:ssm:*:**ACCOUNT_ID**:parameter/MyName",
}
]
def _compute_value(self):
return ssm_client.get_parameter(Name="MyName")["Parameter"]["Value"]
| 142 | 27.67 | 137 | 17 | 852 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_beac715f08faa92b_4e843cef", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 45, "line_end": 45, "column_start": 34, "column_end": 41, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpr7mo7ysm/beac715f08faa92b.py", "start": {"line": 45, "col": 34, "offset": 1271}, "end": {"line": 45, "col": 41, "offset": 1278}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-95"
] | [
"rules.python.lang.security.audit.eval-detected"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
45
] | [
45
] | [
34
] | [
41
] | [
"A03:2021 - Injection"
] | [
"Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources."
] | [
5
] | [
"LOW"
] | [
"HIGH"
] | metric.py | /lambda_function_code/metric.py | aws-samples/ds-dashboard | MIT-0 | |
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} | 2.875 | stackv2 | """
problems.py
Module for handling problem related commands
"""
import requests, argparse, textwrap, os, string, glob, re
import auacm
from auacm.utils import subcommand, _find_pid_from_name, format_str_len
import subprocess
from subprocess import PIPE, STDOUT
from shlex import split
ALLOWED_EXTENSIONS = ['java', 'c', 'cpp', 'py', 'go']
COMPILE_COMMAND = {
'java': 'javac {0}.java',
'py': 'NO COMPILE',
'py3': 'NO COMPILE',
'c': 'gcc {0}.c -o {0}',
'cpp': 'g++ {0}.cpp -o {0}',
'go': 'go build -o {0} {0}.go'
}
RUN_COMMAND = {
'java': 'java -cp {0} {1}',
'py3': 'python2.7 {0}/{1}.py',
'py': 'python3 {0}/{1}.py',
'c': '{0}/{1}',
'cpp': '{0}/{1}',
'go': '{0}/{1}'
}
@subcommand('problem')
def problems(args=None):
"""Get all the problems, or search for a specific one"""
# Some minimal argument parsing
parser = argparse.ArgumentParser(
add_help=False,
usage='problem [-v/--verbose] [-i/--id] <problem>'
)
parser.add_argument('-v', '--verbose', action='store_true')
parser.add_argument('-i', '--id', action='store_true')
parser.add_argument('problem', nargs='?', default='')
args = parser.parse_args(args)
query = args.problem
# GET request to the API
request = requests.get(auacm.BASE_URL + 'problems')
if not request.ok:
raise auacm.exceptions.ConnectionError(
'There was an error getting the problems')
# Filter out problems that aren't similar to the query
problem_data = request.json()['data']
results = list()
for problem in problem_data:
if not args.id and query.lower() in problem['name'].lower():
results.append(problem)
elif args.id and query == str(problem['pid']):
results.append(problem)
if not results and query:
raise auacm.exceptions.ProblemNotFoundError(
'Could not find problem named {}'.format(query))
# Print the results
return_value = ''
for result in results:
return_value += result['name'] + '\n'
if args.verbose:
return_value += textwrap.dedent("""\
| added: {}
| appeared: {}
| difficulty: {}
| pid: {}
| shortname: {}
| solved: {}
| url: {}\n
""".format(
result['added'], result['appeared'],
result['difficulty'], result['pid'],
result['shortname'], result['solved'], result['url']))
return return_value.strip()
@subcommand('problem-info')
def get_problem_info(args=None):
"""Get detailed data on a problem (description, input, etc.)"""
parser = argparse.ArgumentParser(
add_help=False,
usage='problem-info [-i/--id] problem'
)
parser.add_argument('problem')
parser.add_argument('-i', '--id', action='store_true')
args = parser.parse_args(args)
if args.id:
pid = args.problem
else:
pid = _find_pid_from_name(args.problem)
if pid == -1:
raise auacm.exceptions.ProblemNotFoundError(
'Could not find problem named {}'.format(args.problem))
response = requests.get(auacm.BASE_URL + 'problems/ ' + str(pid))
if not response.ok:
raise auacm.exceptions.ProblemNotFoundError(
'There was an error getting problem id {}'.format(pid))
data = response.json()['data']
# Gather all the results
return_value = textwrap.dedent('''
Name: {}
Description
{}
Input
{}
Output
{}
''').format(
data['name'],
format_str_len(data['description'], 80),
format_str_len(data['input_desc'], 80),
format_str_len(data['output_desc'], 80)
)
for case in data['sample_cases']:
return_value += textwrap.dedent('''
Sample Case {}
Input:
{}
Output:
{}
''').format(case['case_num'], case['input'], case['output'])
return return_value.strip()
@subcommand('init')
def init_problem_directory(args=None):
"""Create an initial directory and files for a problem"""
parser = argparse.ArgumentParser(
add_help=False,
usage='init [-i/--id] problem'
)
parser.add_argument('problem')
parser.add_argument('-i', '--id', action='store_true')
args = parser.parse_args(args)
if args.id:
pid = args.problem
else:
pid = _find_pid_from_name(args.problem)
if pid == -1:
raise auacm.exceptions.ProblemNotFoundError(
'Could not find problem: ' + args.problem)
response = requests.get(auacm.BASE_URL + 'problems/' + str(pid))
if not response.ok:
raise auacm.exceptions.ProblemNotFoundError(
'There was an error getting problem id {}'.format(pid))
data = response.json()['data']
# Save everything to files
dir_name = string.capwords(data['name']).replace(' ', '')
os.mkdir(dir_name)
desc_file = open(os.path.join(dir_name, 'description.md'), 'w')
desc_file.write(get_problem_info(['-i', str(pid)]))
desc_file.close()
os.mkdir(os.path.join(dir_name, 'tests'))
for case in data['sample_cases']:
in_file = open(os.path.join(os.path.join(
dir_name, 'tests', 'in' + str(case['case_num']) + '.txt')), 'w')
in_file.write(case['input'])
in_file.close()
out_file = open(os.path.join(os.path.join(
dir_name, 'tests', 'out' + str(case['case_num']) + '.txt')), 'w')
out_file.write(case['output'])
out_file.close()
return 'Done!'
@subcommand('test')
def test_solution(args=None):
"""Run a solution against sample cases"""
parser = argparse.ArgumentParser(
add_help=False,
usage='test [-p {2,3}] <solution> [-i [<problem>]]'
)
parser.add_argument('-p', '--python', type=int, choices=[2, 3])
parser.add_argument('solution')
parser.add_argument('-i', '--id', action='store_true')
parser.add_argument('-l', '--local', action='store_true')
parser.add_argument('problem', nargs='?', default=None)
args = parser.parse_args(args)
# Make sure that we can support this filetype
if not args.solution.split('.')[1] in ALLOWED_EXTENSIONS:
raise Exception('Filetype not supported')
# Get the sample cases for the problem
solution_name = args.solution.split('/')[-1]
cases = (_get_remote_sample_cases(args.problem, solution_name, args.id) if
not args.local else _get_local_sample_cases())
# Compile the solution, if necessary
compiled = _compile(args.solution, args.python == 3)
if not compiled: return 'Compilation error'
filename, filetype = args.solution.split('.')
if filetype == 'py' and not args.python or args.python == 3:
filetype = 'py3'
run_cmd = RUN_COMMAND[filetype].format(os.getcwd(), filename)
for case in cases:
# Execute the test solution
proc = subprocess.Popen(
split(run_cmd),
stdout=PIPE,
stdin=PIPE,
stderr=STDOUT,
universal_newlines=True)
result = proc.communicate(input=case['input'])[0]
if proc.returncode != 0:
return 'Runtime error\n' + str(result)
# Compare the results to the solution
result_lines = result.splitlines()
answer_lines = case['output'].splitlines()
if len(result_lines) != len(answer_lines):
return textwrap.dedent("""
Wrong number of lines
Expected {} line(s)
Found {} line(s)
""").strip().format(len(answer_lines), len(result_lines))
for i in range(len(result_lines)):
if result_lines[i] != answer_lines[i]:
return textwrap.dedent("""
Wrong answer
Expected: {}
Found: {}""").strip().format(answer_lines[i],
result_lines[i])
return 'Passed all sample cases'
def _compile(solution, py2=False):
"""Attempt to compile a solution, return True if successful"""
filename, filetype = solution.split('.')
if COMPILE_COMMAND[filetype] == 'NO COMPILE': return True
# Execute compilation and return success
return subprocess.call(
split(COMPILE_COMMAND[filetype].format(filename))) == 0
def _get_remote_sample_cases(problem, solution, is_id):
"""
Retrieve the sample cases from the server for a problem for local testing.
:param problem: The problem name to get the test cases for, or None
:param solution: the file name of the local solution, if problem is None
:param is_id: True if the problem argument
:throws auacm.exceptions.ProblemNotFoundError: if cannot locate the problem
"""
if problem:
if is_id:
pid = int(problem)
else:
pid = _find_pid_from_name(problem)
else:
# Get the problem name from the solution file
pid = _find_pid_from_name(solution.split('.')[0])
if pid == -1:
raise auacm.exceptions.ProblemNotFoundError(
'Could not frind problem: ' +
problem or solution.split('.')[0])
response = requests.get(auacm.BASE_URL + 'problems/' + str(pid))
return response.json()['data']['sample_cases']
def _get_local_sample_cases():
"""Retrieve the sample cases locally from the tests/ directory"""
test_dir = os.path.join(os.getcwd(), 'tests')
in_files = glob.glob(os.path.join(test_dir, 'in*'))
if not in_files:
raise Exception('No test cases found in tests/ directory')
cases = list()
for in_file in in_files:
# Find the corresponding output file
match = re.search(r'in(\d+).txt', in_file)
if not match:
raise Exception('Test files not properly named.'
'Should be in1.txt, in2.txt, ...')
test_num = match.group(1)
out_file = os.path.join(test_dir, 'out' + test_num + '.txt')
with open(out_file, 'r') as out_f, open(in_file, 'r') as in_f:
cases.append({
'input': in_f.read() + '\n',
'output': out_f.read()
})
return cases
| 325 | 31 | 79 | 21 | 2,396 | python | [{"finding_id": "semgrep_rules.python.requests.best-practice.use-timeout_f7d07ee15e061bf8_291f3863", "tool_name": "semgrep", "rule_id": "rules.python.requests.best-practice.use-timeout", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Detected a 'requests' call without a timeout set. By default, 'requests' calls wait until the connection is closed. This means a 'requests' call without a timeout will hang the program if a response is never received. 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} | 2.625 | stackv2 | #!/usr/bin/env python
# Copyright 2018 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Flakiness Swarming Task Experiment - Task Triggering Script
Triggers the needed tasks to run the experiment described by the input file.
Expects as an argument a path to a json file with the following structure:
{
"experiment_id": "experiment-20180926-30331",
"experiment_start": 1536000000,
"dimensions": "os:Windows-7-SP1,pool:Chrome",
"additional_args_template": "--gtest_repeat=%d <...more args...>",
"task_count": 100,
"repeats_per_task": 1,
"rows": [
{
"isolate_hash": "fd4454258e116e999f16ccd6de5faca7b737fbf4",
},
{
"isolate_hash": "ca8c6b3c106f5fd03df487ab062479ff315ee9a4"
},
{
"isolate_hash": "4ff8e831b038aa18c40715eccf45eda7820484a5"
},
{
"isolate_hash": "d18714f2fe36f603836b8592fbfdc486fe661de5"
}
]
}
This script will read the file, trigger the swarming tasks tagging them with
the experiment name. If there are tasks already with the given experiment name,
only trigger the needed amount to reach the specified task count, so as to
increment the task count if necessary without losing the previous ones.
A separate script will read this file and get the results from swarming server
and aggregate them.
see
https://docs.google.com/document/d/1zHGwa2bcCY8galQmWMc0fiogCj_p3aiC3KUBgXMUQTg/edit?usp=sharing
"""
import os
import sys
import subprocess
import json
REQUIRED_EXPERIMENT_PARAMETERS = ('dimensions', 'additional_args_template',
'task_count', 'repeats_per_task', 'rows')
class NoSwarmingTaskIdException(Exception):
pass
def ParseSwarmingCommandResult(output):
"""Gets the task id from the trigger command output"""
for line in output.splitlines():
if line.strip().startswith('swarming.py collect'):
result = line.strip().split()[-1]
print 'Triggered swarming task:', result
return result
raise NoSwarmingTaskIdException(output)
def ComposeSwarmingTaskTriggerCommand(experiment_id, dimensions, isolate_hash,
repeat_count, additional_args_template):
"""Composes the command line invocation for swarming.py .
Note that the environment variable SWARMING_PY is expected to have been set to
local checkout path of the following file:
https://cs.chromium.org/chromium/infra/luci/client/swarming.py
Args:
experiment_id (str): The value of the tag to use to identify the task runs
as part of a given experiment.
dimensions (str): A string like "os:Mac,pool:Chrome" specifying the
dimensions needed to serve the request.
isolate_hash (str): Input isolate for the task.
repeat_count (int): Number of times the test needs to be repeated. This is
used to populate the template containing additional args.
additional_args_template (str): A template containing the additional
arguments to pass to the command line. It is expected to contain %d in
place of the repeat count.
Returns:
A list of strings representing the command parts, suitable for passing to
subprocess lib.
"""
def DimensionFlags(dimensions):
"""E.g. convert `os:Mac,pool:Chrome` to `-d os Mac -d pool Chrome`."""
result = []
for d in dimensions.split(','):
k, v = d.split(':')
result.append('-d {0} {1}'.format(k, v))
return ' '.join(result)
command_template = ' '.join([
'python {swarming_py} trigger',
'-I isolateserver.appspot.com',
'-S chromium-swarm.appspot.com',
'{dimension_flags}',
'-s {isolate_hash}',
'--priority=190',
'--expiration=86399', # 23:59:59
'--tags=experiment_id:{experiment_id}',
'-- {additional_args}',
])
command = command_template.format(
experiment_id=experiment_id + isolate_hash[:4],
swarming_py=os.environ.get('SWARMING_PY', 'swarming.py'),
dimension_flags=DimensionFlags(dimensions),
isolate_hash=isolate_hash,
additional_args=additional_args_template % repeat_count,
)
return command.split()
def GetTaskCount(experiment_id, isolate_hash, experiment_start):
"""Determines number of swarming tasks with experiment name."""
query_command = [
'python',
os.environ.get('SWARMING_PY', 'swarming.py'), 'query', '-S',
'chromium-swarm.appspot.com',
'tasks/count?tags=experiment_id%%3A%s&start=%d' %
(experiment_id + isolate_hash[:4], experiment_start)
]
return int(json.loads(subprocess.check_output(query_command))['count'])
def main(experiment_path):
experiment = json.load(open(experiment_path))
for parameter in REQUIRED_EXPERIMENT_PARAMETERS:
assert parameter in experiment, \
'"%s" is a required parameter, and missing from %s' % (
parameter, experiment_path)
dimensions = experiment['dimensions']
additional_args_template = experiment['additional_args_template']
task_count = experiment['task_count']
repeats_per_task = experiment['repeats_per_task']
rows = experiment['rows']
experiment_id = experiment['experiment_id']
experiment_start = experiment['experiment_start']
for row in rows:
current_task_count = GetTaskCount(experiment_id, row['isolate_hash'],
experiment_start)
if current_task_count < task_count:
remaining_tasks = task_count - current_task_count
for _ in range(remaining_tasks):
subprocess.check_output(
ComposeSwarmingTaskTriggerCommand(
experiment_id, dimensions, row['isolate_hash'],
repeats_per_task, additional_args_template))
return 0
if __name__ == '__main__':
assert len(sys.argv) == 2, 'Path to a json file expected as first argument'
sys.exit(main(sys.argv[1]))
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"visit_date": "2022-04-22T11:45:56.884954"
} | 2.609375 | stackv2 | #!/usr/local/bin/python
# coding: latin-1
#if you use this code give me credit @tuf_unkn0wn
#i do not give you permission to show / edit this script without my credit
#to ask questions or report a problem message me on instagram @tuf_unkn0wn
"""
██░ ██ ▄▄▄ ▄████▄ ██ ▄█▀▓█████ ▓█████▄
▓██░ ██▒▒████▄ ▒██▀ ▀█ ██▄█▒ ▓█ ▀ ▒██▀ ██▌
▒██▀▀██░▒██ ▀█▄ ▒▓█ ▄ ▓███▄░ ▒███ ░██ █▌
░▓█ ░██ ░██▄▄▄▄██ ▒▓▓▄ ▄██▒▓██ █▄ ▒▓█ ▄ ░▓█▄ ▌
░▓█▒░██▓ ▓█ ▓██▒▒ ▓███▀ ░▒██▒ █▄░▒████▒░▒████▓
▒ ▒░▒ ▒▒ ▓▒█ ░▒ ▒ ░▒ ▒▒ ▓▒ ▒░ ░ ▒▒▓ ▒
▒ ░▒░ ░ ▒ ▒▒ ░ ░ ▒ ░ ░▒ ▒░ ░ ░ ░ ░ ▒ ▒
░ ░ ░ ▒ ░ ░ ░ ░ ░ ░ ░
░ ░ ░ ░ ░ ░ ░ ░ ░ ░
░ ░
"""
import os
import sys
import random
import socks
import socket
lred = '\033[91m'
lblue = '\033[94m'
lgreen = '\033[92m'
yellow = '\033[93m'
cyan = '\033[1;36m'
purple = '\033[95m'
red = '\033[31m'
green = '\033[32m'
blue = '\033[34m'
orange = '\033[33m'
colorlist = [red, blue, green, yellow, lblue, purple, cyan, lred, lgreen, orange]
randomcolor = random.choice(colorlist)
banner3list = [red, blue, green, purple]
def aserver():
gw = os.popen("ip -4 route show default").read().split()
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
s.connect((gw[2], 0))
ipaddr = s.getsockname()[0]
print "\033[93mStarting Server\033[0m..."
os.system("service apache2 start")
br = raw_input("\033[92mBrowser: \033[0m")
a = '{0} {1}'.format(br,ipaddr)
os.system(a)
stop = raw_input("\033[1mhit enter to stop server:\033[0m ")
print "\033[93mStopping Server\033[0m..."
os.system("service apache2 stop")
aserver()
| 56 | 28.62 | 81 | 13 | 723 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_1538cc16c27e5dc9_4ec79fc9", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "remediation": "", "location": {"file_path": "unknown", "line_start": 51, "line_end": 51, "column_start": 2, "column_end": 14, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "path": "/tmp/tmpr7mo7ysm/1538cc16c27e5dc9.py", "start": {"line": 51, "col": 2, "offset": 1989}, "end": {"line": 51, "col": 14, "offset": 2001}, "extra": {"message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b605_start_process_with_a_shell.html", "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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"LOW"
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] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | aserver.py | /commandlist/aserver.py | dAYOShACKER505/htk-lite | Apache-2.0 | |
2024-11-18T20:58:08.900356+00:00 | 1,590,647,484,000 | f36c1553ba060fd7892ff1ff5e7e43aeef7997b4 | 3 | {
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} | 2.859375 | stackv2 | #Algorithme de réseau de neuronne fully connected sans utilisation de Keras
from __future__ import print_function
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import pickle
import tensorflow as tf
import matplotlib.pyplot as plt
X = tf.placeholder(tf.float32, [None, 28, 28, 1]) #Matrice contenant un lot d'images
W = tf.Variable(tf.zeros([28 * 28, 2])) #Matrice des poids
b = tf.Variable(tf.zeros([2])) #Matrice des biais
init = tf.global_variables_initializer()
# modèle
Y = tf.nn.softmax(tf.matmul(tf.reshape(X, [-1, 28 * 28]), W) + b)
# Matrice pour les valeurs correctes
Y_ = tf.placeholder(tf.float32, [None, 2])
# loss function
cross_entropy = -tf.reduce_sum(Y_ * tf.log(Y))
# % de réponses correctes dans un lot d'images
is_correct = tf.equal(tf.argmax(Y, 1), tf.argmax(Y_, 1))
accuracy = tf.reduce_mean(tf.cast(is_correct, tf.float32))
#Optimisation par descente de gradient
optimizer = tf.train.GradientDescentOptimizer(0.0003)
train_step = optimizer.minimize(cross_entropy)
#Lancement de la session
sess = tf.Session()
sess.run(init)
#Chargement des images de la base de données
pickle_in = open("X.pickle", "rb")
Xpickle = pickle.load(pickle_in)
#Chargement des labels de la base de données
pickle_in = open("y.pickle", "rb")
Ypickle_init = pickle.load(pickle_in)
#Modification des labels pour que une place busy ne soit plus 0 mais [1,0] et une place free ne soit plus 1 mais [0,1]
def modif_Y(Ypickle_init):
Ypickle = []
for i in range(len(Ypickle_init)):
if Ypickle_init[i] == 0:
Ypickle.append([1, 0])
if Ypickle_init[i] == 1:
Ypickle.append([0, 1])
return Ypickle
# Compilation du modèle
A = []
index = []
for j in range(1):
train_data = {X: Xpickle[j: j+100], Y_: modif_Y(Ypickle_init)[j: j+100]}
_, loss_val, a = sess.run([train_step, cross_entropy, accuracy], feed_dict = train_data)
# Enregistrement de l'accuracy
A.append(a)
index.append(j)
#Affichage de l'accuracy
plt.plot(index, A)
plt.show()
| 75 | 25.88 | 118 | 13 | 593 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.open-never-closed_41001702859be142_0b3b67bc", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.open-never-closed", "finding_type": "best-practice", "severity": "high", "confidence": "medium", "message": "file object opened without corresponding close", "remediation": "", "location": {"file_path": "unknown", "line_start": 41, "line_end": 41, "column_start": 1, "column_end": 35, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.open-never-closed", "path": "/tmp/tmpr7mo7ysm/41001702859be142.py", "start": {"line": 41, "col": 1, "offset": 1115}, "end": {"line": 41, "col": 35, "offset": 1149}, "extra": {"message": "file object opened without corresponding close", "metadata": {"category": "best-practice", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.file-object-redefined-before-close_41001702859be142_f2454c8d", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.file-object-redefined-before-close", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "Detected a file object that is redefined and never closed. This could leak file descriptors and unnecessarily consume system resources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 41, "line_end": 45, "column_start": 1, "column_end": 35, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.file-object-redefined-before-close", "path": "/tmp/tmpr7mo7ysm/41001702859be142.py", "start": {"line": 41, "col": 1, "offset": 1115}, "end": {"line": 45, "col": 35, "offset": 1264}, "extra": {"message": "Detected a file object that is redefined and never closed. 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"rules.python.lang.security.deserialization.avoid-pickle"
] | [
"security",
"security"
] | [
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"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | [
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5,
5
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | NN_using_Tensorflow.py | /src/NN_using_Tensorflow.py | sirine-chahma/parking_space_detection | MIT | |
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"visit_date": "2023-02-07T09:10:30.750391"
} | 2.390625 | stackv2 | from django.shortcuts import redirect
from django.contrib import messages
# from django.core.mail import send_mail
from contacts.models import Contact
def contact(request):
'''
View for the inquiry form
'''
if request.method == 'POST':
# The data that are get posted from the form: user_id, seller_email
# listing_id, listing(title), name(user), email, phone, message
listing_id = request.POST['listing_id']
user_id = request.POST['user_id']
# seller_email = request.POST['seller_email']
listing_title = request.POST['listing_title']
user_name = request.POST['name']
user_email = request.POST['email']
user_phone = request.POST['phone']
user_message = request.POST['message']
# Check if user has made an inquiry already
if request.user.is_authenticated:
user_id = request.user.id
has_contacted = Contact.objects.all().filter(listing_id=listing_id,
user_id=user_id)
if has_contacted:
messages.error(request, "You have already made an inquiry \
for this item")
return redirect(f'/listings/{listing_id}')
# Inquiry check for not authenticated users, check the email and phone
else:
email_check = Contact.objects.all().filter(email=user_email)
phone_check = Contact.objects.all().filter(phone=user_phone)
if email_check or phone_check:
messages.error(request, "An inquiry with this email or phone \
done already")
return redirect(f'/listings/{listing_id}')
contact = Contact(listing=listing_title,
listing_id=listing_id,
name=user_name,
email=user_email,
phone=user_phone,
message=user_message,
user_id=user_id)
contact.save()
# Send mail
# send_mail(
# 'Usedbrains Listing Inquiry',
# 'There has been an inquiry for ' + listing_title + '. Sign in to \
# the admin panel for more info',
# 'akshaych.dev@gmail.com',
# [seller_email, 'akshaych203@gmail.com'],
# fail_silently=False
# )
messages.success(request, "Your interest recorded, the seller will \
get back to you soon")
return redirect(f'/listings/{listing_id}')
| 65 | 38.77 | 80 | 16 | 497 | python | [{"finding_id": "semgrep_rules.python.django.security.injection.open-redirect_2fa7be4d5edba1d6_2eb82a3b", "tool_name": "semgrep", "rule_id": "rules.python.django.security.injection.open-redirect", "finding_type": "security", "severity": "medium", "confidence": "medium", "message": "Data from request (listing_id) is passed to redirect(). This is an open redirect and could be exploited. Ensure you are redirecting to safe URLs by using django.utils.http.is_safe_url(). 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"CWE-601",
"CWE-601"
] | [
"rules.python.django.security.injection.open-redirect",
"rules.python.django.security.injection.open-redirect"
] | [
"security",
"security"
] | [
"MEDIUM",
"MEDIUM"
] | [
"MEDIUM",
"MEDIUM"
] | [
14,
14
] | [
41,
65
] | [
9,
9
] | [
59,
51
] | [
"A01:2021 - Broken Access Control",
"A01:2021 - Broken Access Control"
] | [
"Data from request (listing_id) is passed to redirect(). This is an open redirect and could be exploited. Ensure you are redirecting to safe URLs by using django.utils.http.is_safe_url(). See https://cwe.mitre.org/data/definitions/601.html for more information.",
"Data from request (listing_id) is passed to redir... | [
5,
5
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | views.py | /app/contacts/views.py | Akshaychdev/Usedbrains-E-market-project | MIT | |
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} | 2.53125 | stackv2 | import networkx as nx
import matplotlib.pyplot as plt
from xml.dom import minidom
def get_sumo_data():
g = nx.grid_2d_graph(6, 6)
dom = minidom.Document()
nodes = dom.createElement("nodes")
nodes.setAttribute("xmlns:xsi", "http://www.w3.org/2001/XMLSchema-instance")
nodes.setAttribute("xsi:noNamespaceSchemaLocation", "http://sumo.dlr.de/xsd/nodes_file.xsd")
vs = g.nodes
index = 0
def get_index(i):
return str(6*i[0]+i[1])
for i in vs:
node = dom.createElement("node")
node.setAttribute("id", str(index))
node.setAttribute("x", str(i[0]*250))
node.setAttribute("y", str(i[1]*250))
nodes.appendChild(node)
index += 1
dom.appendChild(nodes)
with open("sumo.nod.xml", "w") as fp:
dom.writexml(fp, indent="\t", newl="\n", encoding="utf-8")
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"CWE-611"
] | [
"rules.python.lang.security.use-defused-xml"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
3
] | [
3
] | [
1
] | [
28
] | [
"A04:2017 - XML External Entities (XXE)"
] | [
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] | [
7.5
] | [
"LOW"
] | [
"MEDIUM"
] | process_sumo_data.py | /process_data/process_sumo_data.py | TwelveYC/road-network-modeling | MIT | |
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} | 2.65625 | stackv2 | import os
import random
from collections import OrderedDict
import cv2
import numpy as np
import pytorch3d.transforms.rotation_conversions as rc
import torch
from PIL import Image
from pytorch3d.renderer.cameras import get_world_to_view_transform
from pytorch3d.transforms import Transform3d, Rotate
from utils.params import Params
from torch.utils.data import (BatchSampler, ConcatDataset, Dataset, Sampler, SubsetRandomSampler)
from utils.manager import RenderManager
import json
class ConcatDataSampler(Sampler):
def __init__(
self,
dataset: ConcatDataset,
batch_size: int = 0,
shuffle: bool = True,
drop_last: bool = True,
):
"""A Custom sampler that does the very simple yet incredibly unthought of following:
-Takes in a set of datasets in the form of ConcatDataset
-Creates a batched random sampler FOR EACH dataset
-returns batches from each INDIVIDUAL dataset during iteration
-Shuffle: True if you want to sample the shufflers randomly
"""
self.dataset = dataset
self.batch_size = batch_size
self.shuffle = shuffle
self.drop_last = drop_last
self.samplers: list = []
self.generate_new_samplers()
def generate_new_samplers(self):
prev_end = 0
for num, dset in enumerate(self.dataset.datasets):
end = prev_end + len(dset)
sampler = iter(
BatchSampler(
SubsetRandomSampler(list(range(prev_end, end))),
self.batch_size,
self.drop_last,
)
)
prev_end = end
self.samplers.append(sampler)
self.cum_size = end
self.curr_sampler = 0
def fetch_batch(self) -> list:
batch_idx = next(self.samplers[self.curr_sampler])
# batch_idx *= (self.curr_sampler + 1)
return batch_idx
def __iter__(self):
retries = 0
while retries < len(self.samplers):
if self.shuffle:
self.curr_sampler = random.choice(range(len(self.samplers)))
try:
# Fetch a batch of indices
yield self.fetch_batch()
retries = 0
except StopIteration:
self.curr_sampler += 1
retries += 1
# We've reached the end of the epoch - generate a new set of samplers
self.generate_new_samplers()
def __len__(self):
return self.cum_size // self.batch_size
class EvMaskPoseDataset(Dataset):
def __init__(self, dir_num: int, params, transforms: list = []):
self.img_size = params.img_size
self.transforms = transforms
try:
self.render_manager = RenderManager.from_directory(
dir_num=dir_num, render_folder=params.train_dir
)
self.render_manager.rectify_paths(base_folder=params.train_dir)
except:
self.render_manager = None
if self.render_manager is not None:
self.poses = self.preprocess_poses(self.render_manager._trajectory)
@classmethod
def preprocess_poses(cls, poses: tuple):
"""Generates (N, 6) vector of absolute poses
Args:
Tuple of batched rotations (N, 3, 3) and translations (N, 3) in Pytorch3d view-to-world coordinates. usually returned from a call to RenderManager._trajectory
More information about Pytorch3D's coordinate system: https://github.com/facebookresearch/pytorch3d/blob/master/docs/notes/cameras.md
1. Computes rotation and translation matrices in view-to-world coordinates.
2. Generates unit quaternion from R and computes log q repr
3. Normalizes translation according to mean and stdev
Returns:
(N, 6) vector: [t1, t2, t3, logq1, logq2, logq3]
"""
R, T = poses
cam_wvt = get_world_to_view_transform(R=R, T=T)
pose_transform = cam_wvt.inverse().get_matrix()
T = pose_transform[:, 3, :3]
R = pose_transform[:, :3, :3]
# Compute pose stats
std_R, mean_R = torch.std_mean(R)
std_T, mean_T = torch.std_mean(T)
q = rc.matrix_to_quaternion(R)
# q /= torch.norm(q)
# q *= torch.sign(q[0]) # hemisphere constraint
# logq = qlog(q)
T -= mean_T
T /= std_T
return torch.cat((T, q), dim=1)
@classmethod
def preprocess_images(self, img: Image, img_size) -> np.ndarray:
"""Resize and normalize the images to range 0, 1
"""
img = img.resize(img_size)
img_np = np.array(img)
if len(img_np.shape) == 2:
img_np = np.expand_dims(img_np, axis=2)
# HWC to CHW
img_trans = img_np.transpose((2, 0, 1))
if img_trans.max() > 1:
img_trans = img_trans / 255
return img_trans
def __len__(self):
return len(self.render_manager)
def add_noise_to_frame(self, frame, noise_std=0.1, noise_fraction=0.1):
"""Gaussian noise + hot pixels
"""
size = frame.size
noise = noise_std * np.random.randn(*size) * 255
if noise_fraction < 1.0:
noise[np.random.rand(*size) >= noise_fraction] = 0
return Image.fromarray((frame + noise).astype('uint8')).convert('L')
def __getitem__(self, index: int):
mask = self.render_manager.get_image("silhouette", index)
event_frame = self.render_manager.get_event_frame(index)
event_frame = self.add_noise_to_frame(event_frame)
R, T = self.render_manager.get_trajectory_point(index)
tq = self.poses[index: index + 1]
assert mask.size == event_frame.size, "Mask and event frame must be same size"
mask = torch.from_numpy(self.preprocess_images(mask, self.img_size)).type(
torch.FloatTensor
)
event_frame = torch.from_numpy(
self.preprocess_images(event_frame, self.img_size)
).type(torch.FloatTensor)
return event_frame, mask, R, T, tq
class EvimoDataset(Dataset):
"""Dataset to manage Evimo Data"""
def __init__(self, path: str, obj_id="1", is_train=True, slice_name=''):
self.new_camera = None
self.map1 = None
self.map2 = None
self.K = None
self.discoef = None
self.obj_id = obj_id
self.slices_path = os.path.join(path, slice_name)
self.frames_path = os.path.join(self.slices_path, 'slices')
if not os.path.exists(self.slices_path) or not os.path.exists(self.frames_path):
raise ValueError(f'Unavailable data in {self.slices_path}')
if is_train:
dataset_txt = eval(open(os.path.join(self.slices_path, "meta_train.txt")).read())
else:
dataset_txt = eval(open(os.path.join(self.slices_path, "meta_test.txt")).read())
self.calib = dataset_txt["meta"]
self.frames_dict = dataset_txt["frames"]
self.set_undistorted_camera()
@classmethod
def preprocess_images(cls, img: np.ndarray) -> torch.Tensor:
"""Normalize and convert to torch"""
if img.dtype == np.uint16:
img = img.astype(np.uint8)
if img.max() > 1:
img = img / 255
if len(img.shape) == 2:
img = np.expand_dims(img, axis=2)
torch_img = torch.from_numpy(img)
torch_img = torch_img.permute(2, 0, 1).float()
return torch_img
def set_undistorted_camera(self):
# evimo data is fisheye camera
K = np.zeros([3, 3])
K[0, 0] = self.calib['fy']
K[0, 2] = self.calib['cy']
K[1, 1] = self.calib['fx']
K[1, 2] = self.calib['cx']
K[2, 2] = 1.0
# for fisheye
# self.discoef = np.array([self.calib['k1'],
# self.calib['k2'], self.calib['k3'], self.calib['k4']])
# self.new_camera = cv2.fisheye.estimateNewCameraMatrixForUndistortRectify(
# K, self.discoef, (w, h), R=None, new_size=(w, h))
# self.map1, self.map2 = cv2.fisheye.initUndistortRectifyMap(
# K, self.discoef, R=np.eye(3), P=self.new_camera, size=(w, h), m1type=cv2.CV_32FC1)
w, h = self.calib['res_y'], self.calib['res_x']
self.K = K
# for rodtan undistortion
alpha = 0.0
self.discoef = np.array([self.calib['k1'], self.calib['k2'], 0.0, 0.0, self.calib['k3']])
self.new_camera, _ = cv2.getOptimalNewCameraMatrix(K, self.discoef, (w, h), alpha, (w, h))
self.map1, self.map2 = cv2.initUndistortRectifyMap(K, self.discoef, np.eye(3), self.new_camera, (w, h), cv2.CV_32FC1)
@classmethod
def evimo_to_pytorch3d_xyz(self, p: dict):
x_pt3d = float(p["t"]["y"])
y_pt3d = float(p["t"]["x"])
z_pt3d = -float(p["t"]["z"])
t = torch.Tensor([x_pt3d, y_pt3d, z_pt3d]).unsqueeze(0)
return t
@classmethod
def evimo_to_pytorch3d_Rotation(self, p: dict):
pos_q = torch.Tensor([float(e) for e in p['q'].values()])
pos_R = rc.quaternion_to_matrix(pos_q)
pos_R = pos_R.transpose(1, 0)
R = torch.Tensor(np.zeros((3, 3), dtype=float))
R[0, 0], R[0, 1], R[0, 2] = pos_R[1, 1], pos_R[1, 0], -pos_R[1, 2]
R[1, 0], R[1, 1], R[1, 2] = pos_R[0, 1], pos_R[0, 0], -pos_R[0, 2]
R[2, 0], R[2, 1], R[2, 2] = -pos_R[2, 1], -pos_R[2, 0], pos_R[2, 2]
return R
def prepare_pose(self, p: dict) -> Transform3d:
# transform evimo coordinate system to pytorch3d coordinate system
pos_t = self.evimo_to_pytorch3d_xyz(p)
pos_R = self.evimo_to_pytorch3d_Rotation(p)
R_tmp = Rotate(pos_R)
w2v_transform = R_tmp.translate(pos_t)
return Transform3d(matrix=w2v_transform.get_matrix())
def get_new_camera(self):
return self.new_camera
def __len__(self):
return len(self.frames_dict)
def __getitem__(self, idx: int):
# Get Event Frame and mask
event_path = os.path.join(self.frames_path, self.frames_dict[idx]["event_frame"])
event_frame = cv2.imread(event_path, cv2.IMREAD_UNCHANGED)
event_frame = cv2.remap(event_frame, self.map1, self.map2, cv2.INTER_LINEAR)
mask_path = os.path.join(self.frames_path, self.frames_dict[idx]["mask_frame"])
mask = cv2.imread(mask_path, cv2.IMREAD_UNCHANGED)
mask = cv2.remap(mask, self.map1, self.map2, cv2.INTER_LINEAR)
# mask = mask[:, :, 2]
mask[mask > 1] = 1
event_frame = self.preprocess_images(event_frame)
mask = self.preprocess_images(mask)
# Cam Pose and Object Pose
curr_frame = self.frames_dict[idx]
obj_pos = self.prepare_pose(curr_frame[self.obj_id]["pos"])
o2c_mat = obj_pos.get_matrix()
R = o2c_mat[:, :3, :3]
t = o2c_mat[:, 3, :3]
return event_frame, mask, R, t
def test_sampler():
dt1 = EvMaskPoseDataset(1, Params())
dt2 = EvMaskPoseDataset(2, Params())
dt3 = EvMaskPoseDataset(3, Params())
dt4 = EvMaskPoseDataset(4, Params())
cdt = ConcatDataset([dt1, dt2, dt3, dt4])
custom_sampler = ConcatDataSampler(cdt, 4, True)
assert len(custom_sampler) == len(cdt) // 4
for n in custom_sampler:
assert n is not None
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} | 2.765625 | stackv2 | import logging
import traceback
import os.path
from datetime import datetime
from argparse import ArgumentParser
from Board.Board import Board
from Library.Library import Library
# from Schematic.Schematic import Schematic
from xml.etree.ElementTree import ElementTree
from xml.etree.ElementTree import XMLParser
# noinspection PyUnresolvedReferences
def import_tk():
global Tk, Frame, Label, Button, RIDGE, BOTH, X, askopenfilename, asksaveasfilename, showinfo, showerror
from tkinter import Tk, Frame, Label, Button, RIDGE, BOTH, X
from tkinter.filedialog import askopenfilename
from tkinter.filedialog import asksaveasfilename
from tkinter.messagebox import showinfo, showerror
def startGui():
try:
import_tk()
except:
logging.error("Error Starting GUI. Could Not Find Tkinter module" + "Please install the Python Tkinter module")
return
root = Tk()
root.wm_title("Eagle V6 to KiCad Converter")
root.wm_minsize(400, 200)
frame = Frame(root, relief=RIDGE, bg="BLUE", borderwidth=2)
frame.pack(fill=BOTH, expand=1)
label = Label(frame, font=20, bg="BLUE", text="What Would You Like to Do:")
label.pack(fill=X, expand=1)
butBrd = Button(frame, text="Convert Board", command=convertBoardGUI)
butBrd.pack(fill=X, expand=1)
butLib = Button(frame, text="Convert Library", command=convertLibGUI)
butLib.pack(fill=X, expand=1)
butSch = Button(frame, text="Convert Schematic", command=convertSchGUI)
butSch.pack(fill=X, expand=1)
label = Label(frame, bg="BLUE", text="www.github.com/Trump211")
label.pack(fill=X, expand=1)
root.mainloop()
def startCmdLine(args):
if args.Schem is not None:
for sch in args.Schem:
convertSch(sch[0], sch[1])
if args.Board is not None:
for brd in args.Board:
convertBoard(brd[0], brd[1])
if args.Library is not None:
for lib in args.Library:
convertLib(lib[0], lib[1], lib[2])
def getRootNode(fileName):
parser = XMLParser(encoding="UTF-8")
node = ElementTree()
node.parse(fileName, parser)
node = node.getroot()
return node
def convertBoardGUI():
fileName = askopenfilename(title="Board Input", filetypes=[('Eagle V6 Board', '.brd'), ('all files', '.*')],
defaultextension='.brd')
if not fileName:
return
outFileName = asksaveasfilename(title="Board Output", filetypes=[('KiCad Board', '.brd'), ('all files', '.*')],
defaultextension='.brd', initialfile=os.path.splitext(fileName)[0] + "KiCad")
if not outFileName:
return
val = convertBoard(fileName, outFileName)
if val[0]:
showinfo("Conversion Complete", val[1])
else:
showerror("Error", val[1])
def convertBoard(fileName, outFileName):
logging.info("*******************************************")
logging.info("Converting: " + fileName)
logging.info("Outputing: " + outFileName + "\n")
try:
node = getRootNode(fileName)
brd = Board(node)
open(outFileName, 'w').close()
outFile = open(outFileName, "a")
brd.write(outFile)
outFile.close()
except BaseException as e:
logging.error("Conversion Failed")
logging.error(traceback.format_exc())
logging.info("*******************************************\n\n")
return False, "Error Converting Board \n" + str(e) + "\nSee Log.txt for more info"
logging.info("Conversion Successfull")
logging.info("*******************************************\n\n")
return True, "The Board Has Finished Converting"
def convertLibGUI():
fileName = askopenfilename(title="Input Library", filetypes=[('Eagle V6 Library', '.lbr'), ('all files', '.*')],
defaultextension='.lbr')
if not fileName: return
modFileName = asksaveasfilename(title="Module Output Filename",
filetypes=[('KiCad Module', '.mod'), ('all files', '.*')], defaultextension='.mod',
initialfile=os.path.splitext(fileName)[0])
if not modFileName: return
symFileName = asksaveasfilename(title="Symbol Output Filename",
filetypes=[('KiCad Symbol', '.lib'), ('all files', '.*')], defaultextension='.lib',
initialfile=os.path.splitext(fileName)[0])
if not symFileName: return
val = convertLib(fileName, symFileName, modFileName)
if val[0]:
showinfo("Conversion Complete", val[1])
else:
showerror("Error", val[1])
def convertLib(fileName, symFileName, modFileName):
logging.info("*******************************************")
logging.info("Converting Lib: " + fileName)
logging.info("Module Output: " + modFileName)
logging.info("Symbol Output: " + symFileName)
name = fileName.replace("/", "\\")
name = name.split("\\")[-1]
name = name.split(".")[0]
logging.info("Lib Name: " + name + "\n")
try:
node = getRootNode(fileName)
node = node.find("drawing").find("library")
lib = Library(node, name)
open(modFileName, 'w').close()
open(symFileName, 'w').close()
modFile = open(modFileName, "a")
symFile = open(symFileName, "a")
lib.writeLibrary(modFile, symFile)
modFile.close()
symFile.close()
except BaseException as e:
logging.error("Error Converting Library: '" + name + "'")
logging.error(traceback.format_exc())
logging.info("*******************************************\n\n")
return False, "Error Converting Library \n" + str(e) + "\nSee Log.txt for more info"
logging.info("Conversion Successfull")
logging.info("*******************************************\n\n")
return True, "Conversion of Library '" + name + "' Complete"
def convertSchGUI():
val = convertSch("N/A", "N/A")
if val[0]:
showinfo("Conversion Complete", val[1])
else:
showerror("Error", val[1])
def convertSch(schFile, outFile):
logging.info("*******************************************")
logging.info("Converting Schem: " + schFile)
logging.info("Outputing: " + outFile)
logging.error("Error Converting " + schFile + ":")
logging.error("Schematic Conversion not yet Supported")
logging.info("*******************************************\n\n")
return False, "Converting Schematics is not yet supported"
def parseargs():
# Setup argument parser
parser = ArgumentParser(prog="Eagle2KiCad")
parser.add_argument("-l", "-L", "--Library", dest="Library", nargs=3, metavar=("inFile", "symFile", "modFile"),
help="Convert an Eagle Library", action="append", type=str)
parser.add_argument("-b", "-B", "--Board", dest="Board", nargs=2, metavar=("inFile", "brdFile"),
help="Convert an Eagle Board", action="append", type=str)
parser.add_argument("-s", "-S", "--Schematic", dest="Schem", nargs=2, metavar=("inFile", "schFile"),
help="Convert an Eagle Schematic", action="append", type=str)
parser.add_argument('-v', '--verbosity', dest="Verbosity", choices=(0, 1), default=0, type=int,
help="Verbosity Level ")
# Process arguments
return parser.parse_args()
def setupLogging(verbosity, use_console):
lvl = (logging.INFO, logging.DEBUG)[verbosity]
logging.getLogger().setLevel(0)
fh = logging.FileHandler("Log.txt")
fh.setLevel(lvl)
logging.getLogger().addHandler(fh)
ch = logging.StreamHandler()
ch.setLevel(logging.WARNING) # always show Warnings and Errors in the Console
if use_console:
ch.setLevel(lvl) # Use user preference if in non-gui mode
logging.getLogger().addHandler(ch)
logging.info("###############################################################################")
logging.info("#Session: " + datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
logging.info("###############################################################################")
logging.log(lvl, "Logging at Level: " + logging.getLevelName(lvl) + "\n\n")
def shutdownLogging():
for handler in logging.root.handlers[:]:
handler.close()
logging.root.removeHandler(handler)
def main():
args = parseargs()
use_console = not (args.Board is None and args.Library is None and args.Schem is None)
setupLogging(args.Verbosity, use_console)
if use_console:
startCmdLine(args)
else:
startGui()
shutdownLogging()
if __name__ == "__main__":
main()
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"CWE-611"
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"rules.python.lang.security.use-defused-xml"
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"security"
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11,
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1,
1
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"The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service.",
"The Python documentation recommends using `defusedxml` ins... | [
7.5,
7.5
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | Start.py | /Start.py | Autohome2/Eagle2Kicad | MIT | |
2024-11-18T20:58:41.719916+00:00 | 1,601,719,836,000 | 5d2dc019eea7061ab4ea9a75fa2bbfc65dd2ff51 | 3 | {
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} | 2.71875 | stackv2 | """
本ライブラリ実行前に、h2dbを以下のオプションで起動する
java -cp h2-1.4.200.jar org.h2.tools.Server -webAllowOthers -tcpAllowOthers -pgAllowOthers -baseDir ../data/ -ifNotExists
-tcpAllowOthers 外部からの接続を許す
-pgAllowOthers postgresql互換形式
-baseDir データが保存される先のDB
DB名を mem:hoge とすることで、インメモリDBとして動くので何も保存されない
-ifNotExists 外部接続時にテーブル作成を許可する
"""
import psycopg2
#import copy
import psycopg2.extras
from pathlib import Path
from datetime import datetime, date, timedelta
db_connection_info = {}
#GTFSデータが対応している期間を取得する
def get_data_duration(cursor):
sql = """
select
min(start_date) as min_start_date,
max(end_date) as max_end_date
from
calendar
"""
cursor.execute(sql)
results = cursor.fetchall()
for row in results:
min_start_date = row['min_start_date']
max_end_date = row['max_end_date']
sql = """
select
feed_start_date,
feed_end_date
from
feed_info
"""
cursor.execute(sql)
results = cursor.fetchall()
for row in results:
feed_start_date = row['feed_start_date']
feed_end_date = row['feed_end_date']
# print("{}, {}, {}, {}".format(min_start_date, max_end_date, feed_start_date, feed_end_date))
# feed_info の start_date と calendar の start_date の遅い方を start_date に
# feed_info の end_date と calendar の end_date の早いを end_date に
start_date = feed_start_date if feed_start_date >= min_start_date else min_start_date
end_date = feed_end_date if feed_end_date <= max_end_date else max_end_date
return {
"start_date": datetime.strptime(start_date, "%Y%m%d").date(),
"end_date" : datetime.strptime(end_date, "%Y%m%d").date()
}
#順序あり辞書(dictionary)として、key: date, value 空のlist のオブジェクトを返す
def expand_date(from_date, to_date):
next_date = from_date
return_dict = {}
while next_date <= to_date:
return_dict[next_date] = set()
next_date = next_date + timedelta(days=1) #1日加える
return return_dict
# calendar.txt を読み、日付とservice_idのsetというデータ構造を作る
def expand_service_id_in_calendar(date_dict, cursor):
sql = "select * from calendar"
date_map = {0: "monday",1:"tuesday",2:"wednesday",3:"thursday",4:"friday",5:"saturday",6:"sunday"}
cursor.execute(sql)
results = cursor.fetchall()
for row in results:
service_id = row["service_id"]
start_date = datetime.strptime(row["start_date"], "%Y%m%d").date()
end_date = datetime.strptime(row["end_date"], "%Y%m%d").date()
for date, service_set in date_dict.items():
state = row[date_map[date.weekday()]]
if state == "1" and date >= start_date and date <= end_date:
service_set.add(service_id)
def process_exception_in_calendar_dates(date_dict, cursor):
sql = "select * from calendar_dates order by date, exception_type"
cursor.execute(sql)
results = cursor.fetchall()
for row in results:
try:
date_info = date_dict[datetime.strptime(row["date"], "%Y%m%d").date()]
if row["exception_type"] == "1":
date_info.add(row["service_id"])
elif row["exception_type"] == "2":
date_info.remove(row["service_id"])
except KeyError:
print("{} in calendar_date is out of duration.".format(row))
def create_universal_calendar(date_dict, cursor):
sql = """
create table universal_calendar(
service_id char(255),
date date
)
"""
cursor.execute(sql)
insert_sql = "insert into universal_calendar (service_id, date) values (%(service_id)s, %(date)s)"
for date, service_array in date_dict.items():
for service_id in service_array:
# print("{}: {}".format(date, service_id))
cursor.execute(insert_sql, {"service_id": service_id, "date":date})
def load_gtfs(dbname, base_dir):
#postgreSQLに接続（接続情報は環境変数、PG_XXX）
connection = psycopg2.connect("dbname=mem:{} user=sa password='sa' host=localhost port=5435".format(dbname))
#クライアントプログラムのエンコードを設定（DBの文字コードから自動変換してくれる）
connection.set_client_encoding('utf-8')
#select結果を辞書形式で取得するように設定
connection.cursor_factory=psycopg2.extras.DictCursor
#カーソルの取得
cursor = connection.cursor()
gtfs_files = ['agency','calendar','calendar_dates','feed_info','routes','shapes','stop_times','stops','translations','trips']
for file in gtfs_files:
gtfs_file = Path(base_dir,file + ".txt")
sql = "CREATE TABLE {} AS SELECT * FROM CSVREAD('{}')".format(file, str(gtfs_file))
cursor.execute(sql)
duration = get_data_duration(cursor)
date_dict = expand_date(duration['start_date'], duration['end_date'])
expand_service_id_in_calendar(date_dict, cursor)
process_exception_in_calendar_dates(date_dict, cursor)
create_universal_calendar(date_dict, cursor)
db_connection_info[dbname] = {'connection': connection, 'cursor': cursor}
return {'cursor':cursor, 'start': duration['start_date'], 'end':duration['end_date']}
#切断
def close_gtfs(dbname):
info = db_connection_info.pop(dbname) #delete
info['cursor'].close()
info['connection'].close()
| 144 | 34.88 | 129 | 17 | 1,373 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.formatted-sql-query_ba954e943dbb8a8a_2ffd6fa3", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.formatted-sql-query", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected possible formatted SQL query. Use parameterized queries instead.", "remediation": "", "location": {"file_path": "unknown", "line_start": 129, "line_end": 129, "column_start": 9, "column_end": 28, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/775296/mysql-parameterized-queries", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.formatted-sql-query", "path": "/tmp/tmpr7mo7ysm/ba954e943dbb8a8a.py", "start": {"line": 129, "col": 9, "offset": 5069}, "end": {"line": 129, "col": 28, "offset": 5088}, "extra": {"message": "Detected possible formatted SQL query. 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This could lead to SQL injection if the variable is user-controlled and not properly sanitized. In order to prevent SQL injection, use parameterized queries or prepared statements instead. You can use prepared statements by creating a 'sql.SQL' string. You can also use the pyformat binding style to create parameterized queries. For example: 'cur.execute(SELECT * FROM table WHERE name=%s, user_input)'", "remediation": "", "location": {"file_path": "unknown", "line_start": 129, "line_end": 129, "column_start": 9, "column_end": 28, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://www.psycopg.org/docs/sql.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.sqli.psycopg-sqli", "path": "/tmp/tmpr7mo7ysm/ba954e943dbb8a8a.py", "start": {"line": 129, "col": 9, "offset": 5069}, "end": {"line": 129, "col": 28, "offset": 5088}, "extra": {"message": "Detected string concatenation with a non-literal variable in a psycopg2 Python SQL statement. This could lead to SQL injection if the variable is user-controlled and not properly sanitized. In order to prevent SQL injection, use parameterized queries or prepared statements instead. You can use prepared statements by creating a 'sql.SQL' string. You can also use the pyformat binding style to create parameterized queries. For example: 'cur.execute(SELECT * FROM table WHERE name=%s, user_input)'", "metadata": {"cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "references": ["https://www.psycopg.org/docs/sql.html"], "category": "security", "technology": ["psycopg"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_ba954e943dbb8a8a_4e725dc4", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "remediation": "", "location": {"file_path": "unknown", "line_start": 129, "line_end": 129, "column_start": 9, "column_end": 28, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "title": null}, {"url": "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "title": null}, {"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "path": "/tmp/tmpr7mo7ysm/ba954e943dbb8a8a.py", "start": {"line": 129, "col": 9, "offset": 5069}, "end": {"line": 129, "col": 28, "offset": 5088}, "extra": {"message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. 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In most cases, SQLAlchemy ORM will be a better option.", "metadata": {"cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column"], "category": "security", "technology": ["sqlalchemy"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 3 | true | [
"CWE-89",
"CWE-89",
"CWE-89"
] | [
"rules.python.lang.security.audit.formatted-sql-query",
"rules.python.lang.security.audit.sqli.psycopg-sqli",
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query"
] | [
"security",
"security",
"security"
] | [
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"LOW"
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] | [
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129,
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"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Detected possible formatted SQL query. Use parameterized queries instead.",
"Detected string concatenation with a non-literal variable in a psycopg2 Python SQL statement. This could lead to SQL injection if the variable is user-controlled and not properly sanitized. In order to prevent SQL injection, use paramet... | [
5,
5,
7.5
] | [
"LOW",
"LOW",
"LOW"
] | [
"HIGH",
"HIGH",
"HIGH"
] | h2dbgtfs.py | /h2dbgtfs.py | niyalist/GTFSDiff | Apache-2.0 | |
2024-11-18T20:58:42.543550+00:00 | 1,593,831,890,000 | 3cda5108dccda53a5124c3463fa00c6f2ff3d582 | 3 | {
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"detected_licenses": [
"MIT"
],
"directory_id": "25ac6df0589c6e1b79be79847061ba039c9e07fb",
"extension": "py",
"filename": "scientificCalculator.py",
"fork_events_count": 1,
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"gha_language": null,
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"github_id": 248876247,
"is_generated": false,
"is_vendor": false,
"language": "Python",
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"license": "MIT",
"license_type": "permissive",
"path": "/scientificCalculator.py",
"provenance": "stack-edu-0054.json.gz:576422",
"repo_name": "PatrickAttankurugu/Scientific-Calculator",
"revision_date": 1593831890000,
"revision_id": "92902e364dbec33b9efdd4d443891120fcf68b98",
"snapshot_id": "444d23dba8e4ab7cdc4850d7e18568a7dd91c523",
"src_encoding": "UTF-8",
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"url": "https://raw.githubusercontent.com/PatrickAttankurugu/Scientific-Calculator/92902e364dbec33b9efdd4d443891120fcf68b98/scientificCalculator.py",
"visit_date": "2021-04-09T23:10:16.434993"
} | 2.984375 | stackv2 | from tkinter import *
from tkinter import messagebox
from math import *
root = Tk()
root.title("Scientific Calculator")
root.configure(background="powder blue")
calc=Frame(root,bg="grey")
calc.grid()
equa = ""
equation = StringVar()
calculation = Entry(calc, textvariable = equation,fg="black",font=('arial',15,'bold'),bg="powder blue",bd=30,width=50,justify=LEFT)
calculation.grid(row=0, columnspan=4,column=0,pady=1)
def btnPress(num):
global equa
equa = equa + str(num)
equation.set(equa)
def EqualPress():
global equa
x=calculation.get()
if(equa==""):
equa=equa+x
try:
total = str(eval(equa))
equation.set(total)
if(float(total)==0):
equa=""
else:
equa=total
except:
equation.set("Syntax Error")
equa=""
pass
def ClearPress():
global equa
equa = ""
equation.set("")
Button0 = Button(calc, text="0", command = lambda:btnPress(0),bd=4,width=6,height=1,bg="white",relief=SOLID)
Button1 = Button(calc, text="1", command = lambda:btnPress(1), borderwidth=1,bd=4,width=6,height=1,bg="white",relief=SOLID)
Button14 = Button(calc, text="(", command = lambda:btnPress("("), borderwidth=1,bd=4,width=6,height=1,bg="white",relief=SOLID)
Button2 = Button(calc, text="2", command = lambda:btnPress(2), borderwidth=1,bd=4,width=6,height=1,bg="white",relief=SOLID)
Button3 = Button(calc, text="3", command = lambda:btnPress(3), borderwidth=1,bd=4,width=6,height=1,bg="white",relief=SOLID)
Button13 = Button(calc, text="sqrt", command = lambda:btnPress("sqrt("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button4 = Button(calc, text="4", command = lambda:btnPress(4), borderwidth=1,bd=4,width=6,height=1,bg="white",relief=SOLID)
Button15 = Button(calc, text=")", command = lambda:btnPress(")"), borderwidth=1,bd=4,width=6,height=1,bg="white", relief=SOLID)
Button5 = Button(calc, text="5", command = lambda:btnPress(5), borderwidth=1,bd=4,width=6,height=1,bg="white", relief=SOLID)
Button6 = Button(calc, text="6", command = lambda:btnPress(6), borderwidth=1,bd=4,width=6,height=1,bg="white", relief=SOLID)
Button7 = Button(calc, text="7", command = lambda:btnPress(7), borderwidth=1,bd=4,width=6,height=1,bg="white", relief=SOLID)
Button16 = Button(calc, text=".", command = lambda:btnPress("."), borderwidth=1,bd=4,width=6,height=1,bg="white", relief=SOLID)
Button8 = Button(calc, text="8", command = lambda:btnPress(8), borderwidth=1,bd=4,width=6,height=1,bg="white", relief=SOLID)
Button9 = Button(calc, text="9", command = lambda:btnPress(9), borderwidth=1,bd=4,width=6,height=1,bg="white", relief=SOLID)
Plus = Button(calc, text="+", command = lambda:btnPress("+"), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Minus = Button(calc, text="-", command = lambda:btnPress("-"), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button18 = Button(calc, text="sin", command = lambda:btnPress("sin("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button22 = Button(calc, text="log", command = lambda:btnPress("log("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Multiply = Button(calc, text="*", command = lambda:btnPress("*"), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button19 = Button(calc, text="cos", command = lambda:btnPress("cos("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button23 = Button(calc, text="pi", command = lambda:btnPress("pi"), borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Divide = Button(calc, text="/", command = lambda:btnPress("/"), borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Button20 = Button(calc, text="factorial", command = lambda:btnPress("factorial("), borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Equal = Button(calc, text="=", command = EqualPress, borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Clear = Button(calc, text="MC", command = ClearPress, borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Button17 = Button(calc, text="%", command = lambda:btnPress("%"), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button25 = Button(calc, text="degrees", command = lambda:btnPress("degrees("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button26 = Button(calc, text="log", command = lambda:btnPress("log10("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button27 = Button(calc, text="log1p", command = lambda:btnPress("log1p("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button28 = Button(calc, text="radians", command = lambda:btnPress("radians("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button29 = Button(calc, text="sinh", command = lambda:btnPress("sinh("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button30 = Button(calc, text="cosh", command = lambda:btnPress("cosh("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button31 = Button(calc, text="tan", command = lambda:btnPress("tan("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button32 = Button(calc, text="tanh", command = lambda:btnPress("tanh("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button33 = Button(calc, text="E", command = lambda:btnPress("e"), borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Button34 = Button(calc, text="atan", command = lambda:btnPress("atan("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button36 = Button(calc, text="exp", command = lambda:btnPress("exp("), borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Button38 = Button(calc, text="asin", command = lambda:btnPress("asin("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button39 = Button(calc, text="acos", command = lambda:btnPress("acos("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button46 = Button(calc, text="ceil", command = lambda:btnPress("ceil("), borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Button47 = Button(calc, text="floor", command = lambda:btnPress("floor("), borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Button49 = Button(calc, text="abs", command = lambda:btnPress("abs("), borderwidth=1,bd=4,width=6,height=1,bg="powder blue", relief=SOLID)
Button50 = Button(calc, text="int", command = lambda:btnPress("int("), borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Button51 = Button(calc, text="float", command = lambda:btnPress("float("), borderwidth=1,bd=4,width=6,height=1,bg="pink", relief=SOLID)
Button13.grid(row = 2, column = 0, padx=10, pady=10)
Button28.grid(row = 2, column =1, padx=10, pady=10)
Button25.grid(row = 2, column = 2, padx=10, pady=10)
Button32.grid(row = 2, column = 3, padx=10, pady=10)
Button26.grid(row = 3, column = 0, padx=10, pady=10)
Button27.grid(row = 3, column = 1, padx=10, pady=10)
Button29.grid(row = 3, column = 2, padx=10, pady=10)
Button30.grid(row = 3, column = 3, padx=10, pady=10)
Button31.grid(row = 4, column = 0, padx=10, pady=10)
Button19.grid(row = 4, column = 1, padx=10, pady=10)
Button18.grid(row = 4, column = 2, padx=10, pady=10)
Button22.grid(row = 4, column = 3, padx=10, pady=10)
Button1.grid(row = 5, column = 0, padx=10, pady=10)
Button2.grid(row = 5, column = 1, padx=10, pady=10)
Button3.grid(row = 5, column = 2, padx=10, pady=10)
Plus.grid(row = 5, column = 3, padx=10, pady=10)
Button4.grid(row = 6, column = 0, padx=10, pady=10)
Button5.grid(row = 6, column = 1, padx=10, pady=10)
Button6.grid(row = 6, column = 2, padx=10, pady=10)
Minus.grid(row = 6, column = 3, padx=10, pady=10)
Button7.grid(row = 7, column = 0, padx=10, pady=10)
Button8.grid(row = 7, column = 1, padx=10, pady=10)
Button9.grid(row = 7, column = 2, padx=10, pady=10)
Multiply.grid(row = 7, column = 3, padx=10, pady=10)
Button14.grid(row = 8, column = 0, padx=10, pady=10)
Button15.grid(row = 8, column = 1, padx=10, pady=10)
Button0.grid(row = 8, column = 2, padx=10, pady=10)
Button17.grid(row = 8, column = 3, padx=10, pady=10)
Clear.grid(row = 9, column = 0, padx=10, pady=10)
Equal.grid(row=9, column=1, padx=10, pady=10)
Button16.grid(row = 9, column = 2, padx=10, pady=10)
Divide.grid(row = 9, column = 3, padx=10, pady=10)
Button23.grid(row = 10, column = 0, padx=10, pady=10)
Button50.grid(row = 10, column = 1, padx=10, pady=10)
Button51.grid(row = 10, column = 2, padx=10, pady=10)
Button20.grid(row = 10, column = 3, padx=10, pady=10)
#Button44.grid(row = 10, column = 3, padx=10, pady=10)
#Button38.grid(row = 10, column = 4, padx=10, pady=10)
#Button39.grid(row = 10, column = 5, padx=10, pady=10)
Button33.grid(row = 11, column = 0, padx=10, pady=10)
Button46.grid(row = 11, column = 1, padx=10, pady=10)
Button47.grid(row = 11, column = 2, padx=10, pady=10)
Button36.grid(row = 11, column = 3, padx=10, pady=10)
#Button42.grid(row = 11, column = 4, padx=10, pady=10)
#Button43.grid(row = 11, column = 3, padx=10, pady=10)
#Button48.grid(row = 10, column = 6, padx=10, pady=10)
#Button49.grid(row = 10, column = 7, padx=10, pady=10)
def exit():
root.quit()
def scientific():
root.resizable(width=False,height=False)
root.geometry("940x568+0+0")
def standard():
root.resizable(width=False,height=False)
root.geometry("466x568+0+0")
menubar=Menu(calc)
filemenu=Menu(menubar,tearoff=0)
menubar.add_cascade(label="Manu",menu=filemenu)
filemenu.add_command(label="standard",command=standard)
filemenu.add_command(label="scientific",command=scientific)
filemenu.add_separator()
filemenu.add_command(label="exit",command=exit)
Author=Label(root,text="Created by : Patrick Attankurugu",fg="black",font=('arial',10,'bold'),borderwidth=1,bd=4,width=30,height=2,bg="white",relief=SOLID)
Author.grid(row=11,columnspan=8)
root.config(menu=menubar)
root.mainloop() | 202 | 49.22 | 155 | 12 | 3,513 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_a25fec928307f954_02193afb", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. 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"CWE-95"
] | [
"rules.python.lang.security.audit.eval-detected"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
31
] | [
31
] | [
28
] | [
38
] | [
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] | [
"Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources."
] | [
5
] | [
"LOW"
] | [
"HIGH"
] | scientificCalculator.py | /scientificCalculator.py | PatrickAttankurugu/Scientific-Calculator | MIT | |
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"visit_date": "2021-12-31T08:45:51.429647"
} | 2.53125 | stackv2 | #!/usr/bin/env python
# This file is part of the markdown-katex project
# https://github.com/mbarkhau/markdown-katex
#
# Copyright (c) 2019-2021 Manuel Barkhau (mbarkhau@gmail.com) - MIT License
# SPDX-License-Identifier: MIT
import sys
import json
import typing as typ
import subprocess as sp
import markdown_katex
from markdown_katex import html
try:
import pretty_traceback
pretty_traceback.install()
except ImportError:
pass # no need to fail because of missing dev dependency
ExitCode = int
def _selftest() -> ExitCode:
# pylint:disable=import-outside-toplevel ; lazy import to improve cli responsiveness
from markdown_katex import wrapper
print("Command options:")
print(json.dumps(wrapper.parse_options(), indent=4))
print()
html_parts: typ.List[str] = []
test_formulas = markdown_katex.TEST_FORMULAS
for tex_formula in test_formulas:
html_part = wrapper.tex2html(tex_formula)
if not html_part:
return 1
html_parts.append(html_part)
formula_html = "\n<hr/>\n".join(html_parts)
html_text = html.HTML_TEMPLATE.replace("{{content}}", formula_html)
with open("test.html", mode="wb") as fobj:
fobj.write(html_text.encode("utf-8"))
print("Created 'test.html'")
return 0
def main(args: typ.Sequence[str] = sys.argv[1:]) -> ExitCode:
"""Basic wrapper around the katex command.
This is mostly just used for self testing.
$ python -m markdown_katex
"""
# pylint:disable=dangerous-default-value ; mypy will catch mutations of args
if "--markdown-katex-selftest" in args:
return _selftest()
bin_cmd = markdown_katex.get_bin_cmd()
if "--version" in args or "-V" in args:
version = markdown_katex.__version__
bin_str = " ".join(bin_cmd)
print("markdown-katex version: ", version, f"(using binary: {bin_str})")
return sp.check_call(bin_cmd + list(args))
if __name__ == '__main__':
sys.exit(main())
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"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
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72
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12
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47
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"A01:2017 - Injection"
] | [
"Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | __main__.py | /src/markdown_katex/__main__.py | mbarkhau/markdown-katex | MIT | |
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} | 2.640625 | stackv2 | #! /usr/bin/env python
print 'starting'
import os
import sys
import numpy
import matplotlib
#matplotlib.use('cairo')
from matplotlib.gridspec import GridSpec
from matplotlib.ticker import MultipleLocator
import pylab
from mvn import Mvn
from mvn.matrix import Matrix
import mvn.plotTools
from collections import OrderedDict
colors = OrderedDict([
['Actual' , [1, 1, 0]],
['Updated' , [0, 0, 1]],
['Noise' , [1, 0, 0]],
['Updated+Noise', [1, 0, 1]],
['Measurement' , [0, 1, 0]],
['Filter Result', [0, 1, 1]],
])
actualParams = {
'marker':'*',
'markersize':20,
'color':colors['Actual'],
}
otherParams = {
'minalpha':0.5,
'slope':0.333
}
class Publisher(object):
def __init__(self, targetDir, formats=('png','svg')):
self.n = 0
self.formats = formats
self.targetDir = targetDir
try:
os.stat(self.targetDir)
except OSError:
os.mkdir(self.targetDir)
def publish(self, fig):
for format in self.formats:
fig.savefig(
"%s/%0.3d.%s" % (self.targetDir, self.n, format),
format=format
)
self.n += 1
def seed(path):
if len(sys.argv) > 1:
seed = int(sys.argv[1])
else:
seed = numpy.random.randint(10000)
print 'seed: %d' % seed
numpy.random.seed(seed)
open('%s/seed' % path, 'w').write(str(seed))
def drawLegend(ax):
patch = lambda color:matplotlib.patches.Ellipse(
[0, 0],
width=0, height=0, facecolor=color
)
patches = [patch(color) for [name,color] in colors.iteritems()]
ax.legend(
patches, list(colors.keys()),
loc='lower center',
ncol = 2
)
def newAx(fig, transform = Matrix.eye(2)):
fig.clear()
axgrid = GridSpec(1, 1)
#get axes
ax = pylab.subplot(
axgrid[:, :],
projection = 'custom',
transform = transform,
)
ax.autoscale(False)
# ax.set_xticks(numpy.arange(-10., 35., 5.))
# ax.set_yticks(numpy.arange(-10., 35., 5.))
ax.set_xlim([-5, 20])
ax.set_ylim([-5, 10])
ax.xaxis.set_major_locator(MultipleLocator(5))
ax.grid('on')
drawLegend(ax)
return ax
if __name__ == '__main__':
if not os.path.exists('kalman'):
os.mkdir('kalman')
## figure setup
#directory for resulting figures
path = 'kalman'
#seed the rng so results are reproducible.
seed(path)
#create publisher
P = Publisher(path)
#create figure
fig = pylab.figure(figsize = (6, 6))
## kalman filter parameters
#the actual, hidden state
actual = numpy.array([[0, 5]])
#the sensor
sensor = Mvn(vectors = [[1, 0], [0, 1]],var = [1, numpy.inf])
#the system noise
noise = Mvn(vectors = [[1, 0], [0, 1]], var = numpy.array([0.5, 1])**2)
#the shear transform to move the system forward
transform = Matrix([[1, 0], [0.5, 1]])
filtered = sensor.measure(actual)
## initial plot
ax = newAx(fig)
#plot the initial actual position
ax.plot(actual[:, 0], actual[:, 1], **actualParams)
ax.set_title('Kalman Filtering: Start')
pylab.xlabel('Position')
pylab.ylabel('Velocity')
P.publish(fig)
#measure the actual position, and plot the measurment
filtered.plot(facecolor=colors['Filter Result'], **otherParams)
ax.set_title('Initialize to first measurement')
pylab.xlabel('Position')
pylab.ylabel('Velocity')
P.publish(fig)
for n in range(6):
## plot immediately after the step foreward
#create a transformed axis
ax = newAx(fig)#,transform)
#update the system
actual = actual*transform
filtered = filtered*transform
#plot the updated system
ax.plot(actual[:, 0], actual[:, 1], **actualParams)
filtered.plot(facecolor=colors['Updated'], **otherParams)
ax.set_title('Update')
pylab.xlabel('Position')
pylab.ylabel('Velocity')
P.publish(fig)
#realign the axes
ax = newAx(fig)
#re-plot the filter result
filtered.plot(facecolor=colors['Updated'], **otherParams)
#add noise and plot the actual and filtered values
actual_noise = noise+actual
filtered_noise = noise+filtered
actual_noise.plot(facecolor = colors['Noise'], **otherParams)
filtered_noise.plot(facecolor = colors['Noise'], **otherParams)
# sample the position of the actual distribution, to find it's new position
ax.plot(actual[:, 0], actual[:, 1], **actualParams)
actual=actual_noise.sample()
ax.plot(actual[:, 0], actual[:, 1], **actualParams)
ax.set_title('Add process noise')
pylab.xlabel('Position')
pylab.ylabel('Velocity')
P.publish(fig)
ax = newAx(fig)
filtered = filtered_noise
ax.plot(actual[:, 0], actual[:, 1], **actualParams)
filtered.plot(facecolor=colors['Updated+Noise'], **otherParams)
ax.set_title('Add process noise')
pylab.xlabel('Position')
pylab.ylabel('Velocity')
P.publish(fig)
measure=sensor.measure(actual)
measure.plot(facecolor = colors['Measurement'], **otherParams)
ax.set_title('Measure')
P.publish(fig)
filtered = filtered&measure
filtered.plot(facecolor = colors['Filter Result'], **otherParams)
ax.set_title('Merge')
pylab.xlabel('Position')
pylab.ylabel('Velocity')
P.publish(fig)
ax = newAx(fig)
ax.plot(actual[:, 0], actual[:, 1], **actualParams)
filtered.plot(facecolor=colors['Filter Result'], **otherParams)
pylab.xlabel('Position')
pylab.ylabel('Velocity')
ax.set_title('Merge')
P.publish(fig)
# os.system('convert -limit memory 32 -delay 100 %s/*.png kalman.gif' % path)
os.system('convert -delay 150 %s/*.png kalman.gif' % path)
| 248 | 24.12 | 84 | 14 | 1,586 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_3f5d8e0f0eebddb4_2cdba0fa", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 72, "line_end": 72, "column_start": 5, "column_end": 32, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/3f5d8e0f0eebddb4.py", "start": {"line": 72, "col": 5, "offset": 1430}, "end": {"line": 72, "col": 32, "offset": 1457}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_3f5d8e0f0eebddb4_df007d71", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "remediation": "", "location": {"file_path": "unknown", "line_start": 247, "line_end": 247, "column_start": 5, "column_end": 63, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "path": "/tmp/tmpr7mo7ysm/3f5d8e0f0eebddb4.py", "start": {"line": 247, "col": 5, "offset": 6169}, "end": {"line": 247, "col": 63, "offset": 6227}, "extra": {"message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b605_start_process_with_a_shell.html", "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-system-call-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
247
] | [
247
] | [
5
] | [
63
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] | [
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] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | kalman.py | /mvn/examples/kalman.py | MarkDaoust/mvn | BSD-2-Clause | |
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} | 3.0625 | stackv2 | # coding:utf-8
import os
import numpy as np
from torchvision.datasets import ImageFolder
import torchvision.transforms as transforms
import pickle
"""
在训练前先运行该函数获得数据的均值和标准差
"""
class Dataloader():
def __init__(self, isize, dataroot):
# 训练，验证，测试数据集文件夹名
self.isize = isize
self.dataroot = dataroot
self.dirs = ['train', 'test', 'val', 'center_v']
self.means = [0, 0, 0]
self.stdevs = [0, 0, 0]
self.transform = transforms.Compose([transforms.Resize(self.isize),
transforms.CenterCrop(self.isize),
transforms.ToTensor(), # 数据值从[0,255]范围转为[0,1]，相当于除以255操作
# transforms.Normalize((0.485,0.456,0.406), (0.229,0.224,0.225))
])
# 因为这里使用的是ImageFolder，按文件夹给数据分类，一个文件夹为一类，label会自动标注好
self.dataset = {x: ImageFolder(os.path.join(self.dataroot, x), self.transform) for x in self.dirs}
def get_mean_std(self, type, mean_std_path):
"""
计算数据集的均值和标准差
:param type: 使用的是那个数据集的数据，有'train', 'test', 'testing'
:param mean_std_path: 计算出来的均值和标准差存储的文件
:return:
"""
num_imgs = len(self.dataset[type])
for data in self.dataset[type]:
img = data[0]
for i in range(3):
# 一个通道的均值和标准差
self.means[i] += img[i, :, :].mean()
self.stdevs[i] += img[i, :, :].std()
self.means = np.asarray(self.means) / num_imgs
self.stdevs = np.asarray(self.stdevs) / num_imgs
print("{} : normMean = {}".format(type, self.means))
print("{} : normstdevs = {}".format(type, self.stdevs))
# 将得到的均值和标准差写到文件中，之后就能够从中读取
with open(mean_std_path, 'wb') as f:
pickle.dump(self.means, f)
pickle.dump(self.stdevs, f)
print('pickle done')
if __name__ == '__main__':
isize = 32
dataroot = './data-local/images/ruxian/'
dataloader = Dataloader(isize, dataroot)
for x in dataloader.dirs:
mean_std_path = 'mean_std_value_' + x + '.pkl'
dataloader.get_mean_std(x, mean_std_path) | 66 | 32.91 | 109 | 16 | 661 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_e4b21c77e39e224d_b02e522e", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 55, "line_end": 55, "column_start": 13, "column_end": 39, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpr7mo7ysm/e4b21c77e39e224d.py", "start": {"line": 55, "col": 13, "offset": 2197}, "end": {"line": 55, "col": 39, "offset": 2223}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_e4b21c77e39e224d_963ad9b7", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 56, "line_end": 56, "column_start": 13, "column_end": 40, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpr7mo7ysm/e4b21c77e39e224d.py", "start": {"line": 56, "col": 13, "offset": 2236}, "end": {"line": 56, "col": 40, "offset": 2263}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"CWE-502",
"CWE-502"
] | [
"rules.python.lang.security.deserialization.avoid-pickle",
"rules.python.lang.security.deserialization.avoid-pickle"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | [
55,
56
] | [
55,
56
] | [
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13
] | [
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"Avoid using `pickle`, which is known to lead to... | [
5,
5
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"LOW",
"LOW"
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"MEDIUM",
"MEDIUM"
] | get_mean_std.py | /MT-CNV/get_mean_std.py | Wangzheaos/DARD-Net | Unlicense | |
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} | 3.28125 | stackv2 | from sqlite3 import *
from math import *
def init_db():
db = connect(database='world.db')
return db.cursor(), db
def query_data(country_name, count, db_cursor):
sql = "select city.Name from country,city where city.CountryCode=country.code" \
" and country.name='{}' and city.population>={} order by city.Population".format(country_name, count)
db_cursor.execute(sql)
results = db_cursor.fetchall()
print(results)
return results, len(results)
def get_color(num):
colours = ['aqua', 'black', 'blue', 'fuchsia', 'gray',
'green', 'lime', 'maroon', 'navy', 'olive',
'purple', 'red', 'silver', 'teal', 'yellow']
return colours[(len(colours) % (num+1))-1]
def show_population(country_list, count, test):
db_cursor, db = init_db()
for country in country_list:
results, city_count = query_data(country, count, db_cursor)
filename = open(test + "_" + country + ".html", 'w')
filename.write("<html><body><h1 align='center'>cities of{}</h1>"
"<h3 align='center'>with population>={}</h3>"
"<h3 align='center'>city count:{}</h3><hr><p>"
.format(country, count, city_count))
for i in range(len(results)):
filename.write('<span style="font-size:{}px; color:{}"> {}</span>'
.format(city_count - i, get_color(i), results[i][0]))
filename.write('</p><div><a href="" align="right">Previous Page</a>'
'<a href="" align="left">Next Page</a></div></body></html>')
filename.close()
db_cursor.close()
db.close()
if __name__ == "__main__":
show_population(['Germany', 'New Zealand', 'Austria', 'Australia'], 1000000, 'Test05') | 49 | 35.51 | 111 | 15 | 445 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.formatted-sql-query_bb79353fa5826c31_27757485", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.formatted-sql-query", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected possible formatted SQL query. 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"CWE-89",
"CWE-89"
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"rules.python.lang.security.audit.formatted-sql-query",
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] | [
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"LOW",
"LOW"
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13,
13
] | [
13,
13
] | [
5,
5
] | [
27,
27
] | [
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"A01:2017 - Injection"
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"Detected possible formatted SQL query. Use parameterized queries instead.",
"Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepa... | [
5,
7.5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | run.py | /MixNotes/电影简介_贝叶斯/run.py | nickliqian/keep_learning | MIT | |
2024-11-18T21:10:23.271528+00:00 | 1,690,569,342,000 | 99104e1f5f3d9f194dddfbe455aff487f16a77ad | 3 | {
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"visit_date": "2023-08-08T00:05:14.122187"
} | 2.890625 | stackv2 | """This script plot_data_interactive_aerobotany.py takes the output from aggregate_drawing_demo.csv
which is the clustered circle centres for the original Aerobotany project. It plots the data points
and circles the clusters on the original subject image at the appropriate scale. A legend and title
are added.
The source for the subject image which is used for the plot background is the actual zooniverse hosted
subject. Using lookup_url.py, a lookup table of subject-url is created from the subject download from
the project. This uses subject set and workflow_id to select the appropriate subjects and their urls.
We then use this lookup table keyed by subject to find the url for the zooniverse hosted image, and
used the url to download the image to our plot background.
Once the plot has been created and displayed, there are two options to save it. One saves the plot as
a jpeg file with approximately the same resolution as the original image. The down side to this approach
is the points and circles plotted on the image are a fixed size in the pixels of the image - zooming the
image increases the size of the point markers and circle line width, obscuring the image.
The second way to store the image is as a pickle file – sort of an interrupted python script where the
plot is put on hold. To reactivate it, it must be loaded with a Python script that unpacks the pickled
file, essentially returning us to the point the file was put on hold. The advantage of this approach
is the background image is the original subject image with no resolution loss and the pan and zoom widgets
of the original plot work as before. Now if one zooms in the point size and circle line widths do not
change in on-screen pixels so the image is not obscured by large points and thick lines.
"""
import csv
import json
import sys
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
import os
from PIL import Image
import pickle
import requests
csv.field_size_limit(sys.maxsize)
# these paths and file names need to be modified for your application:
data_path = 'C:\\py\\Data_digging\\' # Note the double slashes are required
file_name = 'aggregate_drawing_demo.csv'
data_location = data_path + file_name
subject_url = r'C:\py\AASubject\lookup_list_subject_url.csv'
save_location = 'C:\\py\\Data_digging\\Plots\\'
# build a dictionary of subject-url pairs (executed once and held in memory)
def look_up_url(subject_file):
with open(subject_file, 'r') as l_up_file:
r = csv.DictReader(l_up_file)
look_up = {}
for row in r:
look_up[row['subject_id']] = row['url']
return look_up
# one of two save options, this one is a jpg file, with a scaled dpi and crop to
# retain as much resolution as possible in the smallest image file. The os operations
# ensure the files can be recreated if they already exist.
def save_plot(subject_name, w, h):
temp_file = 'temp.png'
if os.path.isfile(temp_file):
os.remove(temp_file)
plt.savefig(temp_file, dpi=160 * im.size[0] / 795)
file = Image.open(temp_file)
box = (127 * w / 795, .516 * (.966 * w - h), 127 * w / 795 + w,
.516 * (.966 * w - h) + h)
region = file.crop(box)
if os.path.isfile(save_location + subject_name + '.jpg'):
os.remove(save_location + subject_name + '.jpg')
region.save(save_location + subject_name + '.jpg')
# The second save option is to save the plot as a pickle file. This requires the use
# of a script to open it later, but preserves all the plot functionality and resolution.
def save_pickles(subject_name):
pickle_name = save_location + subject_name + '.fig.pickle'
if os.path.isfile(pickle_name):
os.remove(pickle_name)
fig = plt.gca()
pickle.dump(fig, open(pickle_name, 'wb'))
# This function acquires the data to overlay on the image from the aggregated csv.
def get_data(subject_ids):
with open(data_location, 'r') as data_file:
r = csv.DictReader(data_file)
for row in r:
if subject_ids == row['subject_ids']:
print('Data found')
data = {'H_palm_clusters': json.loads(row['H_palm_clusters']),
'Hclusters': json.loads(row['Hclusters']), 'Hnoise': json.loads(row['Hnoise']),
'flowering_clusters': json.loads(row['flowering_clusters']),
'fclusters': json.loads(row['fclusters']), 'fnoise': json.loads(row['fnoise']),
'leafless_clusters': json.loads(row['leafless_clusters']),
'lclusters': json.loads(row['lclusters']), 'lnoise': json.loads(row['lnoise'])}
return data
continue
print('Data Not found!')
return None
# This function calculates a suitable location for the label for each circle that is plotted,
# so the label does not run off the top or right edge of the plot.
def location(centre, r, size):
xlocate = centre[0] + .7 * r
ylocate = centre[1] - .7 * r
if xlocate >= size[0] - .035 * size[0]:
xlocate = centre[0] - .7 * r - .030 * size[0]
if ylocate <= .015 * size[0]:
ylocate = centre[1] + .7 * r + .01*size[0]
return [xlocate, ylocate]
# call the function to build the look_up dictionary
lookup = look_up_url(subject_url)
# begin a loop to input a subject and produce the plot for that subject.
while True:
# get the subject:
subject = str(input('Enter a valid Subject Number:' + '\n'))
try:
url = lookup[subject]
print('Subject found')
except KeyError:
print('Subject not found')
flag = input('Do you want to try again? y or n' + '\n')
if flag != 'y':
break
continue
# acquire the data:
data_points = get_data(subject)
if data_points is None:
flag = input('Do you want to try again? y or n' + '\n')
if flag != 'y':
break
continue
print('Requesting Image')
# acquire the image directly from the zooniverse url for the chosen subject and create the basic plot.
im = Image.open(requests.get(url, stream=True).raw)
plt.axis([0.0, im.size[0], im.size[1], 0.0])
plt.imshow(im)
plt.title(subject + ' ' + file_name)
ax = plt.gca()
ax.axis('off')
print('Acquired image')
# This section accumulates all the points we want to plot in both the clusters
# and the noise points and plots them using ax.scatter for each point type.
font = {'family': 'sans serif', 'color': 'yellow', 'weight': 'normal', 'size': 9}
xh = []
yh = []
xf = []
yf = []
xl = []
yl = []
for cluster in data_points['Hclusters']:
for point in cluster[1]:
xh.append(point[0])
yh.append(point[1])
for point in data_points['Hnoise']:
xh.append(point[0])
yh.append(point[1])
ax.scatter(xh, yh, s=4, c="white", marker='s', label='H. palm', alpha=1)
for cluster in data_points['fclusters']:
for point in cluster[1]:
xf.append(point[0])
yf.append(point[1])
for point in data_points['fnoise']:
xf.append(point[0])
yf.append(point[1])
ax.scatter(xf, yf, s=4, c="cyan", marker='s', label='Flowering', alpha=1)
for cluster in data_points['lclusters']:
for point in cluster[1]:
xl.append(point[0])
yl.append(point[1])
for point in data_points['lnoise']:
xl.append(point[0])
yl.append(point[1])
ax.scatter(xl, yl, s=4, c="red", marker='s', label='Leafless', alpha=1)
# add a legend
ax.legend(loc='upper right', bbox_to_anchor=(1.0, 0.13), fontsize='xx-small')
# this section adds the circles for the clustered points using ax.add.artist(Circle....
# The cluster labels are added using ax.text.
for cluster in data_points['H_palm_clusters']:
radius = 2 * cluster[2] # for eps = .5 of median
ax.add_artist(Circle((cluster[1][0], cluster[1][1]), radius, clip_on=False, zorder=10, linewidth=1,
edgecolor='white', facecolor=(0, 0, 0, 0)))
text_location = location(cluster[1], radius, im.size)
ax.text(text_location[0], text_location[1], str(cluster[0]), fontdict=font, alpha=1)
for cluster in data_points['flowering_clusters']:
radius = 2 * cluster[2] # for eps = .5 of median
ax.add_artist(Circle((cluster[1][0], cluster[1][1]), radius, clip_on=False, zorder=10, linewidth=1,
edgecolor='cyan', facecolor=(0, 0, 0, 0)))
text_location = location(cluster[1], radius, im.size)
ax.text(text_location[0], text_location[1], str(cluster[0]), fontdict=font, alpha=1)
for cluster in data_points['leafless_clusters']:
radius = 2 * cluster[2] # for eps = .5 of median
ax.add_artist(Circle((cluster[1][0], cluster[1][1]), radius, clip_on=False, zorder=10, linewidth=1,
edgecolor='red', facecolor=(0, 0, 0, 0)))
text_location = location(cluster[1], radius, im.size)
ax.text(text_location[0], text_location[1], str(cluster[0]), fontdict=font, alpha=1)
# the two save options are the called in the lines directly below. One or the other (or both)
# can be commented out if that option is not required.
save_plot(subject, im.size[0], im.size[1])
save_pickles(subject)
# actually show the plot zoomed to full screen:
mng = plt.get_current_fig_manager()
mng.window.state('zoomed')
plt.show()
# Close the plot and move to the next subject selection when finished viewing the current plot
plt.close()
print('Session terminated')
| 213 | 44.57 | 107 | 18 | 2,480 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_58e7fce1240429ea_812a8ee2", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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"CWE-502"
] | [
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] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
78
] | [
78
] | [
5
] | [
46
] | [
"A08:2017 - Insecure Deserialization"
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] | [
5
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} | 2.421875 | stackv2 | """
Profile all bench_list
"""
import subprocess as sp
import pandas as pd
import argparse
from util import *
import socket
rpt_cmd = "opreport -l -n".split()
# read a list of interested kernels
def trim_func_param(infile, outfile):
with open(infile, "r") as inf, open(outfile, "w") as outf:
for line in inf:
remainder = line.split("(")[0]
outf.write(remainder + "\n")
def process_rpt(rpt, results_df, idx):
# global results_df, idx
# read results into a datafram
rpt_df = pd.read_table(rpt, delim_whitespace=True, header=None, index_col=False,
names=["samples", "percent", "image_name", "symbol_name"])
# select kernels / exclude kernels
if args.kexclude:
for kernel in kernel_list:
rpt_df = rpt_df[~(rpt_df["symbol_name"].str.contains(kernel))]
# copy rest kernels
for _, row in rpt_df.iterrows():
if args.kexclude:
results_df.set_value(idx, row["symbol_name"], row["percent"])
else:
if row["symbol_name"] in kernel_list:
results_df.set_value(idx, row["symbol_name"], row["percent"])
# move to next record
return idx + 1
def test_bench(args):
# iterate through all benchmarks
with open(args.blist, "r") as bench_list:
for bench in bench_list:
if bench.startswith("#"): # allow commenting in benchmark list
continue
test_cmd = ["timeout", "-k", "3", "3", "python", benchfile]
config_file = get_config_file(benchfile, args.tool)
with open(config_file, "r") as config_list, open(args.output, "w") as outfile:
for config in config_list:
maybe_create_dataset(config)
sp.call(test_cmd + config.split(), stdout=outfile, stderr=outfile)
def perf_bench(args):
# iterate through all benchmarks
with open(args.blist, "r") as bench_list:
for bench in bench_list:
if bench.startswith("#"): # allow commenting in benchmark list
continue
# init
benchfile = "benchmark/" + bench.rstrip()
perf_cmd = ["operf", "--event=CPU_CLK_UNHALTED:3000000", "python", benchfile]
results_df = pd.DataFrame()
idx = 0
with open(get_config_file(benchfile, "perf"), "r") as config_list:
for config in config_list:
maybe_create_dataset(config)
try:
sp.check_call(perf_cmd + config.split())
sp.check_call(rpt_cmd + ["-o", "/tmp/blasrpt.tmp"])
trim_func_param("/tmp/blasrpt.tmp", "/tmp/blasrpt_trimmed.tmp")
idx = process_rpt("/tmp/blasrpt_trimmed.tmp", results_df, idx)
finally:
# post processing (generate signature)
#for index, row in results_df.iterrows():
# sig = get_series_signature(row)
# results_df.set_value(index, "signature", sig)
# export to .csv
results_file = benchfile.replace("bench_", "perf_")
results_file = results_file.replace(".py", ".csv")
results_df.to_csv(results_file, index=False)
def time_bench(args):
# iterate through all benchmarks
with open(args.blist, "r") as bench_list:
for bench in bench_list:
if bench.startswith("#"): # allow commenting in benchmark list
continue
# init
benchfile = "benchmark/" + bench.rstrip()
time_output = benchfile.replace(".py", ".time")
cmd = ["/usr/bin/time", "-a", "-o", time_output, "python"] + [benchfile]
# foreach configuration
with open(get_config_file(benchfile, "time"), "r") as config_file:
for config in config_file:
maybe_create_dataset(config)
sp.check_call(cmd + config.split())
def trace2csv(csvfile, count, comm_mat):
total = 0
for key, value in comm_mat.iteritems():
total += value
with open(csvfile, "a") as resutls:
for key, value in comm_mat.iteritems():
resutls.write("{},{},{},{}\n".format(count, key[0], key[1], float(value)/total))
def accumulate_comm_mat(partial_comm_mat, comm_mat):
total = 0
for key, value in partial_comm_mat.iteritems():
total += value
for key, value in partial_comm_mat.iteritems():
if key in comm_mat:
comm_mat[key] += float(partial_comm_mat[key]) / total
else:
comm_mat[key] = float(partial_comm_mat[key]) / total
def pin_bench(args):
# force numpy to run in single thread
os.environ["OMP_NUM_THREADS"] = "1"
# get pin root
pin_home = os.environ["PIN_ROOT"]
pin_cmd = [pin_home+"/pin", "-t", "pintools/obj-intel64/procatrace.so"]
if not os.path.exists(args.outdir):
os.makedirs(args.outdir)
# iterate through all benchmarks
with open(args.blist, "r") as bench_list:
for bench in bench_list:
if bench.startswith("#"): # allow commenting in benchmark list
continue
# init
bench = bench.rstrip()
benchfile = "benchmark/" + bench
config_file = get_config_file(benchfile, "pin")
count = 0
outfile = benchfile.replace(".py", "_pin.csv")
if os.path.exists(outfile):
os.remove(outfile)
with open(outfile, "w") as f:
f.write("use case,producer,consumer,comm weight\n")
with open(config_file, 'r') as config_list:
for configs in config_list:
# init
tracefile = bench.replace(".py", "_config"+str(count)+".trace")
tracefile = os.path.join(args.outdir, tracefile)
# skip profile if output file exist
if not os.path.exists(tracefile):
# create dataset if not exist
maybe_create_dataset(configs)
# call pin
full_cmd = list(pin_cmd)
full_cmd += ["-output", tracefile, "--", "python", benchfile]
full_cmd += configs.split()
try:
sp.check_call(full_cmd)
except:
os.remove(tracefile)
raise
with open(tracefile, "r") as trace:
comm_mat = parse_trace(trace)
trace2csv(outfile, count, comm_mat)
# remove tracefile if it is too large
if os.path.getsize(tracefile) > 1e10:
os.remove(tracefile)
count += 1
if __name__ == "__main__":
# top level parser
parser = argparse.ArgumentParser(description="Run benchmarks, collect data")
parser.add_argument("--blist", default="bench_list.txt", help="path to benchmark list")
subparsers = parser.add_subparsers(help="available sub-command")
# parser for time
parser_time = subparsers.add_parser("time", help="time each benchmark")
parser_time.set_defaults(func=time_bench)
# parser for operf
parser_perf = subparsers.add_parser("perf", help="profile using operf")
parser_perf.add_argument("--klist", default="kernel_list.txt", help="path to kernel list")
parser_perf.add_argument("--kexclude", action="store_true", help="exclude kernels in klist")
parser_perf.add_argument("--test", action="store_true", help="Test benchmarks, do not profile.")
parser_perf.set_defaults(func=perf_bench)
# parser for pin
parser_pin = subparsers.add_parser("pin", help="run Pin, generate memory reference trace")
parser_pin.add_argument("--klist", default="kernel_list.txt", help="path to kernel list file")
parser_pin.add_argument("--outdir", default="pin_out", help="path to output directory")
parser_pin.set_defaults(func=pin_bench)
# parser for test
parser_test = subparsers.add_parser("test", help="test validity of benchmark configurations")
parser_test.add_argument("--tool", default="perf", choices=["time", "perf", "pin"], help="for which tool")
parser_test.add_argument("--output", default="test.log", help="path to test results file")
parser_test.set_defaults(func=test_bench)
# parser command-line args
args = parser.parse_args()
with open(args.klist, "r") as klist_file:
kernel_list = klist_file.readlines()
kernel_list = map(lambda x: x.rstrip(), kernel_list)
args.func(args)
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Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_2082516de4467d73_5767f6e9", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 79, "line_end": 79, "column_start": 25, "column_end": 65, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/2082516de4467d73.py", "start": {"line": 79, "col": 25, "offset": 2567}, "end": {"line": 79, "col": 65, "offset": 2607}, "extra": {"message": "Detected subprocess function 'check_call' without a static string. 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If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_2082516de4467d73_2493a12b", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_2082516de4467d73_30815660", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 119, "line_end": 119, "column_start": 10, "column_end": 28, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/2082516de4467d73.py", "start": {"line": 119, "col": 10, "offset": 4305}, "end": {"line": 119, "col": 28, "offset": 4323}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_2082516de4467d73_35f8ec60", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 149, "line_end": 149, "column_start": 10, "column_end": 31, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/2082516de4467d73.py", "start": {"line": 149, "col": 10, "offset": 5220}, "end": {"line": 149, "col": 31, "offset": 5241}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_2082516de4467d73_cd4ca6c2", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 164, "line_end": 164, "column_start": 18, "column_end": 36, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/2082516de4467d73.py", "start": {"line": 164, "col": 18, "offset": 5769}, "end": {"line": 164, "col": 36, "offset": 5787}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_2082516de4467d73_40cc9d59", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 167, "line_end": 167, "column_start": 18, "column_end": 40, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/2082516de4467d73.py", "start": {"line": 167, "col": 18, "offset": 5892}, "end": {"line": 167, "col": 40, "offset": 5914}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_2082516de4467d73_afbd9ef6", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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A malicious actor could leverage this to perform command injection. 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"CWE-78",
"CWE-78",
"CWE-78",
"CWE-78",
"CWE-78",
"CWE-78"
] | [
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"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.danger... | [
"security",
"security",
"security",
"security",
"security",
"security"
] | [
"LOW",
"LOW",
"LOW",
"LOW",
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH",
"HIGH",
"HIGH",
"HIGH",
"HIGH"
] | [
59,
79,
80,
111,
183,
183
] | [
59,
79,
80,
111,
183,
183
] | [
21,
25,
25,
21,
29,
43
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87,
65,
76,
56,
52,
51
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"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.",
"Detected subprocess functi... | [
7.5,
7.5,
7.5,
7.5,
7.5,
7.5
] | [
"LOW",
"LOW",
"LOW",
"LOW",
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH",
"HIGH",
"HIGH",
"HIGH",
"MEDIUM"
] | prof_blas.py | /prof_blas.py | doublsky/MLProfile | MIT | |
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"visit_date": "2023-04-04T05:54:49.877548"
} | 2.3125 | stackv2 | import pickle
with open("/home/why2011btv/predicted_logit.txt",'rb') as file:
bb = pickle.load(file)
print(bb)
import h5py
import json
outfile = '/home/why2011btv/KG-embedding/20180727.hdf5'
with h5py.File(outfile, 'r') as fin:
a = fin['embedding'][...]
ent_emb = a[0:14541,:]
rel_emb = a[14541:14778,:]
emb_dict = {}
emb_dict['ent_embeddings'] = ent_emb
emb_dict['rel_embeddings'] = rel_emb
ent_list = ent_emb.tolist()
rel_list = rel_emb.tolist()
emb_dict = {}
emb_dict['ent_embeddings'] = ent_list
emb_dict['rel_embeddings'] = rel_list
with open('/home/why2011btv/KG-embedding/my_emb.json', 'w') as emb_myjson:
json.dump(emb_dict,emb_myjson) | 28 | 23.11 | 74 | 9 | 232 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_bdb3a3126c8445d3_1fc32927", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 3, "line_end": 3, "column_start": 10, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpr7mo7ysm/bdb3a3126c8445d3.py", "start": {"line": 3, "col": 10, "offset": 87}, "end": {"line": 3, "col": 27, "offset": 104}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_bdb3a3126c8445d3_ab520080", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 26, "line_end": 26, "column_start": 6, "column_end": 60, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/bdb3a3126c8445d3.py", "start": {"line": 26, "col": 6, "offset": 565}, "end": {"line": 26, "col": 60, "offset": 619}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"CWE-502"
] | [
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] | [
"security"
] | [
"LOW"
] | [
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] | [
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] | [
3
] | [
10
] | [
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] | [
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] | [
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] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | emb_to_json_for_input_to_OpenKE.py | /emb_to_json_for_input_to_OpenKE.py | why2011btv/Dolores_AKBC20 | Apache-2.0 | |
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} | 2.3125 | stackv2 | #!/usr/bin/python3
#-*- coding:utf-8 -*-
import time
from datetime import datetime
import requests
import json
import argparse
import sys
import platform
import shutil
import os
import random
banner_font = '''
Author : Dxvistxr
CMS Identificator With API => \033[1;96mhttps://whatcms.org\033[00m
2019
'''
def check_platform():
if 'Linux' not in platform.platform():
sys.exit('[*] Linux Required !')
def check_python_version():
version_py = sys.version[0]
if '3' not in version_py:
print(banner_font)
sys.exit('\033[1;91m[*] Please Run cmsid.py with python3')
def check_internet():
try:
print('[*] Checking Internet Connection...')
check_internet = requests.get('https://www.google.com')
print('[*] Internet : \033[1;92mFound !')
except Exception as error_internet:
print('[*] Internet Not \033[1;91mFound !')
sys.exit('\033[1;91m[!] Exiting')
def send_requests(key,target):
try:
check_internet()
r = requests.get('https://whatcms.org/APIEndpoint/Detect?key=%s&url=%s' % (key,target))
content_requests = r.text
obj = json.loads(content_requests)
req = obj['request']
req_web = obj['request_web']
code = obj['result']['code']
msg = obj['result']['msg']
id = obj['result']['id']
name = obj['result']['name']
confidence = obj['result']['confidence']
cms_url = obj['result']['cms_url']
t = datetime.now().strftime('%H:%M:%S')
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;96m Requests Sent At \033[1;92m%s\033[00m' % (t))
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;93mRequests SuccessFull !\033[00m')
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;92mRequest : \033[1;96m%s' % (req))
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;92mRequests Web : \033[1;96m%s' % (req_web))
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;92mStatus Code : \033[1;96m%s' % (code))
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;92mCMS Status : \033[1;96m%s' % (msg))
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;92mID Status : \033[1;96m%s' % (id))
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;92mCMS Name : \033[1;96m%s' % (name))
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;92mConfidence : \033[1;96m%s' % (confidence))
print('\033[1;92m[\033[1;94m*\033[1;92m] \033[1;92mCMS URL : \033[1;96m%s\033[00m' % (cms_url))
except Exception as error_send_requests:
print(error_send_requests)
def banner_show():
try:
check_cowsay = shutil.which('cowsay')
if check_cowsay ==None:
print('\033[1;91m[!] Cowsay Not Found !')
os.system('apt update && apt install cowsay -y')
os.system('cowsay CMS ID V1.0 By Dxvistxr')
else:
theme1 = 'cowsay CMS ID v1.0'
theme2 = 'cowsay -f eyes CMS ID v1.0'
theme3 = 'cowsay -f tux CMS ID v1.0'
theme4 = 'cowsay -f bud-frogs CMS ID v1.0'
choice_banner = [theme1,theme2,theme3,theme4]
random_choice_banner = random.choice(choice_banner)
if random_choice_banner ==theme1:
os.system(random_choice_banner)
print(banner_font)
elif random_choice_banner ==theme2:
os.system(random_choice_banner)
print(banner_font)
elif random_choice_banner ==theme3:
os.system(random_choice_banner)
print(banner_font)
elif random_choice_banner ==theme4:
os.system(random_choice_banner)
print(banner_font)
except Exception as error_banner:
print(error_banner)
def main():
check_platform()
check_python_version()
banner_show()
parser = argparse.ArgumentParser()
parser.add_argument('key',type=str,help='Set API Key')
parser.add_argument('url',type=str,help='Set Target Url')
args = parser.parse_args()
send_requests(args.key,args.url)
if __name__ == '__main__':
main()
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"visit_date": "2021-01-22T10:07:37.150778"
} | 3.21875 | stackv2 | """
Create png image of map given a url containing Layers
"""
import os
import json
from urllib.request import urlopen
import subprocess
def create_map_layer_image(url, layername, output_dir):
output_filename = "{}.png".format(layername)
output_filepath = os.path.join(os.path.abspath(output_dir), output_filename)
cmd = (
"phantomjs",
"./makepng.js",
url,
output_filepath
)
print("command: ", " ".join(cmd))
subprocess.check_call(cmd)
return output_filepath
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("-l", "--layersurl",
dest="layersurl",
default=None,
required=True,
help="URL of link to JSON map layers list")
parser.add_argument("-m", "--mapurl",
dest="mapurl",
default=None,
required=True,
help="URL of map accepting '?layer=<layername>' querystring")
parser.add_argument("-o", "--outputdir",
dest="outputdir",
default=".",
)
parser.add_argument("-n", "--name",
dest="layername",
default=None,
help="If given an image will only be generated for the given layername")
args = parser.parse_args()
if args.layername:
layer_url = "{}?layer={}".format(args.mapurl, args.layername)
result_filepath = create_map_layer_image(layer_url, args.layername, args.outputdir)
print(result_filepath)
else:
# get JSON list from layers
layers_data = json.loads(urlopen(args.layersurl).read().decode('utf-8'))
for layer_data in layers_data:
layer_url = "{}?layer={}".format(args.mapurl, layer_data["layername"])
result_filepath = create_map_layer_image(layer_url, layer_data["layername"], args.outputdir)
print(result_filepath) | 57 | 36.32 | 104 | 18 | 416 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_eed056013c9b11b9_241d397f", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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Audit uses of urllib calls to ensure user data cannot control the URLs, or consider using the 'requests' library instead.", "remediation": "", "location": {"file_path": "unknown", "line_start": 53, "line_end": 53, "column_start": 34, "column_end": 57, "code_snippet": "requires login"}, "cwe_id": "CWE-939: Improper Authorization in Handler for Custom URL Scheme", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A", "references": [{"url": "https://cwe.mitre.org/data/definitions/939.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dynamic-urllib-use-detected", "path": "/tmp/tmpr7mo7ysm/eed056013c9b11b9.py", "start": {"line": 53, "col": 34, "offset": 1817}, "end": {"line": 53, "col": 57, "offset": 1840}, "extra": {"message": "Detected a dynamic value being used with urllib. urllib supports 'file://' schemes, so a dynamic value controlled by a malicious actor may allow them to read arbitrary files. Audit uses of urllib calls to ensure user data cannot control the URLs, or consider using the 'requests' library instead.", "metadata": {"cwe": ["CWE-939: Improper Authorization in Handler for Custom URL Scheme"], "owasp": "A01:2017 - Injection", "source-rule-url": "https://github.com/PyCQA/bandit/blob/b1411bfb43795d3ffd268bef17a839dee954c2b1/bandit/blacklists/calls.py#L163", "bandit-code": "B310", "asvs": {"control_id": "5.2.4 Dynamic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://cwe.mitre.org/data/definitions/939.html"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "LOW", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
20
] | [
20
] | [
5
] | [
31
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | get_map_layer_images.py | /src/phantomjs/get_map_layer_images.py | monkut/safecasttiles | MIT | |
2024-11-18T21:10:38.584837+00:00 | 1,618,673,716,000 | 79449528a034e547fd5498dfe62772b1342e673e | 2 | {
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"visit_date": "2021-06-13T09:33:14.630331"
} | 2.4375 | stackv2 | # -*- coding: utf-8 -*-
from rdkit import RDLogger, Chem
from rdkit.Chem import MolToSmiles, MolFromSmiles, Draw
from rdkit.Chem.QED import qed
from chainer_chemistry import datasets
from chainer_chemistry.dataset.preprocessors.ggnn_preprocessor import GGNNPreprocessor
import numpy as np
import networkx as nx
import tensorflow as tf
import os.path
import time
from keras.utils import to_categorical
import argparse
import pickle
from scat import *
from utils import *
from utilMol import *
# =============================================================================
# settings
# =============================================================================
parser = argparse.ArgumentParser()
parser.add_argument("-s", "--scat", help="choose the scattering method 'S'/'D'", default='S')
parser.add_argument("-g", "--gaussianization", help="choose the gaussianization method 'W'/'N'", default='N')
args = parser.parse_args()
# =============================================================================
# prepare data
# =============================================================================
num_train = 133885
if not os.path.exists("./qm9.data"):
preprocessor = GGNNPreprocessor()
dataset, dataset_smiles = datasets.get_qm9(preprocessor, labels=None, return_smiles=True)
num_of_data = len(dataset)
features = []
adjs = []
for idx in range(num_of_data):
atom, adj, labels = dataset[idx]
if len(atom) < 9:
n_temp = len(atom)
atom_temp = np.zeros(9).astype(int)
atom_temp[:n_temp] = atom
atom_to_append = atom_to_hot(atom_temp)
else:
atom_to_append = atom_to_hot(atom)
if len(atom) < 9:
adj_temp = adj[0] + 2 * adj[1] + 3 * adj[2]
adj_to_append = np.zeros((9,9)).astype(int)
adj_to_append[:n_temp, :n_temp] = adj_temp
else:
adj_to_append = adj[0] + 2 * adj[1] + 3 * adj[2]
features.append( atom_to_append )
adjs.append( adj_to_append )
# make training / validation / testing dataset
train_idx = np.random.choice(len(features), size=num_train, replace=False)
train_data = []
train_features = []
train_adj = []
for idx in train_idx:
train_data.append(dataset_smiles[idx])
train_features.append(features[idx])
train_adj.append(adjs[idx])
with open("./qm9.data", "wb") as f:
pickle.dump(train_data, f)
pickle.dump(train_features, f)
pickle.dump(train_adj, f)
else:
with open("./qm9.data", "rb") as f:
train_data = pickle.load(f)
train_features = pickle.load(f)
train_adj = pickle.load(f)
print("QM9 data loaded.")
# =============================================================================
# encoder
# =============================================================================
feature_final = []
for idx in range(num_train):
G = nx.from_numpy_matrix(train_adj[idx])
if args.scat == 'D':
y_features = diffusion_scat( train_features[idx].T, nx.adjacency_matrix(G) )
else:
L = nx.linalg.laplacianmatrix.laplacian_matrix(G)
lamb, V = np.linalg.eigh(L.toarray())
y_features = getRep(train_features[idx].T, lamb, V)
y_features = y_features.reshape(-1)
feature_final.append(y_features)
feature_final = np.asarray(feature_final)
print("Scattering finished.")
feature_final = feature_final.reshape((num_train, -1))
if args.gaussianization == 'W':
feature_final = gaussianization_whiten(feature_final, pca=True, num_of_components=15*9)
else:
feature_final = gaussianization_spherize(feature_final, pca=True, num_of_components=15*9)
train_mu = np.zeros(np.shape( np.mean(feature_final, axis=0) ))
train_cov = np.cov(feature_final.T)
feature_final = feature_final.reshape((num_train, 9, -1))
# =============================================================================
# decoder
# =============================================================================
dim_atom = 9
dim_bond_type = 4
dim_atom_type = 5
dim_final_feature = 15
dim_final_1 = dim_atom_type
dim_final_2 = dim_atom * dim_bond_type * 15
X = tf.placeholder(tf.float32, shape=[None, dim_atom, dim_final_feature])
W1 = tf.Variable(xavier_init([dim_atom * dim_final_feature, 128]))
b1 = tf.Variable(tf.zeros(shape=[128]))
W11 = tf.Variable(xavier_init([128, 256]))
b11 = tf.Variable(tf.zeros(shape=[256]))
W12 = tf.Variable(xavier_init([256, 512]))
b12 = tf.Variable(tf.zeros(shape=[512]))
W13 = tf.Variable(xavier_init([512, dim_atom * dim_final_1]))
b13 = tf.Variable(tf.zeros(shape=[dim_atom * dim_final_1]))
W2 = tf.Variable(xavier_init([dim_atom * dim_final_feature, 128]))
b2 = tf.Variable(tf.zeros(shape=[128]))
W21 = tf.Variable(xavier_init([128, 256]))
b21 = tf.Variable(tf.zeros(shape=[256]))
W22 = tf.Variable(xavier_init([256, 512]))
b22 = tf.Variable(tf.zeros(shape=[512]))
W23 = tf.Variable(xavier_init([512, dim_final_2]))
b23 = tf.Variable(tf.zeros(shape=[dim_final_2]))
theta = [W1, b1, W11, b11, W12, b12, W13, b13,
W2, b2, W21, b21, W22, b22, W23, b23]
def fcn(x):
out1 = tf.reshape(x, (-1, dim_atom * dim_final_feature))
out1 = leaky_relu( tf.matmul(out1, W1) + b1 )
out1 = leaky_relu( tf.matmul(out1, W11) + b11 )
out1 = leaky_relu( tf.matmul(out1, W12) + b12 )
out1 = leaky_relu( tf.matmul(out1, W13) + b13 )
out1 = tf.reshape(out1, (-1, dim_atom, dim_final_1))
out2 = tf.reshape(x, (-1, dim_atom * dim_final_feature))
out2 = leaky_relu( tf.matmul(out2, W2) + b2 )
out2 = leaky_relu( tf.matmul(out2, W21) + b21 )
out2 = leaky_relu( tf.matmul(out2, W22) + b22 )
out2 = leaky_relu( tf.matmul(out2, W23) + b23 )
out2 = tf.reshape(out2, [-1, dim_atom, dim_bond_type, 15])
out2 = leaky_relu( tf.matmul(tf.transpose(out2, perm=[0,2,1,3]), tf.transpose(out2, perm=[0,2,3,1])) )
out2 = tf.transpose(out2, perm=[0,2,3,1])
return [out1, out2]
Y_adj = tf.placeholder(tf.float32, shape=[None, dim_atom, dim_atom, dim_bond_type])
Y_features = tf.placeholder(tf.float32, shape=[None, dim_atom, dim_atom_type])
fcn_loss_1 = tf.nn.softmax_cross_entropy_with_logits(labels=Y_features, logits=fcn(X)[0])
fcn_loss_2 = tf.nn.softmax_cross_entropy_with_logits(labels=Y_adj, logits=fcn(X)[1])
fcn_loss_2 = tf.matrix_band_part(fcn_loss_2,0,-1) - tf.matrix_band_part(fcn_loss_2,0,0)
fcn_loss = tf.reduce_mean(fcn_loss_1) + 2 * tf.reduce_mean(fcn_loss_2)
fcn_solver = (tf.train.AdamOptimizer(learning_rate=0.001)
.minimize(fcn_loss, var_list=theta))
train_adj_array = to_categorical(np.asarray(train_adj), num_classes=dim_bond_type)
train_features_array = np.transpose(np.asarray(train_features), axes=[0,2,1])
random_idx = list(range(num_train))
shuffle(random_idx)
feature_final = feature_final[random_idx]
train_adj_array = train_adj_array[random_idx]
train_features_array = train_features_array[random_idx]
sess = tf.Session()
sess.run(tf.global_variables_initializer())
num_epoch = 300
for it in range(num_epoch):
for i_batch in range(round(num_train/num_epoch)+1):
train_sample = feature_final[i_batch * num_epoch : (i_batch+1) * num_epoch]
train_adj_sample = train_adj_array[i_batch * num_epoch : (i_batch+1) * num_epoch]
train_features_sample = train_features_array[i_batch * num_epoch : (i_batch+1) * num_epoch]
_, loss_curr = sess.run(
[fcn_solver, fcn_loss],
feed_dict={X: train_sample, Y_features: train_features_sample, Y_adj: train_adj_sample}
)
if it % 10 == 0:
print('Iter: {}; loss: {:.4}'
.format(it, loss_curr))
print("Training finished.")
# =============================================================================
# evaluation
# =============================================================================
z = []
if args.gaussianization == 'W':
for _ in range(100000):
z_sample = sample_z(dim_atom * dim_final_feature).reshape(dim_atom,-1)
z.append(z_sample)
z = np.asarray(z)
else:
z = sample_z_full(mu=train_mu, cov=train_cov, size=100000).reshape(100000, dim_atom, -1)
samples = sess.run(fcn(X), feed_dict={X: z})
samples[0] = np.argmax(samples[0], axis=2)
samples[1] = np.argmax(samples[1], axis=3)
samples[1] = sess.run(samples[1] - tf.matrix_band_part(samples[1],0,0))
num_of_sample = 10000
atom_dict = {0: 'C', 1: 'O', 2: 'N', 3: 'F'}
mols = []
for idx in range(100000):
node_list = samples[0][idx,:]
adjacency_matrix = samples[1][idx,:,:]
where_to_cut = np.where(node_list != 4)
node_list = node_list[where_to_cut]
adjacency_matrix = adjacency_matrix[where_to_cut].T[where_to_cut]
node_name = []
for idx_node in range(len(node_list)):
node_name.append(atom_dict[node_list[idx_node]])
mol = MolFromGraphs(node_name, adjacency_matrix)
if not '.' in MolToSmiles(mol):
mols.append(mol)
if len(mols) == num_of_sample:
break
''' validity check '''
num_valid = 0
svgs = []
qeds = np.zeros(num_of_sample)
for idx in range(num_of_sample):
temp = MolFromSmiles(MolToSmiles(mols[idx]))
if temp is not None:
mols[idx] = temp
num_valid += 1
qeds[idx] = qed(mols[idx])
print( "Validity is {:.2%}".format( num_valid/10000 ) )
''' uniqueness check '''
num_of_unique_gen = len(set([MolToSmiles(mol) for mol in mols]))
print( "Uniqueness is {:.2%}".format( num_of_unique_gen / num_of_sample ) )
''' novelty check '''
data_tgt = [MolFromSmiles(i) for i in train_data]
data_tgt += mols
num_of_novel = len(set([MolToSmiles(mol) for mol in data_tgt])) + num_of_sample - len(train_data) - num_of_unique_gen
print( "Novelty is {:.2%}".format( num_of_novel / num_of_sample ) )
# =============================================================================
# draw, optional
# =============================================================================
# mols_unique = list(set([MolToSmiles(mol) for mol in mols]))
# mols_unique = [MolFromSmiles(mol) for mol in mols_unique]
# mols_uv = []
# qeds_uv = []
# for idx in range(len(mols_unique)):
# temp = mols_unique[idx]
# if temp is not None:
# mols_uv.append(temp)
# qeds_uv.append(qed(temp))
# img = Draw.MolsToGridImage(mols_uv[:25], molsPerRow=5, legends=[str("{:10.4f}".format(x)) for x in qeds_uv])
# img | 306 | 33.45 | 117 | 15 | 2,867 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_404f6e8fdac85e65_13ea4952", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. 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} | 2.59375 | stackv2 | """ Implements most file handling functions for pygrid """
# Copyright (c) 2013 Felix Brockherde
# License: BSD
import shutil
import os
from os.path import join as pjoin
from os.path import exists as pexists
import cPickle as pickle
import time
try:
import numpy
except:
numpy = None
def _save_data(filename, data):
if numpy:
with open(filename, 'w') as f:
if type(data) == dict:
numpy.savez(f, **data)
else:
numpy.save(f, data)
else:
with open(filename, 'w') as f:
pickle.dump(data, f, pickle.HIGHEST_PROTOCOL)
def _load_data(filename):
if numpy:
data = numpy.load(filename)
if hasattr(data, 'files'):
return dict(data)
else:
return data
else:
with open(filename) as f:
return pickle.load(f)
def _create_folder(temp_folder):
os.makedirs(temp_folder)
def delete_folder(temp_folder):
""" Deletes a PyGrid folder
If the folder exists, it must have a ``is_pygrid`` file to avoid accidental
deletion of other files.
Parameters
----------
temp_folder : string
The temporary folder that was given when the job was submitted first.
"""
if os.path.exists(temp_folder):
if os.path.isdir(temp_folder):
if os.path.exists(os.path.join(temp_folder, 'is_pygrid')):
shutil.rmtree(temp_folder)
else:
raise ValueError('`' + temp_folder + '` is not a PyGrid ' +
'folder.')
else:
raise ValueError('`' + temp_folder + '` is not a folder.')
def _write_info(temp_folder, function_name, path, module, cluster_params,
njobs):
with open(pjoin(temp_folder, 'info'), 'w') as f:
pickle.dump({'function_name': function_name,
'path': path,
'module': module,
'cluster_params': cluster_params,
'timestamp': time.time(),
'njobs': njobs}, f, pickle.HIGHEST_PROTOCOL)
def _get_info(temp_folder):
with open(pjoin(temp_folder, 'info')) as f:
return pickle.load(f)
def _write_files(temp_folder, args):
# find args that are common for every job
common_args = {}
for key in args[0]:
if all(key in arg and id(args[0][key]) == id(arg[key]) for
arg in args):
common_args[key] = args[0][key]
for key in common_args:
for arg in args:
del arg[key]
# write common args
if len(common_args) > 0:
_save_data(pjoin(temp_folder, 'common_args'), common_args)
# write individual args
for i, arg in enumerate(args):
if len(arg) > 0:
_save_data(pjoin(temp_folder, 'args_' + str(i)), arg)
# touch is_pygrid file
open(pjoin(temp_folder, 'is_pygrid'), 'w').close()
def get_results(temp_folder):
""" Returns the job results
Parameters
----------
temp_folder : string
The temporary folder that was given when the job was submitted first.
Returns
-------
output : list
A list with the results for each job. Each item in the list corresponds
to the item in the ``args`` list from input. If the job failed or was
not finished, the value will be None.
"""
if not os.path.exists(temp_folder):
return None
info = _get_info(temp_folder)
results = []
for i in range(info['njobs']):
try:
results.append(_load_data(pjoin(temp_folder, 'result_' + str(i))))
except IOError:
results.append(None)
return results
def _get_job_args(temp_folder, id, common_args):
if pexists(pjoin(temp_folder, 'args_' + str(id))):
return dict(_load_data(pjoin(temp_folder, 'args_' + str(id))),
**common_args)
else:
return common_args
def _get_common_args(temp_folder):
if pexists(pjoin(temp_folder, 'common_args')):
return _load_data(pjoin(temp_folder, 'common_args'))
else:
return {}
def get_args(temp_folder):
""" Return the original args
Parameters
----------
temp_folder : string
The temporary folder that was given when the job was submitted first.
Returns
-------
output : list
The ``args`` list given when the job was submitted first.
"""
info = _get_info(temp_folder)
common_args = _get_common_args(temp_folder)
args = []
for i in range(info['njobs']):
args.append(_get_job_args(temp_folder, i, common_args))
return args
def _write_job_map(temp_folder, qid, ids):
# write file that maps the cluster job tasks to jobs from the args list
with open(os.path.join(temp_folder, 'submit_map_' + qid), 'w') as f:
f.write(' '.join([str(id) for id in ids]))
def _get_job_map(temp_folder, qid):
# write file that maps the cluster job tasks to jobs from the args list
with open(os.path.join(temp_folder, 'submit_map_' + qid)) as f:
return [int(id) for id in f.read().split()]
def _get_qids(temp_folder):
with open(os.path.join(temp_folder, 'qids')) as f:
return f.read().split()
def delete_all_folders(root):
""" Deletes all PyGrid folders under a given path
The function walks through the directory structure and identifies all
PyGrid folders. It then asks for each one if it should be deleted and then
deletes the selected folders.
Parameters
----------
temp_folder : string
The temporary folder that was given when the job was submitted first.
"""
folders = []
print('Searching for pygrid folders...')
for folder, dirs, files in os.walk(root):
if 'is_pygrid' in files:
info = _get_info(folder)
folders.append((folder, info['timestamp']))
folders.sort(key=lambda (folder, timestamp): timestamp)
delete = []
for folder, timestamp in folders:
a = raw_input('Delete folder ' + folder + ' (Created ' +
time.strftime('%d %b %Y', time.localtime(timestamp)) +
')? y/[n] ')
if len(a) > 0 and a[0].lower() == 'y':
delete.append(folder)
for folder in delete:
print('Deleting ' + folder + ' ...')
delete_folder(folder)
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} | 2.40625 | stackv2 | #!/usr/bin/env python
import os
import MySQLdb
import sys
import re
import wikipedia
from bs4 import BeautifulSoup
PROJECT_DIR = os.path.abspath(
os.path.join(os.path.dirname(os.path.abspath(__file__)),
'..'))
DATA_DIR = os.path.abspath(
os.path.join(PROJECT_DIR, '..', 'data'))
sys.path.insert(0, PROJECT_DIR)
from config import BaseConfig
db = MySQLdb.connect(
host=BaseConfig.MYSQL_DATABASE_HOST,
user=BaseConfig.MYSQL_DATABASE_USER,
passwd=BaseConfig.MYSQL_DATABASE_PASSWORD,
db=BaseConfig.MYSQL_DATABASE_DB,
charset='utf8',
use_unicode=True)
cur = db.cursor()
def free_mem():
dont = ['os','MySQLdb','sys','re','wikipedia','BeautifulSoup',
'PROJECT_DIR','DATA_DIR','BaseConfig','db','cur']
a = []
for var in globals():
if "__" not in (var[:2],var[-2:]) and var not in dont:
a.append(var)
print a
for var in a:
del globals()[var]
ACTOR_QUERY = """INSERT INTO People (pname,pdob) VALUES """
# Code to generate Actor File Structure
with open(DATA_DIR + '/uci/actors.html.better', 'r') as f:
count = 0
soup = BeautifulSoup(f.read())
tbl = soup.findAll('table')
for table in tbl:
for row in table.findAll('tr')[1:]:
cells = row.findAll('td')
if len(cells) > 0:
name = cells[0].contents[0][1:].replace('"','\"').replace("'",'\"').replace('`','\"')#.encode('ascii','replace')
ACTOR_QUERY += "('%s'" % (name)
dob = '0000-00-00'
if len(cells) > 5:
dob = cells[5].contents[0][:]
try:
dob = int(dob)
dob = "%d-01-01" % (dob)
except:
dob = '0000-00-00'
#try:
# content = wikipedia.page(name).html()
# birth_year = int(re.match('.*born.*(\d{4})', content, re.DOTALL).group(1))
# print name + ' ' + str(birth_year)
# dob = '%d-01-01' % (birth_year)
#except:
# pass
ACTOR_QUERY += ",'%s')," % (dob)
count += 1
if not count % 10:
print count
ACTOR_QUERY = ACTOR_QUERY[:-1] + ";"
del soup, tbl
print 'Executing Actor Query...'
cur.execute(ACTOR_QUERY)
db.commit()
#########
PEOPLE_QUERY = """INSERT INTO People (pname,pdob) VALUES """
with open(DATA_DIR + '/uci/people.html', 'r') as f:
count = 0
soup = BeautifulSoup(f.read())
tbl = soup.findAll('table')
for table in tbl:
for row in table.findAll('tr')[1:]:
cells = row.findAll('td')
if len(cells) > 6:
#if 'A' not in ''.join(cells[1].contents):
if True:
first_name = cells[5].contents[0][1:].replace('"','\"').replace("'",'\"').replace('`','\"')
last_name = cells[4].contents[0][1:].replace('"','\"').replace("'",'\"').replace('`','\"')
PEOPLE_QUERY += "('%s %s'" % (first_name, last_name)
dob = '0000-00-00'
dob = cells[6].contents[0][:]
try:
dob = int(dob)
dob = "%d-01-01" % (dob)
except:
dob = '0000-00-00'
PEOPLE_QUERY += ",'%s')," % (dob)
count += 1
if not count % 10:
print str(count)
PEOPLE_QUERY = PEOPLE_QUERY [:-1] + ";"
del soup, tbl, f
print 'Executing People Query...'
cur.execute(PEOPLE_QUERY)
db.commit()
####################
def wiki_parse(sidebar, header_text, multiple=0):
try:
strs = []
elem = sidebar.find('th', text=header_text).parent.find('td')
if not multiple:
for s in elem.stripped_strings:
# only return first one
return s.replace("'","''")
for s in elem.stripped_strings:
strs.append(s.replace("'","''"))
return strs
#else:
# return elem.text.strip()
except:
if not multiple:
return ''
return []
def grab_col(tr, col_num):
text = tr.xpath('./td[%d]//text()' % (col_num))
if text:
text = text[0].strip().replace("'","''")
return text
return ''
def repr_int(s):
try:
int(s)
return True
except ValueError:
return False
except TypeError:
return False
except:
return False
def closest_wiki_page(title, year):
search = wikipedia.search(title)
if search:
if title in search[0] or 'film' in search[0]:
return wikipedia.page(title)
def convert_to_int(s):
if not s:
return 0
regex = re.compile(ur'[0-9\,]+',re.UNICODE)
cl = s.replace('$','').replace(',','')
try:
i = int(cl)
except ValueError:
if 'million' in cl:
pars = cl.split()
try:
i = int(float(pars[0]) * 1000000.)
return i
except ValueError:
i = regex.search(cl)
if i:
i = int(float(i.group(0)) * 1000000.)
return i
i = regex.search(cl)
if i:
return i.group(0)
return 0
def convert_runtime(r):
if not r:
return 0
regex = re.compile('\d+', re.UNICODE)
if 'minutes' in r:
m = regex.search(r)
if m:
m = m.group(0)
try:
return int(m)
except:
print m + ' WTFFFFFFFFFF'
return 0
if 'hours' in r:
m = regex.search(r)
if m:
m = m.group(0)
try:
return int(float(m) * 60.)
except:
print m + ' WTFFFFFFFFFFFFFFFFFF'
return 0
print r + '\tdafuq'
return 0
#free_mem()
from lxml import etree
movie_attrs = "mid,title,mdate,runtime,languages,description,budget,box_office,country"
MOVIE_QUERY = """INSERT INTO Movies (%s) VALUES """ % (movie_attrs)
GENRE_QUERY = """INSERT INTO Genres (gname) VALUES """
PERSON_QUERY = """INSERT INTO People (pname) VALUES """
IS_GENRE_QUERY = """INSERT INTO Is_Genre (mid,gid) VALUES """
involved_attrs = "pid,mid,directed,produced,wrote,composed,acted"
INVOLVED_IN_QUERY = """INSERT INTO Involved_In (%s) VALUES """ % (involved_attrs)
def check_exists(cur, table, pkname, chkname, chkval):
qry = """SELECT %s FROM %s WHERE %s='%s';""" % (pkname, table, chkname, chkval)
print qry
cur.execute(qry)
r = cur.fetchone()
print 'exists' + str(r)
if not r:
return False
try:
r = r[0]
return r
except TypeError:
return r
print 'Starting Main Movie Data'
import gc
gc.collect()
#with open(DATA_DIR + '/uci/main.html', 'r') as f:
# doc = etree.HTML(f.read())
# for tr in doc.xpath('//table/tr'):
# mid = grab_col(tr, 1)
# print 'mid ' + mid
# if not mid:
# continue
# if not check_exists(cur, 'Movies', 'mid', 'mid', mid):
# continue
# if check_exists(cur, 'Is_Genre', 'mid', 'mid', mid):
# continue
# genres = grab_col(tr, 8).split(',')
# while genres:
# genre = genres.pop().strip()
# ggg = check_exists(cur, 'Genres', 'gid', 'gname', genre)
# if ggg:
# igq = IS_GENRE_QUERY + "('%s',%s);" % (mid, ggg)
# print igq
# cur.execute(igq)
# else:
# gq = GENRE_QUERY + "('%s');" % (genre)
# print gq
# cur.execute(gq)
# gid = int(cur.lastrowid)
# igq = IS_GENRE_QUERY + "('%s',%s);" % (mid,gid)
# print igq
# cur.execute(igq)
with open(DATA_DIR + '/uci/main.html', 'r') as f:
count = 1
doc = etree.HTML(f.read())
tmpp = False
for tr in doc.xpath('//table/tr'):
mid = grab_col(tr, 1)
#if mid == 'AMt10':
# tmpp = True
#if not tmpp:
# print mid
# continue
if not mid: continue
#if check_exists(cur, 'Movies', 'mid', 'mid', mid):
# continue
title = grab_col(tr, 2)
title_orig = title.replace("''","'")
if not title or title[0:2] != "T:": continue
title = title.split("T:")[1]
if not title: continue
print '\n\n' + title
# if title != "My Cousin Vinny": continue
rdate = grab_col(tr, 3)
if not repr_int(rdate): continue
releasedate = '%s-01-01' % (int(rdate))
genres = grab_col(tr, 8).split(',')
print genres
if not genres: continue
if len(genres) == 1 and not genres[0]: continue
gids = []
while genres:
genre = genres.pop().strip()
ggg = check_exists(cur, 'Genres', 'gid', 'gname', genre)
if not ggg:
gq = GENRE_QUERY + "('%s');" % (genre)
print gq
cur.execute(gq)
gids.append(int(cur.lastrowid))
else:
gids.append(ggg)
db.commit()
page_name = "%s" % (title_orig)
try:
wiki = wikipedia.page(page_name)
summary = wiki.summary
if 'film' not in summary and 'movie' not in summary and 'directed' not in summary:
wiki = wikipedia.page(page_name + ' (%s film)' %(rdate))
summary = wiki.summary
if rdate not in summary:
continue
except wikipedia.exceptions.DisambiguationError as e:
try:
wiki = wikipedia.page(page_name + ' (%s film)' %(rdate))
except:
continue
except wikipedia.exceptions.PageError as e:
continue
if wiki and title.lower() in wiki.title.lower():
count += 1
print str(count) + ' ' + title
# look for runtime, languages, *keywords, description
# *tagline, budget, box_office, *mpaa rating, country
wiki_soup = BeautifulSoup(wiki.html())
sidebar = wiki_soup.find('table', {"class": 'infobox vevent'})
description = wiki.summary.replace("'","''")
runtime = wiki_parse(sidebar, 'Running time')
runtime = convert_runtime(runtime)
languages = ','.join(wiki_parse(sidebar, 'Language', True)).replace("'","''")
country = ','.join(wiki_parse(sidebar, 'Country', True)).replace("'","''")
budget = wiki_parse(sidebar, 'Budget')
budget = convert_to_int(budget)
box_office = wiki_parse(sidebar, 'Box office')
box_office = convert_to_int(box_office)
if not runtime and not languages and not country and not budget and not box_office:
continue
QUERY = MOVIE_QUERY + "('%s','%s','%s',%s,'%s','%s',%s,%s,'%s')" % (mid,
title,releasedate,runtime,languages,description,budget,box_office,country)
print QUERY
cur.execute(QUERY)
db.commit()
# genre & mid
while gids:
gid = gids.pop()
mg_qry = IS_GENRE_QUERY + "('%s',%s)" % (mid,gid)
print mg_qry
cur.execute(mg_qry)
db.commit()
# involvement: direct, produce, write, music, act
directed = wiki_parse(sidebar, 'Directed by', True)
produced = wiki_parse(sidebar, 'Produced by', True)
wrote = wiki_parse(sidebar, 'Written by', True)
music = wiki_parse(sidebar, 'Music by', True)
starred = wiki_parse(sidebar, 'Starring', True)
# set
people = set().union(*[directed,produced,wrote,music,starred])
while people:
person = people.pop()
print person
pid = check_exists(cur, 'People', 'pid', 'pname', person)
print pid
if not pid:
pq = PERSON_QUERY + "('%s')" % (person)
print pq
cur.execute(pq)
pid = cur.lastrowid
pid = int(pid)
db.commit()
d = 1 if person in directed else 0
p = 1 if person in produced else 0
w = 1 if person in wrote else 0
c = 1 if person in music else 0
a = 1 if person in starred else 0
ii_qry = INVOLVED_IN_QUERY + "(%s,'%s',%s,%s,%s,%s,%s);" % (pid,
mid,d,p,w,c,a)
print ii_qry
cur.execute(ii_qry)
db.commit()
cur.close()
db.commit()
db.close()
| 409 | 30.7 | 128 | 24 | 3,235 | python | [{"finding_id": "semgrep_rules.python.lang.security.dangerous-globals-use_e858dc3388309c59_f08b968e", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.dangerous-globals-use", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Found non static data as an index to 'globals()'. This is extremely dangerous because it allows an attacker to execute arbitrary code on the system. Refactor your code not to use 'globals()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 40, "line_end": 40, "column_start": 13, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": "CWE-96: Improper Neutralization of Directives in Statically Saved Code ('Static Code Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://github.com/mpirnat/lets-be-bad-guys/blob/d92768fb3ade32956abd53bd6bb06e19d634a084/badguys/vulnerable/views.py#L181-L186", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.dangerous-globals-use", "path": "/tmp/tmpr7mo7ysm/e858dc3388309c59.py", "start": {"line": 40, "col": 13, "offset": 926}, "end": {"line": 40, "col": 27, "offset": 940}, "extra": {"message": "Found non static data as an index to 'globals()'. This is extremely dangerous because it allows an attacker to execute arbitrary code on the system. Refactor your code not to use 'globals()'.", "metadata": {"cwe": ["CWE-96: Improper Neutralization of Directives in Statically Saved Code ('Static Code Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://github.com/mpirnat/lets-be-bad-guys/blob/d92768fb3ade32956abd53bd6bb06e19d634a084/badguys/vulnerable/views.py#L181-L186"], "category": "security", "technology": ["python"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_e858dc3388309c59_cda85bb9", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_e858dc3388309c59_0d3cf3dc", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 85, "line_end": 85, "column_start": 6, "column_end": 46, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/e858dc3388309c59.py", "start": {"line": 85, "col": 6, "offset": 2532}, "end": {"line": 85, "col": 46, "offset": 2572}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.formatted-sql-query_e858dc3388309c59_28032a0f", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.formatted-sql-query", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected possible formatted SQL query. Use parameterized queries instead.", "remediation": "", "location": {"file_path": "unknown", "line_start": 222, "line_end": 222, "column_start": 5, "column_end": 21, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/775296/mysql-parameterized-queries", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.formatted-sql-query", "path": "/tmp/tmpr7mo7ysm/e858dc3388309c59.py", "start": {"line": 222, "col": 5, "offset": 6676}, "end": {"line": 222, "col": 21, "offset": 6692}, "extra": {"message": "Detected possible formatted SQL query. Use parameterized queries instead.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "references": ["https://stackoverflow.com/questions/775296/mysql-parameterized-queries"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_e858dc3388309c59_915edf38", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 269, "line_end": 269, "column_start": 6, "column_end": 44, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/e858dc3388309c59.py", "start": {"line": 269, "col": 6, "offset": 7954}, "end": {"line": 269, "col": 44, "offset": 7992}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_e858dc3388309c59_9a1dd738", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. 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"CWE-96",
"CWE-89",
"CWE-89",
"CWE-89",
"CWE-89",
"CWE-89",
"CWE-89",
"CWE-89"
] | [
"rules.python.lang.security.dangerous-globals-use",
"rules.python.lang.security.audit.formatted-sql-query",
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query",
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query",
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query",
"ru... | [
"security",
"security",
"security",
"security",
"security",
"security",
"security",
"security"
] | [
"LOW",
"LOW",
"LOW",
"LOW",
"LOW",
"LOW",
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM",
"HIGH",
"HIGH",
"HIGH",
"HIGH",
"HIGH",
"HIGH"
] | [
40,
222,
222,
309,
360,
368,
389,
403
] | [
40,
222,
222,
309,
360,
368,
389,
403
] | [
13,
5,
5,
17,
13,
17,
21,
17
] | [
27,
21,
21,
32,
31,
36,
36,
36
] | [
"A03:2021 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Found non static data as an index to 'globals()'. This is extremely dangerous because it allows an attacker to execute arbitrary code on the system. Refactor your code not to use 'globals()'.",
"Detected possible formatted SQL query. Use parameterized queries instead.",
"Avoiding SQL string concatenation: untr... | [
5,
5,
7.5,
7.5,
7.5,
7.5,
7.5,
7.5
] | [
"LOW",
"LOW",
"LOW",
"LOW",
"LOW",
"LOW",
"LOW",
"LOW"
] | [
"MEDIUM",
"HIGH",
"HIGH",
"HIGH",
"HIGH",
"HIGH",
"HIGH",
"HIGH"
] | populate.py | /IsPepsiOkay/database/populate.py | kharddie/is-pepsi-okay | MIT | |
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} | 2.65625 | stackv2 | from flask import Flask, request
from flask_restful import Resource, Api, reqparse
from sqlalchemy import create_engine
from json import dumps
from flask import jsonify
# Connecting to the DB
db_connect = create_engine('sqlite:///sample.db')
# Creating the application
app = Flask(__name__)
api = Api(app)
# API to get the list of all the empoyees
class Employee(Resource):
def get(self):
conn = db_connect.connect() # connect to database
# This line performs query and returns json result
query = conn.execute("select * from employees")
# Fetches first column that is employee ID
return {'employees': [i[0] for i in query.cursor.fetchall()]}
# API to get info about an empoyee
class Employee_info(Resource):
def get(self):
conn = db_connect.connect()
emp = request.args.get('employee_id')
query = conn.execute(
"select * from employees where EmployeeId =%d " % int(emp))
result = {'data': [dict(zip(tuple(query.keys()), i))
for i in query.cursor]}
return jsonify(result)
class SlackEvents(Resource):
def __init__(self):
self.parser = reqparse.RequestParser()
self.parser.add_argument('challenge')
def post(self):
args = self.parser.parse_args()
if 'challenge' in args.keys():
return args['challenge']
# Publishing APIs
api.add_resource(Employee, '/employee/list') # Route 1
api.add_resource(Employee_info, '/employee') # Route 2
# Slack APIs
api.add_resource(SlackEvents, '/slack/events')
if __name__ == '__main__':
app.run(port=5002)
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"CWE-89",
"CWE-89",
"CWE-915",
"CWE-704"
] | [
"rules.python.lang.security.audit.formatted-sql-query",
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query",
"rules.python.django.security.injection.tainted-sql-string",
"rules.python.flask.security.injection.tainted-sql-string"
] | [
"security",
"security",
"security",
"security"
] | [
"LOW",
"LOW",
"LOW",
"MEDIUM"
] | [
"MEDIUM",
"HIGH",
"HIGH",
"HIGH"
] | [
32,
32,
33,
33
] | [
33,
33,
33,
33
] | [
17,
17,
13,
13
] | [
72,
72,
71,
71
] | [
"A01:2017 - Injection",
"A01:2017 - Injection",
"A08:2021 - Software and Data Integrity Failures",
"A01:2017 - Injection"
] | [
"Detected possible formatted SQL query. Use parameterized queries instead.",
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5,
7.5,
7.5,
7.5
] | [
"LOW",
"LOW",
"MEDIUM",
"MEDIUM"
] | [
"HIGH",
"HIGH",
"LOW",
"MEDIUM"
] | server.py | /server/server.py | yrahul3910/csc510-project | MIT | |
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} | 2.53125 | stackv2 | import numpy as np
import os
import string
import re
import tensorflow as tf
tf.compat.v1.enable_eager_execution()
def probability(n):
try:
counts = int(n)
except:
return 0.
return 2.**(-counts/1000.)
def find_rows(filename):
with open(filename) as f:
contents=f.read()
result = re.search('LENG (.*) match', contents)
return int(result.group(1))
def find_hashtag(data):
for i,line in enumerate(data):
if line=="#\n":
return i
def parse_a3m(filename):
seqs = []
table = str.maketrans(dict.fromkeys(string.ascii_lowercase))
for line in open(filename,"r"):
if line[0] != '>' and line[0] != '#':
# remove lowercase letters and right whitespaces
seqs.append(line.rstrip().translate(table))
# convert letters into numbers
alphabet = np.array(list("ARNDCQEGHILKMFPSTWYV-"), dtype='|S1').view(np.uint8)
msa = np.array([list(s) for s in seqs], dtype='|S1').view(np.uint8)
for i in range(alphabet.shape[0]):
msa[msa == alphabet[i]] = i
# treat all unknown characters as gaps
msa[msa > 20] = 20
return msa
def fast_dca(msa1hot, weights, penalty = 4.5):
nr = tf.shape(msa1hot)[0]
nc = tf.shape(msa1hot)[1]
ns = tf.shape(msa1hot)[2]
with tf.name_scope('covariance'):
x = tf.reshape(msa1hot, (nr, nc * ns))
num_points = tf.reduce_sum(weights) - tf.sqrt(tf.reduce_mean(weights))
mean = tf.reduce_sum(x * weights[:,None], axis=0, keepdims=True) / num_points
x = (x - mean) * tf.sqrt(weights[:,None])
cov = tf.matmul(tf.transpose(x), x)/num_points
with tf.name_scope('inv_convariance'):
cov_reg = cov + tf.eye(nc * ns) * penalty / tf.sqrt(tf.reduce_sum(weights))
inv_cov = tf.linalg.inv(cov_reg)
x1 = tf.reshape(inv_cov,(nc, ns, nc, ns))
x2 = tf.transpose(x1, [0,2,1,3])
features = tf.reshape(x2, (nc, nc, ns * ns))
x3 = tf.sqrt(tf.reduce_sum(tf.square(x1[:,:-1,:,:-1]),(1,3))) * (1-tf.eye(nc))
apc = tf.reduce_sum(x3,0,keepdims=True) * tf.reduce_sum(x3,1,keepdims=True) / tf.reduce_sum(x3)
contacts = (x3 - apc) * (1-tf.eye(nc))
return tf.concat([features, contacts[:,:,None]], axis=2)
def reweight(msa1hot, cutoff):
"""reweight MSA based on cutoff"""
with tf.name_scope('reweight'):
id_min = tf.cast(tf.shape(msa1hot)[1], tf.float32) * cutoff
id_mtx = tf.tensordot(msa1hot, msa1hot, [[1,2], [1,2]])
id_mask = id_mtx > id_min
w = 1.0/tf.reduce_sum(tf.cast(id_mask, dtype=tf.float32),-1)
return w
class Sequence(object):
def __init__(self, a3m_file, **kwargs):
self.a3m_file = a3m_file
self.name = a3m_file.split('.a3m')[0]
def build(self):
self.get_seq()
self.make_hhm()
self.fast_dca()
os.system('rm '+self.hhm_file)
def get_seq(self):
with open(self.a3m_file) as f:
lns = f.readlines()
#might not always be the second line in the file
seq = ''
l = 0
while seq == '' and l < len(lns):
if lns[l][0] == '>':
seq = lns[l+1].strip('\n')
break
else:
l += 1
if seq == '':
print('ERROR! Unable to derive sequence from input a3m file')
return
self.seq = seq
def make_hhm(self):
#create hhm
self.hhm_file = 'temp.hhm'
os.system('hhmake -i '+self.a3m_file+' -o '+self.hhm_file)
try:
with open(self.hhm_file) as f:
data = f.readlines()
except:
print('ERROR! Unable to process hhm converted from a3m')
return
NUM_COL = 30
NUM_ROW = find_rows(self.hhm_file)
pssm = np.zeros((NUM_ROW, NUM_COL))
line_counter = 0
start = find_hashtag(data)+5
for x in range (0, NUM_ROW * 3):
if x % 3 == 0:
line = data[x + start].split()[2:-1]
for i, element in enumerate(line):
prop = probability(element)
pssm[line_counter,i] = prop
elif x % 3 == 1:
line = data[x+start].split()
for i, element in enumerate(line):
prop = probability(element)
pssm[line_counter, i+20] = prop
line_counter += 1
self.hhm = pssm
def fast_dca(self):
ns = 21
wmin = 0.8
a3m = parse_a3m(self.a3m_file)
ncol = a3m.shape[1]
nrow = tf.Variable(a3m.shape[0])
msa = tf.Variable(a3m)
msa1hot = tf.one_hot(msa, ns, dtype=tf.float32)
w = reweight(msa1hot, wmin)
f2d_dca = tf.cond(nrow>1, lambda: fast_dca(msa1hot, w), lambda: tf.zeros([ncol,ncol,442], tf.float32))
f2d_dca = tf.expand_dims(f2d_dca, axis=0).numpy()
dimensions = f2d_dca.shape
f2d_dca = f2d_dca.reshape(dimensions[1],dimensions[2],dimensions[3])
self.dca = f2d_dca.astype('float16')
| 158 | 32.49 | 136 | 18 | 1,501 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_dfcc26bc45c2f115_1a4fa2ea", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 97, "line_end": 97, "column_start": 14, "column_end": 33, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/dfcc26bc45c2f115.py", "start": {"line": 97, "col": 14, "offset": 2961}, "end": {"line": 97, "col": 33, "offset": 2980}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.useless-eqeq_dfcc26bc45c2f115_c486c651", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.useless-eqeq", "finding_type": "correctness", "severity": "low", "confidence": "medium", "message": "This expression is always True: `seq == seq` or `seq != seq`. If testing for floating point NaN, use `math.isnan(seq)`, or `cmath.isnan(seq)` if the number is complex.", "remediation": "", "location": {"file_path": "unknown", "line_start": 102, "line_end": 102, "column_start": 19, "column_end": 28, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 3.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.useless-eqeq", "path": "/tmp/tmpr7mo7ysm/dfcc26bc45c2f115.py", "start": {"line": 102, "col": 19, "offset": 3137}, "end": {"line": 102, "col": 28, "offset": 3146}, "extra": {"message": "This expression is always True: `seq == seq` or `seq != seq`. If testing for floating point NaN, use `math.isnan(seq)`, or `cmath.isnan(seq)` if the number is complex.", "metadata": {"category": "correctness", "technology": ["python"]}, "severity": "INFO", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_dfcc26bc45c2f115_4bf20822", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. 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] | [
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"LOW",
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] | [
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"Found dynamic conte... | [
7.5,
7.5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | sequence.py | /prospr/sequence.py | bbyun28/prospr | MIT | |
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} | 2.5 | stackv2 | import os
import socket
from datetime import datetime
from subprocess import getstatusoutput
import boto3
from botocore.exceptions import ClientError
AWS_ACCESS_KEY_ID = os.getenv('AWS_ACCESS_KEY_ID')
AWS_SECRET_ACCESS_KEY = os.getenv('AWS_SECRET_ACCESS_KEY')
AWS_S3_BUCKET = os.getenv('AWS_S3_BUCKET')
if not (AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY and AWS_S3_BUCKET):
raise Exception('set AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY and '
'AWS_S3_BUCKET environment vars')
def _get_ip():
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
s.connect(("8.8.8.8", 80))
result = s.getsockname()[0]
s.close()
return result
AWS_S3_CLIENT = boto3.client('s3')
LOCAL_IP_ADDRESS = _get_ip()
HOSTNAME = os.uname().nodename
def get_metadata():
result = { # noqa
'local_ip_address': LOCAL_IP_ADDRESS,
'hostname': HOSTNAME,
'date_day': datetime.utcnow().strftime('%Y%m%d'),
'upload_timestamp': str(int(datetime.utcnow().timestamp() * 1000000)),
}
return result
def delete_file(filepath):
error, output = getstatusoutput(f'rm {filepath}')
if error:
raise OSError(error, output)
def take_a_picture():
filepath = f"/home/pi/camera_service/images/image_{datetime.utcnow().strftime('%Y%m%dT%H%M%S')}.jpg"
command = f"raspistill --mode 0 -o {filepath} --nopreview --exposure sports --timeout 1"
error, output = getstatusoutput(command)
if error:
raise OSError(error, output)
return filepath
def upload_aws(filepath):
file_basename = os.path.basename(filepath)
s3_path = f'{file_basename}'
try:
AWS_S3_CLIENT.upload_file(filepath, AWS_S3_BUCKET, s3_path,
ExtraArgs={'Metadata': get_metadata()}) # noqa
except ClientError as e:
print(f'> error: {e}')
return False
print(f'> uploaded {s3_path}')
return s3_path
def main():
while True:
filepath = take_a_picture()
upload_aws(filepath)
delete_file(filepath)
if __name__ == '__main__':
main()
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You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 42, "line_end": 42, "column_start": 21, "column_end": 54, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/f7f717c85cea8053.py", "start": {"line": 42, "col": 21, "offset": 1101}, "end": {"line": 42, "col": 54, "offset": 1134}, "extra": {"message": "Detected subprocess function 'getstatusoutput' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_f7f717c85cea8053_091c1f6b", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'getstatusoutput' without a static string. 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You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 50, "line_end": 50, "column_start": 21, "column_end": 45, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/f7f717c85cea8053.py", "start": {"line": 50, "col": 21, "offset": 1428}, "end": {"line": 50, "col": 45, "offset": 1452}, "extra": {"message": "Detected subprocess function 'getstatusoutput' without a static string. 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"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | [
42,
50
] | [
42,
50
] | [
21,
21
] | [
54,
45
] | [
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Detected subprocess function 'getstatusoutput' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.",
"Detected subpro... | [
7.5,
7.5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | main.py | /main.py | WesleyBatista/raspiii | MIT | |
2024-11-18T21:11:01.828972+00:00 | 1,597,068,944,000 | 8c83fccd62fcf84524d88bf414a45ab44486936b | 3 | {
"blob_id": "8c83fccd62fcf84524d88bf414a45ab44486936b",
"branch_name": "refs/heads/main",
"committer_date": 1597068944000,
"content_id": "abe837f7236af01b0f09f4e467cdf0a3b3f4629c",
"detected_licenses": [
"MIT"
],
"directory_id": "1266f756e04f96a58b4a02a18499506fbdbe0391",
"extension": "py",
"filename": "copymove.py",
"fork_events_count": 2,
"gha_created_at": 1477722763000,
"gha_event_created_at": 1620157867000,
"gha_language": "Python",
"gha_license_id": "MIT",
"github_id": 72269046,
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5493,
"license": "MIT",
"license_type": "permissive",
"path": "/src/actions/copymove.py",
"provenance": "stack-edu-0054.json.gz:576886",
"repo_name": "cmu-delphi/github-deploy-repo",
"revision_date": 1597068944000,
"revision_id": "2c3e2f201fec7b96fa1e5412482b3ff510546d5b",
"snapshot_id": "c838cdc98a8943988a10bb9723e8fb12471e642c",
"src_encoding": "UTF-8",
"star_events_count": 1,
"url": "https://raw.githubusercontent.com/cmu-delphi/github-deploy-repo/2c3e2f201fec7b96fa1e5412482b3ff510546d5b/src/actions/copymove.py",
"visit_date": "2021-07-07T07:58:34.682130"
} | 2.515625 | stackv2 | """Copy and/or move files."""
# standard library
import datetime
import glob
import json
import os
import re
import shutil
import subprocess
import time
# first party
import delphi.github_deploy_repo.file_operations as file_operations
# header for generated files
HEADER_WIDTH = 55
HEADER_LINES = [
# output from `figlet 'DO NOT EDIT'`
r' ____ ___ _ _ ___ _____ _____ ____ ___ _____ ',
r'| _ \ / _ \ | \ | |/ _ \_ _| | ____| _ \_ _|_ _|',
r'| | | | | | | | \| | | | || | | _| | | | | | | | ',
r'| |_| | |_| | | |\ | |_| || | | |___| |_| | | | | ',
r'|____/ \___/ |_| \_|\___/ |_| |_____|____/___| |_| ',
]
def add_header(repo_link, commit, src, dst_ext):
# build the header based on the source language
ext = dst_ext.lower()
pre_block, post_block, pre_line, post_line = '', '', '', ''
blanks = '\n\n\n'
if ext in ('html', 'xml'):
pre_block, post_block = '<!--\n', '-->\n' + blanks
elif ext in ('js', 'min.js', 'css', 'c', 'cpp', 'h', 'hpp', 'java'):
pre_block, post_block = '/*\n', '*/\n' + blanks
elif ext in ('py', 'r', 'coffee', 'htaccess', 'sh'):
pre_line, post_line, post_block = '# ', ' #', blanks
elif ext in ('php'):
# be sure to not introduce whitespace (e.g. newlines) outside php tags
pre_block, post_block = '<?php /*\n', '*/\n' + blanks + '?>'
else:
# nothing modified, return the original file
print(' warning: skipped header for file extension [%s]' % dst_ext)
return src
# additional header lines
t = round(time.time())
dt = datetime.datetime.fromtimestamp(t).isoformat(' ')
lines = [
'',
'Automatically generated from sources at:',
repo_link,
'',
('Commit hash: %s' % commit),
('Deployed at: %s (%d)' % (dt, t)),
]
# add the header to a copy of the source file
tmp = file_operations.get_file(src[0] + '__header')
print(' adding header [%s] -> [%s]' % (src[0], tmp[0]))
with open(tmp[0], 'wb') as fout:
fout.write(bytes(pre_block, 'utf-8'))
for line in HEADER_LINES + [line.center(HEADER_WIDTH) for line in lines]:
fout.write(bytes(pre_line + line + post_line + '\n', 'utf-8'))
fout.write(bytes(post_block, 'utf-8'))
with open(src[0], 'rb') as fin:
fout.write(fin.read())
# return the new file
return tmp
def replace_keywords(src, templates):
# load list of (key, value) pairs
pairs = []
for t in templates:
with open(t[0], 'r') as f:
pairs.extend(json.loads(f.read()))
# make a new file to hold the results
tmp = file_operations.get_file(src[0] + '__valued')
print(' replacing %d keywords [%s] -> [%s]' % (len(pairs), src[0], tmp[0]))
with open(tmp[0], 'w') as fout:
with open(src[0], 'r') as fin:
for line in fin.readlines():
for (k, v) in pairs:
line = line.replace(k, v)
fout.write(line)
# return the new file
return tmp
def copymove_single(repo_link, commit, path, row, src, dst, is_move):
action = 'move' if is_move else 'copy'
print(' %s %s -> %s' % (action, src[2], dst[2]))
# check access
file_operations.check_file(src[0], path)
# put a big "do not edit" warning at the top of the file
if row.get('add-header-comment', False) is True:
src = add_header(repo_link, commit, src, dst[3])
# replace template keywords with values
templates = row.get('replace-keywords')
if type(templates) is str:
templates = [templates]
if type(templates) in (tuple, list):
full_templates = [file_operations.get_file(t, path) for t in templates]
src = replace_keywords(src, full_templates)
# make the copy (method depends on destination)
if dst[0].startswith('/var/www/html/'):
# copy to staging area
tmp = file_operations.get_file(src[2] + '__tmp', '/common/')
print(' [%s] -> [%s]' % (src[0], tmp[0]))
shutil.copy(src[0], tmp[0])
# make directory and move the file as user `webadmin`
cmd = "sudo -u webadmin -s mkdir -p '%s'" % (dst[1])
print(' [%s]' % cmd)
subprocess.check_call(cmd, shell=True)
cmd = "sudo -u webadmin -s mv -fv '%s' '%s'" % (tmp[0], dst[0])
print(' [%s]' % cmd)
subprocess.check_call(cmd, shell=True)
else:
# make directory and copy the file
print(' [%s] -> [%s]' % (src[0], dst[0]))
os.makedirs(dst[1], exist_ok=True)
shutil.copy(src[0], dst[0])
# maybe delete the source file
if is_move:
os.remove(src[0])
def copymove(repo_link, commit, path, row, substitutions):
# {copy|move} <src> <dst> [add-header-comment] [replace-keywords]
src = file_operations.get_file(row['src'], path, substitutions)
dst = file_operations.get_file(row['dst'], path, substitutions)
# determine which file(s) should be used
if 'match' in row:
sources, destinations = [], []
recursive = row.get("recursive", False)
glob_path = "**" if recursive else "*"
for name in glob.glob(os.path.join(src[0], glob_path),
recursive=recursive):
src2 = file_operations.get_file(name)
basename = os.path.relpath(src2[0], start=src[0])
if re.match(row['match'], basename) is not None:
sources.append(src2)
file_path = os.path.join(dst[0], basename)
destinations.append(file_operations.get_file(file_path))
else:
sources, destinations = [src], [dst]
# apply the action to each file
is_move = row.get('type').lower() == 'move'
for src, dst in zip(sources, destinations):
copymove_single(repo_link, commit, path, row, src, dst, is_move)
| 158 | 33.77 | 77 | 16 | 1,606 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_46266cf4bbc22da4_f4b5f8b1", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 78, "line_end": 78, "column_start": 10, "column_end": 25, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/46266cf4bbc22da4.py", "start": {"line": 78, "col": 10, "offset": 2417}, "end": {"line": 78, "col": 25, "offset": 2432}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_46266cf4bbc22da4_c6825c57", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 85, "line_end": 85, "column_start": 10, "column_end": 27, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/46266cf4bbc22da4.py", "start": {"line": 85, "col": 10, "offset": 2696}, "end": {"line": 85, "col": 27, "offset": 2713}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_46266cf4bbc22da4_d4282b48", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 119, "line_end": 119, "column_start": 5, "column_end": 43, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/46266cf4bbc22da4.py", "start": {"line": 119, "col": 5, "offset": 3983}, "end": {"line": 119, "col": 43, "offset": 4021}, "extra": {"message": "Detected subprocess function 'check_call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_46266cf4bbc22da4_c5e68be1", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'check_call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. 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"rules.python.lang.security.audit.subprocess-shell-true"
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} | 2.4375 | stackv2 | #
# 2020 ExpertSystem
#
'''Script for generating predictions for the coinform250 dataset
using the acred predictor
See https://github.com/co-inform/Datasets
See also scripts/fetch-data.sh, which should download the input json file
and place it in the `data/evaluation/` folder.
'''
import argparse
import time
import json
import os
import os.path as osp
import requests
import traceback
import pandas as pd
def ensure_req_tweet_content(req):
for t in req['tweets']:
c = t['content']
if c is None:
t['content'] = ''
print('Fixed null content')
def acred_as_coinfo_label(credreview, thresh=0.4):
assert thresh >= 0.0
assert thresh <= 1.0
conf = credreview['reviewRating']['confidence']
if conf <= thresh:
return 'not_verifiable'
val = credreview['reviewRating']['ratingValue']
if val >= 0.5:
return 'credible'
if val >= 0.25:
return 'mostly_credible'
if val >= -0.25:
return 'credible_uncertain'
if val >= -0.5:
return 'credible_uncertain'
return 'not_credible'
def exec_req(i, req, args):
print('\n\nExecuting request %s' % (i))
ensure_req_tweet_content(req)
req['reviewFormat'] = 'schema.org'
start = time.time()
resp = requests.post(args.credpred_url, json=req,
verify=False,
timeout=args.req_timeout)
result = []
if resp.ok:
respd = resp.json()
result = [{
'tweet_id': request['tweet_id'],
'ratingValue': r['reviewRating']['ratingValue'],
'confidence': r['reviewRating']['confidence'],
'label': acred_as_coinfo_label(r)
} for request, r in zip(req['tweets'], respd)]
resp_f = 'coinform250_%s.json' % i
with open('%s/%s' % (args.outDir, resp_f), 'w') as outf:
json.dump(respd, outf)
else:
print("Failed: %s %s" % (str(resp), resp.text))
print('Processed in %ss.' % (time.time() - start))
return result
def as_acred_requests(tweets, batchSize=5):
batch = []
for i, t in enumerate(tweets):
batch.append({
'content': t['full_text'],
'tweet_id': t['id'],
'url': 'https://twitter.com/x/status/%s' % (t['id'])})
if len(batch) == batchSize:
yield {'tweets': batch,
'source': 'coinform250.json',
'batch_id': '%s-%s' % (i-batchSize, i)}
batch = []
if len(batch) > 0:
yield {'tweets': batch,
'source': 'coinform250.json',
'batch_id': '%s-%s' % (len(tweets) - len(batch), len(tweets))}
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Generate tweet credibility predictions for a dir with requests',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument(
'-inputJson',
help='Path to the coinform250.json file',
required=True)
parser.add_argument(
'-batchSize', type=int, default=5,
help='Number of tweets to send per request to acred endpoint')
parser.add_argument(
'-outDir',
help='Path to a local dir where the CredibilityReviews will be stored',
required=True)
parser.add_argument(
'-credpred_url',
help='URL of the acred endpoint for the tweet credibility')
parser.add_argument(
'-credpred_id',
help='ID of the generation task')
parser.add_argument(
'-req_timeout',
type=int, default=90,
help='Seconds to wait for a response')
args = parser.parse_args()
all_start = time.time()
assert osp.isdir(osp.join(args.outDir))
assert osp.isfile(args.inputJson)
tweets = []
with open(args.inputJson) as jsonl_file:
tweets = [json.loads(line) for line in jsonl_file]
assert len(tweets) > 0, '%s' % (len(tweets))
print('Reviewing credibility of %s tweets using batchSize %s' % (len(tweets), args.batchSize))
preds = []
for i, req in enumerate(as_acred_requests(tweets, args.batchSize)):
try:
preds.extend(exec_req(i, req, args))
except Exception as e:
print('Error executing request %s %s %s' % (i, req, str(e)))
print(traceback.format_exc())
pd.DataFrame(preds).to_csv('%s/%s.csv' % (args.outDir, 'predictions'), index=False)
print('Finished in %.3fs' % (time.time() - all_start))
| 143 | 30.61 | 98 | 16 | 1,131 | python | [{"finding_id": "semgrep_rules.python.requests.security.disabled-cert-validation_3bfd6a6299d9c740_b1a46ef1", "tool_name": "semgrep", "rule_id": "rules.python.requests.security.disabled-cert-validation", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Certificate verification has been explicitly disabled. This permits insecure connections to insecure servers. 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"CWE-295"
] | [
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] | [
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] | [
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] | [
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] | [
57
] | [
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] | [
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] | [
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] | [
7.5
] | [
"LOW"
] | [
"LOW"
] | pred_coinfo250.py | /scripts/pred_coinfo250.py | expertailab/acred | Apache-2.0 | |
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} | 3.0625 | stackv2 | #!/usr/bin/python3
"""Aggregate testlogs XMLs into a single XML file
This scripts takes a directory as an input, collects all XML files that exist
in the directory tree and aggregates results for testsuites and testcases that
are present within. The tests that are run multiple times are indexed with a
numeric suffix counter. Aggregated result is written to a file.
Example:
$ ./aggregate_xmls.py --testlogs_dir=/mydir/testlogs --output_file=out.xml
Arguments:
--testlogs_dir: directory where test logs are located. ex: <bazel-testlogs>
--output_file: name of the XML file where the aggregated results will be
written to. (default: aggregated_results.xml)
"""
import argparse
import os
import xml.etree.ElementTree as ET
def merge_xmls(filelist):
root = ET.Element('testsuites')
classcounter = {}
testcounter = {}
for filename in filelist:
data = ET.parse(filename).getroot()
for child in data.findall('testsuite'):
for subchild in child:
if subchild.tag != "testcase":
continue
else:
classname = child.attrib['name']
testname = subchild.attrib["name"]
if classname not in classcounter:
classcounter[classname] = 0
else:
classcounter[classname] += 1
if testname not in testcounter:
testcounter[testname] = 0
else:
testcounter[testname] += 1
child.attrib["name"] = child.attrib["name"] \
+ "-" + str(classcounter[classname])
subchild.attrib["name"] = subchild.attrib["name"] \
+ "-" + str(classcounter[classname])
subchild.attrib["classname"] = subchild.attrib["classname"] \
+ "-" + str(testcounter[testname])
root.append(child)
break
return root
def main():
parser = argparse.ArgumentParser(description='Aggregate test results')
parser.add_argument('--testlogs_dir', required=True)
parser.add_argument('--output_file', default='aggregate_results.xml')
args = parser.parse_args()
filelist = []
for dirname, subdir, filenames in os.walk(args.testlogs_dir):
for filename in filenames:
if filename.endswith('.xml'):
filelist.append(dirname+"/"+filename)
data = merge_xmls(filelist)
ET.ElementTree(data).write(args.output_file)
if __name__ == '__main__':
main()
| 70 | 33.67 | 78 | 19 | 532 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_efa3f9a5a4259b5e_e7a684a6", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. 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"The native Python `xml` library is vulnerable to XML Exter... | [
7.5,
7.5
] | [
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} | 4.84375 | stackv2 | # You can use the input() function to ask for input:
# n = input("Enter number: ")
# print(n)
# To build a simple calculator we could just rely on the eval function of Python:
# print(eval(input("Expression: "))) # e.g. 21 + 12
# Store result in variable and it can be used in expression:
while True:
exp = input("Expression: ") # e.g. 21 + 12, or m - 7
m = eval(exp)
print(m)
# HOWEVER, using eval is a very bad, as in dangerous, idea. If someone were to enter: os.system(‘rm -rf /’): disaster.
# So, let's quickly get rid of this eval and make our own much more specific eval that only excepts some basic mathematical expressions
| 18 | 35.28 | 135 | 9 | 180 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_0ace61f8d09a3347_8438d801", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 11, "line_end": 11, "column_start": 9, "column_end": 18, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpr7mo7ysm/0ace61f8d09a3347.py", "start": {"line": 11, "col": 9, "offset": 371}, "end": {"line": 11, "col": 18, "offset": 380}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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] | [
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"LOW"
] | [
"HIGH"
] | calculator.py | /exercises/python intro/google/calculator.py | Artimbocca/python | Apache-2.0 | |
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} | 2.765625 | stackv2 | import logging
from selenium.webdriver.support.ui import Select
import subprocess
import os
import pickle
import requests
import sqlite3
from time import sleep
def get_years(driver):
'''Retrieve a list of fiscal years available in the FCRA database'''
years = []
driver.get('https://fcraonline.nic.in/fc_qtrfrm_report.aspx')
years_options = driver.find_elements_by_xpath \
("//select[@id='ddl_block_year']//option[@value!='0']")
for option in years_options:
years.append(option.text)
print("Years available: ", years)
return years
def get_quarters(years, driver):
'''Retrieve a list of quarters available for each fiscal year'''
quarters = []
driver.get('https://fcraonline.nic.in/fc_qtrfrm_report.aspx')
for year in years:
years_menu = Select(driver.find_element_by_id("ddl_block_year"))
years_menu.select_by_value(year)
sleep(2)
quarters_options = driver.find_elements_by_xpath \
("//select[@id='ddl_qtr_returns']//option")
for option in quarters_options[1:]:
option_value = option.get_attribute("value")
quarters.append((year, option_value))
print("Quarters available: ", quarters)
return quarters
def get_state_list(driver):
'''Construct a dictionary of numerical state IDs and state names'''
driver.get('https://fcraonline.nic.in/fc_qtrfrm_report.aspx')
states_values = (driver.find_elements_by_xpath \
("//select[@id='DdnListState']//option"))
state_ids = []
for item in states_values:
state_ids.append(item.get_attribute("value"))
print(state_ids)
states = {}
for id in state_ids[1:]:
states[id] = (driver.find_element_by_xpath \
("//select[@id='DdnListState']//option[@value=" \
+ '"' + id + '"' + ']').text)
# Save states list to file
pickle.dump(states, open("./obj/states.p", "wb"))
print("States available: ", states)
return states
def get_district_lists(states, driver):
'''
Retrieve a list of districts in the FCRA database by navigating the
drop-down menus. Takes as input a dictionary that has state IDs as keys.
Returns a dictionary of dictionaries in the following format:
{'state1_id':{'state1_dist1_id':'state1_dist1_name'...}, /
'state2_id':{'state2_dist1_id':'state2_dist1_name'...}...}
'''
district_list = {}
for id in states.keys():
state_dists = {}
driver.get('https://fcraonline.nic.in/fc_qtrfrm_report.aspx')
states_menu = Select(driver.find_element_by_id("DdnListState"))
states_menu.select_by_value(id)
sleep(3)
dist_options = (driver.find_elements_by_xpath \
("//select[@id='DdnListdist']//option"))
for option in dist_options[1:]:
dist_id = option.get_attribute("value")
dist_name = option.text
state_dists[dist_id] = dist_name
district_list[id] = state_dists
# Save districts list to file
pickle.dump(district_list, open("./obj/districts.p", "wb"))
return(district_list)
# SQLite database initialization
def database_connect(db_name):
'''Connect to SQLite database'''
db = sqlite3.connect("./database/" + db_name)
c = db.cursor()
return db, c
def initialize_database(db):
'''Set up an SQLite database'''
# Districts table
db.execute("CREATE TABLE IF NOT EXISTS `districts` ( \
`dist_id` INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT, \
`state_id` VARCHAR(3) NOT NULL, \
`state_name` VARCHAR(25) NOT NULL, \
`state_dist_id` VARCHAR(4) NOT NULL, \
`state_dist_name` VARCHAR(255) NOT NULL)")
# Organizations table
db.execute("CREATE TABLE IF NOT EXISTS `organizations` ( \
`org_id` INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT UNIQUE, \
`fcra` VARCHAR(15) NOT NULL, \
`org_name` VARCHAR(255))")
# Files table
db.execute("CREATE TABLE IF NOT EXISTS `files` ( \
`file_id` INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT UNIQUE, \
`fcra` VARCHAR(10) NOT NULL, \
`dist_id` INTEGER NOT NULL, \
`path` VARCHAR(255) UNIQUE, \
`year` VARCHAR(15) NOT NULL, \
`quarter` VARCHAR(4) NOT NULL, \
`dldate` DATETIME DEFAULT CURRENT_TIME)")
# Disclosures table
db.execute("CREATE TABLE IF NOT EXISTS `disclosures` ( \
`disc_id` INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT UNIQUE, \
`file_id` INTEGER NOT NULL, \
`donor_name` VARCHAR(255), \
`donor_type` VARCHAR(255), \
`donor_address` TEXT, \
`purposes` VARCHAR(255), \
`amount` VARCHAR(20))")
db.commit()
def populate_district_table(driver, db, c):
'''Populate database table of states and districts'''
print("Gathering all districts for all states. This will take a few minutes.")
states = get_state_list(driver)
districts = get_district_lists(states, driver)
counter = 0
for state in states.keys():
for district in districts[state].keys():
c.execute("INSERT INTO districts (state_id, state_name, \
state_dist_id, state_dist_name) VALUES (:state_id, \
:state_name, :state_dist_id, :state_dist_name)", \
{'state_id':state, 'state_name':states[state], \
'state_dist_id':district, \
'state_dist_name':districts[state][district]})
counter += 1
db.commit()
print("Populated districts table with ", counter, "districts")
# Linux only (requires pdftk): verify integrity of downloaded file
def verify_pdf(path):
'''Checks PDF integrity and re-downloads if file appears corrupt'''
result = subprocess.run(["./verify_pdf.sh", path], stdout=subprocess.PIPE)
return result
def get_file(yr, qtr, org, filepath, starturl, db, c, state, district):
'''Downloads a disclosure'''
r = requests.get(starturl + org + "R&fin_year=" \
+ yr +"&quarter=" + qtr)
# Look up district id
dist_id, = c.execute("SELECT dist_id FROM districts WHERE \
state_id = :state AND state_dist_id = :district", \
{'state':state, 'district':district})
# Create file information in database
c.execute("INSERT INTO files (fcra, year, quarter, dist_id) VALUES \
(:fcra, :year, :quarter, :dist_id)", {'fcra':org, 'year':yr, \
'quarter':qtr, 'dist_id':dist_id})
db.commit()
# Get unique file ID to append to filename (unpack tuple)
file_id, = c.execute("SELECT file_id FROM files WHERE fcra = :org AND \
year = :yr AND quarter = :quarter", {'org':org, \
'yr':yr, 'quarter':qtr}).fetchone()
# Download disclosure
full_path = (filepath + '/D_' + str(file_id) + '_' + org + '_' + yr + '_' \
+ qtr + ".pdf")
with open(full_path, 'wb') as file:
file.write(r.content)
# Associate path with file_id in database
c.execute("UPDATE files SET path = :full_path WHERE file_id = :file_id", \
{'file_id':file_id, 'full_path':full_path})
db.commit()
print("Wrote file D_" + str(file_id) + '_' + org + '_' + yr + '_' \
+ qtr +".pdf to disk")
sleep(1)
return(full_path)
# Download disclosures of selected years, quarters, districts
def download_disclosures(quarters, districts, driver, db, c):
'''Downloads PDF disclosures for the quarters and districts specified by
the user
INPUT:
quarters: [('yyyy-yyyy', 'q')...] e.g., [('2015-2016', '3'), ('2015-2016', '4')]
districts: {'stateid':{'districtid1':'name1'...}...}
'''
starturl='https://fcraonline.nic.in/Fc_qtrFrm_PDF.aspx?rcn='
for quarter in quarters:
(yr, qtr) = quarter
for state in districts.keys():
for district in districts[state].keys():
try:
# Navigate the drop-down menus
driver.get('https://fcraonline.nic.in/fc_qtrfrm_report.aspx')
years_menu = Select(driver.find_element_by_id("ddl_block_year"))
years_menu.select_by_value(yr)
sleep(2.5)
quarters_menu = Select(driver.find_element_by_id("ddl_qtr_returns"))
quarters_menu.select_by_value(qtr)
states_menu = Select(driver.find_element_by_id("DdnListState"))
states_menu.select_by_value(state)
sleep(2.5)
districts_menu = Select(driver.find_element_by_id("DdnListdist"))
districts_menu.select_by_value(district)
submit_btn = driver.find_element_by_id("Button1")
submit_btn.click()
# Create directory to store district disclosures if none exists
filepath = "./disclosures/" + state +'/' + district
os.makedirs(filepath, exist_ok=True)
sleep(2)
except requests.exceptions.ConnectionError as e:
logging.exception(f"{yr} q{qtr} state {state} \
district {district} failed: \
Connection error")
sleep(10)
continue
except:
logging.exception(f"{yr} q{qtr} {state} {district} failed.")
sleep(10)
continue
# Compile dict of organization names and FCRA reg numbers
dyq_orgs={}
null_returns=set()
table_rows = driver.find_elements_by_xpath \
("//table[@id='GridView1']//tr")
for row in table_rows[1:]:
table_data = row.find_elements_by_tag_name('td')
org_name = table_data[1].text
org_fcra = table_data[2].text
amount = table_data[3].text
# Save dictionary of district-year-quarter disclosures to scrape
dyq_orgs[org_fcra] = org_name
# If amount is 0.00, add to set of null returns (don't download!)
if amount == "0.00":
null_returns.add(org_fcra)
# Check if each organization is already in the database; if not,
# update organizations data table
for org in dyq_orgs.keys():
rows = c.execute("SELECT org_id FROM organizations WHERE \
fcra = :key", {'key':org}).fetchall()
if len(rows) == 0:
c.execute("INSERT INTO organizations (fcra, org_name) \
VALUES (:fcra, :org_name)", {'fcra':org,\
'org_name':dyq_orgs[org]})
db.commit()
# Save PDF disclosures
for org in dyq_orgs.keys():
try:
if org in null_returns:
continue
else:
try_count = 0
path = get_file(yr, qtr, org, filepath, starturl, \
db, c, state, district)
result = verify_pdf(path)
while result == "broken" and try_count < 3:
print("File corrupted, retrying")
logging.info(f"Re-downloading %s", path)
sleep(5)
get_file(yr, qtr, org, filepath, starturl, \
db, c, state, district)
try_count += 1
else:
continue
except:
logging.exception(f"Exception at {org} {yr} {qtr}")
logging.info(f"Finished {state} {yr} qtr {qtr}")
print(f"Finished state {state} {yr} qtr {qtr}")
return 0
| 295 | 40.5 | 88 | 23 | 2,756 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.arbitrary-sleep_cdac9df42228b333_c7a6d9cf", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.arbitrary-sleep", "finding_type": "best-practice", "severity": "high", "confidence": "medium", "message": "time.sleep() call; did you mean to leave this in?", "remediation": "", "location": {"file_path": "unknown", "line_start": 28, "line_end": 28, "column_start": 9, "column_end": 17, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.arbitrary-sleep", "path": "/tmp/tmpr7mo7ysm/cdac9df42228b333.py", "start": {"line": 28, "col": 9, "offset": 916}, "end": {"line": 28, "col": 17, "offset": 924}, "extra": {"message": "time.sleep() call; did you mean to leave this in?", "metadata": {"category": "best-practice", "technology": ["python"]}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_cdac9df42228b333_4d8c4454", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. 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"rules.python.lang.security.deserialization.avoid-pickle"
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"Avoid using `pickle`, which is known to lead to... | [
5,
5
] | [
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] | modules_dl.py | /data-sets/spfrantz-code/modules_dl.py | ruralhuman/accountability | CC0-1.0 | |
2024-11-18T21:11:08.494988+00:00 | 1,510,267,898,000 | 8c77c556534fee53c2d8b3f8323b07fa4aa34f7a | 2 | {
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} | 2.4375 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
import paho.mqtt.client as paho
import json
import time
import uuid
import Queue
import subprocess
import unicodedata
MQTT_SERVER = 'localhost'
MAYORDOMO_TOPIC = 'rcr/Mayordomo'
SPEAK_TOPIC = 'rcr/Speak'
PLAYER_TOPIC = 'rcr/MusicPlayer'
DRONE_TOPIC = 'rcr/RollerSpider'
DHT22_TOPIC = 'rcr/DHT22'
MINDSET_TOPIC = 'rcr/MindSet'
MAX7219_TOPIC = 'rcr/Max7219'
NOISE_TOPIC = 'rcr/Ruido'
S2_TOPIC = 'rcr/S2'
messages = Queue.Queue( 1 )
data_dht22 = None
def sendToSpeak( msg ):
global mqtt_client, SPEAK_TOPIC
mqtt_client.publish( SPEAK_TOPIC, msg )
def sendToMusicPlayer( msg ):
global mqtt_client, PLAYER_TOPIC
mqtt_client.publish( PLAYER_TOPIC, msg )
def sendToDrone( msg ):
global mqtt_client, DRONE_TOPIC
mqtt_client.publish( DRONE_TOPIC, msg )
def sendToMindSet( msg ):
global mqtt_client, MINDSET_TOPIC
mqtt_client.publish( MINDSET_TOPIC, msg )
def sendToMax7219( msg ):
global mqtt_client, MAX7219_TOPIC
mqtt_client.publish( MAX7219_TOPIC, msg )
def sendToNoise( msg ):
global mqtt_client, NOISE_TOPIC
mqtt_client.publish( NOISE_TOPIC, msg )
def sendToS2( msg ):
global mqtt_client,S2_TOPIC
mqtt_client.publish( S2_TOPIC, msg )
def mqtt_on_message( client, userdata, message ):
global messages, data_dht22
# es el dht22
if( message.topic == DHT22_TOPIC ):
data_dht22 = message.payload
return
# lon comandos para el mayordomo
# si no se ha procesado el ultimo mensaje lo eliminamos
try:
messages.get_nowait()
except Queue.Empty:
pass
# agregamos el mensaje
try:
messages.put_nowait( message )
except Queue.Full:
pass
def mqtt_on_connect( client, arg1, arg2, arg3 ):
global MAYORDOMO_TOPIC, MQTT_SERVER
client.subscribe( MAYORDOMO_TOPIC )
client.subscribe( DHT22_TOPIC )
print( "[Mayordomo] Esperando en %s - %s" % ( MQTT_SERVER, MAYORDOMO_TOPIC ) )
def main():
global mqtt_client, MQTT_SERVER, messages, data_dht22
print( '[Mayordomo] Iniciando sistema' )
subprocess.Popen( '/bin/sh ./Speak.sh', shell=True )
subprocess.Popen( '/usr/bin/python ./MusicPlayer/MusicPlayer.py', shell=True )
mqtt_client = paho.Client( 'Mayordomo-' + uuid.uuid4().hex )
mqtt_client.on_connect = mqtt_on_connect
mqtt_client.on_message = mqtt_on_message
mqtt_client.connect( MQTT_SERVER, 1883 )
mqtt_client.loop_start()
time.sleep( 2 )
sendToSpeak( ' ' )
sendToSpeak( ' Sistema inicializado' )
abort = False
while( not abort ):
message = messages.get()
# hacemos el manejo del payload que viene en utf-8 (se supone)
# la idea es cambiar tildes y otros caracteres especiales
# y llevar todo a minuscula
cmd = message.payload.decode('utf-8').lower()
cmd = ''.join((c for c in unicodedata.normalize('NFD', cmd) if unicodedata.category(c) != 'Mn'))
cmd = cmd.replace( 'mary', 'mari' )
cmd = cmd.replace( 'detener', 'deten' )
cmd = cmd.replace( 'tocar', 'toca' )
cmd = cmd.replace( 'pausar', 'pausa' )
cmd = cmd.replace( 'iniciar', 'inicia' )
cmd = cmd.replace( 'finalizar', 'finaliza' )
cmd = cmd.replace( 'mostrar', 'muestra' )
cmd = cmd.replace( 'robots', 'robot' )
cmd = cmd.replace( 'conectar', 'conecta' )
cmd = cmd.replace( 'desconectar', 'desconecta' )
print( "[Mayordomo] Mensaje recibido:", message.payload, "<<" + cmd + ">>" )
# locales
if( cmd == 'finaliza sistema' ):
abort = True
elif( cmd == 'mari' ):
sendToSpeak( 'Dime Padre' )
elif( cmd == 'que hora es' ):
now = time.localtime()
sendToSpeak( 'son las %d horas con %d minutos' % (now.tm_hour, now.tm_min) )
elif( cmd == 'conversemos' ):
now = time.localtime()
sendToSpeak( 'de que deseas conversar?' )
# MusicPlayer
elif( cmd == 'toca musica' ):
sendToMusicPlayer( 'play' )
elif( cmd == 'deten musica' ):
sendToMusicPlayer( 'stop' )
elif( cmd == 'pausa musica' ):
sendToMusicPlayer( 'pause' )
elif( cmd == 'tema siguiente' ):
sendToMusicPlayer( 'next' )
elif( cmd == 'tema anterior' ):
sendToMusicPlayer( 'previous' )
elif( cmd == 'quien canta' ):
sendToMusicPlayer( 'songtitle' )
# DroneRollerSpider
elif( cmd == 'inicia spider' ):
subprocess.Popen( '/usr/bin/python ./DroneRollerSpider/DroneRollerSpider.py', shell=True )
elif( cmd == 'finaliza spider' ):
sendToDrone( 'exit' )
elif( cmd == 'conecta spider' ):
sendToDrone( 'connect' )
elif( cmd == 'desconecta spider' or cmd =='desconectar spyder' ):
sendToDrone( 'disconnect' )
elif( cmd == 'sube spider' ):
sendToDrone( 'takeoff' )
elif( cmd == 'baja spider' ):
sendToDrone( 'land' )
elif( cmd == 'gira spider' ):
for i in range( 10 ):
sendToDrone( 'turn_left' )
time.sleep( 0.100 )
# MindSet
elif( cmd == 'inicia sensor neuronal' ):
subprocess.Popen( '/usr/bin/python ./MindSet/MindSetPub.py', shell=True )
subprocess.Popen( '/usr/bin/python ./MindSet/MindSetGraphics.py', shell=True )
subprocess.Popen( '/usr/bin/python ./MindSet/MindSetMusic.py', shell=True )
elif( cmd == 'finaliza sensor neuronal' ):
sendToMindSet( 'exit' )
# DHT22
elif( cmd == 'temperatura' ):
if( data_dht22 == None ):
sendToSpeak( 'No tengo datos de temperatura' )
else:
d = data_dht22
d = json.loads( d )
sendToSpeak( 'La Temperatura es de %3.1f grados' % ( d["temperatura"] ) )
elif( cmd == 'humedad' ):
if( data_dht22 == None ):
sendToSpeak( 'No tengo datos de humedad' )
else:
d = data_dht22
d = json.loads( d )
sendToSpeak( 'La humedad es de un %3.1f por ciento' % ( d["humedad"] ) )
# Max72129
elif( cmd.startswith( 'muestra ' ) and len( cmd ) == 9 ):
try:
digit = int( cmd[8] )
sendToSpeak( "Mostrando un %d en la matriz" % digit )
sendToMax7219( str( digit ) )
except Exception as e:
pass
# Sensor de ruido
elif( cmd == 'inicia analisis de ruido' ):
subprocess.Popen( '/usr/bin/python ./Noise/NoiseGraphics.py', shell=True )
elif( cmd == 'finaliza analisis de ruido' ):
sendToNoise( 'exit' )
# robot S2
elif( cmd == 'inicia control de robot' ):
subprocess.Popen( '/usr/bin/python ./S2/S2.py', shell=True )
elif( cmd == 'nombre de robot' ):
sendToS2( 'name' )
elif( cmd == 'robot izquierda' ):
sendToS2( 'left 1' )
elif( cmd == 'robot derecha' ):
sendToS2( 'right 1' )
elif( cmd == 'robot avanza' ):
sendToS2( 'forward 5' )
elif( cmd == 'robot retrocede' ):
sendToS2( 'backward 5' )
elif( cmd == 'finaliza control de robot' ):
sendToS2( 'exit' )
sendToSpeak( 'Sistema finalizado' )
time.sleep( 2 )
mqtt_client.loop_stop()
print( '[Mayordomo] Sistema finalizado' )
#--
main()
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2024-11-18T21:11:16.262414+00:00 | 1,606,450,715,000 | 0c8d03f5d906e864de8af65afce16732d44f0c83 | 2 | {
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"visit_date": "2021-06-22T13:21:54.870396"
} | 2.40625 | stackv2 | #!/usr/bin/python
import sys
import os
import time
import datetime
from datetime import timedelta
import requests
from bs4 import BeautifulSoup
from ftplib import FTP
#if len(sys.argv) != 2:
# print >>sys.stderr, "Useage: ",sys.argv[0]," [YYYY_MM_DD]"
# quit()
#date = sys.argv[1]
# get current date and time minus one hour
UTC_OFFSET_TIMEDELTA = datetime.datetime.utcnow() - datetime.datetime.now()
date_1_hour_ago = datetime.datetime.now() - timedelta(hours=1) + UTC_OFFSET_TIMEDELTA
date = date_1_hour_ago.strftime("%Y_%m_%d")
dateNoHyphens = date_1_hour_ago.strftime("%Y%m%d")
hour = date_1_hour_ago.strftime("%H")
#nowTime = time.gmtime()
#now = datetime.datetime(nowTime.tm_year, nowTime.tm_mon, nowTime.tm_mday,
# nowTime.tm_hour, nowTime.tm_min, nowTime.tm_sec)
#date = now.strftime("%Y_%m_%d")
#date = '2018_11_01'
url = 'https://engineering.arm.gov/~radar/amf1_csapr2_incoming_images/hsrhi/'+date+'/'
ext = 'png'
homeDir = os.getenv('HOME')
outDir = os.path.join(homeDir, 'radar/csapr2/' + date)
category = 'radar'
platform = 'DOE_CSapr2'
ftpCatalogServer = 'catalog.eol.ucar.edu'
ftpCatalogUser = 'anonymous'
catalogDestDir = '/pub/incoming/catalog/relampago'
debug = 1
def listFD(url, ext=''):
page = requests.get(url).text
print page
soup = BeautifulSoup(page, 'html.parser')
return [url + '/' + node.get('href') for node in soup.find_all('a') if node.get('href').endswith(ext)]
if not os.path.exists(outDir):
os.makedirs(outDir)
os.chdir(outDir)
for file in listFD(url, ext):
tmp = os.path.basename(file)
(f,e) = os.path.splitext(tmp)
parts = f.split('_')
(fdate,ftime) = parts[3].split('-')
fhour = ftime[0:2]
if fdate == dateNoHyphens and fhour == hour:
print file
cmd = 'wget '+file
os.system(cmd)
# correct names of -0.0 files
#cmd = 'mmv "*_-0.0.png" "#1_00.0.png"'
#os.system(cmd)
# rename files and ftp them
for file in os.listdir(outDir):
if file.startswith('cor_'):
if debug:
print >>sys.stderr, "file = ",file
(filename, file_ext) = os.path.splitext(file)
parts = filename.split('_')
(date,time) = parts[3].split('-')
angle_parts = parts[5].split('.')
if len(angle_parts[0]) == 1:
angle = '00'+angle_parts[0]
elif len(angle_parts[0]) == 2:
angle = '0'+angle_parts[0]
else:
angle = angle_parts[0]
product = parts[2]+'_'+parts[4]+'_'+angle
file_cat = category+'.'+platform+'.'+date+time+'.'+product+file_ext
if debug:
print >>sys.stderr, "file_cat = ",file_cat
cmd = 'mv '+file+' '+file_cat
os.system(cmd)
# ftp file
try:
catalogFTP = FTP(ftpCatalogServer,ftpCatalogUser)
catalogFTP.cwd(catalogDestDir)
file = open(file_cat,'rb')
catalogFTP.storbinary('STOR '+file_cat,file)
file.close()
catalogFTP.quit()
except Exception as e:
print >>sys.stderr, "FTP failed, exception: ", e
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This could allow a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b605_start_process_with_a_shell.html", "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "confidence": "MEDIUM", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["vuln"], "likelihood": "MEDIUM", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.insecure-transport.ftplib.use-ftp-tls_eeb474d05e8588cc_367398d2", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.insecure-transport.ftplib.use-ftp-tls", "finding_type": "security", "severity": "low", "confidence": "low", "message": "The 'FTP' class sends information unencrypted. Consider using the 'FTP_TLS' class instead.", "remediation": "FTP_TLS(ftpCatalogServer,ftpCatalogUser, context=ssl.create_default_context())", "location": {"file_path": "unknown", "line_start": 90, "line_end": 90, "column_start": 26, "column_end": 62, "code_snippet": "requires login"}, "cwe_id": "CWE-319: Cleartext Transmission of Sensitive Information", "cwe_name": null, "cvss_score": 3.0, "cvss_vector": null, "owasp_category": "A03:2017 - Sensitive Data Exposure", "references": [{"url": "https://docs.python.org/3/library/ftplib.html#ftplib.FTP_TLS", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.insecure-transport.ftplib.use-ftp-tls", "path": "/tmp/tmpr7mo7ysm/eeb474d05e8588cc.py", "start": {"line": 90, "col": 26, "offset": 2762}, "end": {"line": 90, "col": 62, "offset": 2798}, "extra": {"message": "The 'FTP' class sends information unencrypted. Consider using the 'FTP_TLS' class instead.", "fix": "FTP_TLS(ftpCatalogServer,ftpCatalogUser, context=ssl.create_default_context())", "metadata": {"owasp": ["A03:2017 - Sensitive Data Exposure", "A02:2021 - Cryptographic Failures", "A04:2025 - Cryptographic Failures"], "cwe": ["CWE-319: Cleartext Transmission of Sensitive Information"], "references": ["https://docs.python.org/3/library/ftplib.html#ftplib.FTP_TLS"], "category": "security", "technology": ["ftplib"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "LOW", "confidence": "LOW"}, "severity": "INFO", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 6 | true | [
"CWE-78",
"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-system-call-audit",
"rules.python.lang.security.audit.dangerous-system-call-audit",
"rules.python.lang.security.audit.dangerous-system-call-tainted-env-args"
] | [
"security",
"security",
"security"
] | [
"LOW",
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH",
"HIGH"
] | [
60,
86,
86
] | [
60,
86,
86
] | [
9,
9,
9
] | [
23,
23,
23
] | [
"A01:2017 - Injection",
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.",
"Found dynamic conte... | [
7.5,
7.5,
7.5
] | [
"LOW",
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH",
"HIGH"
] | ftpCSapr2Images.py | /projDir/uw/scripts/ftpCSapr2Images.py | NCAR/lrose-projects-relampago | BSD-2-Clause | |
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"visit_date": "2022-11-19T08:37:40.228472"
} | 2.484375 | stackv2 | import io
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import glob
import cv2
import numpy as np
import pickle
def calibrate_camera():
'''use calibration images to automatically calculate the undistortion coefficients'''
# initialzing
imgpoints = [] # 2d image world
objpoints = [] # 3d image world
objp = np.zeros((6*9,3), np.float32) # size of array is 9 by 6
objp[:,:2] = np.mgrid[0:9,0:6].T.reshape(-1,2) # x and y coordinates
cal_set = []
for image in glob.glob('./camera_cal/calibration*.jpg'): # folder path
n = mpimg.imread(image)
cal_set.append(n)
img = np.copy(n)
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
ret,corners = cv2.findChessboardCorners(gray, (9,6), None)
if ret == True:
imgpoints.append(corners)
objpoints.append(objp)
img = cv2.drawChessboardCorners(img,(9,6),corners,ret)
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, (6,9) , None, None)
with open(b'camera_cal.pickle','wb') as output_file:
pickle.dump([mtx,dist],output_file) | 35 | 31.77 | 96 | 13 | 322 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_85d2f06c1444c93f_b54970a7", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 35, "line_end": 35, "column_start": 9, "column_end": 44, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpr7mo7ysm/85d2f06c1444c93f.py", "start": {"line": 35, "col": 9, "offset": 1111}, "end": {"line": 35, "col": 44, "offset": 1146}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-502"
] | [
"rules.python.lang.security.deserialization.avoid-pickle"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
35
] | [
35
] | [
9
] | [
44
] | [
"A08:2017 - Insecure Deserialization"
] | [
"Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format."
] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | camera_cal.py | /camera_cal.py | rajath12/Advanced_Lane_Lines | MIT | |
2024-11-18T21:11:18.877410+00:00 | 1,431,694,191,000 | a7986fc4856134f491a10dca266409bf04d3aa39 | 3 | {
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} | 2.59375 | stackv2 | __author__ = 'kian'
import os
import time
from subprocess import Popen
# This file is needed to loop over the different keys and produce their .wav file
# NB This uses the bash command 'sed' !
letters = ['A', 'Ab', 'Ad', 'B', 'C', 'Cd', 'D', 'Dd', 'E', 'F', 'Fd', 'G']
nums = ['2', '3', '4', '5']
moduleNext = None
par = "Parameters.parameters"
names = ['main', 'plot_and_save','update']
present = os.listdir("./Notes")
tonePrev = letters[0]+nums[0]
threadCount = 0
for j, num in enumerate(nums):
for i, letter in enumerate(letters):
if num == nums[0]:
try:
tonePrev = letter+num
toneNext = letters[i+1]+num
except:
break
modulePrev = par+tonePrev
moduleNext = par+toneNext
else:
modulePrev = moduleNext
tonePrev = toneNext
toneNext = letters[i]+num
moduleNext = par+toneNext
if "piano"+tonePrev+".wav" not in present:
print "python thread processing "+tonePrev
bashPythoncommand = "/home/kian/anaconda/bin/python"
threadCount += 1
p = Popen([bashPythoncommand, 'main.py'])
print modulePrev, moduleNext
for name in names:
bashCommand_module = "sed -i -e 's/" + modulePrev +"/"+ moduleNext+"/g' "+ "./"+name+".py"
os.system(bashCommand_module)
time.sleep(1)
bashCommand_filename = "sed -i -e 's/" + "piano"+tonePrev +"/"+ "piano"+toneNext+"/g' "+ "./"+name+".py"
os.system(bashCommand_filename)
time.sleep(1)
if "piano"+letters[-1]+nums[-1]+".wav" not in present:
print "python thread processing "+letters[-1]+nums[-1]
bashPythoncommand = "/home/kian/anaconda/bin/python"
p = Popen([bashPythoncommand, 'main.py'])
threadCount += 1
time.sleep(15)
print "Thread starter complete - Total number of threads running: " + str(threadCount) | 51 | 37.47 | 116 | 20 | 527 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_495d7138b35a8dcd_6eb60e77", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. 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"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-system-call-audit",
"rules.python.lang.security.audit.dangerous-system-call-audit"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | [
40,
43
] | [
40,
43
] | [
13,
13
] | [
42,
44
] | [
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.",
"Found dynamic conte... | [
7.5,
7.5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | renamer.py | /renamer.py | kianvde/PianoSimulation | MIT | |
2024-11-18T19:03:18.415945+00:00 | 1,421,517,685,000 | fa30b9ba4a29ebf791629079edf3f480058326bd | 3 | {
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"visit_date": "2021-01-17T21:53:11.207408"
} | 2.671875 | stackv2 |
"""
Dynamic synaptic weight implementing phenomenological short term
depression and facilitation.
Description:
Implemented is the ODE form of the short-term depression and
facilitation model as described Eq (2) and Eq (3) in [1] or Eq (6)
in [2], whereby Eq (2) in [1] seems to have an error in the
subscript of u_{n+1}. It should be u_{n}.
The model corresponds to the markram_synapse in NEST, which is a
simplification of the NEST tsodyks_synapse (synaptic time course is
neglected).
References:
[1] Markram, Wang, Tsodyks (1998) Differential Signaling via the same axon
of neocortical pyramidal neurons. PNAS, vol 95, pp. 5323-5328.
[2] D. Sussillo, T. Toyoizumi, and W. Maass. Self-tuning of neural circuits through
short-term synaptic plasticity. Journal of Neurophysiology, 97:4079-4095, 2007.
Author: Eilif Muller, 2010.
"""
import nineml.abstraction_layer as nineml
regimes = [
nineml.Regime(
"dR/dt = (1-R)/tau_r", # tau_r is the recovery time constant for depression
"du/dt = -(u-U)/tau_f", # tau_f is the time constant of facilitation
transitions=nineml.On(nineml.SpikeInputEvent,
do=["Wout = u*R*Win",
"R -= u*R",
"u += U*(1-u)",
nineml.PreEventRelay]) # Should I put a SpikeOutputEvent here?
)]
ports = [nineml.SendPort("Wout")]
c1 = nineml.Component("MarkramSynapseDynamics", regimes=regimes, ports=ports)
# write to file object f if defined
try:
# This case is used in the test suite for examples.
c1.write(f)
except NameError:
import os
base = "markram_synapse_dynamics"
c1.write(base + ".xml")
c2 = nineml.parse(base + ".xml")
assert c1 == c2
c1.to_dot(base + ".dot")
os.system("dot -Tpng %s -o %s" % (base + ".dot", base + ".png"))
| 61 | 30.38 | 97 | 13 | 570 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-system-call-audit_64c9592c3131a1ab_3aebdcc0", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "remediation": "", "location": {"file_path": "unknown", "line_start": 61, "line_end": 61, "column_start": 5, "column_end": 69, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-system-call-audit", "path": "/tmp/tmpr7mo7ysm/64c9592c3131a1ab.py", "start": {"line": 61, "col": 5, "offset": 1849}, "end": {"line": 61, "col": 69, "offset": 1913}, "extra": {"message": "Found dynamic content used in a system call. This is dangerous if external data can reach this function call because it allows a malicious actor to execute commands. Use the 'subprocess' module instead, which is easier to use without accidentally exposing a command injection vulnerability.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b605_start_process_with_a_shell.html", "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | markram_synapse_dynamics.py | /lib9ml/python/nineml/examples/examples_from_trunk_pre_merge/AL/markram_synapse_dynamics.py | iraikov/nineml | BSD-3-Clause,BSD-2-Clause | |
2024-11-18T19:03:24.423031+00:00 | 1,495,456,731,000 | 182de9b68255fba10d34b354b19c0b8db0d42e34 | 3 | {
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} | 3.015625 | stackv2 | from __future__ import division
from math import ceil, floor
from itertools import permutations as p, combinations as c
def safe_eval(expr):
try:
return eval(expr)
except ZeroDivisionError:
return 0
max_cons, max_abcd = 0, 0
operators = ['+', '-', '*', '/']*3
nos_set = [str(i) for i in xrange(1, 10)]
for nos_ in c(nos_set, 4):
ans = set()
for nos in p(nos_):
for op in p(operators, 3):
# ((a*b)*c)*d (a*(b*c))*d a*((b*c)*d) (a*b)*(c*d) a*(b*(c*d))
a, b, c, d = nos
w, t, h = op
subs = (a, w, b, t, c, h, d)
exprs = ["((%s%s%s)%s%s)%s%s"%subs, "(%s%s(%s%s%s))%s%s"%subs, \
"%s%s((%s%s%s)%s%s)"%subs, "(%s%s%s)%s(%s%s%s)"%subs, \
"%s%s(%s%s(%s%s%s))"%subs]
for no in map(safe_eval, exprs):
if ceil(no) == floor(no) and no > 0:
ans.add(no)
# Find maximum consecutive nos
k = 1
while k in ans:
k += 1
if k > max_cons:
max_cons = k-1
max_abcd = ''.join(nos_)
print max_abcd, max_cons
| 41 | 26.24 | 76 | 15 | 375 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_18d6942b04b66c68_77d38961", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 7, "line_end": 7, "column_start": 16, "column_end": 26, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpr7mo7ysm/18d6942b04b66c68.py", "start": {"line": 7, "col": 16, "offset": 166}, "end": {"line": 7, "col": 26, "offset": 176}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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] | [
"security"
] | [
"LOW"
] | [
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] | [
7
] | [
7
] | [
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] | [
26
] | [
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] | [
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] | [
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] | [
"LOW"
] | [
"HIGH"
] | 93.py | /src/solutions/93.py | bshankar/euler | MIT | |
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} | 2.5625 | stackv2 | import os
import pandas as pd
import pymongo
import redis
import socket
import tempfile
import cPickle
import subprocess
import shutil
import vislab
def zero_results(collection, query):
return collection.find(query).limit(1).count() == 0
def exclude_ids_in_collection(image_ids, collection):
"""
Exclude ids already stored in the collection.
Useful for submitting map jobs.
"""
computed_image_ids = [
x['image_id'] for x in collection.find(fields=['image_id'])
]
print 'len(computed_image_ids)', len(computed_image_ids)
num_ids = len(image_ids)
not_computed_ids = image_ids = list(set(image_ids) - set(computed_image_ids))
print("Cut down on {} existing out of {} total image ids.".format(
num_ids - len(not_computed_ids), num_ids))
return not_computed_ids
def load_or_generate_df(filename, generator_fn, force=False, args=None):
"""
If filename does not already exist, gather data with generator_fn,
and write to filename.
If filename does exist, load from it.
"""
print 'load_or_generate_df(force={}): {}'.format(force, filename)
if not force and os.path.exists(filename):
df = pd.read_hdf(filename, 'df')
else:
print 'Generating'
df = generator_fn(args)
df.to_hdf(filename, 'df', mode='w')
return df
def running_on_icsi():
"""
Return True if this script is running on the ICSI cluster.
"""
return socket.gethostname().endswith('ICSI.Berkeley.EDU')
def get_mongodb_client():
"""
Establish connection to MongoDB.
"""
try:
host, port = vislab.config['servers']['mongo']
connection = pymongo.MongoClient(host, port)
except pymongo.errors.ConnectionFailure:
raise Exception(
"Need a MongoDB server running on {}, port {}".format(host, port))
return connection
def get_mozila_request_header():
user_agent = "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:47.0) Gecko/20100101 Firefox/47.0"
headers = {'User-Agent': user_agent}
return headers
def print_collection_counts():
"""
Print all collections and their counts for all databases in MongoDB.
"""
client = get_mongodb_client()
for db_name in client.database_names():
for coll_name in client[db_name].collection_names():
print('{} |\t\t{}: {}'.format(
db_name, coll_name, client[db_name][coll_name].count()))
def get_redis_client(host=None, port=None):
if host is None or port is None:
host, port = vislab.config['servers']['redis']
try:
connection = redis.Redis(host, port)
connection.ping()
except redis.ConnectionError:
raise Exception(
"Need a Redis server running on {}, port {}".format(host, port))
return connection
def pickle_function_call(func_name, args):
f, temp_filename = tempfile.mkstemp()
with open(temp_filename, 'w') as f:
cPickle.dump((func_name, args), f)
c = "import os; import cPickle;"
c += "f = open('{0}'); func, args = cPickle.load(f); f.close();"
c += "os.remove('{0}'); func(*args)"
c = c.format(temp_filename)
return c
def run_through_bash_script(cmds, filename=None, verbose=False, num_workers=1):
"""
Write out given commands to a bash script file and execute it.
This is useful when the commands to run include pipes, or are chained.
subprocess is not too easy to use in those cases.
Parameters
----------
cmds: list of string
filename: string or None [None]
If None, a temporary file is used and deleted after.
verbose: bool [False]
If True, output the commands that will be run.
num_workers: int [1]
If > 1, commands are piped through parallel -j num_workers
"""
assert(num_workers > 0)
remove_file = False
if filename is None:
f, filename = tempfile.mkstemp()
remove_file = True
if num_workers > 1:
contents = "echo \"{}\" | parallel --env PATH -j {}".format(
'\n'.join(cmds), num_workers)
else:
contents = '\n'.join(cmds)
with open(filename, 'w') as f:
f.write(contents + '\n')
if verbose:
print("Contents of script file about to be run:")
print(contents)
p = subprocess.Popen(['bash', filename])
out, err = p.communicate()
if remove_file:
os.remove(filename)
if not p.returncode == 0:
print(out)
print(err)
raise Exception("Script exited with code {}".format(p.returncode))
def run_shell_cmd(cmd, echo=True):
"""
Run a command in a sub-shell, capturing stdout and stderr
to temporary files that are then read.
"""
_, stdout_f = tempfile.mkstemp()
_, stderr_f = tempfile.mkstemp()
print("Running command")
print(cmd)
p = subprocess.Popen(
'{} >{} 2>{}'.format(cmd, stdout_f, stderr_f), shell=True)
p.wait()
with open(stdout_f) as f:
stdout = f.read()
os.remove(stdout_f)
with open(stderr_f) as f:
stderr = f.read()
os.remove(stderr_f)
if echo:
print("stdout:")
print(stdout)
print("stderr:")
print(stderr)
return stdout, stderr
def makedirs(dirname):
if os.path.exists(dirname):
return dirname
try:
os.makedirs(dirname)
except OSError:
pass
except:
raise
return dirname
def cleardirs(dirname):
if os.path.exists(dirname):
shutil.rmtree(dirname)
return makedirs(dirname)
| 202 | 26.52 | 95 | 17 | 1,330 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_4599d30ce0f657ff_73424ac5", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_4599d30ce0f657ff_172f50f4", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. 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"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security",
"security"
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"LOW",
"LOW"
] | [
"MEDIUM",
"HIGH"
] | [
101,
166
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101,
167
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9,
9
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43,
67
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"Detected subprocess function 'Popen' without a... | [
5,
7.5
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"HIGH"
] | util.py | /vislab/util.py | asanakoy/vislab | BSD-2-Clause | |
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} | 3.96875 | stackv2 | #!/usr/bin/evn python3
# coding:utf-8
# 009_03.py 的另一种改进
def collect_prime(n): # (*)
global prime_lst # 话说回来，这句不写也行
for i in range(2, int(n**0.5)+1):
if n % i == 0:
prime_lst.append(str(i))
return collect_prime(n//i)
prime_lst.append(str(n)) # 最后一个质因数
return prime_lst
prime_lst = []
# 输入数据并检查数据的合法性
num_input = input("Please enter a natural number greater than 1: ")
while not num_input.isdigit() or eval(num_input) < 2:
num_input = input("Please enter a positive integer greater than 1 again: ")
print(num_input, "=", " x ".join(collect_prime(int(num_input))))
'''
(*) 可以改成如下样子
def collect_prime(n):
k = 2
while n != 1:
if n % k == 0:
prime_lst.append(str(k))
return collect_prime(n//k)
k += 1
相应的输出要改为
collect_prime(int(num_input))
print(num_input, "=", " x ".join(prime_lst))
'''
| 38 | 22.84 | 79 | 13 | 279 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.eval-detected_516cf7045eafa8d0_2601412c", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.eval-detected", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "remediation": "", "location": {"file_path": "unknown", "line_start": 19, "line_end": 19, "column_start": 34, "column_end": 49, "code_snippet": "requires login"}, "cwe_id": "CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A03:2021 - Injection", "references": [{"url": "https://owasp.org/Top10/A03_2021-Injection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.eval-detected", "path": "/tmp/tmpr7mo7ysm/516cf7045eafa8d0.py", "start": {"line": 19, "col": 34, "offset": 541}, "end": {"line": 19, "col": 49, "offset": 556}, "extra": {"message": "Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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] | [
5
] | [
"LOW"
] | [
"HIGH"
] | 009_05.py | /FishCDailyQuestion/ex001-010/Python3_009/009_05.py | YorkFish/git_study | MIT | |
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} | 2.65625 | stackv2 | #!/usr/bin/env python
"""
Markdown documentation generator and checker.
Generate HTML documentation from Markdown files in the current working
directory, and check that their links are valid.
"""
import BaseHTTPServer
import argparse
import itertools
import os
import re
import socket
import string
import subprocess
import sys
import urllib2
class CheckDir(argparse.Action):
def __call__(self, parser, namespace, values, option_string=None):
d = values
if not os.path.isdir(d):
raise argparse.ArgumentTypeError('Invalid directory "%s"' % d)
if os.access(d, os.R_OK):
setattr(namespace, self.dest, d)
else:
raise argparse.ArgumentTypeError('Cannot read directory "%s"' % d)
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('--socket-timeout', type=int, default=30,
help='timeout for URL fetch (seconds)')
parser.add_argument('--dir', type=str, action=CheckDir, default=os.getcwd(),
help='Markdown file location (default: current)')
parser.add_argument('--out', type=str, default='out',
help='subdirectory for output HTML files')
parser.add_argument('--markdown', type=str, default='markdown',
help='Markdown generator program')
parser.add_argument('--extension', type=str, default='.md',
help='Markdown file extension')
parser.add_argument('--html', type=str, default='.html',
help='HTML file extension')
parser.add_argument('--link_regex', type=str, default='href="([^"]+)"',
help='Regular expression used to find links in HTML')
args = parser.parse_args()
socket.setdefaulttimeout(args.socket_timeout)
href = re.compile(args.link_regex)
template = """<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>$title: WebAssembly</title>
</head>
<body>
$content
</body>
</html>
"""
def trunc_extension(filename, extension):
return filename[:-len(extension)]
def find_markdown_sources():
return sorted([trunc_extension(f, args.extension) for f in
os.listdir(args.dir) if f.endswith(args.extension)])
def start_threadpool():
from multiprocessing import Pool
return Pool()
def path_to_markdown(name):
return os.path.join(args.dir, name + args.extension)
def create_outdir():
path = os.path.join(args.dir, args.out)
if not os.path.exists(path):
os.makedirs(path)
def path_to_html(name):
return os.path.join(args.dir, args.out, name + args.html)
def generate_html(name):
md_sp = subprocess.Popen(
[args.markdown, path_to_markdown(name)],
stdout=subprocess.PIPE, stderr=subprocess.PIPE)
md_out, md_err = md_sp.communicate()
md_code = md_sp.returncode
if not md_code:
with open(path_to_html(name), 'w+') as html:
t = string.Template(template)
html.write(t.substitute(title=name, content=md_out))
return (name, md_code, md_err)
def check_generated(generated):
errors = 0
for g in generated:
if g[1]:
errors = errors + 1
print '\t%s failed with code %i: %s' % g
else:
print '\t%s' % g[0]
if errors:
sys.exit(1)
def collect_links_from_html(name):
html = open(path_to_html(name), 'r').read()
return re.findall(href, html)
def flatten_and_deduplicate(list_of_lists):
return sorted(list(set(itertools.chain(*list_of_lists))))
def check_inner_link(link):
parts = link.split('#')
if not parts[0].endswith(args.extension):
return (link, 'Not a link to an internal markdown file')
name = trunc_extension(parts[0], args.extension)
md = path_to_markdown(name)
if not os.path.isfile(md):
return (link, 'No such markdown file')
if len(parts) == 1:
return (link, None)
if len(parts) > 2:
return (link, 'Too many hashes in link')
with open(path_to_html(name), 'r') as html:
# TODO: The current Markdown generator doesn't output link IDs, whereas
# github's Markdown generator does output the IDs.
return (link, None)
def check_outer_link(link):
req = urllib2.Request(link)
try:
urllib2.urlopen(req)
except ValueError as e:
return (link, 'Value error ' + e.args[0])
except urllib2.URLError as e:
return (link, 'URL error ' + str(e.reason))
except urllib2.HTTPError as e:
responses = BaseHTTPServer.BaseHTTPRequestHandler.responses
return (link, 'HTTP error ' + responses[e.code()])
except socket.timeout as e:
return (link, 'Socket timeout after %i seconds' % args.socket_timeout)
return (link, None)
def print_invalid_links(links):
errors = 0
for link in links:
if link[1]:
errors = errors + 1
print ' Invalid link "%s": %s.' % link
return errors
if __name__ == '__main__':
sources = find_markdown_sources()
print 'Found %i markdown sources:' % len(sources)
pool = start_threadpool()
create_outdir()
generated = pool.map(generate_html, sources)
check_generated(generated)
links = flatten_and_deduplicate(pool.map(collect_links_from_html, sources))
inner_links = [l for l in links if l.startswith(tuple(sources))]
outer_links = [l for l in links if not l.startswith(tuple(sources))]
print ('Found %i unique inner links, and %i unique outer links.' %
(len(inner_links), len(outer_links)))
bad_inner = print_invalid_links(pool.map(check_inner_link, inner_links))
bad_outer = print_invalid_links(pool.map(check_outer_link, outer_links))
if not (bad_inner or bad_outer):
print 'No invalid links.'
else:
print 'Found %i bad inner and %i outer links.' % (bad_inner, bad_outer)
sys.exit(1)
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7.5,
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] | generate.py | /tools/generate.py | sunfishcode/design | Apache-2.0 | |
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} | 2.640625 | stackv2 | """
Author: Michael S. P. Kelley
Background subtract and de-stripe NIRSpec IFU data, then run the stage 2
spectroscopic pipeline.
NIRSpec observations of 22P/Kopff from program 1252 observed the comet at all
requested instrument settings, then moved to the background and repeated the
observation sequence. This is not ideal as the instrument may not return to the
exact grating settings. Typically, one would rather observe both the target and
background before changing instrument settings. However, in the interest of
time efficiency, the slew to the background was only done once.
When the background step is enabled, the pipeline compares the grating positions
of the target and background files. If they do not precisely match, the
background is not subtracted. This script bypasses that test and subtracts a
background.
In addition to the background subtraction, vertical striping (1/f noise?) is
also measured with a sigma-clipped median and removed.
"""
import os
from glob import glob
import numpy as np
import scipy.ndimage as nd
from astropy.io import fits
from astropy.stats import sigma_clip
from jwst.pipeline.calwebb_spec2 import Spec2Pipeline
from jwst.background.background_sub import background_sub
from jwst import datamodels
import stdatamodels
import crds
output_dir = "processed"
# files to process, must be _rate files
input_files = glob("data/jw01252001001_03101_0000?_nrs1/*_rate.fits")
# define the area outside of the spectra for de-striping using the sflat
h = fits.getheader(input_files[0])
ref = crds.getreferences(h, reftypes=["sflat"])
spec_mask = fits.getdata(ref["sflat"]) != 0
# grow the mask by a couple pixels
spec_mask = nd.binary_dilation(spec_mask, iterations=2)
# files for manual background subtraction to bypass grating position test
background_files = glob("data/jw01252002001_03101_*nrs1/*_rate.fits")
for fn in input_files:
# output file name
outf = fn.replace("data/", f"{output_dir}/")
if os.path.exists(outf):
print("skipping", outf, "(file already exists)")
continue
# create directories as needed
os.system(f"mkdir -p {os.path.dirname(outf)}")
# copied-edited code from jwst.background.background_step
with datamodels.open(fn) as input_model:
bkg_model, result = background_sub(
input_model, background_files, 3.0, None
)
result.meta.cal_step.back_sub = "COMPLETE"
# remove vertical stripes
im = np.ma.MaskedArray(result.data, mask=spec_mask)
clipped = sigma_clip(im, axis=0, sigma=2.5)
stripes = np.outer(np.ones(im.shape[0]), np.ma.mean(clipped, axis=0))
result.data -= stripes
# This seems like the right way to add a history entry, but I don't see
# it in the resulting FITS file. Possibly because the history has not
# been created.
comment = stdatamodels.util.create_history_entry("De-striped")
result.history.append(comment)
# save the file
result.save(outf)
# save the background
bkg_model.save(outf.replace("_rate", "_rate_combinedbackground"))
# process with the stage 2 pipeline as usual, but do not run the background step
input_files = glob(f"{output_dir}/jw01252001001_03101_0000?_nrs1/*_rate.fits")
for fn in input_files:
out_file = fn.replace("rate", "s3d")
if os.path.exists(out_file):
# compare modification times, update as needed
rate_stat = os.stat(fn)
s3d_stat = os.stat(out_file)
if rate_stat.st_mtime < s3d_stat.st_mtime:
print("skipping", out_file, "(s3d is newer than rate).")
continue
Spec2Pipeline.call(
fn,
config_file="spec2.asdf",
output_dir=os.path.dirname(fn),
logcfg="jwst-pipeline-log.cfg",
)
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] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | spec2.py | /nirspec/backgrounds/spec2.py | mkelley/jwst-comets | MIT,BSD-3-Clause | |
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} | 2.46875 | stackv2 | from __future__ import print_function, division
import torch
import torch.optim as optim
import torch.nn.functional as F
from torch.autograd import Variable
import time
from datetime import datetime
import os
import copy
import json
import argparse
import pickle
from data_loader.data_loader import get_data_loaders
from utils.util import adjust_learning_rate
from utils.util import model_snapshot
from utils.util import ensure_dir
from model.resnet import get_resnet
parser = argparse.ArgumentParser(description='Test your model')
parser.add_argument('--resume',help='Resume from previous work')
def main():
args = parser.parse_args()
config = json.load(open("config.json"))
torch.manual_seed(config['seed'])
torch.cuda.manual_seed(config['seed'])
model = get_resnet().cuda()
if args.resume is not None:
print("Resume from previous work")
model.load_state_dict(torch.load(args.resume))
optimizer = optim.SGD(model.parameters(),
lr=config['lr'],
weight_decay=config['weight_decay'])
train(config,model,optimizer)
def train(config,model,optimizer):
"""Train the model
Params:
config:
json config data
model:
model to train
optimizer:
optimizer used in training
Return:
None
"""
data_loaders = get_data_loaders()
ensure_dir(config['log_dir'])
t_begin = time.time()
best_acc, old_file = 0, None
history = {'train':{'loss':[],'acc':[]},'val':{'loss':[],'acc':[]}}
for epoch in range(config['epoch_num']):
model.train() # train phase
epoch_loss = 0
epoch_correct = 0
adjust_learning_rate(config,optimizer,epoch)
for batch_idx, (data,target) in enumerate(data_loaders['train']):
indx_target = target.clone()
data, target = Variable(data.cuda()),Variable(target.cuda())
optimizer.zero_grad()
output = model(data)
#define your own loss function here
loss = F.cross_entropy(output,target)
epoch_loss += loss.data[0]
loss.backward()
optimizer.step()
pred = output.data.max(1)[1]
correct = pred.cpu().eq(indx_target).sum()
epoch_correct += correct
if config['batch_log'] and batch_idx % config['batch_log_interval'] == 0 and batch_idx > 0:
acc = correct * 1.0 / len(data)
print('Train Epoch: {} [{}/{}] Batch_Loss: {:.6f} Batch_Acc: {:.4f} lr: {:.2e}'.format(
epoch, batch_idx * len(data), len(data_loaders['train'].dataset),
loss.data[0], acc, optimizer.param_groups[0]['lr']))
elapse_time = time.time() - t_begin
speed_epoch = elapse_time / (epoch + 1)
speed_batch = speed_epoch / len(data_loaders['train'])
eta = speed_epoch * config['epoch_num'] - elapse_time
print("{}/{} Elapsed {:.2f}s, {:.2f} s/epoch, {:.2f} s/batch, ets {:.2f}s".format(epoch+1,
config['epoch_num'],elapse_time, speed_epoch, speed_batch, eta))
epoch_loss = epoch_loss / len(data_loaders['train']) # average over number of mini-batch
acc = 100. * epoch_correct / len(data_loaders['train'].dataset)
print('\tTrain set: Average loss: {:.4f}, Accuracy: {}/{} ({:.0f}%)'.format(
epoch_loss, epoch_correct, len(data_loaders['train'].dataset), acc))
history['train']['loss'].append(epoch_loss)
history['train']['acc'].append(acc)
model_snapshot(model, os.path.join(config['log_dir'], 'latest.pth'))
if epoch % config['val_interval'] == 0:
model.eval()
val_loss = 0
correct = 0
for data, target in data_loaders['val']:
indx_target = target.clone()
data, target = Variable(data.cuda(),volatile=True), Variable(target.cuda())
output = model(data)
val_loss += F.cross_entropy(output, target).data[0]
pred = output.data.max(1)[1] # get the index of the max log-probability
correct += pred.cpu().eq(indx_target).sum()
val_loss = val_loss / len(data_loaders['val']) # average over number of mini-batch
acc = 100. * correct / len(data_loaders['val'].dataset)
print('\tVal set: Average loss: {:.4f}, Accuracy: {}/{} ({:.0f}%)'.format(
val_loss, correct, len(data_loaders['val'].dataset), acc))
history['val']['loss'].append(val_loss)
history['val']['acc'].append(acc)
if acc > best_acc:
new_file = os.path.join(config['log_dir'], datetime.now().strftime('%Y-%m-%d-%H-%M-%S')+'-best-{}.pth'.format(epoch))
model_snapshot(model, new_file, old_file=old_file, verbose=True)
best_acc = acc
old_file = new_file
f = open(config['history'],'wb')
try:
pickle.dump(history,f)
finally:
f.close()
print("Total Elapse: {:.2f}s, Best Val Acc: {:.3f}%".format(time.time()-t_begin, best_acc))
if __name__ == "__main__":
assert torch.cuda.is_available()
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} | 2.421875 | stackv2 | import load_sample
import pandas as pd
from pandas import DataFrame
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
from os.path import join
from copy import deepcopy
import time
import datetime
from queue import LifoQueue
import pickle
sample = load_sample.sample
ids_to_rows = load_sample.ids_to_rows
ixs_to_rows = load_sample.ixs_to_rows
stopwords_sample = pd.read_json(join('..', 'data', 'index', 'stopwords-bg.json'))[259:]
short_stop_word = stopwords_sample[stopwords_sample[0].apply(lambda x: len(x) <= 3)][0]
search_tokens_text = sample['tokens'].apply(lambda x: ' '.join(x))
tfidf_vectorizer = TfidfVectorizer(stop_words=short_stop_word.tolist())
tfidf_vectorizer.fit_transform(search_tokens_text)
train_corpus_vectors = tfidf_vectorizer.transform(search_tokens_text)
def time_now():
ts = time.time()
return datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d %H:%M:%S')
print(time_now(), "Loading corpus similarity")
try:
dup_pairs_df = pd.read_json(join('data', 'dup_pairs.json'), orient='split')
dup_pairs = [tuple(x) for x in dup_pairs_df.values]
except:
print(time_now(), "Count not read 'data/dup_pairs.json'. Creating...")
duplicates = cosine_similarity(train_corpus_vectors, train_corpus_vectors)
dup_pairs = []
for i in range(len(sample)):
for j in range(len(sample)):
if duplicates[i, j] >= 0.9 and i < j:
dup_pairs.append((i, j))
DataFrame(data=dup_pairs).to_json(join('data', 'dup_pairs.json'), orient='split')
dup_pairs_df = pd.read_json(join('data', 'dup_pairs.json'), orient='split')
print(time_now(), "Loading ready:", len(dup_pairs), " pairs loaded.")
def has_more(tuples, ix):
return any(filter(lambda x: x[0] == ix or x[1] == ix, tuples))
def find_first(tuples, ix):
return next((x[0] for x in tuples if x[1] == ix), None)
def get_dups_group_iter(tuples, ix):
group = set()
queue = LifoQueue()
queue.put(ix)
visited = set()
while not queue.empty():
current = queue.get()
group.add(current)
for i, (ix1, ix2) in enumerate(tuples):
if i in visited:
continue
if ix1 == current:
visited.add(i)
queue.put(ix2)
elif ix2 == current:
visited.add(i)
queue.put(ix1)
return group
starters = set(map(lambda x: x[0], dup_pairs))
def find_all_groups(tuples, ixs):
all_groups = list()
l = len(starters)
for i, ix in enumerate(starters):
print("{0:0.2f}".format(float(i) * 100/ l) , " %")
if not any(map(lambda group: ix in group, all_groups)):
all_groups.append(get_dups_group_iter(dup_pairs, ix))
return all_groups
print(time_now(), "Groups loading...")
all_grs = find_all_groups(dup_pairs, starters)
with open(join('data', 'dup_groups.p'), 'wb') as fp:
pickle.dump(all_grs, fp, protocol=pickle.HIGHEST_PROTOCOL)
# with open(join('data', 'dup_groups.p'), 'rb') as fp:
# data = pickle.load(fp)
# if data ==
print(time_now(), "Done...")
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} | 2.484375 | stackv2 | # -*- coding: utf-8 -*-
"""
Apply Gauss-Seidel Iteration Scheme to smooth high-frequency distortions across a slice stack.
NOTE: Nipype ready code - inner functions used inside the 'run' function.
Author: Alexander Woodward, Connectome Analysis Unit, RIKEN CBS, Wako, Japan
Email: alexander.woodward@riken.jp
"""
def run(in_dir, cur_dir, out_dir_images, out_dir_transforms,
iterations, ants_thread_count):
"""Apply Gauss-Seidel Iteration Scheme algorithm to a folder of images in sequence.
Args:
in_dir: The folder of images to process. Images should be padded with leading zeroes
and a starting index of 1, e.g. slice_001.tif
cur_dir: The current directory to work from.
out_dir_images: The directory to place the transformed images.
out_dir_transforms: Directory for calculated transforms.
iterations: Number of iterations of G.S. smoothing, 2,4 is recommended.
ants_thread_count: Number of threads assigned to the antsRegistration program.
"""
import numpy as np
# TODO(AW): Remove dependency on OpenCV and use only SimpleITK calls
import cv2
import subprocess
import SimpleITK as sitk
import copy
from nipype.interfaces.ants import Registration
from natsort import natsorted
def reg_run(
fixed_image,
moving_image,
output_transform_prefix,
output_warped_image,
ants_thread_count):
# os.environ['PATH']+=':/path_to_antsbin'
reg = Registration()
reg.inputs.fixed_image = fixed_image
reg.inputs.moving_image = moving_image
reg.inputs.output_transform_prefix = output_transform_prefix
reg.inputs.transforms = ['SyN']
reg.inputs.transform_parameters = [(0.01,)]
reg.inputs.number_of_iterations = [[200, 200, 200, 200, 150, 50]]
# reg.inputs.number_of_iterations = [[50,50,50,40,30,20]]
reg.inputs.dimension = 2
reg.inputs.num_threads = ants_thread_count
reg.inputs.metric = ['Mattes']
# Default (value ignored currently by ANTs)
reg.inputs.metric_weight = [1]
reg.inputs.radius_or_number_of_bins = [32]
reg.inputs.sampling_strategy = ['Regular']
reg.inputs.sampling_percentage = [1.0] # 0.3]
reg.inputs.convergence_threshold = [1.e-8]
reg.inputs.convergence_window_size = [10]
reg.inputs.smoothing_sigmas = [[6, 5, 4, 3, 2, 1]]
reg.inputs.sigma_units = ['vox']
reg.inputs.shrink_factors = [[6, 5, 4, 3, 2, 1]]
reg.inputs.use_estimate_learning_rate_once = [True]
reg.inputs.use_histogram_matching = [True] # This is the default
reg.inputs.output_warped_image = output_warped_image
reg1 = copy.deepcopy(reg)
# reg1.cmdline
reg1.run()
# Be careful to scale by the pixel size when using both SimpleITK and
# OpenCV functions
def deform_image(img_in, deform_in, scale_factor, out_filename):
spacing = img_in.GetSpacing()
img_a = sitk.GetArrayFromImage(img_in)
img_a = img_a.astype(np.float32)
img_c = sitk.GetArrayFromImage(deform_in)
m_x = np.zeros([deform_in.GetHeight(), deform_in.GetWidth()])
m_y = np.zeros([deform_in.GetHeight(), deform_in.GetWidth()])
m_y = m_y.astype(np.float32)
m_x = m_x.astype(np.float32)
for j in range(0, deform_in.GetHeight()):
for i in range(0, deform_in.GetWidth()):
pix = img_c[j, i]
m_x[j, i] = float(j) + scale_factor * \
float(pix[1]) * (1.0 / spacing[1])
m_y[j, i] = float(i) + scale_factor * \
float(pix[0]) * (1.0 / spacing[0])
out = cv2.remap(img_a, m_y, m_x, cv2.INTER_CUBIC)
out = sitk.GetImageFromArray(out)
out.CopyInformation(img_in)
sitk.WriteImage(out, out_filename)
return out
def setup_folders(in_dir):
# Copy from the input directory first
names_in = subprocess.check_output(
["ls " + in_dir], shell=True, text=True)
names_in = names_in.split()
# Sort the strings using natural sort
names_in = natsorted(names_in)
img_count = len(names_in)
# Copy and duplicate first and last (Neumann boundary conditions)
for i in range(0, img_count):
img = sitk.ReadImage(in_dir + names_in[i])
index = i + 1
sitk.WriteImage(
img,
cur_dir +
'/input_with_boundary/slice_' +
format(
index,
'04d') +
'.nii')
if index == 1:
sitk.WriteImage(
img, cur_dir + '/input_with_boundary/slice_0000.nii')
elif index == img_count:
sitk.WriteImage(
img,
cur_dir +
'/input_with_boundary/slice_' +
format(
index +
1,
'04d') +
'.nii')
# Copy files into directories
subprocess.call("cp " + cur_dir + '/input_with_boundary/* ' +
cur_dir + "/current_iter/", shell=True)
print("Copied files to ./current_iter")
subprocess.call("cp " + cur_dir + '/input_with_boundary/* ' +
cur_dir + '/prev_iter/', shell=True)
print("Copied files to ./prev_iter")
names_in = subprocess.check_output(
['ls ' + cur_dir + '/current_iter/'], shell=True, text=True)
names_in = names_in.split()
return names_in
def one_pass(
start_index,
end_index,
step,
cur_dir,
current_iteration,
images_names,
img_count,
ants_thread_count):
for j in range(start_index, end_index, step):
# Calculate transform between j-1 and j+1
# fixed is j-1 moving is j+1
reg_run(cur_dir +
'/current_iter/' +
image_names[j - 1], cur_dir +
'/current_iter/' +
image_names[j + 1], cur_dir +
'/registration_output_transform/u_', cur_dir +
'/registration_output_image/output_warped_image.nii', ants_thread_count)
img_u = sitk.ReadImage(
cur_dir +
'/registration_output_transform/u_0Warp.nii.gz',
sitk.sitkVectorFloat64)
# Multiply it by half the deformation field
img_jm1 = sitk.ReadImage(
cur_dir + '/current_iter/' + image_names[j + step])
# Make sure to account for pixel scale factor
deform_image(img_jm1, img_u, 0.5, cur_dir +
'/i_hat_image/output.nii')
# Register Ij to IHat
reg_run(
cur_dir +
'/i_hat_image/output.nii',
cur_dir +
'/prev_iter/' +
image_names[j],
cur_dir +
'/registration_output_transform/u_',
cur_dir +
'/registration_output_image/output_warped_image.nii',
ants_thread_count)
# Merge it with previous
img_u_acc_new = sitk.ReadImage(
cur_dir + '/registration_output_transform/u_0Warp.nii.gz',
sitk.sitkVectorFloat64)
# if t == 0:
if current_iteration == 0:
sitk.WriteImage(img_u_acc_new, cur_dir +
'/current_transforms/u' + str(j) + '_Warp.nii')
else:
img_u_acc = sitk.ReadImage(
cur_dir +
'/current_transforms/u' +
str(j) +
'_Warp.nii',
sitk.sitkVectorFloat64)
img_u_acc_new = img_u_acc + img_u_acc_new
sitk.WriteImage(img_u_acc_new, cur_dir +
'/current_transforms/u' + str(j) + '_Warp.nii')
# Update Ij using Ij0
img_j_orig = sitk.ReadImage(
cur_dir + '/input_with_boundary/' + image_names[j])
deform_image(img_j_orig, img_u_acc_new, 1.0, cur_dir +
'/current_iter/' + image_names[j])
# Update boundaries
img_b = sitk.ReadImage(cur_dir + '/current_iter/' + image_names[1])
sitk.WriteImage(img_b, cur_dir + '/current_iter/' + image_names[0])
img_b = sitk.ReadImage(
cur_dir + '/current_iter/' + image_names[img_count - 2])
sitk.WriteImage(img_b, cur_dir + '/current_iter/' +
image_names[img_count - 1])
# Copy current_iter to prev_iter
for j in range(0, img_count):
img_b = sitk.ReadImage(cur_dir + '/current_iter/' + image_names[j])
sitk.WriteImage(img_b, cur_dir + '/prev_iter/' + image_names[j])
names_in = setup_folders(in_dir)
img_count = len(names_in)
image_names = []
for i in range(0, img_count):
image_names.append(names_in[i])
# Do nothing if iterations == 0
if iterations > 0:
# iterations = 4
# Z = img_count
for i in range(0, iterations):
print("Starting iteration " + str(i + 1) + " of " + str(iterations))
if i % 2 == 0:
one_pass(1, img_count - 1, 1, cur_dir, i, image_names,
img_count, ants_thread_count)
else:
one_pass(img_count - 2, 0, 1, cur_dir, i, image_names,
img_count, ants_thread_count)
# Copy results to output directories
subprocess.call("cp " + cur_dir + '/current_iter/* ' +
out_dir_images, shell=True)
# Remove the first and last since they were boundary conditions
subprocess.call("rm " + out_dir_images + '/slice_0000.nii', shell=True)
subprocess.call("rm " + out_dir_images + '/slice_' +
format(img_count - 1, '04d') + '.nii', shell=True)
# Copy the transforms to the correct output folder
subprocess.call("cp " + cur_dir + '/current_transforms/* ' +
out_dir_transforms, shell=True)
# Copy from the input directory first
names_in = subprocess.check_output(
["ls " + out_dir_images], shell=True, text=True)
names_in = names_in.split()
img_count = len(names_in)
# These images should be ordered based on the file naming convention
for i in range(0, img_count):
img = sitk.ReadImage(out_dir_images + '/' + names_in[i])
sitk.WriteImage(
img,
out_dir_images +
'/out_' +
format(
i +
1,
'04d') +
'.nii')
# Finally remove the old images
subprocess.call('rm ' + out_dir_images + '/slice_*', shell=True)
return out_dir_images
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If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_8c1ecfecb43ce455_7d580f37", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'check_output' with 'shell=True'. 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If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 131, "line_end": 132, "column_start": 9, "column_end": 64, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 131, "col": 9, "offset": 5223}, "end": {"line": 132, "col": 64, "offset": 5348}, "extra": {"message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.unchecked-subprocess-call_8c1ecfecb43ce455_4cbd0f1c", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.unchecked-subprocess-call", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. 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If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.unchecked-subprocess-call_8c1ecfecb43ce455_a5b9d253", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.unchecked-subprocess-call", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "remediation": "check_call", "location": {"file_path": "unknown", "line_start": 134, "line_end": 134, "column_start": 20, "column_end": 24, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python.org/3/library/subprocess.html#subprocess.check_call", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.unchecked-subprocess-call", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 134, "col": 20, "offset": 5416}, "end": {"line": 134, "col": 24, "offset": 5420}, "extra": {"message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "fix": "check_call", "metadata": {"references": ["https://docs.python.org/3/library/subprocess.html#subprocess.check_call"], "category": "correctness", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_8c1ecfecb43ce455_1b2b89fa", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "remediation": "False", "location": {"file_path": "unknown", "line_start": 135, "line_end": 135, "column_start": 56, "column_end": 60, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.subprocess-shell-true", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 135, "col": 56, "offset": 5522}, "end": {"line": 135, "col": 60, "offset": 5526}, "extra": {"message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "fix": "False", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b602_subprocess_popen_with_shell_equals_true.html", "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["secure default"], "likelihood": "HIGH", "impact": "LOW", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_8c1ecfecb43ce455_fcba5410", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 137, "line_end": 138, "column_start": 20, "column_end": 73, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 137, "col": 20, "offset": 5592}, "end": {"line": 138, "col": 73, "offset": 5689}, "extra": {"message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_8c1ecfecb43ce455_8123e23d", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'check_output' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "remediation": "False", "location": {"file_path": "unknown", "line_start": 138, "line_end": 138, "column_start": 57, "column_end": 61, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.subprocess-shell-true", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 138, "col": 57, "offset": 5673}, "end": {"line": 138, "col": 61, "offset": 5677}, "extra": {"message": "Found 'subprocess' function 'check_output' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "fix": "False", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b602_subprocess_popen_with_shell_equals_true.html", "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["secure default"], "likelihood": "HIGH", "impact": "LOW", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_8c1ecfecb43ce455_8104295e", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 239, "line_end": 240, "column_start": 5, "column_end": 48, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 239, "col": 5, "offset": 9875}, "end": {"line": 240, "col": 48, "offset": 9977}, "extra": {"message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.unchecked-subprocess-call_8c1ecfecb43ce455_9e41af13", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.unchecked-subprocess-call", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "remediation": "check_call", "location": {"file_path": "unknown", "line_start": 239, "line_end": 239, "column_start": 16, "column_end": 20, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python.org/3/library/subprocess.html#subprocess.check_call", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.unchecked-subprocess-call", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 239, "col": 16, "offset": 9886}, "end": {"line": 239, "col": 20, "offset": 9890}, "extra": {"message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "fix": "check_call", "metadata": {"references": ["https://docs.python.org/3/library/subprocess.html#subprocess.check_call"], "category": "correctness", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_8c1ecfecb43ce455_fd6e37bc", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "remediation": "False", "location": {"file_path": "unknown", "line_start": 240, "line_end": 240, "column_start": 43, "column_end": 47, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.subprocess-shell-true", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 240, "col": 43, "offset": 9972}, "end": {"line": 240, "col": 47, "offset": 9976}, "extra": {"message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "fix": "False", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b602_subprocess_popen_with_shell_equals_true.html", "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["secure default"], "likelihood": "HIGH", "impact": "LOW", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_8c1ecfecb43ce455_3ed92ce3", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 242, "line_end": 242, "column_start": 5, "column_end": 76, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 242, "col": 5, "offset": 10050}, "end": {"line": 242, "col": 76, "offset": 10121}, "extra": {"message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.unchecked-subprocess-call_8c1ecfecb43ce455_bc0f62fb", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.unchecked-subprocess-call", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "remediation": "check_call", "location": {"file_path": "unknown", "line_start": 242, "line_end": 242, "column_start": 16, "column_end": 20, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python.org/3/library/subprocess.html#subprocess.check_call", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.unchecked-subprocess-call", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 242, "col": 16, "offset": 10061}, "end": {"line": 242, "col": 20, "offset": 10065}, "extra": {"message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "fix": "check_call", "metadata": {"references": ["https://docs.python.org/3/library/subprocess.html#subprocess.check_call"], "category": "correctness", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_8c1ecfecb43ce455_25c558fd", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "remediation": "False", "location": {"file_path": "unknown", "line_start": 242, "line_end": 242, "column_start": 71, "column_end": 75, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.subprocess-shell-true", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 242, "col": 71, "offset": 10116}, "end": {"line": 242, "col": 75, "offset": 10120}, "extra": {"message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "fix": "False", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b602_subprocess_popen_with_shell_equals_true.html", "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["secure default"], "likelihood": "HIGH", "impact": "LOW", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_8c1ecfecb43ce455_c295fa0a", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 243, "line_end": 244, "column_start": 5, "column_end": 71, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 243, "col": 5, "offset": 10126}, "end": {"line": 244, "col": 71, "offset": 10249}, "extra": {"message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.unchecked-subprocess-call_8c1ecfecb43ce455_d37935d1", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.unchecked-subprocess-call", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "remediation": "check_call", "location": {"file_path": "unknown", "line_start": 243, "line_end": 243, "column_start": 16, "column_end": 20, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python.org/3/library/subprocess.html#subprocess.check_call", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.unchecked-subprocess-call", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 243, "col": 16, "offset": 10137}, "end": {"line": 243, "col": 20, "offset": 10141}, "extra": {"message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "fix": "check_call", "metadata": {"references": ["https://docs.python.org/3/library/subprocess.html#subprocess.check_call"], "category": "correctness", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_8c1ecfecb43ce455_b92d3f60", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "remediation": "False", "location": {"file_path": "unknown", "line_start": 244, "line_end": 244, "column_start": 66, "column_end": 70, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.subprocess-shell-true", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 244, "col": 66, "offset": 10244}, "end": {"line": 244, "col": 70, "offset": 10248}, "extra": {"message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "fix": "False", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b602_subprocess_popen_with_shell_equals_true.html", "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["secure default"], "likelihood": "HIGH", "impact": "LOW", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_8c1ecfecb43ce455_e100965d", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 246, "line_end": 247, "column_start": 5, "column_end": 52, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 246, "col": 5, "offset": 10309}, "end": {"line": 247, "col": 52, "offset": 10421}, "extra": {"message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.correctness.unchecked-subprocess-call_8c1ecfecb43ce455_b40ce83f", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.unchecked-subprocess-call", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "remediation": "check_call", "location": {"file_path": "unknown", "line_start": 246, "line_end": 246, "column_start": 16, "column_end": 20, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://docs.python.org/3/library/subprocess.html#subprocess.check_call", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.unchecked-subprocess-call", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 246, "col": 16, "offset": 10320}, "end": {"line": 246, "col": 20, "offset": 10324}, "extra": {"message": "This is not checking the return value of this subprocess call; if it fails no exception will be raised. Consider subprocess.check_call() instead", "fix": "check_call", "metadata": {"references": ["https://docs.python.org/3/library/subprocess.html#subprocess.check_call"], "category": "correctness", "technology": ["python"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_8c1ecfecb43ce455_da518671", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "remediation": "False", "location": {"file_path": "unknown", "line_start": 247, "line_end": 247, "column_start": 47, "column_end": 51, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.subprocess-shell-true", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 247, "col": 47, "offset": 10416}, "end": {"line": 247, "col": 51, "offset": 10420}, "extra": {"message": "Found 'subprocess' function 'call' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "fix": "False", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b602_subprocess_popen_with_shell_equals_true.html", "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["secure default"], "likelihood": "HIGH", "impact": "LOW", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_8c1ecfecb43ce455_9904d55a", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 249, "line_end": 250, "column_start": 16, "column_end": 57, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 249, "col": 16, "offset": 10479}, "end": {"line": 250, "col": 57, "offset": 10560}, "extra": {"message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.subprocess-shell-true_8c1ecfecb43ce455_899789ef", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.subprocess-shell-true", "finding_type": "security", "severity": "high", "confidence": "medium", "message": "Found 'subprocess' function 'check_output' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "remediation": "False", "location": {"file_path": "unknown", "line_start": 250, "line_end": 250, "column_start": 41, "column_end": 45, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.subprocess-shell-true", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 250, "col": 41, "offset": 10544}, "end": {"line": 250, "col": 45, "offset": 10548}, "extra": {"message": "Found 'subprocess' function 'check_output' with 'shell=True'. This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. Use 'shell=False' instead.", "fix": "False", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/plugins/b602_subprocess_popen_with_shell_equals_true.html", "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["secure default"], "likelihood": "HIGH", "impact": "LOW", "confidence": "MEDIUM"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_8c1ecfecb43ce455_e6e4be92", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 267, "line_end": 267, "column_start": 5, "column_end": 69, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/8c1ecfecb43ce455.py", "start": {"line": 267, "col": 5, "offset": 11033}, "end": {"line": 267, "col": 69, "offset": 11097}, "extra": {"message": "Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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} | 2.578125 | stackv2 | #!/usr/bin/env python2
import io
from io import open
import fcntl
import string
import time
import datetime
import logging
import json
import os
import socket
import sys
import lib.iw_motor
import lib.iw_acc
import lib.iw_hot
import lib.iw_rgb
import lib.iw_sal
# Change per well
well_num = 9
sleep_between_trials = 5
num_samples = 3
# For sending readings to database
import requests
_token = '4d197a543681b336b817f951f998e64'
def uploadFileToIkewai(token, filename):
headers = {
'authorization': "Bearer " + token
}
files ={'fileToUpload' : open(filename,'rb')}
res = requests.post('https://ikeauth.its.hawaii.edu/files/v2/media/system/mydata-tamrako/dropsensor_data/', files=files, headers=headers,verify=False)
resp = json.loads(res.content)
return resp
# Defining all the read functions for sensors
def log_iw(message):
"""
Prints out message to terminal and adds to log
:param message: message to be printed/logged
:type message: string
:return: nothing
"""
with open('log/' + create_datestamp() + '.txt', "a") as f:
message_ = create_timestamp() + ': ' + message + '\n'
f.write(message_.decode('utf-8'))
print(message)
logging.debug(message)
def read_rgb_initial():
"""
Method to check if the RGB sensor is working.
This is because a reading of 0,0,0 is still considered a success
by the system, but could mean that the LED is broken and RGB
should not be considered useful.
:return: nothing
"""
lib.iw_rgb.get_rgb()
def read_rgb():
"""
Method to get a reading from RGB Sensor, then displays and logs it
Turns on LED, obtains reading, logs reading, turns off LED
:return: a list containing the RGB reading
"""
lib.iw_rgb.turn_led_on()
time.sleep(2)
rgb_values = lib.iw_rgb.get_rgb()
log_iw("Red: " + str(rgb_values[0]))
log_iw("Green: " + str(rgb_values[1]))
log_iw("Blue: " + str(rgb_values[2]))
time.sleep(2)
lib.iw_rgb.turn_led_off()
return rgb_values
def read_acc():
"""
Method to get a reading from accelerometer,then displays and logs
it
:return: a list of the X, Y, and Z components
"""
acc = lib.iw_acc.get_acc()
log_iw("X-Acc: " + str(acc[0]))
log_iw("Y-Acc: " + str(acc[1]))
log_iw("Z-Acc: " + str(acc[2]))
log_iw("X-Mag: " + str(acc[3]))
log_iw("Y-Mag: " + str(acc[4]))
log_iw("Z-Mag: " + str(acc[5]))
return acc
def read_hot():
"""
Method to get a reading from temperature sensor, then displays and
logs it
:return: a list of the temp in Celsius and Fahrenheit
"""
hot = lib.iw_hot.get_hot()
log_iw("Temp (C): " + str(hot[0]))
log_iw("Temp (F): " + str(hot[1]))
return hot
def read_sal():
"""
Method to get a reading from salinity sensor, then displays and
logs it
:return: an integer of the salinity
"""
sal_string = ''.join(lib.iw_sal.get_sal()).split(',')
sal = []
for i in sal_string:
try:
sal.append(float(i))
except ValueError:
log_iw("Invalid read from Salinity, skipping...")
sal.append('X') # micro-S/cm bad reading
sal.append('X') # PSU bad reading
log_iw("Salinity (micro-S/cm): " + str(sal[0]))
try:
log_iw("Salinity (PSU): " + str(sal[1]))
except ValueError:
print('PSU Reading not found. Make sure it is enabled on the chip!')
except IndexError:
pass
return sal
# Determine which sensor failed during the 10-sample collection.
def get_bad_sensor(y_value):
"""
Method to get which sensor has failed
:param y_value: an integer to store the index of failed sensor
:type y_value: int
:return: an integer containing the index of the failed sensor
"""
switcher = {
0: 'RGB failed...',
1: 'ACC failed...',
2: 'HOT failed...',
3: 'SAL failed...'
}
# Returns the current index of read_array being run.
return switcher.get(y_value, "nothing")
def create_datestamp():
"""
creates a datestamp in the month/dd/yyyy format
:return: a string of the datestamp
"""
return time.strftime('%b-%d-%Y', time.localtime(time.time()))
def create_timestamp():
"""
creates a timestamp in the 24hr HH:MM:SS format
:return: a string of the timestamp
"""
return time.strftime('%H:%M:%S', time.localtime(time.time()))
def average_list(list_):
"""
averages all the values in list_ together, ignores any invalid entries
:param list_: a list containing values to be averaged
:type list_: list
:return: a number of the average
"""
num_val = 0
total = 0
for i in list_:
if type(i) is int or type(i) is float:
valid = type(i)
num_val += 1
total += i
if num_val > 0:
if valid is float:
return float('%.3f' % (total/num_val))
else:
return total/num_val
else:
return "No Readings Found"
read_array = [read_rgb, read_acc, read_hot, read_sal]
# steps_for_foot = 125 #demo
if __name__ == "__main__":
# save path for sensor data
save_path = '/home/pi/IkeWai/data/dict_' + create_datestamp() + '/well-'+ str(well_num) + '-' + create_timestamp()
# flag to control manual quiting of program
terminate = False
# Log files for debug in case of errors
# log_name = 'log_' + dt + '.txt'
# logging.basicConfig(filename=r'/home/pi/Desktop/ikewai/logs/client_logs/' + log_name,
# level=logging.DEBUG,
# format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %I:%M:%S %p')
# log_iw('iw.py starting...')
# log_iw('Time_Date: ' + str(dt))
# For some reason, the first read of the RGB sensor returns 0,0,0.
try:
read_rgb_initial()
except IOError:
log_iw('IOError from initial RGB occurred...')
pass
# Read Samples
json_dump = {
'DATE': create_datestamp(),
'TIME': create_timestamp(),
'DATA': {},
'SAMPLES TAKEN': num_samples,
'TIME BETWEEN SAMPLES': sleep_between_trials
}
json_data = {
'AVERAGE': {},
'READINGS': {
'RGB': {
'UNITLESS': {
'R': [],
'G': [],
'B': []
}
},
'MAGNETIC': {
'GAUSS': {
'X': [],
'Y': [],
'Z': []
}
},
'ACCEL': {
'M/S^2': {
'X': [],
'Y': [],
'Z': []
}
},
'SALINITY': {
'PSU': [],
'MICRO-S/CM': []
},
'TEMP': {
'C': [],
'F': []
}
}
}
json_read = json_data['READINGS']
for x in range(0, num_samples):
for y in range(0, 4):
try:
# Read sensor values
value = read_array[y]()
if y == 0:
json_read['RGB']['UNITLESS']['R'].append(value[0])
json_read['RGB']['UNITLESS']['G'].append(value[1])
json_read['RGB']['UNITLESS']['B'].append(value[2])
elif y == 1:
json_read['ACCEL']['M/S^2']['X'].append(value[0])
json_read['ACCEL']['M/S^2']['Y'].append(value[1])
json_read['ACCEL']['M/S^2']['Z'].append(value[2])
json_read['MAGNETIC']['GAUSS']['X'].append(value[3])
json_read['MAGNETIC']['GAUSS']['Y'].append(value[4])
json_read['MAGNETIC']['GAUSS']['Z'].append(value[5])
elif y == 2:
json_read['TEMP']['C'].append(value[0])
json_read['TEMP']['F'].append(value[1])
elif y == 3:
json_read['SALINITY']['MICRO-S/CM'].append(value[0])
json_read['SALINITY']['PSU'].append(value[1])
# When there is an error (sensor not working)
except IOError:
log_iw('IOError occurred')
log_iw(get_bad_sensor(y))
error = 'X'
if y == 0:
json_read['RGB']['UNITLESS']['R'].append(error)
json_read['RGB']['UNITLESS']['G'].append(error)
json_read['RGB']['UNITLESS']['B'].append(error)
elif y == 1:
json_read['ACCEL']['M/S^2']['X'].append(error)
json_read['ACCEL']['M/S^2']['Y'].append(error)
json_read['ACCEL']['M/S^2']['Z'].append(error)
json_read['MAGNETIC']['GAUSS']['X'].append(error)
json_read['MAGNETIC']['GAUSS']['Y'].append(error)
json_read['MAGNETIC']['GAUSS']['Z'].append(error)
elif y == 2:
json_read['TEMP']['C'].append(error)
json_read['TEMP']['F'].append(error)
elif y == 3:
json_read['SALINITY']['MICRO-S/CM'].append(error)
json_read['SALINITY']['PSU'].append(error)
pass
# If process is killed before runs finished
except KeyboardInterrupt:
log_iw('Process terminated early')
lib.iw_rgb.turn_led_off()
terminate = True
break
if not terminate:
# SLEEPING AT BOTTOM
log_iw('Sleeping')
time.sleep(sleep_between_trials)
else:
break
# Average the readings
for sensor in json_data['READINGS']:
json_data['AVERAGE'][sensor] = {}
for scale in json_data['READINGS'][sensor]:
if type(json_data['READINGS'][sensor][scale]) == dict:
json_data['AVERAGE'][sensor][scale] = {}
for subcat in json_data['READINGS'][sensor][scale]:
json_data['AVERAGE'][sensor][scale][subcat] = \
average_list(json_data['READINGS'][sensor][scale][subcat])
else:
json_data['AVERAGE'][sensor][scale] = []
json_data['AVERAGE'][sensor][scale] = average_list(json_data['READINGS'][sensor][scale])
json_dump['DATA'] = json_data
print(save_path)
try:
os.makedirs(save_path)
except:
print('File Exists')
# The 'a' appends the file if there is an existing file
# the '+' creates the file if there isn't an existing file
with open(save_path + '/pretty.txt', "w") as f:
# Dumping the data from the earlier conversion
# into the newly created file
print(json_dump)
f.write(json.dumps(json_dump, sort_keys=True, indent=4).decode('utf-8'))
data_path = save_path + '/well-' + str(well_num) + '-' + create_timestamp() + '_data.json'
with open(data_path, "w") as f:
# Dumping the data from the earlier conversion
# into the newly created file
#print(json_dump)
f.write(json.dumps(json_dump).decode('utf-8'))
uploadFileToIkewai(_token, data_path)
log_iw('Exiting...')
# Turn off the LED before exiting
lib.iw_rgb.turn_led_off()
log_iw('Exited...')
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"CWE-295"
] | [
"rules.python.requests.security.disabled-cert-validation"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
37
] | [
37
] | [
11
] | [
155
] | [
"A03:2017 - Sensitive Data Exposure"
] | [
"Certificate verification has been explicitly disabled. This permits insecure connections to insecure servers. Re-enable certification validation."
] | [
7.5
] | [
"LOW"
] | [
"LOW"
] | fall2019-2.py | /fall2019-2.py | jie-zhou/Ike-Wai-Sensors | Apache-2.0 | |
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} | 2.765625 | stackv2 | from subprocess import call
DATAFILE_PATH = 'temp/'
class CRF:
def __init__(self):
return None
def preprocess_dataset(self, dataset, filename):
'''
TODO as the task in hand
'''
f = open(DATAFILE_PATH + filename, 'w')
for discussion in dataset:
if filename == 'train.data':
ground_truths = discussion['ground_truth']
predicted_val = discussion['predicted_ground_truth']
for i, item in enumerate(predicted_val):
if filename == 'train.data':
assert item['post_id'] == ground_truths[i]['post_id']
for pred_word, word in\
zip(item['consensus']['tokens'],
ground_truths[i]['consensus']['tokens']):
assert word['word'] == pred_word['word']
f.write(' '.join([word['word'], pred_word['lang'],
word['lang']]) + '\n')
else:
for pred_word in item['consensus']['tokens']:
f.write(' '.join([pred_word['word'],
pred_word['lang']]) + '\n')
f.write('\n')
f.close()
def postprocess_data(self, dataset, filename):
'''
TODO as the task in hand
'''
f = open(DATAFILE_PATH + filename, 'r')
for discussion in dataset:
predicted_val = discussion['predicted_ground_truth']
for item in predicted_val:
for word in item['consensus']['tokens']:
splits = f.readline().strip().split('\t')
assert word['word'] == splits[0]
word['lang'] = splits[-1]
f.readline()
return dataset
def train_crf(self):
c = 150 # emphirically that found 150 works better
command = 'CRF++.58/crf_learn -c ' + \
str(c) + ' temp/template temp/train.data temp/model'
call(command, shell=True)
def test_crf(self):
command = 'CRF++.58/crf_test -m temp/model temp/test.data >\
temp/results_test.data'
call(command, shell=True)
def rm_crf(self):
command = 'rm -rf temp/model'
call(command, shell=True)
def train_and_predict(self, training_dataset, testing_dataset):
self.preprocess_dataset(training_dataset, 'train.data')
self.preprocess_dataset(testing_dataset, 'test.data')
self.train_crf()
self.test_crf()
testing_dataset = self.postprocess_data(testing_dataset,
'results_test.data')
return testing_dataset
def predict(self, testing_dataset):
self.preprocess_dataset(testing_dataset, 'test.data')
self.test_crf()
testing_dataset = self.postprocess_data(testing_dataset,
'results_test.data')
return testing_dataset
if __name__ == '__main__':
dataset1 = read_data('data/Dataset1.json')
dataset2 = read_data('data/Dataset2.json')
preprocess_dataset(dataset1+dataset2, 'train.data')
test_dataset = read_data('data/TestData1.json')
preprocess_dataset(test_dataset, 'test.data')
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"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.subprocess-shell-true"
] | [
"security",
"security"
] | [
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH"
] | [
61,
61
] | [
61,
61
] | [
9,
29
] | [
34,
33
] | [
"A01:2017 - Injection",
"A01:2017 - Injection"
] | [
"Detected subprocess function 'call' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.",
"Found 'subprocess' functio... | [
7.5,
7.5
] | [
"LOW",
"HIGH"
] | [
"HIGH",
"LOW"
] | CRF.py | /CRF.py | amilasilva92/multilingual-communities-by-code-switching | MIT | |
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# This file is part of Pyblosxom.
#
# Copyright (C) 2004-2011 by the Pyblosxom team. See AUTHORS.
#
# Pyblosxom is distributed under the MIT license. See the file
# LICENSE for distribution details.
#######################################################################
"""
Summary
=======
Walks through your blog root figuring out all the available years for
the archives list. It stores the years with links to year summaries
in the variable ``$(archivelinks)``. You should put this variable in
either your head or foot template.
Install
=======
This plugin comes with Pyblosxom. To install, do the following:
1. Add ``Pyblosxom.plugins.yeararchives`` to the ``load_plugins`` list
in your ``config.py`` file.
2. Add ``$(archivelinks)`` to your head and/or foot templates.
3. Configure as documented below.
Usage
=====
When the user clicks on one of the year links
(e.g. ``http://base_url/2004/``), then yeararchives will display a
summary page for that year. The summary is generated using the
``yearsummarystory`` template for each month in the year.
My ``yearsummarystory`` template looks like this::
<div class="blosxomEntry">
<span class="blosxomTitle">$title</span>
<div class="blosxomBody">
<table>
$body
</table>
</div>
</div>
The ``$(archivelinks)`` link can be configured with the
``archive_template`` config variable. It uses the Python string
formatting syntax.
Example::
py['archive_template'] = (
'<a href="%(base_url)s/%(Y)s/index.%(f)s">'
'%(Y)s</a><br />')
The vars available with typical example values are::
Y 4-digit year ex: '1978'
y 2-digit year ex: '78'
f the flavour ex: 'html'
.. Note::
The ``archive_template`` variable value is formatted using Python
string formatting rules--not Pyblosxom template rules!
"""
__author__ = "Will Kahn-Greene"
__email__ = "willg at bluesock dot org"
__version__ = "2010-05-08"
__url__ = "http://pyblosxom.github.com/"
__description__ = "Builds year-based archives listing."
__category__ = "archives"
__license__ = "MIT"
__registrytags__ = "1.4, 1.5, core"
from Pyblosxom import tools, entries
from Pyblosxom.memcache import memcache_decorator
from Pyblosxom.tools import pwrap
import time
def verify_installation(request):
config = request.get_configuration()
if not 'archive_template' in config:
pwrap(
"missing optional config property 'archive_template' which "
"allows you to specify how the archive links are created. "
"refer to yeararchives plugin documentation for more details.")
return True
class YearArchives:
def __init__(self, request):
self._request = request
self._archives = None
self._items = None
@memcache_decorator('yeararchives', True)
def __str__(self):
if self._archives is None:
self.gen_linear_archive()
return self._archives
def gen_linear_archive(self):
config = self._request.get_configuration()
data = self._request.get_data()
root = config["datadir"]
archives = {}
archive_list = tools.walk(self._request, root)
items = []
fulldict = {}
fulldict.update(config)
fulldict.update(data)
flavour = data.get(
"flavour", config.get("default_flavour", "html"))
template = config.get(
'archive_template',
'<a href="%(base_url)s/%(Y)s/index.%(f)s">%(Y)s</a><br />')
for mem in archive_list:
timetuple = tools.filestat(self._request, mem)
timedict = {}
for x in ["m", "Y", "y", "d"]:
timedict[x] = time.strftime("%" + x, timetuple)
fulldict.update(timedict)
fulldict["f"] = flavour
year = fulldict["Y"]
if not year in archives:
archives[year] = template % fulldict
items.append(
["%(Y)s-%(m)s" % fulldict,
"%(Y)s-%(m)s-%(d)s" % fulldict,
time.mktime(timetuple),
mem])
arc_keys = archives.keys()
arc_keys.sort()
arc_keys.reverse()
result = []
for key in arc_keys:
result.append(archives[key])
self._archives = '\n'.join(result)
self._items = items
def new_entry(request, yearmonth, body):
"""
Takes a bunch of variables and generates an entry out of it. It
creates a timestamp so that conditionalhttp can handle it without
getting all fussy.
"""
entry = entries.base.EntryBase(request)
entry['title'] = yearmonth
entry['filename'] = yearmonth + "/summary"
entry['file_path'] = yearmonth
entry._id = yearmonth + "::summary"
entry["template_name"] = "yearsummarystory"
entry["nocomments"] = "yes"
entry["absolute_path"] = ""
entry["fn"] = ""
entry.set_time(time.strptime(yearmonth, "%Y-%m"))
entry.set_data(body)
return entry
INIT_KEY = "yeararchives_initiated"
def cb_prepare(args):
request = args["request"]
data = request.get_data()
data["archivelinks"] = YearArchives(request)
def cb_date_head(args):
request = args["request"]
data = request.get_data()
if INIT_KEY in data:
args["template"] = ""
return args
def parse_path_info(path):
"""Returns None or (year, flav) tuple.
Handles urls of this type:
- /2003
- /2003/
- /2003/index
- /2003/index.flav
"""
path = path.split("/")
path = [m for m in path if m]
if not path:
return
year = path[0]
if not year.isdigit() or not len(year) == 4:
return
if len(path) == 1:
return (year, None)
if len(path) == 2 and path[1].startswith("index"):
flav = None
if "." in path[1]:
flav = path[1].split(".", 1)[1]
return (year, flav)
return
def cb_filelist(args):
request = args["request"]
pyhttp = request.get_http()
data = request.get_data()
config = request.get_configuration()
baseurl = config.get("base_url", "")
path = pyhttp["PATH_INFO"]
ret = parse_path_info(path)
if ret == None:
return
# note: returned flavour is None if there is no .flav appendix
year, flavour = ret
data[INIT_KEY] = 1
# get all the entries
wa = YearArchives(request)
wa.gen_linear_archive()
items = wa._items
# peel off the items for this year
items = [m for m in items if m[0].startswith(year)]
items.sort()
items.reverse()
# Set and use current (or default) flavour for permalinks
if not flavour:
flavour = data.get(
"flavour", config.get("default_flavour", "html"))
data["flavour"] = flavour
l = ("(%(path)s) <a href=\"" + baseurl +
"/%(file_path)s." + flavour + "\">%(title)s</a><br>")
e = "<tr>\n<td valign=\"top\" align=\"left\">%s</td>\n<td>%s</td></tr>\n"
d = ""
m = ""
day = []
month = []
entrylist = []
for mem in items:
if not m:
m = mem[0]
if not d:
d = mem[1]
if m != mem[0]:
month.append(e % (d, "\n".join(day)))
entrylist.append(new_entry(request, m, "\n".join(month)))
m = mem[0]
d = mem[1]
day = []
month = []
elif d != mem[1]:
month.append(e % (d, "\n".join(day)))
d = mem[1]
day = []
entry = entries.fileentry.FileEntry(
request, mem[3], config['datadir'])
day.append(l % entry)
if day:
month.append(e % (d, "\n".join(day)))
if month:
entrylist.append(new_entry(request, m, "\n".join(month)))
return entrylist
| 312 | 24.3 | 77 | 18 | 2,050 | python | [{"finding_id": "semgrep_rules.python.django.security.injection.raw-html-format_7fb5f182dc2a0f01_cb3c09f5", "tool_name": "semgrep", "rule_id": "rules.python.django.security.injection.raw-html-format", "finding_type": "security", "severity": "medium", "confidence": "medium", "message": "Detected user input flowing into a manually constructed HTML string. You may be accidentally bypassing secure methods of rendering HTML by manually constructing HTML and this could create a cross-site scripting vulnerability, which could let attackers steal sensitive user data. To be sure this is safe, check that the HTML is rendered safely. Otherwise, use templates (`django.shortcuts.render`) which will safely render HTML instead.", "remediation": "", "location": {"file_path": "unknown", "line_start": 275, "line_end": 276, "column_start": 9, "column_end": 63, "code_snippet": "requires login"}, "cwe_id": "CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A07:2017 - Cross-Site Scripting (XSS)", "references": [{"url": "https://docs.djangoproject.com/en/3.2/topics/http/shortcuts/#render", "title": null}, {"url": "https://docs.djangoproject.com/en/3.2/topics/security/#cross-site-scripting-xss-protection", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.django.security.injection.raw-html-format", "path": "/tmp/tmpr7mo7ysm/7fb5f182dc2a0f01.py", "start": {"line": 275, "col": 9, "offset": 6901}, "end": {"line": 276, "col": 63, "offset": 7000}, "extra": {"message": "Detected user input flowing into a manually constructed HTML string. You may be accidentally bypassing secure methods of rendering HTML by manually constructing HTML and this could create a cross-site scripting vulnerability, which could let attackers steal sensitive user data. To be sure this is safe, check that the HTML is rendered safely. Otherwise, use templates (`django.shortcuts.render`) which will safely render HTML instead.", "metadata": {"cwe": ["CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')"], "owasp": ["A07:2017 - Cross-Site Scripting (XSS)", "A03:2021 - Injection", "A05:2025 - Injection"], "category": "security", "technology": ["django"], "references": ["https://docs.djangoproject.com/en/3.2/topics/http/shortcuts/#render", "https://docs.djangoproject.com/en/3.2/topics/security/#cross-site-scripting-xss-protection"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["vuln"], "likelihood": "HIGH", "impact": "MEDIUM", "confidence": "MEDIUM"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
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} | 2.75 | stackv2 | """pyextensions is a proof-of-concept of implementing code transformations
using import hooks.
By code transformation, we mean that instead of executing the code found
in a module *as is*, it is first transformed prior to its execution.
The transformations are done by other modules, called transformers, which
are normal Python file.
A transformer needs to include at least one of the following:
1. A function named ``transform_source()`` which takes as its argument a string,
like the content of a regular Python script, modifies it, and return another
string. Such transformations can be chained.
2. A function named ``transform_ast()`` which takes as its argument an abstract
syntax tree, modifies it, and returns another tree. Such transformations can
also be chained.
3. A function named ``transform_bytecode()`` which takes as its argument
a code object, modifies it, and returns another code object. Such
transformations can also be chained.
In addition to the above, two other functions can be can potentially
be used by pyextensions if they are found in a transformer:
1. By default, pyextension uses the ``parse()`` function from the ast module
in the standard library to create an abstract syntax tree. If a
transformer includes a similarly named function, it will be used instead.
For example, one could use a parser that can handle cython notation,
possibly converting all type information into a format acceptable
for Python. Note that if such a function is found in more than one
transformer, only the last one found will be used.
2. If a transformation requires that some additional module needs to be
imported by the transformed source, it should be using a function named
``add_import()`` which returns the appropriate import statements.
While this could be done using the ``transform_source()``
function to simply prepend the required imports in the transformed
source, it is more useful to do so in a separate function as it allows
pyextensions to be used in other contexts -- like
in a custom REPL.
By default, this module looks for files ending with a ".notpy" extension;
however, this can be changed using a configuration settings.
"""
import argparse
import ast
import os.path
import sys
from importlib import import_module
from importlib.abc import Loader, MetaPathFinder
from importlib.util import spec_from_file_location
def create_fake_site_packages_dir():
"""It is assumed that code transformers are third-party modules
to be installed in a location from where they can be imported.
For this proof of concept, we add a fake site-packages directory
where the sample transformers will be located.
"""
top_dir = os.path.abspath(os.path.dirname(__file__))
fake_site_pkg = os.path.join(top_dir, "fake_site_pkg")
if not os.path.exists(fake_site_pkg):
raise NotImplementedError(
"A fake_site_pkg directory must exist for this demo to work correctly."
)
sys.path.insert(0, fake_site_pkg)
create_fake_site_packages_dir()
CONFIG = {"file_ext": ["notpy"], "main_module_name": None, "version": 0.2}
TRANSFORMERS = {"<cache>": []} # [(tr_name1, tr_mod1), ...]
class ExtensionMetaFinder(MetaPathFinder):
"""A custom finder to locate modules, based on looking for files
with a specific extension."""
def find_spec(self, fullname, path, target=None):
"""Finds the appropriate properties (spec) of a module, and sets
its loader."""
if not path:
path = [os.getcwd()]
if "." in fullname:
module_name = fullname.split(".")[-1]
else:
module_name = fullname
for entry in path:
filename = None
submodule_locations = None
for ext in CONFIG["file_ext"]:
fn = os.path.join(entry, module_name + "." + ext)
if os.path.exists(fn):
filename = fn
break
else:
if os.path.isdir(os.path.join(entry, module_name)):
# this module has child modules
fn = os.path.join(entry, module_name, "__init__.py")
if os.path.exists(fn):
filename = fn
submodule_locations = [os.path.join(entry, module_name)]
if filename is not None:
return spec_from_file_location(
fullname,
filename,
loader=ExtensionLoader(filename),
submodule_search_locations=submodule_locations,
)
return None # default to other finders
sys.meta_path.insert(0, ExtensionMetaFinder())
class ExtensionLoader(Loader):
"""A custom loader which transforms the source prior to its execution"""
def __init__(self, filename):
self.filename = filename
def exec_module(self, module):
"""Import the source code, transforms it before executing it so that
it becomes valid Python."""
module_name = module.__name__
if module.__name__ == CONFIG["main_module_name"]:
module.__name__ = "__main__"
with open(self.filename) as f:
source = f.read()
get_required_transformers(module_name, source)
if TRANSFORMERS[module_name]:
source = add_all_imports(module_name, source)
source = apply_source_transformations(module_name, source)
parse = get_parser(module_name)
if parse is None:
parse = ast.parse
tree = parse(source)
tree = apply_ast_transformations(module_name, tree)
code_object = compile(tree, module_name, "exec")
code_object = apply_bytecode_transformations(module_name, code_object)
exec(code_object, vars(module))
else:
exec(source, vars(module))
def import_main(module_name):
"""Imports the module that is to be interpreted as the main module.
pyextensions would normally be called with a script meant to be run as
the main module with its source to be transformed.
This script is specified the -s (or --source) option, as in::
python -m pyextensions -s name
With the -m flag, Python identifies pyextensions as the main script;
we artificially change this so that "main_script" is properly
identified as ``name``.
"""
CONFIG["main_module_name"] = module_name
return import_module(module_name)
def get_required_transformers(module_name, source):
"""
Scan a source for lines of the form::
#ext transformer1 [transformer2 ...]
identifying transformers to be used and ensure that they are imported
in the order in which they are specifid in the file.
"""
lines = source.split("\n")
for number, line in enumerate(lines):
if line.startswith("#ext "):
line = line[5:]
for trans_name in line.split(" "):
import_transformer(module_name, trans_name.strip())
return None
def import_transformer(module_name, trans_name):
"""This function needed, import a transformer for a given module and
appends it to the appropriate lists.
"""
if module_name in TRANSFORMERS:
for (name, transformer) in TRANSFORMERS[module_name]:
if name == trans_name:
return transformer
else:
for (name, transformer) in TRANSFORMERS["<cache>"]:
if name == trans_name:
if module_name not in TRANSFORMERS:
TRANSFORMERS[module_name] = []
TRANSFORMERS[module_name].append((name, transformer))
return transformer
# We have not imported the required transformer before.
#
# The code inside a module where a transformer is defined should be
# standard Python code, which does not need any transformation.
# So, we disable the import hook, and let the normal module import
# do its job - which is faster and likely more reliable than our
# custom method.
hook = sys.meta_path[0]
sys.meta_path = sys.meta_path[1:]
try:
transformer = __import__(trans_name)
except ImportError:
sys.stderr.write(
"Fatal: Import Error in add_transformers: %s not found\n" % trans_name
)
raise SystemExit
except Exception as e:
sys.stderr.write(
"\nUnexpected exception in import_transformer %s\n " % e.__class__.__name__
)
sys.stderr.write(str(e.args))
sys.stderr.write(f"\nname = {trans_name}\n")
sys.meta_path.insert(0, hook) # restore import hook
TRANSFORMERS["<cache>"].append((trans_name, transformer))
if module_name not in TRANSFORMERS:
TRANSFORMERS[module_name] = []
TRANSFORMERS[module_name].append((trans_name, transformer))
return transformer
##############
# The code above dealt with adding an import hook, identifying and loading
# transformers and redefining a __main__ module.
#
# What follows is the code required for doing the actual transformations.
############
def add_all_imports(module_name, source):
"""Adds required import in transformed module.
Some transformers may require that other modules be imported
in the source code for it to work properly. While this could in principle
be done in transform_source(), we have found it useful to be done in
a separate function. In particular, this makes it possible to use the
import hook machinery of pyextensions in an REPL where the act of
importing additional modules is done once, separately from the act
of transforming the interactive input provided by a user.
"""
if module_name not in TRANSFORMERS:
return source
for _, transformer in TRANSFORMERS[module_name]:
if hasattr(transformer, "add_import"):
source = transformer.add_import() + source
return source
def apply_source_transformations(module_name, source):
"""Converts the source code.
Applies all the source transformers specified in the module to be
transformed, in the order listed.
Source transformers are transformers that contain a function named
``transform_source`` which takes a string (source of a program)
and returned a transformed string.
"""
if module_name not in TRANSFORMERS:
return source
for trans_name, transformer in TRANSFORMERS[module_name]:
if hasattr(transformer, "transform_source"):
source = transformer.transform_source(source)
return source
def get_parser(module_name):
"""Used to potentially substitute a different parser than the one provided
in the ast module.
"""
if module_name not in TRANSFORMERS:
return None
for trans_name, transformer in TRANSFORMERS[module_name]:
if hasattr(transformer, "parse"):
return transformer.parse
return None
def apply_ast_transformations(module_name, tree):
"""Converts the abstract source tree.
Applies all the AST transformers specified in the module,
in the order listed.
AST transformers are applied on a abstract syntax tree.
They are transformers that contain a function named
``transform_ast`` which take an abstract syntax tree as input
and return a new tree.
"""
if module_name not in TRANSFORMERS:
return tree
for trans_name, transformer in TRANSFORMERS[module_name]:
if hasattr(transformer, "transform_ast"):
tree = transformer.transform_ast(tree)
return tree
def apply_bytecode_transformations(module_name, code_object):
"""Converts the bytecode
Applies all the bytecode transformers specified in the module,
in the order listed.
Bytecode transformers are transformers that contain a function
named ``transform_bytecode`` which take a code object as input
and return a new code_object.
"""
if module_name not in TRANSFORMERS:
return code_object
for trans_name, transformer in TRANSFORMERS[module_name]:
if hasattr(transformer, "transform_bytecode"):
code_object = transformer.transform_bytecode(code_object)
return code_object
def main():
"""**Basic invocation**
The primary role of pyextensions is to run programs that have a
modified syntax.
This is done by one of the following alternatives::
python -m pyextensions -s path/to/name
python pyextensions.py -s path/to/name
or ... --source path/to/name
where ``name`` refers to a file named ``name.notpy``. Any subsequent
``import`` statement will first look for file whose extension is
``notpy`` before looking for normal ``py`` or ``pyc`` files.
Any file with the ``notpy`` extension that is imported will also be
processed by the relevant source transformers.
Normal Python files will bypass the transformations.
Instead of the ``notpy`` default, different extensions can be
specified as follows::
python -m pyextensions -s name -x EXTENSION [EXTENSION_2 ...]
or --file_extension EXTENSION [EXTENSION_2 ...]
"""
parser = argparse.ArgumentParser(
description="""
pyextensions sets up an import hook which makes it possible
to execute modules that contains modified Python syntax
provided the relevant source transformers can be imported.
"""
)
parser.add_argument(
"-s",
"--source",
help="""Source file to be transformed.
Format: path/to/file -- Do not include an extension.""",
)
parser.add_argument(
"-x",
"--file_extension",
nargs="+",
help="The file extension(s) of the module to load; default=notpy",
)
args = parser.parse_args()
if args.file_extension is not None:
CONFIG["file_ext"] = args.file_extension
if args.source is not None:
try:
CONFIG["main_module"] = import_main(args.source)
except ModuleNotFoundError:
print("Could not find module ", args.source, "\n")
raise
else:
parser.print_help()
if __name__ == "__main__":
main()
| 396 | 35.3 | 87 | 21 | 2,976 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_9e861dc87ad22d7e_b3a7ac9d", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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"CWE-95",
"CWE-95"
] | [
"rules.python.lang.security.audit.exec-detected",
"rules.python.lang.security.audit.exec-detected"
] | [
"security",
"security"
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"LOW"
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"MEDIUM"
] | [
148,
150
] | [
148,
150
] | [
13,
13
] | [
44,
39
] | [
"A03:2021 - Injection",
"A03:2021 - Injection"
] | [
"Detected the use of exec(). exec() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.",
"Detected the use of exec(). exec() can be dangerous if used... | [
5,
5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | pyextensions.py | /pyextensions.py | aroberge/pyextensions | MIT | |
2024-11-18T19:28:48.286293+00:00 | 1,686,794,745,000 | 231e7d5c7ffe24d261569df007170edf99de10dd | 3 | {
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"revision_date": 1686794745000,
"revision_id": "15cf4f843095a4e92fb8a413e856f4dd2ea288d5",
"snapshot_id": "f0baa9a51ad41bafc4245182d5defb13f98a2c42",
"src_encoding": "UTF-8",
"star_events_count": 38,
"url": "https://raw.githubusercontent.com/blueset/alfred-search-unicode/15cf4f843095a4e92fb8a413e856f4dd2ea288d5/alfred-search-unicode/unicode_search.py",
"visit_date": "2023-06-26T12:45:53.943251"
} | 2.59375 | stackv2 | #!/usr/bin/python3
"""
Search for Unicode Descriptions
uni binary from: https://github.com/arp242/uni
"""
import sys
import re
import subprocess
import json
import csv
if len(sys.argv) >= 2:
query = sys.argv[1]
try:
out: str = subprocess.check_output(
["./uni", "-q", "search", query, "-f",
"%(char q),%(cpoint q),%(dec q),%(name q),%(cat q)", ]
).decode()
out = out.strip().splitlines()
except subprocess.CalledProcessError:
out = []
if re.match(r"((U\+)?[0-9A-Fa-f]+ ?)+$", query):
pr_out: str = subprocess.check_output([
"./uni", "-q", "print", "-f", "%(char q),%(cpoint q),%(dec q),%(name q),%(cat q)"
] + query.split()).decode()
out = pr_out.strip().splitlines() + out
out = list(csv.reader(out, quotechar="'"))
else:
out = []
data = []
for i in out[:20]:
char, c_hex, c_int, name, category = i
disp_char = char
try:
out_char = chr(int(c_int))
except ValueError:
out_char = "�"
name = name.title()
data.append({
"uid": f"unicode_{c_int}",
"title": f"{disp_char} — {name}",
"subtitle": f"{c_hex} ({c_int}) {category}",
"arg": out_char,
"text": {
"copy": out_char,
"largetype": out_char
},
"icon": {
"path": "unicode.png"
},
"mods": {
"alt": {
"subtitle": f"Copy name: {name}",
"arg": name,
"valid": True
},
"cmd": {
"subtitle": f"Copy hex code: {c_hex}",
"arg": c_hex,
"valid": True
},
},
})
json.dump({"items": data}, sys.stdout)
| 76 | 22.37 | 93 | 15 | 482 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_92f1e8136521d08a_33cfbada", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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"CWE-78",
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit",
"rules.python.lang.security.audit.dangerous-subprocess-use-tainted-env-args"
] | [
"security",
"security"
] | [
"LOW",
"MEDIUM"
] | [
"HIGH",
"HIGH"
] | [
29,
29
] | [
31,
31
] | [
23,
47
] | [
27,
26
] | [
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"Detected subproces... | [
7.5,
7.5
] | [
"LOW",
"MEDIUM"
] | [
"HIGH",
"MEDIUM"
] | unicode_search.py | /alfred-search-unicode/unicode_search.py | blueset/alfred-search-unicode | MIT | |
2024-11-18T19:28:49.313768+00:00 | 1,520,576,881,000 | 48a8bf55874e1f03ce27af5162231a0419c345bc | 3 | {
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"detected_licenses": [
"Apache-2.0"
],
"directory_id": "cab4ca8b262ed2f3b99d81e710f2bfbad9bfc8b9",
"extension": "py",
"filename": "google_stock_price_to_mysql_etl.py",
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"is_vendor": false,
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"path": "/dataEngineering/google_stock_price_to_mysql_etl.py",
"provenance": "stack-edu-0054.json.gz:577494",
"repo_name": "ferdinand33/TestingRepo",
"revision_date": 1520576881000,
"revision_id": "fd70df20f7c5e81be9f723aca874fe00d06b5bbb",
"snapshot_id": "957517fe9c517339770ba6fd634fcf6025271b7e",
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"star_events_count": 0,
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"visit_date": "2021-04-26T23:30:24.393595"
} | 3.0625 | stackv2 | """
A sample Airflow job copying doing the followings:
- copying Google Stock price info from Google Finance
- pushing to a local MySQL
You need to have this table created in your local MySQL
create table test.google_stock_price (
date date NOT NULL PRIMARY KEY,
open float,
high float,
low float,
close float,
volume int
);
"""
from datetime import timedelta
from datetime import datetime
import airflow
import pymysql
import csv
from airflow import DAG
from airflow.operators.http_operator import SimpleHttpOperator
from airflow.operators.python_operator import PythonOperator
default_args = {
'owner': 'airflow',
'depends_on_past': False,
'start_date': airflow.utils.dates.days_ago(2),
'email': ['airflow@example.com'],
'email_on_failure': False,
'email_on_retry': False,
'retries': 1,
'retry_delay': timedelta(minutes=5),
}
# note that there is no schedule_interval
# which means the only way to run this job is:
# 1> manual trigger in the Airflow web interface
# 2> programmatic trigger from other job
dag = DAG(
'google_stock_price',
default_args=default_args
)
dag.doc_md = __doc__
# note the followings:
# 1> it is using a http connection named "google_finance" which is created separately
# from Airflow web interface (menu:Admin -> Connections)
# 2> xcom_push is set to True so that the downloaded content is pushed to Xcom which
# will be retrieved in the next Operator instance
t1 = SimpleHttpOperator(
task_id='get_google_stock',
http_conn_id='google_finance',
method='GET',
endpoint='finance/historical?q=goog&startdate=27-Mar-2014&output=csv',
xcom_push=True,
dag=dag
)
def pull_csv_and_push_to_mysql(**kwargs):
"""
A callback function used in PythonOperator instance.
- Pull the google stock price info from Xcom
- Push those records into MySQL
"""
# Another tip for debugging is to print something and check logs folder in $AIRFLOW_HOME
# print(kwargs)
value = kwargs['task_instance'].xcom_pull(task_ids='get_google_stock')
reader = csv.reader(value.split("\n"))
# skip the header
# Date,Open,High,Low,Close,Volume
next(reader)
conn = pymysql.connect(host='localhost',
user='root', password='keeyonghan',
db='test', charset='utf8', autocommit=True)
curs = conn.cursor()
for row in reader:
try:
sql = "insert into test.google_stock_price value ('{date}', {open}, {high}, {low}, {close}, {volume});".format(
date=datetime.strptime(row[0], "%d-%b-%y").date(),
open=row[1],
high=row[2],
low=row[3],
close=row[4],
volume=row[5] if row[5] != '-' else "NULL"
)
print(sql)
curs.execute(sql)
except:
print(row)
pass
conn.close()
'''
- For debugging purpose, you can write to a file
f = open("keeyong.csv", "w")
f.write(value)
f.close()
'''
t2 = PythonOperator(
task_id='read_csv',
provide_context=True,
dag=dag,
python_callable=pull_csv_and_push_to_mysql)
t1 >> t2
| 112 | 27.75 | 123 | 18 | 780 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.formatted-sql-query_8256bd302780f531_fd63af1e", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.formatted-sql-query", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected possible formatted SQL query. Use parameterized queries instead.", "remediation": "", "location": {"file_path": "unknown", "line_start": 94, "line_end": 94, "column_start": 13, "column_end": 30, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/775296/mysql-parameterized-queries", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.formatted-sql-query", "path": "/tmp/tmpr7mo7ysm/8256bd302780f531.py", "start": {"line": 94, "col": 13, "offset": 2851}, "end": {"line": 94, "col": 30, "offset": 2868}, "extra": {"message": "Detected possible formatted SQL query. Use parameterized queries instead.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "references": ["https://stackoverflow.com/questions/775296/mysql-parameterized-queries"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_8256bd302780f531_98502bb9", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "remediation": "", "location": {"file_path": "unknown", "line_start": 94, "line_end": 94, "column_start": 13, "column_end": 30, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "title": null}, {"url": "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "title": null}, {"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "path": "/tmp/tmpr7mo7ysm/8256bd302780f531.py", "start": {"line": 94, "col": 13, "offset": 2851}, "end": {"line": 94, "col": 30, "offset": 2868}, "extra": {"message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "metadata": {"cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "references": ["https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column"], "category": "security", "technology": ["sqlalchemy"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"CWE-89",
"CWE-89"
] | [
"rules.python.lang.security.audit.formatted-sql-query",
"rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
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} | 3.234375 | stackv2 | """NFL Playcalling Environment"""
import random
import gym
from gym import spaces
import data_loader as nfl_data
# Create some test functions until api is built
class NFLPlaycallingEnv(gym.Env):
"""Custom Environment that follows gym interface"""
metadata = {'render.modes': ['human']}
def __init__(self):
super(NFLPlaycallingEnv, self).__init__()
# Get data for probabilistic data
filename = './data/nfl-play-by-play.csv'
with open('data/dtypes.txt', 'r') as inf:
dtypes_dict = eval(inf.read())
self.FieldPos = nfl_data.FieldPositionLoader(filename, dtypes_dict=dtypes_dict)
# self._get_field_pos()
# Define action and observation space
# They must be gym.spaces objects
# three discrete actions - pass, run, qb sneak
self.action_space = spaces.Discrete(5)
# observation space: field position, down, to_go, turnover, touchdown
self.observation_space = spaces.Tuple((
spaces.Discrete(100), #field position
spaces.Discrete(4), #down
spaces.Discrete(99), #to_go
spaces.Discrete(2), #turnover
spaces.Discrete(2),#touchdown
spaces.Discrete(2))) # field_goal
self.action_dict = {
0: 'PASS',
1: 'RUN',
2: 'QB_SNEAK',
3: 'FIELD_GOAL',
4: 'PUNT'
}
def step(self, action):
"""Increment the environment one step given an action
Attributes:
action (int): 0-6 value specifying the action taken
Returns:
obs, reward, done, {} (Tuple): observations, current reward for step, and done flag
"""
assert self.action_space.contains(action)
obs = self._get_observation(action)
# check if observation state is a touchdown
if obs[4] == 1:
# print(f"action {self.action_dict[action]} td {obs}")
done = True
reward = 7.
# check if observation state is a field goal
elif obs[5] == 1:
# print(f"action {self.action_dict[action]} field goal {obs}")
done = True
reward = 3.
# check if it is a turnover
elif obs[1] <= 0 or obs[3] == 1:
# print(f"action {self.action_dict[action]} turnover {obs}")
done = True
reward = -7. * (1 - obs[0]/100)
# if not TO or TD then not done and no rewards
else:
# print(f"action {self.action_dict[action]} continue {obs}")
done = False
reward = 0.
print(f'state: action {self.action_dict[action]}, obs: {obs}, done: {done}, reward: {reward}')
return obs, reward, done, {}
def _get_observation(self, action):
"""Calculate the observation space using historical outcomes based on the action taken
Attributes:
action (int): 0-6 value specifying the action taken
Returns:
obs (Tuple of Discreet): the current observation space after the action has been applied
"""
# get outcomes from historical data
outcomes = self._get_field_pos(action)
try:
outcome_idx = random.choices([i for i, x in enumerate(outcomes)], weights=[x[2] for x in outcomes])
outcome = outcomes[outcome_idx[0]]
except:
print(f"NO OUTCOMES: action {action}, outcomes: {outcomes}")
outcome = nfl_data.PlayOutcome(type='BALL_MOVED', yards=0.0, prob=1)
if outcome[0] == 'BALL_MOVED':
# update field position for any BALL_MOVED outcome
self.field_position = self.field_position + outcome[1]
# ball moved
if action == 4:
#punted
self.turnover = 1
elif self.field_position >= 100:
# implied touchdown
self.field_position = 100
self.touchdown = 1
elif outcome[1] >= self.to_go:
# first down
self.remaining_downs = 4 # will get decremented to 3 below
self.to_go = 100 - self.field_position if self.field_position >= 90 else 10
else:
# move the ball and decrement the down
self.to_go -= outcome[1]
elif outcome[0] == 'INTERCEPTION' or outcome[0] == 'FUMBLE':
# turnover
self.turnover = 1
self.field_position = self.field_position + outcome[1]
elif outcome[0] == 'TOUCHDOWN':
# touchdown
self.field_position = 100
self.touchdown = 1
elif outcome[0] == 'FIELD_GOAL_MADE':
# field goal was made
self.field_goal = 1
elif outcome[0] == 'FIELD_GOAL_MISSED':
# field goal was missed
self.turnover = 1
self.field_position = self.field_position + outcome[1]
else:
raise ValueError('invalid action')
# decrement downs
self.remaining_downs -= 1
# print(f"updates: yardline:{self.field_position} turnover:{self.turnover} td:{self.touchdown}")
return self._return_obs_state()
def _return_obs_state(self):
"""Return the observation space at a given time
"""
return (self.field_position, self.remaining_downs, self.to_go, self.turnover, self.touchdown, self.field_goal)
def _gen_rand_outcomes(self):
outcomes = []
for i in range(4):
outcomes.append(('BALL_MOVED', random.randint(0,self.to_go*2), 0.2))
outcomes.append(('INTERCEPTION', -5, 0.1))
outcomes.append(('TOUCHDOWN', 100-self.field_position, 0.1))
return outcomes
def _get_field_pos(self, action):
"""Given an action, return the outcome based on the likelihood from historical data
Attributes:
action (int): Number associated with action taken for discrete observation space. See if statement for number coding
"""
if action == 0:
action_val = nfl_data.PlayType.PASS
elif action == 1:
action_val = nfl_data.PlayType.RUN
elif action == 2:
action_val = nfl_data.PlayType.QB_SNEAK
elif action == 3:
action_val = nfl_data.PlayType.FIELD_GOAL
elif action == 4:
action_val = nfl_data.PlayType.PUNT
else:
raise ValueError('invalid action')
# print(f"Action Taken {action_val}")
outcomes = self.FieldPos.get_probability(down = self.remaining_downs,
to_go = self.to_go,
position = 100-self.field_position,
play = action_val
)
return outcomes
def _set_field_pos(self, field_position = 20, remaining_downs = 3, to_go = 10, turnover = 0, touchdown = 0, field_goal = 0):
"""Used for testing to set different scenarios
Attributes:
field_position (int): 0-100 value of field position where 20 is own 20 and 80 is opp 20
remaining_downs (int): remaining downs before turnover
to_go (int): distance to go for first down
turnover (int): terminal state flag where 0=no turnover, 1=turnover
touchdown (int): terminal state flag where 0=no touchdown, 1=touchdown
"""
self.field_position = field_position
self.remaining_downs = remaining_downs
self.to_go = to_go
self.turnover = turnover
self.touchdown = touchdown
self.field_goal = field_goal
def reset(self):
self._set_field_pos()
return self._return_obs_state()
def render(self, mode='human'):
print(f'Current Field Position: {self.field_position}')
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} | 2.3125 | stackv2 | # %%
import numpy as np
import sys
sys.path.append('../..')
from utils.tester import Tester
import pickle
import os
import matplotlib
import matplotlib.pyplot as plt
import math
import tikzplotlib
city_name = 'Phoenix'
data = []
# data.append({'save_file_name': '2021-04-09_16-35-32', 'description': 'Regular cost'})
# data.append({'save_file_name': '2021-04-09_16-38-49', 'description': '2x cost'})
# data.append({'save_file_name': '2021-04-09_16-44-04', 'description': '4x cost'})
# data.append({'save_file_name': '2021-04-09_16-46-39', 'description': '8x cost'})
# data.append({'save_file_name': '2021-04-09_18-01-51', 'description': '20x cost'})
# data.append({'save_file_name': '2021-04-09_21-26-07', 'description': 'Regular cost'})
# data.append({'save_file_name': '2021-04-11_12-57-45', 'description': '2x cost'})
# data.append({'save_file_name': '2021-04-11_12-53-45', 'description': '4x cost'})
# data.append({'save_file_name': '2021-04-11_13-01-47', 'description': '8x cost'})
# data.append({'save_file_name': '2021-04-11_12-51-09', 'description': '20x cost'})
# param_vals = [0.01, 0.02, 0.04, 0.08, 0.2]
data.append({'save_file_name': '2021-04-24_12-35-23', 'description': '0.1x cost'})
data.append({'save_file_name': '2021-04-24_12-34-29', 'description': '0.2x cost'})
data.append({'save_file_name': '2021-04-24_12-20-26', 'description': '0.5x cost'})
data.append({'save_file_name': '2021-04-23_14-02-29', 'description': 'Regular cost'})
data.append({'save_file_name': '2021-04-23_15-02-03', 'description': '2x cost'})
data.append({'save_file_name': '2021-04-23_15-00-02', 'description': '4x cost'})
param_vals = np.array([0.1, 0.2, 0.5, 1, 2, 4]) * 1e-4
base_directory = os.getcwd()
base_directory = base_directory[0:base_directory.find('src')+3]
if city_name == 'Phoenix':
data_folder_name = 'Phoenix'
if city_name == 'Seattle':
data_folder_name = 'IntercityFlow_Seattle'
if city_name == 'Dallas':
data_folder_name = 'Intercity_Dallas'
# Load county data
county_data_file_path = os.path.join(base_directory, '..', 'data', data_folder_name, 'data_processing_outputs', 'city_data.p')
with open(county_data_file_path,'rb') as f:
county_data = pickle.load(f)
county_list = list(county_data.keys())
# %%
total_population = 0
for county in county_data.keys():
total_population = total_population + county_data[county]['population']
tester_list = []
peak_infections_list = []
num_deaths_list = []
average_lockdown_list = []
for ind in range(len(data)):
file_path = os.path.join(base_directory, 'optimization', 'save', data[ind]['save_file_name'])
with open(file_path,'rb') as f:
tester = pickle.load(f)
data[ind]['tester'] = tester
data[ind]['scale_frac'] = tester.params['scale_frac']
data[ind]['I'] = np.sum(tester.results['I_best'] * data[ind]['scale_frac'], axis=1)
data[ind]['D'] = np.sum(tester.results['D_best'] * data[ind]['scale_frac'], axis=1)
# data[ind]['peak_infections'] = 100 * np.max(data[ind]['I']) / 100,000 total_population
# data[ind]['num_deaths'] = 100 * data[ind]['D'][-1] / total_population
data[ind]['peak_infections'] = np.max(data[ind]['I']) * 100000 / total_population
data[ind]['num_deaths'] = data[ind]['D'][-1] * 100000 / total_population
peak_infections_list.append(data[ind]['peak_infections'])
num_deaths_list.append(data[ind]['num_deaths'])
average_lockdown_list.append(1 - np.average(data[ind]['tester'].results['L_best'][0:98]))
# %%
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.plot(param_vals, [data[i]['peak_infections'] for i in range(len(data))], marker='d')
ax1.set_xscale('log')
ax1.set_xlabel('Economic Impact Parameter')
ax1.set_ylabel('Infections per 100,000')
save_location = os.path.join(base_directory, 'plotting', 'tikz_plotting', city_name)
filename = os.path.join(save_location, 'scale_cost_by_pop_different_cost_infections_comparison.tex')
tikzplotlib.save(filename)
# %%
fig = plt.figure()
ax2 = fig.add_subplot(111)
ax2.plot(param_vals, [data[i]['num_deaths'] for i in range(len(data))], marker='d')
ax2.set_xscale('log')
ax2.set_xlabel('Economic Impact Parameter')
ax2.set_ylabel('Deaths per 100,000')
save_location = os.path.join(base_directory, 'plotting', 'tikz_plotting', city_name)
filename = os.path.join(save_location, 'scale_cost_by_pop_different_cost_deaths_comparison.tex')
tikzplotlib.save(filename)
# %%
fig = plt.figure()
ax3 = fig.add_subplot(111)
ax3.plot(param_vals, average_lockdown_list, marker='d')
ax3.set_xscale('log')
ax3.set_xlabel('Economic Impact Parameter')
ax3.set_ylabel('Average Lockdown Rate')
save_location = os.path.join(base_directory, 'plotting', 'tikz_plotting', city_name)
filename = os.path.join(save_location, 'scale_cost_by_pop_different_cost_lockdown_comparison.tex')
tikzplotlib.save(filename)
# %%%%%%%%%% OLD BAR PLOTS
# Plot the results
x = np.arange(len(data))
cmap = matplotlib.cm.get_cmap('Oranges')
norm = matplotlib.colors.Normalize(vmin=np.min(peak_infections_list), vmax=np.max(peak_infections_list))
color_list = []
for i in range(len(data)):
color_list.append(cmap(norm(data[i]['peak_infections'])))
width = 0.5
# %%
fig = plt.figure()
### PLOT PEAK INFECTIONS COMPARISON
ax1 = fig.add_subplot(111)
labels = []
for i in range(len(data)):
val = data[i]['peak_infections']
ax1.bar(i, val, width, edgecolor='black', facecolor=color_list[i], label=data[i]['description'])
labels = [
'0.01',
'0.02',
'0.04',
'0.08',
'0.20'
]
# ax1.set_title('Peak Infections', fontsize=fontsize)
ax1.set_ylabel('Peak Infections per 100,000 People')
ax1.set_xlabel('Economic Impact Parameter')
ax1.set_xticks(x)
ax1.set_xticklabels(labels)
ax1.tick_params(axis='both')
save_location = os.path.join(base_directory, 'plotting', 'tikz_plotting', city_name)
filename = os.path.join(save_location, 'different_cost_infections_comparison.tex')
tikzplotlib.save(filename)
# %%
fig = plt.figure()
### PLOT DEATHS COMPARISON
ax2 = fig.add_subplot(111)
cmap = matplotlib.cm.get_cmap('Oranges')
norm = matplotlib.colors.Normalize(vmin=np.min(num_deaths_list), vmax=np.max(num_deaths_list))
color_list = []
for i in range(len(data)):
color_list.append(cmap(norm(data[i]['num_deaths'])))
labels = []
for i in range(len(data)):
val = data[i]['num_deaths']
ax2.bar(i, val, width, edgecolor='black', facecolor=color_list[i], label=data[i]['description'])
labels = [
'0.01',
'0.02',
'0.04',
'0.08',
'0.20'
]
ax2.set_ylabel('Deaths per 100,000 People')
ax2.set_xlabel('Economic Impact Parameter')
ax2.set_xticks(x)
ax2.set_xticklabels(labels)
ax2.tick_params(axis='both')
save_location = os.path.join(base_directory, 'plotting', 'tikz_plotting', city_name)
filename = os.path.join(save_location, 'different_cost_deaths_comparison.tex')
tikzplotlib.save(filename)
# %%
# %%
fig = plt.figure()
### PLOT lockdown COMPARISON
ax3 = fig.add_subplot(111)
cmap = matplotlib.cm.get_cmap('Blues')
norm = matplotlib.colors.Normalize(vmin=np.min(average_lockdown_list), vmax=np.max(average_lockdown_list))
color_list = []
for i in range(len(data)):
color_list.append(cmap(norm(average_lockdown_list[i])))
labels = []
for i in range(len(data)):
val = average_lockdown_list[i]
ax3.bar(i, val, width, edgecolor='black', facecolor=color_list[i], label=data[i]['description'])
labels = [
'0.01',
'0.02',
'0.04',
'0.08',
'0.20'
]
ax3.set_ylabel('Average Lockdown')
ax3.set_xlabel('Economic Impact Parameter')
ax3.set_xticks(x)
ax3.set_xticklabels(labels)
ax3.tick_params(axis='both')
save_location = os.path.join(base_directory, 'plotting', 'tikz_plotting', city_name)
filename = os.path.join(save_location, 'different_cost_lockdown_comparison.tex')
tikzplotlib.save(filename)
# %%
| 240 | 31.5 | 126 | 15 | 2,440 | python | [{"finding_id": "semgrep_rules.python.lang.correctness.useless-eqeq_9ea6929026020bd5_1b5d97df", "tool_name": "semgrep", "rule_id": "rules.python.lang.correctness.useless-eqeq", "finding_type": "correctness", "severity": "low", "confidence": "medium", "message": "This expression is always True: `city_name == city_name` or `city_name != city_name`. If testing for floating point NaN, use `math.isnan(city_name)`, or `cmath.isnan(city_name)` if the number is complex.", "remediation": "", "location": {"file_path": "unknown", "line_start": 41, "line_end": 41, "column_start": 4, "column_end": 26, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 3.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.correctness.useless-eqeq", "path": "/tmp/tmpr7mo7ysm/9ea6929026020bd5.py", "start": {"line": 41, "col": 4, "offset": 1771}, "end": {"line": 41, "col": 26, "offset": 1793}, "extra": {"message": "This expression is always True: `city_name == city_name` or `city_name != city_name`. 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Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_9ea6929026020bd5_b386b9ad", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. 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"CWE-502",
"CWE-502"
] | [
"rules.python.lang.security.deserialization.avoid-pickle",
"rules.python.lang.security.deserialization.avoid-pickle"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | [
51,
67
] | [
51,
67
] | [
19,
18
] | [
33,
32
] | [
"A08:2017 - Insecure Deserialization",
"A08:2017 - Insecure Deserialization"
] | [
"Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.",
"Avoid using `pickle`, which is known to lead to... | [
5,
5
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | plot_different_cost_comparisons.py | /src/plotting/tikz_plotting/plot_different_cost_comparisons.py | cyrusneary/multiscaleLockdownCovid19 | MIT | |
2024-11-18T19:28:56.613046+00:00 | 1,468,576,532,000 | 9f881efdc6196e692394faee554b86e3a9e66f2f | 3 | {
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"visit_date": "2021-01-17T20:08:34.465622"
} | 2.71875 | stackv2 | import subprocess
import os
class PythonRunner:
def __init__(self, input_directory, algorithm_name):
self.algorithm_name = algorithm_name
self.python_file_name = self.algorithm_name + '.py'
self.input_directory = input_directory
def get_output(self, user_input):
p = subprocess.Popen(["python", os.path.join(self.input_directory, self.python_file_name)],
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE
)
out, err = p.communicate(input=bytes(user_input, 'utf-8'))
output = out.decode("utf-8")
return output
if __name__ == '__main__':
pass
| 25 | 29.08 | 99 | 14 | 142 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_de1a4ff701684d03_56482ac0", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 13, "line_end": 17, "column_start": 13, "column_end": 31, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/de1a4ff701684d03.py", "start": {"line": 13, "col": 13, "offset": 311}, "end": {"line": 17, "col": 31, "offset": 586}, "extra": {"message": "Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
13
] | [
17
] | [
13
] | [
31
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'Popen' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | python_runner.py | /python_runner.py | radzak/ResultChecker | MIT | |
2024-11-18T19:28:58.499789+00:00 | 1,603,100,319,000 | 08eaf9b37938a2a2c9c63ec50f6d67345ec2ada2 | 2 | {
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} | 2.421875 | stackv2 | import sqlite3
from settings import *
entry = sqlite3.connect(db_name)
cur = entry.cursor()
print('wrapper library imported.')
def fetch_ID(id):
res = cur.execute("""SELECT * FROM quotes WHERE msgID IS %s""" % id).fetchall()
res = [(i[0].replace(r';!;', r"'"), i[1].replace(r';!;', r"'"), i[2], i[3], i[4], i[5]) for i in res]
# print(res[0])
return res
def add_quote(msg_obj):
# reaction.message should be passed here
text, usr, msgID, usr_id = msg_obj.content, str(msg_obj.author), msg_obj.id, msg_obj.author.id
dateUTC, jumplink = msg_obj.created_at, msg_obj.jump_url
# print(fetch_ID(msgID))
if not fetch_ID(msgID):
cur.execute(
"""INSERT INTO quotes(content, author, msgID, authorID, date, jumplink) VALUES('%s', '%s', '%s', '%s', '%s', '%s')""" %
(text.replace(r"'", r";!;"), usr.replace(r"'", r";!;"), msgID, usr_id, dateUTC, jumplink))
entry.commit()
return True
else:
return False
def fecth_quote(tags=None):
# tags - list of strings1
if tags is None:
return cur.execute("""SELECT * FROM quotes""").fetchall()
tmp = []
for tag in tags:
tmp.append(r"content like '%{}%' ".format(tag))
request = ' OR '.join(tmp)
res = cur.execute("""SELECT * FROM quotes WHERE """ + request).fetchall()
res = [(i[0].replace(r';!;', r"'"), i[1].replace(r';!;', r"'"), i[2], i[3], i[4], i[5]) for i in res]
# print(res[0])
return res
def book_renderer(search='none', results=None, page=0):
if search == 'none' or search is None:
search = ['no tags in search', ]
tags_hud = '; '.join(search)
quotes_hud = ""
l, r = quotes_per_page * page, min((quotes_per_page * (page + 1)), len(results))
if l > len(results):
l = 0
pagelen = len(results) // quotes_per_page
pagelen = len(results)//quotes_per_page + int(len(results)/quotes_per_page > len(results)//quotes_per_page)
page_results = results[l:r]
for cur_quote in page_results:
author, text = cur_quote[1], cur_quote[0].replace('\n', '\t')
date, id = cur_quote[4][:16], cur_quote[2]
quote_hud = """> <o>=============<%s>=============<o> [msgID:%s]
> **%s** - %s\n""" % (date, id, author, text)
quotes_hud += quote_hud
if pagelen:
page_hud = "page %d from %d" % (page + 1, pagelen)
else:
page_hud = "no pages"
debug = """debug:
l, r: %d, %d
pagelen: %d
len(): %d
""" % (l, r, pagelen, len(results))
hull = """quote search for [%s]:
> [ %s ]
> quotes:
%s
%s""" % (tags_hud, page_hud, quotes_hud, debug)
if len(hull) > 2000:
return "unexpected 2k limit error on page %d" % page, pagelen
return hull, pagelen
def quote_del(id):
cur.execute("""DELETE FROM quotes WHERE msgID = '%s'""" % id)
entry.commit() | 92 | 30.02 | 131 | 14 | 869 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.formatted-sql-query_6639e67c6df60b25_bc32c700", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.formatted-sql-query", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Detected possible formatted SQL query. Use parameterized queries instead.", "remediation": "", "location": {"file_path": "unknown", "line_start": 12, "line_end": 12, "column_start": 11, "column_end": 73, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/775296/mysql-parameterized-queries", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.formatted-sql-query", "path": "/tmp/tmpr7mo7ysm/6639e67c6df60b25.py", "start": {"line": 12, "col": 11, "offset": 160}, "end": {"line": 12, "col": 73, "offset": 222}, "extra": {"message": "Detected possible formatted SQL query. Use parameterized queries instead.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')"], "references": ["https://stackoverflow.com/questions/775296/mysql-parameterized-queries"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query_6639e67c6df60b25_885509e7", "tool_name": "semgrep", "rule_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. In order to execute raw query safely, prepared statement should be used. SQLAlchemy provides TextualSQL to easily used prepared statement with named parameters. For complex SQL composition, use SQL Expression Language or Schema Definition Language. In most cases, SQLAlchemy ORM will be a better option.", "remediation": "", "location": {"file_path": "unknown", "line_start": 12, "line_end": 12, "column_start": 11, "column_end": 73, "code_snippet": "requires login"}, "cwe_id": "CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-textual-sql", "title": null}, {"url": "https://www.tutorialspoint.com/sqlalchemy/sqlalchemy_quick_guide.htm", "title": null}, {"url": "https://docs.sqlalchemy.org/en/14/core/tutorial.html#using-more-specific-text-with-table-expression-literal-column-and-expression-column", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.sqlalchemy.security.sqlalchemy-execute-raw-query", "path": "/tmp/tmpr7mo7ysm/6639e67c6df60b25.py", "start": {"line": 12, "col": 11, "offset": 160}, "end": {"line": 12, "col": 73, "offset": 222}, "extra": {"message": "Avoiding SQL string concatenation: untrusted input concatenated with raw SQL query can result in SQL Injection. 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} | 2.734375 | stackv2 | import logging
import os
import pkgutil
import re
import sys
from pathlib import Path
import attr
import jinja2
@attr.s
class Template(object):
"""Jinja-driven template for documentation.
Args:
filename (str): Path to Jinja template.
Attributes:
filename (str): Path to Jinja template.
text (str): Text of Jinja template.
"""
filename = attr.ib()
def __attrs_post_init__(self):
template_bytes = pkgutil.get_data('medsldocs', 'templates/{}'.format(self.filename))
self.text = template_bytes.decode('utf-8')
def write(self, data, dest='', strict=True):
"""Render a template and write the result to the disk.
Args:
data (dict): A mapping of template variables to values.
dest (str): Destination path (e.g., `./release-notes.md`).
strict (bool): Whether undefined template variables should result in an error. `True` by default because
our templates aren't written to handle this gracefully.
Returns:
str: The rendered template text.
"""
template = jinja2.Template(self.text, undefined=jinja2.StrictUndefined if strict else None)
rendered = template.render(data)
if dest:
Path(dest).resolve().write_text(rendered)
return rendered
@attr.s
class RdTemplate(Template):
"""Jinja-driven template for R documentation.
Args:
filename (str): Path to Jinja template.
Attributes:
filename (str): Path to Jinja template.
text (str): Text of Jinja template.
"""
def __attrs_post_init__(self):
module_dir = os.path.dirname(sys.modules['medsldocs'].__file__)
loader = jinja2.FileSystemLoader(searchpath=os.path.join(module_dir, 'templates'))
self.env = jinja2.Environment(loader=loader, block_start_string='<+', block_end_string='+>',
variable_start_string='<<', variable_end_string='>>', comment_start_string='<#',
comment_end_string='>#')
self.env.filters['r_alias'] = self._r_alias
self.env.filters['format_code'] = self._format_code
def write(self, data, dest='', strict=True):
"""Render a template and write the result to the disk.
Args:
data (dict): A mapping of template variables to values.
dest (str): Destination path (e.g., `./release-notes.md`).
strict (bool): Whether undefined template variables should result in an error. `True` by default because
our templates aren't written to handle this gracefully.
Returns:
str: The rendered template text.
"""
if strict:
self.env.undefined = jinja2.StrictUndefined
template = self.env.get_template(self.filename)
rendered = template.render(data)
if dest:
Path(dest).resolve().write_text(rendered)
return rendered
@staticmethod
def _r_alias(text: str) -> str:
"""Jinja filter for translating dataset names to valid R object names.
Example: '2016-precinct-house' -> 'house_precinct_2016'.
See http://jinja.pocoo.org/docs/2.10/api/#custom-filters.
"""
if text:
print(text)
no_dashes = re.sub('[- ]', '_', text)
return re.sub(r'([0-9]*)(_*)(.*)', '\g<3>\g<2>\g<1>', no_dashes)
else:
return ''
@staticmethod
def _format_code(text: str) -> str:
"""Jinja filter for translating Markdown code markup to Latex code markup.
Example: \`inline snippet\` -> \\code\{inline snippet\}.
See http://jinja.pocoo.org/docs/2.10/api/#custom-filters.
"""
if text:
return re.sub(r'`([^`]+)`', '\code{\g<1>}', text)
else:
return ''
@attr.s
class Readme(Template):
"""Jinja-driven template for GitHub repo READMEs.
Args:
filename (str): Path to Jinja template.
Attributes:
filename (str): Path to Jinja template.
text (str): Text of Jinja template.
"""
filename = attr.ib(default='precinct_repo_readme.jinja')
def __attrs_post_init__(self):
self.template = self.env.get_template(self.filename)
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} | 2.578125 | stackv2 | #!/usr/bin/python3
#coding=utf-8
from datetime import datetime
import itertools
import networkx as nx
import pickle
import math
from abstract_type import abstract_type
import sys
sys.path.append('..')
import insummer
from insummer.common_type import Question,Answer
from insummer.read_conf import config
from insummer.util import NLP
from insummer.query_expansion.entity_finder import NgramEntityFinder
#获得问题的路径信息
question_conf = config('../../conf/question.conf')
filter_path = question_conf['filter_qa']
duc_path = question_conf['duc_question']
filter_abstract = question_conf['filter_abstract']
duc_abstract = question_conf['duc_abstract']
#为了ROUGE要将每个topic分开存放到duc/sum_result中
textrank_path = question_conf['textrank_sum']
nlp = NLP()
#xx_quesiton里面即问题列表
filter_file = open(filter_path,'rb')
filter_quesiton = pickle.load(filter_file)
duc_file = open(duc_path,'rb')
duc_question = pickle.load(duc_file)
#single_question => nbest_content => top_k sents => abstract
def get_abstract(questions,q_path,K):
"根据问题list获得摘要list"
abstract_list = []
for idx,s_question in enumerate(questions):
print('处理第 %s 个问题'%idx)
start_time = datetime.now()
#获得标题和答案的文本，修改了commontype里面的get_nbest_content函数，返回以空格链接的答案
title = s_question.get_title()
answer_text = s_question.get_nbest_content()
#为每个答案创建一个摘要类，以标题和答案初始化
tmp_abstract = abstract_type(title,answer_text)
#对某一答案抽取topK个句子作为摘要，需改成限定词语数量。
abstract_text = ExtractSentence(answer_text,K)
#为了ROUGE，存放单个摘要，文件名用topic名D0701A etc.
filename = s_question.get_author()
if filename[-1] == '/':
filename = filename[:-1]
sum_path = textrank_path + filename
with open(sum_path,'w') as sum_file:
sum_file.write(abstract_text)
print('abstract for %s is wrote..'%filename)
sum_file.close()
#保存并添加到摘要list中，准备扔到pickle里
tmp_abstract.update_abstract(abstract_text)
abstract_list.append(tmp_abstract)
times = datetime.now() - start_time
print("text_length : %s used_time : %s \n abstract : %s"%(len(answer_text),times,abstract_text))
#将duc或者filter的所有问题和相应的摘要保存起来
out_file = open(q_path,'wb')
pickle.dump(abstract_list,out_file,True)
def filter_sent(sent_tokens,filter_val):
"根据句子中的实体数，筛选在构建图结构时，要保留的句子"
tmp_sents = []
for sent in sent_tokens:
finder = NgramEntityFinder(sent)
enti_tokens = finder.extract_entity()
if len(enti_tokens) >= filter_val:
tmp_sents.append(sent)
return tmp_sents
#text => sentences => graph => calculate => scores
def ExtractSentence(text,k):
"根据文本内容获得句子重要性排名"
print('开始句子重要性排名')
sent_tokens = nlp.sent_tokenize(text)
#可以加入限制条件，如果句子中的实体数少于阈值则放弃这个句子，等等，待扩展
sent_tokens = filter_sent(sent_tokens,1)
#建图结构
text_graph = graph_construct(sent_tokens)
#这里pagerank有三种，一种是正常的pg，一种是利用numpy还有一种就是下面的利用scipy的稀疏矩阵
print('start to calculate')
#cal_gr_page_rank = nx.pagerank(text_graph,weight='weight')
cal_gr_page_rank = nx.pagerank_scipy(text_graph)
print('ended')
#按照最后的score得分进行排序，获得前K个，待扩展，使之取不超250个词的句子
sents = sorted(cal_gr_page_rank,key = cal_gr_page_rank.get, reverse=True)
kth = get_sum_sents(sents,250)
#topK
str_tmp_list = []
for sidx in range(kth):
str_tmp = sents[sidx]
str_tmp += '[%.4f]'%(cal_gr_page_rank[sents[sidx]])
str_tmp_list.append(str_tmp)
print_score(str_tmp_list)
return ' '.join(sents[:kth])
def print_score(str_list):
for i in str_list:
print(i)
def get_sum_sents(sents,limit_num):
"对于按重要性排序的句子，获得不超过limit_num词数的尽量多的句子"
total_num = 0
idx = 0
while(total_num <= limit_num and idx < len(sents)):
total_num += len(nlp.word_tokenize(sents[idx]))
if (total_num > limit_num):
break
idx += 1
return idx
#实际运行时，发现整个构建图结构才是最耗时的阶段，可以在这上面优化时间复杂度
def graph_construct(nodes):
"构建text_rank_graph"
print('构建text_graph')
#利用networkx简历图结构，节点即传入的sentences
text_graph = nx.Graph()
text_graph.add_nodes_from(nodes)
#这里没有对边进行筛选，假设任意两个句子都是有相似性的
nodePairs = list(itertools.combinations(nodes,2))
for pair in nodePairs:
first_sent = pair[0]
second_sent= pair[1]
#weights = lDistance(first_sent,second_sent)
weights = sent_sim(first_sent,second_sent)
text_graph.add_edge(first_sent,second_sent,weight=weights)
print('graph construction end.')
return text_graph
#论文中提到的共现相似度，也可以用其他的方法，如lexrank中的词袋+余弦距离
def sent_sim(sent_1,sent_2):
sent_1_tokens = nlp.word_tokenize(sent_1)
sent_2_tokens = nlp.word_tokenize(sent_2)
#交集即为共现的词语
sim_set = set(sent_1_tokens) & set(sent_2_tokens)
num_up = len(sim_set)
num_down = math.log(len(sent_1_tokens)) + math.log(len(sent_2_tokens))
return num_up * 1. / num_down
'''
def lDistance(firstString, secondString):
"Function to find the Levenshtein distance between two words/sentences"
if len(firstString) > len(secondString):
firstString, secondString = secondString, firstString
distances = range(len(firstString) + 1)
for index2, char2 in enumerate(secondString):
newDistances = [index2 + 1]
for index1, char1 in enumerate(firstString):
if char1 == char2:
newDistances.append(distances[index1])
else:
newDistances.append(1 + min((distances[index1], distances[index1+1], newDistances[-1])))
distances = newDistances
return distances[-1]
'''
if __name__ == "__main__":
#get_abstract(filter_quesiton,filter_abstract,3)
get_abstract(duc_question,duc_abstract,3)
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] | text_rank.py | /code/statistic/text_rank.py | lavizhao/insummer | MIT | |
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} | 2.859375 | stackv2 | """
zipfix is a library for efficiently working with changes in git repositories.
It holds an in-memory copy of the object database and supports efficient
in-memory merges and rebases.
"""
from typing import Tuple, List, Optional
from argparse import ArgumentParser
from pathlib import Path
import subprocess
import tempfile
import textwrap
import sys
# Re-export primitives from the odb module to expose them at the root.
from .odb import MissingObject, Oid, Signature, GitObj, Commit, Mode, Entry, Tree, Blob
def commit_range(base: Commit, tip: Commit) -> List[Commit]:
"""Oldest-first iterator over the given commit range,
not including the commit |base|"""
commits = []
while tip != base:
commits.append(tip)
tip = tip.parent()
commits.reverse()
return commits
def run_editor(filename: str, text: bytes,
comments: Optional[str] = None,
allow_empty: bool = False) -> bytes:
"""Run the editor configured for git to edit the given text"""
with tempfile.TemporaryDirectory() as tmpdir:
path = Path(tmpdir) / filename
with open(path, 'wb') as f:
for line in text.splitlines():
f.write(line + b'\n')
if comments: # If comments were provided, write them after the text.
f.write(b'\n')
for comment in textwrap.dedent(comments).splitlines():
f.write(b'# ' + comment.encode('utf-8') + b'\n')
# Invoke the editor
proc = subprocess.run([
"bash", "-c", f"exec $(git var GIT_EDITOR) '{path}'"])
if proc.returncode != 0:
print("editor exited with a non-zero exit code", file=sys.stderr)
sys.exit(1)
# Read in all lines from the edited file.
lines = []
with open(path, 'rb') as of:
for line in of.readlines():
if comments and line.startswith(b'#'):
continue
lines.append(line)
# Concatenate parsed lines, stripping trailing newlines.
data = b''.join(lines).rstrip() + b'\n'
if data == b'\n' and not allow_empty:
print("empty file - aborting", file=sys.stderr)
sys.exit(1)
return data
def parser() -> ArgumentParser:
parser = ArgumentParser(description='''\
Rebase staged changes onto the given commit, and rewrite history to
incorporate these changes.''')
parser.add_argument('target', help='target commit to apply fixups to')
parser.add_argument('--ref', default='HEAD', help='reference to update')
parser.add_argument('--no-index', action='store_true',
help='ignore the index while rewriting history')
parser.add_argument('--reauthor', action='store_true',
help='reset the author of the targeted commit')
msg_group = parser.add_mutually_exclusive_group()
msg_group.add_argument('--edit', '-e', action='store_true',
help='edit commit message of targeted commit')
msg_group.add_argument('--message', '-m', action='append',
help='specify commit message on command line')
return parser
def main(argv):
args = parser().parse_args(argv)
final = head = Commit.get(args.ref)
current = replaced = Commit.get(args.target)
to_rebase = commit_range(current, head)
# If --no-index was not supplied, apply staged changes to the target.
if not args.no_index:
print(f"Applying staged changes to '{args.target}'")
final = Commit.from_index(b"git index")
current = current.update(tree=final.rebase(current).tree())
# Update the commit message on the target commit if requested.
if args.message:
message = b'\n'.join(l.encode('utf-8') + b'\n' for l in args.message)
current = current.update(message=message)
# Prompt the user to edit the commit message if requested.
if args.edit:
message = run_editor('COMMIT_EDITMSG', current.message, comments="""\
Please enter the commit message for your changes. Lines starting
with '#' will be ignored, and an empty message aborts the commit.
""")
current = current.update(message=message)
# Rewrite the author to match the current user if requested.
if args.reauthor:
current = current.update(author=Signature.default_author())
if current != replaced:
# Rebase commits atop the commit range.
for idx, commit in enumerate(to_rebase):
print(f"Reparenting commit {idx + 1}/{len(to_rebase)}: {commit.oid}")
current = commit.rebase(current)
# Update the HEAD commit to point to the new value.
print(f"Updating {args.ref} ({head.oid} => {current.oid})")
current.update_ref(args.ref, "git-zipfix rewrite", head.oid)
# We expect our tree to match the tree we started with (including index
# changes). If it does not, print out a warning.
if current.tree() != final.tree():
print("(warning) unexpected final tree\n"
f"(note) expected: {final.tree().oid}\n"
f"(note) actual: {current.tree().oid}\n"
"(note) working directory & index have not been updated.\n"
"(note) use `git status` to see what has changed.",
file=sys.stderr)
sys.exit(1)
| 136 | 39.17 | 87 | 20 | 1,189 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_3f22d7ad20e7df27_8b78f330", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 46, "line_end": 47, "column_start": 16, "column_end": 67, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/3f22d7ad20e7df27.py", "start": {"line": 46, "col": 16, "offset": 1524}, "end": {"line": 47, "col": 67, "offset": 1607}, "extra": {"message": "Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-78"
] | [
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] | [
"security"
] | [
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] | [
"HIGH"
] | [
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] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | __init__.py | /zipfix/__init__.py | emilio/git-zipfix | MIT | |
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"visit_date": "2023-07-20T15:27:26.420794"
} | 2.6875 | stackv2 | import os, sys, subprocess, random, uuid
class Plopper:
def __init__(self,sourcefile,outputdir):
# Initializing global variables
self.sourcefile = sourcefile
self.outputdir = outputdir+"/tmp_files"
if not os.path.exists(self.outputdir):
os.makedirs(self.outputdir)
#Creating a dictionary using parameter label and value
def createDict(self, x, params):
dictVal = {}
for p, v in zip(params, x):
dictVal[p] = v
return(dictVal)
# Function to find the execution time of the interim file, and return the execution time as cost to the search module
def findRuntime(self, x, params):
interimfile = ""
exetime = 1
# Generate intermediate file
dictVal = self.createDict(x, params)
#compile and find the execution time
tmpbinary = self.outputdir + '/tmp_'+str(uuid.uuid4())+'.bin'
kernel_idx = self.sourcefile.rfind('/')
kernel_dir = self.sourcefile[:kernel_idx]
gcc_cmd = 'g++ ' + kernel_dir +'/mmm_block.cpp '
gcc_cmd += ' -D{0}={1}'.format('BLOCK_SIZE', dictVal['BLOCK_SIZE'])
gcc_cmd += ' -o ' + tmpbinary
run_cmd = kernel_dir + "/exe.pl " + tmpbinary
#Find the compilation status using subprocess
compilation_status = subprocess.run(gcc_cmd, shell=True, stderr=subprocess.PIPE)
#Find the execution time only when the compilation return code is zero, else return infinity
if compilation_status.returncode == 0 :
execution_status = subprocess.run(run_cmd, shell=True, stdout=subprocess.PIPE)
exetime = float(execution_status.stdout.decode('utf-8'))
if exetime == 0:
exetime = 1
else:
print(compilation_status.stderr)
print("compile failed")
return exetime #return execution time as cost
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This is dangerous because this call will spawn the command using a shell process. Doing so propagates current shell settings and variables, which makes it much easier for a malicious actor to execute commands. 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] | plopper.py | /ytopt/benchmark/mmm-block/plopper/plopper.py | ytopt-team/ytopt | BSD-2-Clause | |
2024-11-18T19:39:36.977527+00:00 | 1,368,396,177,000 | 4d3c05ae00dc998920f9c0845717fa0b60c7ed92 | 2 | {
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} | 2.40625 | stackv2 | import cPickle, logging, multiprocessing, os, Queue, redis, string, threading
from apscheduler.scheduler import Scheduler
from datetime import datetime, timedelta
from PlanetLabNode import PlanetLabNode
from utilities import outputException, distance
import argparse
parser = argparse.ArgumentParser(description='Tking Controller')
parser.add_argument('--max', default=None, type=int, help='Set a Maximum Distance between targets')
parser.add_argument('--min', default=0, type=int, help='Set a Minimum Distance between targets')
args = parser.parse_args()
round_length = 20
time_limit = 110.0
num_processes = 90
num_threads = 30
all_dns = redis.Redis(connection_pool=redis.ConnectionPool(host='localhost', port=6379, db=0))
open_resolvers = redis.Redis(connection_pool=redis.ConnectionPool(host='localhost', port=6379, db=1))
geoip = redis.Redis(connection_pool=redis.ConnectionPool(host='localhost', port=6379, db=2))
pl_hosts = [line.split(' ')[0:4] for line in map(string.strip,open('pl-host-list-geo').readlines())]
pl_nodes = map(lambda args: PlanetLabNode(*args), pl_hosts)
def select_random_points():
target1 = open_resolvers.randomkey()
target2 = open_resolvers.randomkey()
while not geoip.exists(target1):
target1 = open_resolvers.randomkey()
while not geoip.exists(target2):
target2 = open_resolvers.randomkey()
ip1, coord1 = list(all_dns.smembers(target1))[0], eval(list(geoip.smembers(target1))[0])[1:]
ip2, coord2 = list(all_dns.smembers(target2))[0], eval(list(geoip.smembers(target2))[0])[1:]
return (target1, ip1, coord1), (target2, ip2, coord2)
def closestNodes(target):
name1, ip1, coord1 = target
# Get closest 10 PL Nodes
distances = map(lambda node: (distance(coord1, (node.lat, node.lon)), node), pl_nodes)
distances.sort()
distances = map(lambda x: x[1], distances)
return distances[:10]
def query_latency(target1, target2, node):
name1, ip1, coord1 = target1
name2, ip2, coord2 = target2
return cPickle.loads(node.get_latency(name1, ip1, name2, ip2))
def perThread(queue):
from DataPoint import DataPoint, Session
session = Session()
while True:
try:
target1, target2, node = queue.get()
#print target1, target2, node
result = query_latency(target1, target2, node)
success = False
if result:
end_time, start_time, ping_times, address = result
if end_time and start_time and ping_times and address:
success = True
else:
end_time = start_time = ping_times = address = None
point = DataPoint(target1[0], target2[0], target1, target2, start_time, end_time, ping_times, address, node.host, success)
while True:
try:
session.add(point)
session.commit()
break
except Exception, e:
print e
session.close()
session = Session()
except Exception, e:
outputException(e)
# TODO: Store None Responses As Well
def perProcess():
thread_queue = Queue.Queue(num_threads)
threads = []
for i in range(num_threads):
t = threading.Thread(target=perThread, args=(thread_queue,))
t.daemon = True
t.start()
threads.append(t)
for i in range(round_length):
while True:
t1, t2 = select_random_points()
dist = distance(t1[2], t2[2])
if args.max and dist > args.max:
continue
elif dist <= args.min:
continue
else:
break
closest_nodes1 = closestNodes(t1)
closest_nodes2 = closestNodes(t2)
for node in closest_nodes1:
thread_queue.put((t1, t2, node))
for node in closest_nodes2:
thread_queue.put((t2, t1, node))
def main():
print 'Start:', datetime.now()
processes = []
for i in range(num_processes):
p = multiprocessing.Process(target=perProcess)
p.daemon = True
p.start()
processes.append(p)
for p in processes:
p.join(time_limit/num_processes)
print '\nEnd:', datetime.now()
main()
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Ensure evaluated content is not definable by external sources.", "metadata": {"source-rule-url": "https://bandit.readthedocs.io/en/latest/blacklists/blacklist_calls.html#b307-eval", "cwe": ["CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')"], "owasp": ["A03:2021 - Injection", "A05:2025 - Injection"], "asvs": {"control_id": "5.2.4 Dyanmic Code Execution Features", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v52-sanitization-and-sandboxing-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "category": "security", "technology": ["python"], "references": ["https://owasp.org/Top10/A03_2021-Injection"], "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-cPickle_deef89c98b9d1385_40c124f3", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-cPickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `cPickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 50, "line_end": 50, "column_start": 12, "column_end": 67, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-cPickle", "path": "/tmp/tmpr7mo7ysm/deef89c98b9d1385.py", "start": {"line": 50, "col": 12, "offset": 2009}, "end": {"line": 50, "col": 67, "offset": 2064}, "extra": {"message": "Avoid using `cPickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 5 | true | [
"CWE-95",
"CWE-95",
"CWE-502"
] | [
"rules.python.lang.security.audit.eval-detected",
"rules.python.lang.security.audit.eval-detected",
"rules.python.lang.security.deserialization.avoid-cPickle"
] | [
"security",
"security",
"security"
] | [
"LOW",
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM",
"MEDIUM"
] | [
34,
35,
50
] | [
34,
35,
50
] | [
55,
55,
12
] | [
93,
93,
67
] | [
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"A03:2021 - Injection",
"A08:2017 - Insecure Deserialization"
] | [
"Detected the use of eval(). eval() can be dangerous if used to evaluate dynamic content. If this content can be input from outside the program, this may be a code injection vulnerability. Ensure evaluated content is not definable by external sources.",
"Detected the use of eval(). eval() can be dangerous if used... | [
5,
5,
5
] | [
"LOW",
"LOW",
"LOW"
] | [
"HIGH",
"HIGH",
"MEDIUM"
] | controller.py | /king/controller.py | nebgnahz/CS268NetworkMeasurement | BSD-2-Clause | |
2024-11-18T19:39:46.964162+00:00 | 1,497,492,721,000 | 0f9b6bfe8a27e5dcf9e60f933c59d1b2c98e8231 | 2 | {
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"visit_date": "2021-01-20T02:41:22.924078"
} | 2.421875 | stackv2 | import subprocess
import os
from .settings import Settings
class ShellCommand:
def __init__(self, args):
self.__args = args
self.__startup_info = None
self.__shell = False
if os.name == 'nt':
self.__startup_info = subprocess.STARTUPINFO()
self.__startup_info.dwFlags |= subprocess.STARTF_USESHOWWINDOW
self.__startup_info.wShowWindow = subprocess.SW_HIDE
self.__shell = True
@property
def args(self):
return self.__args
@staticmethod
def env():
path = os.pathsep.join(Settings.paths())
env = os.environ.copy()
env['PATH'] = path + os.pathsep + env['PATH']
return env
def run(self, input):
process = subprocess.Popen(
self.args,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
startupinfo=self.__startup_info,
shell=self.__shell,
env=self.env(),
universal_newlines=True)
stdout, stderr = process.communicate(input=input)
ok = process.returncode == 0
return ok, stdout, stderr
| 40 | 28.38 | 74 | 13 | 248 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_21463b8d4b886ba1_68632b2c", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'STARTUPINFO' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. 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"CWE-78",
"CWE-78"
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"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | [
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29
] | [
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35,
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] | [
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"Detected subprocess... | [
7.5,
7.5
] | [
"LOW",
"LOW"
] | [
"HIGH",
"HIGH"
] | command.py | /plugin/command.py | andykingking/sublime-format | MIT | |
2024-11-18T19:39:52.923725+00:00 | 1,692,828,071,000 | e4cc582229b6fa327be9064fd628450ce99bbd21 | 3 | {
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} | 2.625 | stackv2 | #!/usr/bin/env python3
# Copyright 2013 The Chromium Authors
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
description = """
Make a symlink and optionally touch a file (to handle dependencies).
"""
usage = "%prog [options] source[ source ...] linkname"
epilog = """\
A symlink to source is created at linkname. If multiple sources are specified,
then linkname is assumed to be a directory, and will contain all the links to
the sources (basenames identical to their source).
On Windows, this will use hard links (mklink /H) to avoid requiring elevation.
This means that if the original is deleted and replaced, the link will still
have the old contents.
"""
import errno
import optparse
import os.path
import shutil
import subprocess
import sys
def Main(argv):
parser = optparse.OptionParser(usage=usage, description=description,
epilog=epilog)
parser.add_option('-f', '--force', action='store_true')
parser.add_option('--touch')
options, args = parser.parse_args(argv[1:])
if len(args) < 2:
parser.error('at least two arguments required.')
target = args[-1]
sources = args[:-1]
for s in sources:
t = os.path.join(target, os.path.basename(s))
if len(sources) == 1 and not os.path.isdir(target):
t = target
t = os.path.expanduser(t)
if os.path.realpath(t) == os.path.realpath(s):
continue
try:
# N.B. Python 2.x does not have os.symlink for Windows.
# Python 3 has os.symlink for Windows, but requires either the admin-
# granted privilege SeCreateSymbolicLinkPrivilege or, as of Windows 10
# 1703, that Developer Mode be enabled. Hard links and junctions do not
# require any extra privileges to create.
if os.name == 'nt':
# mklink does not tolerate /-delimited path names.
t = t.replace('/', '\\')
s = s.replace('/', '\\')
# N.B. This tool only handles file hardlinks, not directory junctions.
subprocess.check_output(['cmd.exe', '/c', 'mklink', '/H', t, s],
stderr=subprocess.STDOUT)
else:
os.symlink(s, t)
except OSError as e:
if e.errno == errno.EEXIST and options.force:
if os.path.isdir(t):
shutil.rmtree(t, ignore_errors=True)
else:
os.remove(t)
os.symlink(s, t)
else:
raise
except subprocess.CalledProcessError as e:
# Since subprocess.check_output does not return an easily checked error
# number, in the 'force' case always assume it is 'file already exists'
# and retry.
if options.force:
if os.path.isdir(t):
shutil.rmtree(t, ignore_errors=True)
else:
os.remove(t)
subprocess.check_output(e.cmd, stderr=subprocess.STDOUT)
else:
raise
if options.touch:
os.makedirs(os.path.dirname(options.touch), exist_ok=True)
with open(options.touch, 'w'):
pass
if __name__ == '__main__':
sys.exit(Main(sys.argv))
| 92 | 32.33 | 79 | 17 | 731 | python | [{"finding_id": "semgrep_rules.python.lang.security.audit.dangerous-subprocess-use-audit_6870e2749a8a867a_a9d3dc83", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "finding_type": "security", "severity": "high", "confidence": "low", "message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "remediation": "", "location": {"file_path": "unknown", "line_start": 80, "line_end": 80, "column_start": 9, "column_end": 65, "code_snippet": "requires login"}, "cwe_id": "CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')", "cwe_name": null, "cvss_score": 7.5, "cvss_vector": null, "owasp_category": "A01:2017 - Injection", "references": [{"url": "https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "title": null}, {"url": "https://docs.python.org/3/library/subprocess.html", "title": null}, {"url": "https://docs.python.org/3/library/shlex.html", "title": null}, {"url": "https://semgrep.dev/docs/cheat-sheets/python-command-injection/", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.audit.dangerous-subprocess-use-audit", "path": "/tmp/tmpr7mo7ysm/6870e2749a8a867a.py", "start": {"line": 80, "col": 9, "offset": 2796}, "end": {"line": 80, "col": 65, "offset": 2852}, "extra": {"message": "Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'.", "metadata": {"owasp": ["A01:2017 - Injection", "A03:2021 - Injection", "A05:2025 - Injection"], "cwe": ["CWE-78: Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')"], "asvs": {"control_id": "5.3.8 OS Command Injection", "control_url": "https://github.com/OWASP/ASVS/blob/master/4.0/en/0x13-V5-Validation-Sanitization-Encoding.md#v53-output-encoding-and-injection-prevention-requirements", "section": "V5: Validation, Sanitization and Encoding Verification Requirements", "version": "4"}, "references": ["https://stackoverflow.com/questions/3172470/actual-meaning-of-shell-true-in-subprocess", "https://docs.python.org/3/library/subprocess.html", "https://docs.python.org/3/library/shlex.html", "https://semgrep.dev/docs/cheat-sheets/python-command-injection/"], "category": "security", "technology": ["python"], "confidence": "LOW", "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "HIGH"}, "severity": "ERROR", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_6870e2749a8a867a_e2029379", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "remediation": "", "location": {"file_path": "unknown", "line_start": 87, "line_end": 87, "column_start": 10, "column_end": 34, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [{"url": "https://www.python.org/dev/peps/pep-0597/", "title": null}, {"url": "https://docs.python.org/3/library/functions.html#open", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.best-practice.unspecified-open-encoding", "path": "/tmp/tmpr7mo7ysm/6870e2749a8a867a.py", "start": {"line": 87, "col": 10, "offset": 2973}, "end": {"line": 87, "col": 34, "offset": 2997}, "extra": {"message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 2 | true | [
"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
80
] | [
80
] | [
9
] | [
65
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'check_output' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | symlink.py | /build/symlink.py | chromium/chromium | BSD-3-Clause | |
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"visit_date": "2020-09-26T05:25:44.059755"
} | 2.78125 | stackv2 | #!/usr/bin/env python3
import argparse
import statistics
import os
import sys
import subprocess
from typing import Optional, Iterator, Iterable, Tuple, List
def get_commits_list(
repo_path: str,
author: Optional[str] = None,
after: Optional[str] = None,
rev_list_args: Optional[str] = None,
) -> Iterator[str]:
args = []
if author:
args.append("--author={:s}".format(author))
if after:
args.append("--after={:s}".format(after))
if rev_list_args:
args.extend(rev_list_args.split())
result = subprocess.run(
["git", "rev-list"] + args + ["HEAD"],
cwd=os.path.abspath(repo_path),
stdout=subprocess.PIPE,
)
return filter(None, result.stdout.decode("utf-8").split("\n"))
def get_commit_message(repo_path: str, revision: str) -> str:
result = subprocess.run(
["git", "show", "--no-patch", "--format=%B", revision],
cwd=os.path.abspath(repo_path),
stdout=subprocess.PIPE,
)
return result.stdout.decode("utf-8").strip()
def get_length_stats(
repo_paths: Iterable[str],
author: Optional[str] = None,
after: Optional[str] = None,
rev_list_args: Optional[str] = None,
) -> Tuple[int, int, int, float, float]:
messages = (
get_commit_message(repo, revision)
for repo in repo_paths
for revision in get_commits_list(repo, author, after, rev_list_args)
)
lengths = [len(m) for m in messages]
return (
len(lengths),
min(lengths),
max(lengths),
statistics.median(lengths),
statistics.mean(lengths),
)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Get git commit message stats.")
parser.add_argument(
"--author", type=str, default="", required=False, help="author email"
)
parser.add_argument(
"--after", type=str, default="", required=False, help="after timestamp"
)
parser.add_argument(
"--rev-list-args",
type=str,
default="",
required=False,
help="any further arguments for git rev-list",
)
parser.add_argument("repo_paths", type=str, nargs="+", help="path to the repos")
args = parser.parse_args(sys.argv[1:])
total_num, min_length, max_length, median, mean = get_length_stats(
args.repo_paths, args.author, args.after, args.rev_list_args
)
print("Commit message stats:")
print(" total number of commits: {:4d}".format(total_num))
print(" min length: {:4d}".format(min_length))
print(" median length: {:7.2f}".format(median))
print(" mean length: {:7.2f}".format(mean))
print(" max length: {:4d}".format(max_length))
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"CWE-78"
] | [
"rules.python.lang.security.audit.dangerous-subprocess-use-audit"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
24
] | [
28
] | [
14
] | [
6
] | [
"A01:2017 - Injection"
] | [
"Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'."
] | [
7.5
] | [
"LOW"
] | [
"HIGH"
] | message_stats.py | /message_stats.py | mp4096/git-achievements | MIT | |
2024-11-18T19:39:56.571115+00:00 | 1,398,650,275,000 | a0ac897955bc88f75ce1145877d9d70d72619a01 | 3 | {
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"detected_licenses": [
"Apache-2.0"
],
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"extension": "py",
"filename": "hierarchy_config.py",
"fork_events_count": 0,
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"gha_event_created_at": null,
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"github_id": null,
"is_generated": false,
"is_vendor": false,
"language": "Python",
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"license": "Apache-2.0",
"license_type": "permissive",
"path": "/user-interface/src/ConfigUtil/hierarchy_config.py",
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"repo_name": "linmichaelj/avalanche",
"revision_date": 1398650275000,
"revision_id": "727776b5fdfcad9345dd23be90fdf5e1fb2876c8",
"snapshot_id": "94f6987d2e8fcd64de86f97960d82a6092573949",
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"star_events_count": 0,
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"visit_date": "2020-06-12T11:25:04.810559"
} | 2.515625 | stackv2 | from ConfigUtil import config_util
__author__ = 'michaellin'
import xml.etree.ElementTree as ET
class HierarchyConfig:
def __init__(self, file_name, repeated_tag):
self.config_map = {}
self.file_name = file_name
self.repeated_tag = repeated_tag
def write_to_file(self):
if not self.is_valid():
print 'Validation Exception Occurred'
return
f = open(self.file_name, 'w')
f.write(self.get_xml())
f.close()
def load_from_file(self):
f = open(self.file_name, 'r')
root = ET.fromstring(f.read())
self.config_map = config_util.xml_to_hierarchy(root, self.repeated_tag)
if not self.is_valid():
print 'Validation Exception Ocurred'
self.alias_list = {}
return
f.close()
def get_xml(self):
config_elem = ET.Element('config')
config_util.hierarchy_to_xml(config_elem, self.config_map)
return config_util.format_url(config_elem)
#Abstract Methods is_valid, add_config
| 40 | 25.68 | 79 | 12 | 234 | python | [{"finding_id": "semgrep_rules.python.lang.security.use-defused-xml_d246e5e03149b16a_d36b8c5b", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.use-defused-xml", "finding_type": "security", "severity": "high", "confidence": "low", "message": "The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. 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"CWE-611"
] | [
"rules.python.lang.security.use-defused-xml"
] | [
"security"
] | [
"LOW"
] | [
"HIGH"
] | [
5
] | [
5
] | [
1
] | [
35
] | [
"A04:2017 - XML External Entities (XXE)"
] | [
"The Python documentation recommends using `defusedxml` instead of `xml` because the native Python `xml` library is vulnerable to XML External Entity (XXE) attacks. These attacks can leak confidential data and \"XML bombs\" can cause denial of service."
] | [
7.5
] | [
"LOW"
] | [
"MEDIUM"
] | hierarchy_config.py | /user-interface/src/ConfigUtil/hierarchy_config.py | linmichaelj/avalanche | Apache-2.0 | |
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} | 2.78125 | stackv2 | import numpy as np
import os
import pickle
NUM_LABELS = {'ENZYMES':3, 'COLLAB':0, 'IMDBBINARY':0, 'IMDBMULTI':0, 'MUTAG':7, 'NCI1':37, 'NCI109':38, 'PROTEINS':3, 'PTC':22, 'DD':89}
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
def load_dataset(ds_name):
"""
construct graphs and labels from dataset text in data folder
:param ds_name: name of data set you want to load
:return: two numpy arrays of shape (num_of_graphs).
the graphs array contains in each entry a ndarray represent adjacency matrix of a graph of shape (num_vertex, num_vertex, num_vertex_labels)
the labels array in index i represent the class of graphs[i]
"""
directory = BASE_DIR + "/data/benchmark_graphs/{0}/{0}.txt".format(ds_name)
graphs = []
labels = []
with open(directory, "r") as data:
num_graphs = int(data.readline().rstrip().split(" ")[0])
for i in range(num_graphs):
graph_meta = data.readline().rstrip().split(" ")
num_vertex = int(graph_meta[0])
curr_graph = np.zeros(shape=(num_vertex, num_vertex, NUM_LABELS[ds_name]+1), dtype=np.float32)
labels.append(int(graph_meta[1]))
for j in range(num_vertex):
vertex = data.readline().rstrip().split(" ")
if NUM_LABELS[ds_name] != 0:
curr_graph[j, j, int(vertex[0])+1]= 1.
for k in range(2,len(vertex)):
curr_graph[j, int(vertex[k]), 0] = 1.
curr_graph = noramlize_graph(curr_graph)
graphs.append(curr_graph)
graphs = np.array(graphs)
for i in range(graphs.shape[0]):
graphs[i] = np.transpose(graphs[i], [2,0,1])
return graphs, np.array(labels)
def load_qm9(target_param):
"""
Constructs the graphs and labels of QM9 data set, already split to train, val and test sets
:return: 6 numpy arrays:
train_graphs: N_train,
train_labels: N_train x 12, (or Nx1 is target_param is not False)
val_graphs: N_val,
val_labels: N_train x 12, (or Nx1 is target_param is not False)
test_graphs: N_test,
test_labels: N_test x 12, (or Nx1 is target_param is not False)
each graph of shape: 19 x Nodes x Nodes (CHW representation)
"""
train_graphs, train_labels = load_qm9_aux('train', target_param)
val_graphs, val_labels = load_qm9_aux('val', target_param)
test_graphs, test_labels = load_qm9_aux('test', target_param)
return train_graphs, train_labels, val_graphs, val_labels, test_graphs, test_labels
def load_qm9_aux(which_set, target_param):
"""
Read and construct the graphs and labels of QM9 data set, already split to train, val and test sets
:param which_set: 'test', 'train' or 'val'
:param target_param: if not false, return the labels for this specific param only
:return: graphs: (N,)
labels: N x 12, (or Nx1 is target_param is not False)
each graph of shape: 19 x Nodes x Nodes (CHW representation)
"""
base_path = BASE_DIR + "/data/QM9/QM9_{}.p".format(which_set)
graphs, labels = [], []
with open(base_path, 'rb') as f:
data = pickle.load(f)
for instance in data:
labels.append(instance['y'])
nodes_num = instance['usable_features']['x'].shape[0]
graph = np.empty((nodes_num, nodes_num, 19))
for i in range(13):
# 13 features per node - for each, create a diag matrix of it as a feature
graph[:, :, i] = np.diag(instance['usable_features']['x'][:, i])
graph[:, :, 13] = instance['usable_features']['distance_mat']
graph[:, :, 14] = instance['usable_features']['affinity']
graph[:, :, 15:] = instance['usable_features']['edge_features'] # shape n x n x 4
graphs.append(graph)
graphs = np.array(graphs)
for i in range(graphs.shape[0]):
graphs[i] = np.transpose(graphs[i], [2, 0, 1])
labels = np.array(labels).squeeze() # shape N x 12
if target_param is not False: # regression over a specific target, not all 12 elements
labels = labels[:, target_param].reshape(-1, 1) # shape N x 1
return graphs, labels
def get_train_val_indexes(num_val, ds_name):
"""
reads the indexes of a specific split to train and validation sets from data folder
:param num_val: number of the split
:param ds_name: name of data set
:return: indexes of the train and test graphs
"""
directory = BASE_DIR + "/data/benchmark_graphs/{0}/10fold_idx".format(ds_name)
train_file = "train_idx-{0}.txt".format(num_val)
train_idx=[]
with open(os.path.join(directory, train_file), 'r') as file:
for line in file:
train_idx.append(int(line.rstrip()))
test_file = "test_idx-{0}.txt".format(num_val)
test_idx = []
with open(os.path.join(directory, test_file), 'r') as file:
for line in file:
test_idx.append(int(line.rstrip()))
return train_idx, test_idx
def get_parameter_split(ds_name):
"""
reads the indexes of a specific split to train and validation sets from data folder
:param ds_name: name of data set
:return: indexes of the train and test graphs
"""
directory = BASE_DIR + "/data/benchmark_graphs/{0}/".format(ds_name)
train_file = "tests_train_split.txt"
train_idx=[]
with open(os.path.join(directory, train_file), 'r') as file:
for line in file:
train_idx.append(int(line.rstrip()))
test_file = "tests_val_split.txt"
test_idx = []
with open(os.path.join(directory, test_file), 'r') as file:
for line in file:
test_idx.append(int(line.rstrip()))
return train_idx, test_idx
def group_same_size(graphs, labels):
"""
group graphs of same size to same array
:param graphs: numpy array of shape (num_of_graphs) of numpy arrays of graphs adjacency matrix
:param labels: numpy array of labels
:return: two numpy arrays. graphs arrays in the shape (num of different size graphs) where each entry is a numpy array
in the shape (number of graphs with this size, num vertex, num. vertex, num vertex labels)
the second arrayy is labels with correspons shape
"""
sizes = list(map(lambda t: t.shape[1], graphs))
indexes = np.argsort(sizes)
graphs = graphs[indexes]
labels = labels[indexes]
r_graphs = []
r_labels = []
one_size = []
start = 0
size = graphs[0].shape[1]
for i in range(len(graphs)):
if graphs[i].shape[1] == size:
one_size.append(np.expand_dims(graphs[i], axis=0))
else:
r_graphs.append(np.concatenate(one_size, axis=0))
r_labels.append(np.array(labels[start:i]))
start = i
one_size = []
size = graphs[i].shape[1]
one_size.append(np.expand_dims(graphs[i], axis=0))
r_graphs.append(np.concatenate(one_size, axis=0))
r_labels.append(np.array(labels[start:]))
return r_graphs, r_labels
# helper method to shuffle each same size graphs array
def shuffle_same_size(graphs, labels):
r_graphs, r_labels = [], []
for i in range(len(labels)):
curr_graph, curr_labels = shuffle(graphs[i], labels[i])
r_graphs.append(curr_graph)
r_labels.append(curr_labels)
return r_graphs, r_labels
def split_to_batches(graphs, labels, size):
"""
split the same size graphs array to batches of specified size
last batch is in size num_of_graphs_this_size % size
:param graphs: array of arrays of same size graphs
:param labels: the corresponding labels of the graphs
:param size: batch size
:return: two arrays. graphs array of arrays in size (batch, num vertex, num vertex. num vertex labels)
corresponds labels
"""
r_graphs = []
r_labels = []
for k in range(len(graphs)):
r_graphs = r_graphs + np.split(graphs[k], [j for j in range(size, graphs[k].shape[0], size)])
r_labels = r_labels + np.split(labels[k], [j for j in range(size, labels[k].shape[0], size)])
# Avoid bug for batch_size=1, where instead of creating numpy array of objects, we had numpy array of floats with
# different sizes - could not reshape
ret1, ret2 = np.empty(len(r_graphs), dtype=object), np.empty(len(r_labels), dtype=object)
ret1[:] = r_graphs
ret2[:] = r_labels
return ret1, ret2
# helper method to shuffle the same way graphs and labels arrays
def shuffle(graphs, labels):
shf = np.arange(labels.shape[0], dtype=np.int32)
np.random.shuffle(shf)
return np.array(graphs)[shf], labels[shf]
def noramlize_graph(curr_graph):
split = np.split(curr_graph, [1], axis=2)
adj = np.squeeze(split[0], axis=2)
deg = np.sqrt(np.sum(adj, 0))
deg = np.divide(1., deg, out=np.zeros_like(deg), where=deg!=0)
normal = np.diag(deg)
norm_adj = np.expand_dims(np.matmul(np.matmul(normal, adj), normal), axis=2)
ones = np.ones(shape=(curr_graph.shape[0], curr_graph.shape[1], curr_graph.shape[2]), dtype=np.float32)
spred_adj = np.multiply(ones, norm_adj)
labels= np.append(np.zeros(shape=(curr_graph.shape[0], curr_graph.shape[1], 1)), split[1], axis=2)
return np.add(spred_adj, labels)
if __name__ == '__main__':
graphs, labels = load_dataset("MUTAG")
a, b = get_train_val_indexes(1, "MUTAG")
print(np.transpose(graphs[a[0]], [1, 2, 0])[0])
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} | 2.421875 | stackv2 | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""Notebooklet base classes."""
from pathlib import Path
from typing import Any, Dict, List, Optional, Set, Tuple, Union
import attr
import yaml
from attr import Factory
from ._version import VERSION
__version__ = VERSION
__author__ = "Ian Hellen"
@attr.s(auto_attribs=True)
class NBMetadata:
"""Notebooklet metadata class."""
name: str = "Unnamed"
mod_name: str = ""
description: str = ""
default_options: List[Union[str, Dict]] = Factory(list)
other_options: List[Union[str, Dict]] = Factory(list)
inputs: List[str] = ["value"]
entity_types: List[str] = Factory(list)
keywords: List[str] = Factory(list)
req_providers: List[str] = Factory(list)
# pylint: disable=not-an-iterable
@property
def search_terms(self) -> Set[str]:
"""Return set of search terms for the object."""
return set(
[self.name]
+ [obj.casefold() for obj in self.entity_types] # type: ignore
+ [key.casefold() for key in self.keywords] # type: ignore
+ [opt.casefold() for opt in self.all_options] # type: ignore
)
def __str__(self):
"""Return string representation of object."""
return "\n".join(f"{name}: {val}" for name, val in attr.asdict(self).items())
@property
def all_options(self) -> List[str]:
"""Return combination of default and other options."""
opts = []
if self.default_options:
for opt in self.default_options:
if isinstance(opt, str):
opts.append(opt)
elif isinstance(opt, dict):
opts.append(next(iter(opt.keys())))
if self.other_options:
for opt in self.other_options:
if isinstance(opt, str):
opts.append(opt)
elif isinstance(opt, dict):
opts.append(next(iter(opt.keys())))
return sorted(opts)
def get_options(self, option_set: str = "all") -> List[Tuple[str, Optional[str]]]:
"""
Return list of options and descriptions.
Parameters
----------
option_set : str, optional
The subset of options to return, by default "all"
Other values are "default" and "other"
Returns
-------
List[Tuple[str, Optional[str]]]
A list of tuples of option name and description.
"""
opt_list: List[Tuple[str, Optional[str]]] = []
if option_set.casefold() in ["all", "default"] and self.default_options:
for opt in self.default_options:
if isinstance(opt, str):
opt_list.append((opt, None))
elif isinstance(opt, dict):
opt_list.extend(opt.items())
if option_set.casefold() in ["all", "other"] and self.other_options:
for opt in self.other_options:
if isinstance(opt, str):
opt_list.append((opt, None))
elif isinstance(opt, dict):
opt_list.extend(opt.items())
return opt_list
@property
def options_doc(self) -> str:
"""Return list of options and documentation."""
def_options = self.get_options("default")
opt_list = [
"",
" Default Options",
" ---------------",
]
if def_options:
opt_list.extend([f" - {key}: {value}" for key, value in def_options])
else:
opt_list.append(" None")
opt_list.extend(
[
"",
" Other Options",
" -------------",
]
)
if self.get_options("other"):
opt_list.extend(
[f" - {key}: {value}" for key, value in self.get_options("other")]
)
else:
opt_list.append(" None")
# Add a blank line to the end
opt_list.extend(["", ""])
return "\n".join(opt_list)
# pylint: enable=not-an-iterable
def read_mod_metadata(mod_path: str, module_name) -> Tuple[NBMetadata, Dict[str, Any]]:
"""
Read notebooklet metadata from yaml file.
Parameters
----------
mod_path : str
The fully-qualified (dotted) module name
module_name : str
The full module name.
Returns
-------
Tuple[NBMetadata, Dict[str, Any]]
A tuple of the metadata class
and the documentation dictionary
"""
md_dict = _read_metadata_file(mod_path)
if not md_dict:
return NBMetadata(), {}
metadata_vals = md_dict.get("metadata", {})
metadata_vals["mod_name"] = module_name
metadata = NBMetadata(**metadata_vals)
output = md_dict.get("output", {})
return metadata, output
def _read_metadata_file(mod_path):
md_path = Path(str(mod_path).replace(".py", ".yaml"))
if not md_path.is_file():
md_path = Path(str(mod_path).replace(".py", ".yml"))
if md_path.is_file():
with open(md_path, "r", encoding="utf-8") as _md_file:
return yaml.safe_load(_md_file)
return None
def update_class_doc(cls_doc: str, cls_metadata: NBMetadata):
"""Append the options documentation to the `cls_doc`."""
options_doc = cls_metadata.options_doc
if options_doc is not None:
return cls_doc + options_doc
return cls_doc
| 177 | 31.41 | 87 | 24 | 1,229 | python | [{"finding_id": "semgrep_rules.python.attr.correctness.attr-mutable-initializer_d9e81976bfac381f_993e7b92", "tool_name": "semgrep", "rule_id": "rules.python.attr.correctness.attr-mutable-initializer", "finding_type": "correctness", "severity": "medium", "confidence": "medium", "message": "Unsafe usage of mutable initializer with attr.s decorator. Multiple instances of this class will re-use the same data structure, which is likely not the desired behavior. Consider instead: replace assignment to mutable initializer (ex. dict() or {}) with attr.ib(factory=type) where type is dict, set, or list", "remediation": "", "location": {"file_path": "unknown", "line_start": 29, "line_end": 29, "column_start": 5, "column_end": 34, "code_snippet": "requires login"}, "cwe_id": null, "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": null, "references": [], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.attr.correctness.attr-mutable-initializer", "path": "/tmp/tmpr7mo7ysm/d9e81976bfac381f.py", "start": {"line": 29, "col": 5, "offset": 844}, "end": {"line": 29, "col": 34, "offset": 873}, "extra": {"message": "Unsafe usage of mutable initializer with attr.s decorator. Multiple instances of this class will re-use the same data structure, which is likely not the desired behavior. Consider instead: replace assignment to mutable initializer (ex. dict() or {}) with attr.ib(factory=type) where type is dict, set, or list", "metadata": {"category": "correctness", "technology": ["attr"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
""
] | [
"rules.python.attr.correctness.attr-mutable-initializer"
] | [
"correctness"
] | [
"MEDIUM"
] | [
"MEDIUM"
] | [
29
] | [
29
] | [
5
] | [
34
] | [
""
] | [
"Unsafe usage of mutable initializer with attr.s decorator. Multiple instances of this class will re-use the same data structure, which is likely not the desired behavior. Consider instead: replace assignment to mutable initializer (ex. dict() or {}) with attr.ib(factory=type) where type is dict, set, or list"
] | [
5
] | [
""
] | [
""
] | nb_metadata.py | /msticnb/nb_metadata.py | microsoft/msticnb | MIT | |
2024-11-18T20:18:08.233918+00:00 | 1,608,510,203,000 | ac4a97d9e58461b77cc927163736d43a3e87749b | 2 | {
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"license_type": "permissive",
"path": "/dataset_analyses/get_hf_datasets.py",
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"repo_name": "positivevaib/ood-detection",
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"visit_date": "2023-02-05T17:16:14.723034"
} | 2.328125 | stackv2 | import os
import argparse
import pickle
import numpy as np
import pandas as pd
from sklearn.utils import shuffle
import datasets
from datasets import load_dataset
from tqdm import tqdm
data_out = os.path.join('.','datasets')
custom_out = os.path.join(data_out, 'used_evals')
in_domains = [
'imdb',
'sst2',
]
seed = 42
hf_datasets = [
'imdb',
'rte',
'snli',
'sst2',
]
glue = ['rte', 'sst2']
entailment = ['snli', 'rte']
other_datasets = {
'counterfactual-imdb':{
'base': os.path.join(data_out, 'counterfactually-augmented-data', 'sentiment', 'new'),
'files': [
'dev.tsv',
'test.tsv',
'train.tsv',
]
}
}
train_split_keys = {
'imdb': 'train',
'rte': 'train',
'snli': 'train',
'sst2': 'train',
'counterfactual-imdb': 'train'
}
eval_split_keys = {
'imdb': 'test',
'rte': 'validation',
'snli': 'validation',
'sst2': 'validation',
'counterfactual-imdb': 'dev'
}
datasets_to_keys = {
'imdb': ('text', None),
'rte': ('sentence1', 'sentence2'),
'snli': ('premise', 'hypothesis'),
'sst2': ('sentence', None),
'counterfactual-imdb': ('Text', None)
}
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('cache', type=str, default=None)
args = parser.parse_args()
data = {}
t = tqdm(hf_datasets)
for data_name in t:
t.set_description(data_name)
if data_name in glue:
data[data_name] = load_dataset('glue', data_name, split=eval_split_keys[data_name], cache_dir=args.cache)
else:
data[data_name] = load_dataset(data_name, split=eval_split_keys[data_name], cache_dir=args.cache)
data_out = {}
for data_name, val_data in data.items():
domain_key = 'ood'
# for in-domain random split
if data_name in in_domains:
sentences, labels = shuffle(
val_data[datasets_to_keys[data_name][0]], val_data['label'], random_state=seed
)
print(type(val_data[datasets_to_keys[data_name][0]]), type(val_data[datasets_to_keys[data_name][0]][0]))
split_idx = int(0.2*len(sentences))
data_out[('id', 'val', data_name)] = {'text': sentences[split_idx:], 'label': labels[split_idx:]}
# training data
# temp = load_dataset(data_name, split=train_split_keys[data_name], cache_dir=args.cache)
# data_out[('id', 'train', data_name)] = {'text': temp[datasets_to_keys[data_name][0]], 'label': temp['label']}
# out-of-domain splits
if data_name in entailment:
sentences = [
sentence1 + ' ' + sentence2
for sentence1, sentence2 in zip(val_data[datasets_to_keys[data_name][0]], val_data[datasets_to_keys[data_name][1]])
]
labels = val_data['label']
data_out[(domain_key, 'val', data_name)] = {'text': sentences, 'label': labels}
else:
data_out[(domain_key, 'val', data_name)] = {'text': val_data[datasets_to_keys[data_name][0]], 'label': val_data['label']}
with open(os.path.join(args.cache, 'hf_data.p'), 'wb') as f:
pickle.dump(data_out, f)
| 112 | 28.91 | 133 | 17 | 851 | python | [{"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_0997373f2fe359fa_2a1f41e4", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "remediation": "", "location": {"file_path": "unknown", "line_start": 112, "line_end": 112, "column_start": 9, "column_end": 33, "code_snippet": "requires login"}, "cwe_id": "CWE-502: Deserialization of Untrusted Data", "cwe_name": null, "cvss_score": 5.0, "cvss_vector": null, "owasp_category": "A08:2017 - Insecure Deserialization", "references": [{"url": "https://docs.python.org/3/library/pickle.html", "title": null}], "fingerprint": "requires login", "tags": [], "raw_output": {"check_id": "rules.python.lang.security.deserialization.avoid-pickle", "path": "/tmp/tmpr7mo7ysm/0997373f2fe359fa.py", "start": {"line": 112, "col": 9, "offset": 3325}, "end": {"line": 112, "col": 33, "offset": 3349}, "extra": {"message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 1 | true | [
"CWE-502"
] | [
"rules.python.lang.security.deserialization.avoid-pickle"
] | [
"security"
] | [
"LOW"
] | [
"MEDIUM"
] | [
112
] | [
112
] | [
9
] | [
33
] | [
"A08:2017 - Insecure Deserialization"
] | [
"Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format."
] | [
5
] | [
"LOW"
] | [
"MEDIUM"
] | get_hf_datasets.py | /dataset_analyses/get_hf_datasets.py | positivevaib/ood-detection | MIT | |
2024-11-18T20:18:08.346135+00:00 | 1,556,253,230,000 | 9c1176e2631ce90b2cfb200ad10d6d5f1ba13964 | 3 | {
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} | 2.71875 | stackv2 | import numpy as np
import os
import sys
import nltk
import pickle
import pprint
import copy
nltk.download('punkt')
class Dataset(object):
def __init__(self, config):
self.config = config
# dictionary settings
self.initialize_dictionary()
self.build_corpus(self.config.train_path, self.train_corpus)
self.build_corpus(self.config.valid_path, self.valid_corpus)
self.build_corpus(self.config.test_path, self.test_corpus)
print()
self.train_data = self.process_data(
self.train_corpus,
update_dict=True)
self.valid_data = self.process_data(
self.valid_corpus,
update_dict=True)
self.test_data = self.process_data(
self.test_corpus)
print()
self.pad_data(self.train_data)
self.pad_data(self.valid_data)
self.pad_data(self.test_data)
# data = [batch_size, batches, maxlen], [batch_size, batches]
# where data[0] is char idx and data[1] is the corresponding word idx
self.train_data = self.reshape_data(self.train_data)
self.valid_data = self.reshape_data(self.valid_data)
self.test_data = self.reshape_data(self.test_data)
print()
self.train_ptr = 0
self.valid_ptr = 0
self.test_ptr = 0
print('char_dict', len(self.char2idx))
print('word_dict', len(self.word2idx), end='\n\n')
def initialize_dictionary(self):
self.train_corpus = []
self.valid_corpus = []
self.test_corpus = []
self.char2idx = {}
self.idx2char = {}
self.word2idx = {}
self.idx2word = {}
self.UNK = '<unk>'
self.PAD = 'PAD'
self.CONJ = '+'
self.START = '{'
self.END = '}'
self.char2idx[self.UNK] = 0
self.char2idx[self.PAD] = 1
self.char2idx[self.CONJ] = 2
self.char2idx[self.START] = 3
self.char2idx[self.END] = 4
self.idx2char[0] = self.UNK
self.idx2char[1] = self.PAD
self.idx2char[2] = self.CONJ
self.idx2char[3] = self.START
self.idx2char[4] = self.END
self.word2idx[self.UNK] = 0
self.word2idx[self.PAD] = 1
self.word2idx[self.CONJ] = 2
self.idx2word[0] = self.UNK
self.idx2word[1] = self.PAD
self.idx2word[2] = self.CONJ
def update_dictionary(self, key, mode=None):
if mode == 'c':
if key not in self.char2idx:
self.char2idx[key] = len(self.char2idx)
self.idx2char[len(self.idx2char)] = key
elif mode == 'w':
if key not in self.word2idx:
self.word2idx[key] = len(self.word2idx)
self.idx2word[len(self.idx2word)] = key
def map_dictionary(self, key_list, dictionary, reverse=False):
output = []
# reverse=False : word2idx, char2idx
# reverse=True : idx2word, idx2char
for key in key_list:
if key in dictionary:
if reverse and key == 1: # PAD
continue
else:
output.append(dictionary[key])
else:
if not reverse:
output.append(dictionary[self.UNK])
else:
output.append(dictionary[0]) # 0 for UNK
return output
def build_corpus(self, path, corpus):
print('building corpus %s' % path)
with open(path) as f:
for k, line in enumerate(f):
# sentence_split = nltk.word_tokenize(line[:-1])
sentence_split = line[:-1].split()
for word in sentence_split:
corpus.append(word)
corpus.append(self.CONJ)
def process_data(self, corpus, update_dict=False):
print('processing corpus %d' % len(corpus))
total_data = []
max_wordlen = 0
for k, word in enumerate(corpus):
# dictionary update
if update_dict:
self.update_dictionary(word, 'w')
for char in word:
self.update_dictionary(char, 'c')
# user special characters or mapping
if word == self.UNK or word == self.CONJ or word == self.PAD:
word_char = word
charidx = [self.char2idx[word_char]]
else:
word_char = self.START + word + self.END
charidx = self.map_dictionary(word_char, self.char2idx)
# get max word length
max_wordlen = (len(word_char)
if len(word_char) > max_wordlen else max_wordlen)
if max_wordlen > self.config.max_wordlen:
self.config.max_wordlen = max_wordlen
# word / char
total_data.append([self.word2idx[word], charidx])
if update_dict:
self.config.char_vocab_size = len(self.char2idx)
self.config.word_vocab_size = len(self.word2idx)
print('data size', len(total_data))
print('max wordlen', max_wordlen)
return total_data
def pad_data(self, dataset):
for data in dataset:
sentword, sentchar = data
# pad word in sentchar
while len(sentchar) != self.config.max_wordlen:
sentchar.append(self.char2idx[self.PAD])
return dataset
def reshape_data(self, dataset):
inputs = [d[1] for d in dataset]
targets = [d[0] for d in dataset]
seq_len = len(dataset) // self.config.batch_size
inputs = np.array(inputs[:seq_len * self.config.batch_size])
targets = np.array(targets[:seq_len * self.config.batch_size])
inputs = np.reshape(inputs, (self.config.batch_size, seq_len, -1))
targets = np.reshape(targets, (self.config.batch_size, -1))
print('reshaped data', inputs.shape)
return inputs, targets
# inputs, targets such that inputs[1:] = target[0:-1], i.e., predict the next
def get_next_batch(self, seq_len, mode='tr'):
if mode == 'tr':
ptr = self.train_ptr
data = self.train_data
elif mode == 'va':
ptr = self.valid_ptr
data = self.valid_data
elif mode == 'te':
ptr = self.test_ptr
data = self.test_data
seq_len = (seq_len if ptr + seq_len < len(data[0][0])
else len(data[0][0]) - ptr - 1)
inputs = data[0][:,ptr:ptr+seq_len,:]
targets = data[1][:,ptr+1:ptr+seq_len+1]
if len(data[0][0]) - (ptr + seq_len) == 1: # last batch
ptr += 1
if mode == 'tr':
self.train_ptr = (ptr + seq_len) % len(data[0][0])
elif mode == 'va':
self.valid_ptr = (ptr + seq_len) % len(data[0][0])
elif mode == 'te':
self.test_ptr = (ptr + seq_len) % len(data[0][0])
return inputs, targets
def get_batch_ptr(self, mode):
if mode == 'tr':
return self.train_ptr
elif mode == 'va':
return self.valid_ptr
elif mode == 'te':
return self.test_ptr
class Config(object):
def __init__(self):
user_home = os.path.expanduser('~')
self.train_path = os.path.join(user_home, 'datasets/ptb/train.txt')
self.valid_path = os.path.join(user_home, 'datasets/ptb/valid.txt')
self.test_path = os.path.join(user_home, 'datasets/ptb/test.txt')
self.batch_size = 20
self.max_wordlen = 0
self.char_vocab_size = 0
self.word_vocab_size = 0
self.save_preprocess = True
self.preprocess_save_path = './data/preprocess(tmp).pkl'
self.preprocess_load_path = './data/preprocess(tmp).pkl'
if __name__ == '__main__':
if not os.path.exists('./data'):
os.makedirs('./data')
config = Config()
if config.save_preprocess:
dataset = Dataset(config)
pickle.dump(dataset, open(config.preprocess_save_path, 'wb'))
else:
print('## load preprocess %s' % config.preprocess_load_path)
dataset = pickle.load(open(config.preprocess_load_path, 'rb'))
# dataset config must be valid
pp = lambda x: pprint.PrettyPrinter().pprint(x)
pp(([(k,v) for k, v in vars(dataset.config).items() if '__' not in k]))
print()
input, target = dataset.get_next_batch(seq_len=5)
print([dataset.map_dictionary(i, dataset.idx2char) for i in input[0,:,:]])
print([dataset.idx2word[t] for t in target[0,:]])
print()
input, target = dataset.get_next_batch(seq_len=5)
print([dataset.map_dictionary(i, dataset.idx2char) for i in input[0,:,:]])
print([dataset.idx2word[t] for t in target[0,:]])
print('train', dataset.train_data[0].shape)
print('valid', dataset.valid_data[0].shape)
print('test', dataset.test_data[0].shape)
while True:
i, t = dataset.get_next_batch(seq_len=100, mode='te')
print(dataset.test_ptr, len(i[0]))
if dataset.test_ptr == 0:
print('\niteration test pass!')
break
| 264 | 33.91 | 81 | 18 | 2,215 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_e0a57ca5f40a5e36_86ad7698", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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"rules.python.lang.security.deserialization.avoid-pickle"
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"LOW"
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238
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238
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5,
5
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"LOW",
"LOW"
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] | dataset.py | /dataset.py | unixnme/charnlm-pytorch | MIT | |
2024-11-18T20:18:10.539112+00:00 | 1,487,178,095,000 | 9ba63847dc305562ad3865281b02077eaa636762 | 3 | {
"blob_id": "9ba63847dc305562ad3865281b02077eaa636762",
"branch_name": "refs/heads/master",
"committer_date": 1487178095000,
"content_id": "45db7e9ee66a039a73e76aa619d3c64d0a200340",
"detected_licenses": [
"MIT"
],
"directory_id": "80c92410009407145959e71c9fa7a9c221aef332",
"extension": "py",
"filename": "tracker1.py",
"fork_events_count": 0,
"gha_created_at": null,
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"gha_language": null,
"gha_license_id": null,
"github_id": 82084611,
"is_generated": false,
"is_vendor": false,
"language": "Python",
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"license": "MIT",
"license_type": "permissive",
"path": "/tracker1.py",
"provenance": "stack-edu-0054.json.gz:578047",
"repo_name": "doctorwho42/Reeve-Work-Tracker",
"revision_date": 1487178095000,
"revision_id": "059578baadb2711f38ddc2c5442616dbb5bf46af",
"snapshot_id": "64ed256de3b674af1393330f7ad2af260d311ae2",
"src_encoding": "UTF-8",
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"url": "https://raw.githubusercontent.com/doctorwho42/Reeve-Work-Tracker/059578baadb2711f38ddc2c5442616dbb5bf46af/tracker1.py",
"visit_date": "2021-01-19T09:05:08.838512"
} | 2.8125 | stackv2 | #!/usr/bin/env python
import RPi.GPIO as GPIO
import datetime
import time
import sys
import pickle
from Adafruit_LED_Backpack import SevenSegment
GPIO.setmode(GPIO.BCM)
display = SevenSegment.SevenSegment()
display.begin()
GPIO.setup(26, GPIO.IN, pull_up_down=GPIO.PUD_UP)
GPIO.setup(19, GPIO.IN, pull_up_down=GPIO.PUD_UP)
GPIO.setup(13, GPIO.IN, pull_up_down=GPIO.PUD_UP)
GPIO.setup(6, GPIO.IN, pull_up_down=GPIO.PUD_UP)
state1 = GPIO.input(26)
state2 = GPIO.input(19)
state3 = GPIO.input(13)
state4 = GPIO.input(6)
keys = False
#write values to LED Display- (d4 d3: d2 d1) - (43:21) - d4=4,d3=3,d2=2,d1=1
def ledoutput(d1,d2,d3,d4):
display.clear()
display.set_digit(0,d4)
display.set_digit(1,d3)
display.set_digit(2,d2)
display.set_digit(3,d1)
display.set_colon(True)
display.write_display()
#Example read/write pickle
# with open('/home/pi/pythoncode/worktracker/tracking.p', 'w') as write:
# pickle.dump([write1, write2, write3, write4], write)
# with open('/home/pi/pythoncode/worktracker/tracking.p') as read:
# read1, read2, read3, read4 = pickle.load(read)
with open('/home/pi/pythoncode/worktracker/tracking.p') as read:
read1,read2,read3,read4,read5= pickle.load(read)
x1 = read1 #lowest digit
x2 = read2 #second lowest digit
x3 = read3 #second highest digit
x4 = read4 #highest digit
crap = read5 #rob has worked over 99H:99M in a week,then this will =1
if state1 == 0:
keys = True
elif state2 == 0:
keys = True
elif state3 == 0:
keys = True
elif state4 == 0:
keys = True
#print(keys)
if keys==True:
if x1<=8:
x1 = x1 + 1
elif x1==9:
x1 = 0
x2 = x2 + 1
if x3==9 and x2==6:
x3 = 0
x2 = 0
if x4==9:
crap = 1
elif x4<=8:
x4 = x4 + 1
if x2==6:
x2=0
x3=x3+1
ledoutput(x1,x2,x3,x4)
if crap== 1:
display.set_decimal(0,True)
display.set_decimal(1,True)
display.set_decimal(2,True)
display.set_decimal(3,True)
display.write_display()
#ledoutput(x1,x2,x3,x4)
with open('/home/pi/pythoncode/worktracker/tracking.p', 'w') as write:
pickle.dump([x1,x2,x3,x4,crap], write)
| 92 | 21.16 | 76 | 12 | 710 | python | [{"finding_id": "semgrep_rules.python.lang.best-practice.unspecified-open-encoding_eb9e9b4357d3e0dd_e6c16067", "tool_name": "semgrep", "rule_id": "rules.python.lang.best-practice.unspecified-open-encoding", "finding_type": "best-practice", "severity": "medium", "confidence": "medium", "message": "Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. 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'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding=\"utf-8\").", "metadata": {"category": "best-practice", "technology": ["python"], "references": ["https://www.python.org/dev/peps/pep-0597/", "https://docs.python.org/3/library/functions.html#open"]}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}, {"finding_id": "semgrep_rules.python.lang.security.deserialization.avoid-pickle_eb9e9b4357d3e0dd_657a3637", "tool_name": "semgrep", "rule_id": "rules.python.lang.security.deserialization.avoid-pickle", "finding_type": "security", "severity": "medium", "confidence": "low", "message": "Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. 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Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.", "metadata": {"owasp": ["A08:2017 - Insecure Deserialization", "A08:2021 - Software and Data Integrity Failures", "A08:2025 - Software or Data Integrity Failures"], "cwe": ["CWE-502: Deserialization of Untrusted Data"], "references": ["https://docs.python.org/3/library/pickle.html"], "category": "security", "technology": ["python"], "cwe2022-top25": true, "cwe2021-top25": true, "subcategory": ["audit"], "likelihood": "LOW", "impact": "MEDIUM", "confidence": "LOW"}, "severity": "WARNING", "fingerprint": "requires login", "lines": "requires login", "validation_state": "NO_VALIDATOR", "engine_kind": "OSS"}}}] | 4 | true | [
"CWE-502",
"CWE-502"
] | [
"rules.python.lang.security.deserialization.avoid-pickle",
"rules.python.lang.security.deserialization.avoid-pickle"
] | [
"security",
"security"
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | [
42,
90
] | [
42,
90
] | [
33,
2
] | [
50,
40
] | [
"A08:2017 - Insecure Deserialization",
"A08:2017 - Insecure Deserialization"
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"Avoid using `pickle`, which is known to lead to code execution vulnerabilities. When unpickling, the serialized data could be manipulated to run arbitrary code. Instead, consider serializing the relevant data as JSON or a similar text-based serialization format.",
"Avoid using `pickle`, which is known to lead to... | [
5,
5
] | [
"LOW",
"LOW"
] | [
"MEDIUM",
"MEDIUM"
] | tracker1.py | /tracker1.py | doctorwho42/Reeve-Work-Tracker | MIT |
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