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import random
import string
import numpy as np
import rstr
from fuzzer_dir.schema_validator import validate
from fuzzer_dir.runtime_dictionary import RuntimeDictionary
from fuzzer_dir.constant import ValueSource
from model.parameter import TargetType, TargetStatus
from model.method import Method
import uuid
class RandomDataGenerator:
SKIP_OPTIONAL = "SKIP_OPTIONAL"
def __init__(self, parameter, runtime_dictionary: RuntimeDictionary, ref_dict: {}, method: Method):
self.parameter = parameter
self.parameter_name = parameter.name
self.runtime_dictionary = runtime_dictionary
self.ref_dict = ref_dict
self.ref_prefix = "%{APIGen"
self.ref_suffix = "}"
self.threshold = 0.7
self.validate_value = False
self.refs_varabile = set()
self.value_source_count = {}
self.potential_targets = set()
self.value_source = {}
self.method = method
def generate(self):
if self.should_skip_optional_parameter(self.parameter.raw_body):
self.record_source(ValueSource.skip)
# self.value_source[self.parameter_name] = (self.parameter_name, ValueSource.skip)
return RandomDataGenerator.SKIP_OPTIONAL
if self.is_simple_request_parameter(self.parameter.raw_body):
val = self.value_factory(self.parameter_name, self.parameter.raw_body)
else:
val = self.value_factory("", self.parameter.raw_body)
# validate generated value
if self.validate_value:
validate(val, self.parameter.raw_body)
assert val is not None, f'{self.parameter.name}'
return val
def is_simple_request_parameter(self, parameter_body):
if parameter_body.__contains__("in") and parameter_body["in"] == "body":
return False
return True
def get_value_source_stat(self):
return self.value_source_count
def record_source(self, source_type):
self.value_source_count[source_type] = self.value_source_count.get(source_type, 0) + 1
def _build_ref(self, property):
refs = '#'.join([self.ref_dict.method.method_signature + i for i in list(property)])
refs = '#' + refs
self.refs_varabile = self.refs_varabile.union(property)
# print('hit',property)
return f'{self.ref_prefix}{refs}{self.ref_suffix}'
def should_use_example(self, path, parameter_body):
# only for debug should be modified
if isinstance(parameter_body, dict) and (parameter_body.__contains__('example') or parameter_body.__contains__(
'x-example')) and np.random.random() < 0.5:
return True
return False
def should_skip_optional_parameter(self, parameter_body):
if parameter_body.__contains__('required') and parameter_body['required'] is True:
return False
if parameter_body.__contains__('in') and parameter_body['in'] in ['path', 'body']:
return False
# only for debug should be modified
if np.random.random() < 0.4:
return False
return True
def should_skip_optional_property(self, parameter_body, key):
if parameter_body.__contains__('required') and key in parameter_body['required']:
return False
if parameter_body.__contains__('in') and parameter_body['in'] in ['path', 'body']:
return False
if np.random.random() < 0.4:
return False
return True
def use_example(self, path, parameter_body):
potential_target = (path, TargetType.EXAMPLE, TargetStatus.EXAMPLE)
self.potential_targets.add(potential_target)
if parameter_body.__contains__('example'):
example = parameter_body['example']
else:
example = parameter_body['x-example']
val = example
return val
def value_factory(self, path, parameter):
if self.should_use_example(path, parameter):
val = self.use_example(path, parameter)
self.record_source(ValueSource.example)
self.value_source[path] = (val, ValueSource.example)
return val
if path in self.ref_dict:
ref = self._build_ref(self.ref_dict[path])
assert ref is not None, 'ref is None'f'{path}'
self.record_source(ValueSource.reference)
self.value_source[path] = (ref, ValueSource.reference)
return ref
param_type = self.check_parameter_type(path, parameter)
if param_type == "integer":
val = self.integer_factory(path, parameter)
assert val is not None, 'val(integer) is None'f'{path}'
return val
elif param_type == "string":
val = self.string_factory(path, parameter)
assert val is not None, 'val(string) is None'f'{path}'
return val
elif param_type == "file":
val = self.string_factory(path, parameter)
assert val is not None, 'val(file) is None'f'{path}'
return val
elif param_type == 'array':
if self.should_use_example(path, parameter):
val = self.use_example(path, parameter)
self.record_source(ValueSource.example)
self.value_source[path] = (val, ValueSource.example)
return val
if self.should_use_dictionary_value(path):
value = self.runtime_dictionary.generate_value_from_dictionary(path, self.method, parameter)
if isinstance(value, list):
try:
validate(value, parameter)
self.record_source(ValueSource.dictionary)
self.value_source[path] = (value, ValueSource.dictionary)
return value
except Exception:
pass
items = parameter["items"]
array = []
for i in range(np.random.choice(range(0, 2))):
item = self.value_factory(f'{path}[0]', items)
if self.should_skip_optional_parameter(items):
path_signature = f'{path}[{i}]_skip'
self.record_source(ValueSource.skip)
# self.value_source[path_signature] = (item, ValueSource.skip)
continue
assert item is not None, f'val(array,item) is None'f'{path}'
array.append(item)
self.value_source[f'{path}[0]'] = (item, ValueSource.random)
# # fix for array's notation
# if not path.endswith('[0]'):
# path += '[0]'
if len(array) == 0:
potential_target = (path, TargetType.ARRAY, TargetStatus.EMPTY)
else:
potential_target = (path, TargetType.ARRAY, TargetStatus.NON_EMPTY)
self.potential_targets.add(potential_target)
self.value_source[path] = (array, ValueSource.random)
return array
elif param_type == 'schema':
val = self.build_schema(path, parameter["schema"])
assert val is not None, f'val(array,item) is None'f'{path},{parameter}'
return val
elif param_type == "properties":
parameter['type'] = 'object'
val = self.build_schema(path, parameter)
assert val is not None, f'val(properties) is None'f'{path}'
return val
elif param_type == 'object':
val = self.object_factory(path, parameter)
assert val is not None, f'val(object) is None'f'{path}'
return val
elif param_type == 'boolean':
val = self.boolean_factory(path)
assert val is not None, f'val(boolean) is None'f'{path}'
return val
elif param_type == "allOf":
if self.should_use_example(path, parameter):
val = self.use_example(path, parameter)
self.record_source(ValueSource.example)
self.value_source[path] = (val, ValueSource.example)
return val
if path in self.ref_dict:
ref = self._build_ref(self.ref_dict[path])
self.record_source(ValueSource.reference)
self.value_source[path] = (ref, ValueSource.reference)
return ref
if self.should_use_dictionary_value(path):
value = self.runtime_dictionary.generate_value_from_dictionary(path, self.method, parameter)
if isinstance(value, dict):
try:
validate(value, parameter)
self.record_source(ValueSource.dictionary)
self.value_source[path] = (value, ValueSource.dictionary)
return value
except:
pass
result = {}
for item in parameter["allOf"]:
elem = self.value_factory(path, item)
# if self.should_skip_optional_parameter(item):
# self.value_source[path] = (path, ValueSource.skip)
# continue
assert elem is not None, f'val(allOf) is None'f'{path}'
for key in elem.keys():
if self.should_skip_optional_property(item, key):
path_signature = f'{path}.{key}'
self.record_source(ValueSource.skip)
# self.value_source[path_signature] = (path, ValueSource.skip)
continue
result[key] = elem[key]
self.value_source[path] = (result, ValueSource.random)
return result
elif param_type == 'number':
val = self.number_factory(path, parameter)
assert val is not None, 'val(number) is None'f'{path}'
return val
elif param_type == 'skip':
pass
else:
raise Exception("Unrecognized type in parameter", parameter)
def check_parameter_type(self, path, parameter={}):
param_type = None
if parameter.__contains__("type") and isinstance(parameter['type'], str
):
param_type = parameter["type"]
elif parameter.__contains__("schema"):
param_type = "schema"
elif parameter.__contains__("properties"):
param_type = "properties"
elif parameter.__contains__("allOf"):
param_type = "allOf"
elif parameter.__contains__('number'):
param_type = 'number'
# elif path.endswith('required'):
# param_type = 'skip'
else:
raise Exception(f"unknown parameter type: {parameter}")
return param_type
def build_schema(self, path, schema={}):
if self.should_use_example(path, schema):
val = self.use_example(path, schema)
self.record_source(ValueSource.example)
return val
if path in self.ref_dict:
ref = self._build_ref(self.ref_dict[path])
self.record_source(ValueSource.reference)
return ref
try:
if isinstance(schema['type'], str):
schema_type = schema["type"]
else:
raise Exception('not a schema type')
except:
if schema.__contains__("properties"):
schema_type = "object"
elif schema.__contains__("items"):
schema_type = "array"
elif schema.__contains__('allOf'):
schema_type = 'allOf'
else:
schema_type = "object"
if schema_type == "object":
return self.object_factory(path, schema)
if schema_type == "array":
if self.should_use_example(path, schema):
self.record_source(ValueSource.example)
val = self.use_example(path, schema)
self.value_source[path] = (val, ValueSource.example)
return val
if path in self.ref_dict:
self.record_source(ValueSource.reference)
ref = self._build_ref(self.ref_dict[path])
self.value_source[path] = (ref, ValueSource.reference)
return ref
if self.should_use_dictionary_value(path):
value = self.runtime_dictionary.generate_value_from_dictionary(path, self.method, schema)
if isinstance(value, list):
try:
validate(value, schema)
self.record_source(ValueSource.dictionary)
self.value_source[path] = (value, ValueSource.dictionary)
return value
except:
pass
items = schema["items"]
array = []
for i in range(np.random.choice(range(0, 2))):
res = self.value_factory(f'{path}[0]', items)
if self.should_skip_optional_parameter(items):
path_signature = f'{path}[0]'
self.record_source(ValueSource.skip)
# self.value_source[path_signature] = (path, ValueSource.skip)
continue
array.append(res)
self.value_source[f'{path}[0]'] = (res, ValueSource.random)
if len(array) == 0:
potential_target = (path, TargetType.ARRAY, TargetStatus.EMPTY)
else:
potential_target = (path, TargetType.ARRAY, TargetStatus.NON_EMPTY)
self.potential_targets.add(potential_target)
self.value_source[path] = (array, ValueSource.random)
return array
if schema_type == 'allOf':
if self.should_use_example(path, schema):
val = self.use_example(path, schema)
self.record_source(ValueSource.example)
self.value_source[path] = (val, ValueSource.example)
return val
if path in self.ref_dict:
ref = self._build_ref(self.ref_dict[path])
self.record_source(ValueSource.reference)
self.value_source[path] = (ref, ValueSource.reference)
return ref
if self.should_use_dictionary_value(path):
value = self.runtime_dictionary.generate_value_from_dictionary(path, self.method, schema)
if isinstance(value, dict):
try:
validate(value, schema)
self.record_source(ValueSource.dictionary)
self.value_source[path] = (value, ValueSource.dictionary)
return value
except:
pass
result = {}
for item in schema["allOf"]:
elem = self.value_factory(path, item)
# if self.should_skip_optional_parameter(item):
# path_signature = f'{path}'
# self.value_source[path_signature] = (path, ValueSource.skip)
# continue
assert elem is not None, f'val(allOf) is None'f'{path}'
for key in elem.keys():
if self.should_skip_optional_property(item, key):
path_signature = f'{path}.{key}'
self.record_source(ValueSource.skip)
# self.value_source[path_signature] = (path, ValueSource.skip)
continue
result[key] = elem[key]
self.value_source[path] = (result, ValueSource.random)
return result
val = self.value_factory(path, schema)
self.value_source[path] = (val, ValueSource.random)
return val
def should_use_dictionary_value(self, path: str):
if not self.runtime_dictionary.has_candidate_in_dictionary(path):
self.runtime_dictionary.calculate_path_threshold(path)
# if len(self.runtime_dictionary.signature_to_value) > 0 and str.lower(path).endswith("id"):
# return True
return self.runtime_dictionary.should_use_dictionary(path)
def string_factory(self, path, string_body={}):
if self.should_use_example(path, string_body):
val = self.use_example(path, string_body)
self.record_source(ValueSource.example)
self.value_source[path] = (val, ValueSource.example)
return val
if path in self.ref_dict:
ref = self._build_ref(self.ref_dict[path])
self.record_source(ValueSource.reference)
self.value_source[path] = (ref, ValueSource.reference)
return ref
min_len = 0
max_len = 100
self.record_source(ValueSource.random)
if string_body.__contains__("enum"):
self.record_source(ValueSource.enum)
enum = np.random.choice(string_body["enum"])
potential_target = (path, TargetType.ENUM, enum)
self.potential_targets.add(potential_target)
self.value_source[path] = (enum, ValueSource.enum)
return enum
if self.should_use_dictionary_value(path):
value = self.runtime_dictionary.generate_value_from_dictionary(path, self.method, string_body)
if isinstance(value, str):
self.record_source(ValueSource.dictionary)
self.value_source[path] = (value, ValueSource.dictionary)
return value
if string_body.__contains__("minLength") and string_body.__contains__("maxLength"):
min_len = string_body["minLength"]
max_len = string_body["maxLength"]
if string_body.__contains__("minLength") and np.random.random() < 0.2:
max_len = string_body["minLength"]
potential_target = (path, TargetType.STRING, TargetStatus.MIN)
self.potential_targets.add(potential_target)
elif string_body.__contains__("maxLength") and np.random.random() < 0.2:
min_len = string_body["maxLength"]
potential_target = (path, TargetType.STRING, TargetStatus.MAX)
self.potential_targets.add(potential_target)
elif string_body.__contains__("minLength") and string_body.__contains__("maxLength"):
potential_target = (path, TargetType.STRING, TargetStatus.MIDDLE)
self.potential_targets.add(potential_target)
if string_body.__contains__('format'):
self.record_source(ValueSource.random)
format = string_body['format']
if format == 'date-time':
res = datetime.datetime.now().isoformat('T')
self.value_source[path] = (res, ValueSource.random)
return res
elif format == 'uuid':
res = uuid.uuid4().__str__()
self.value_source[path] = (res, ValueSource.random)
return res
else:
raise Exception('unknown string format')
if string_body.__contains__('pattern'):
self.record_source(ValueSource.random)
pattern = string_body['pattern']
res = rstr.xeger(pattern)
self.value_source[path] = (res, ValueSource.random)
return res
# avoid body size too large
max_len = min(max_len, 100)
if max_len <= min_len:
str_len = max_len
else:
str_len = np.random.randint(min_len, max_len + 1)
res = ''.join(random.choices(string.ascii_uppercase +
string.digits, k=str_len))
if str_len == min_len:
self.record_source(ValueSource.min)
self.value_source[path] = (res, ValueSource.min)
elif str_len == max_len:
self.record_source(ValueSource.max)
self.value_source[path] = (res, ValueSource.max)
else:
self.record_source(ValueSource.middle)
self.value_source[path] = (res, ValueSource.middle)
return res
def object_factory(self, path, object_body={}):
if self.should_use_example(path, object_body):
val = self.use_example(path, object_body)
self.record_source(ValueSource.example)
self.value_source[path] = (val, ValueSource.example)
return val
if path in self.ref_dict:
ref = self._build_ref(self.ref_dict[path])
self.record_source(ValueSource.reference)
self.value_source[path] = (ref, ValueSource.reference)
return ref
if self.should_use_dictionary_value(path):
value = self.runtime_dictionary.generate_value_from_dictionary(path, self.method, object_body)
if isinstance(value, dict):
try:
validate(value, object_body)
self.record_source(ValueSource.dictionary)
self.value_source[path] = (value, ValueSource.dictionary)
return value
except:
pass
self.record_source(ValueSource.random)
data = {}
if object_body.__contains__("properties"):
for name in object_body["properties"]:
if len(path) > 0:
property_path = f'{path}.{name}'
else:
property_path = name
# add array notation
# if self.check_parameter_type(path, object_body["properties"][name]) == 'array':
# property_path += '[0]'
res = self.value_factory(property_path, object_body["properties"][name])
if self.should_skip_optional_property(object_body,
name):
if len(path) > 0:
path_signature = f'{path}.{name}'
else:
path_signature = name
self.record_source(ValueSource.skip)
# self.value_source[path_signature] = (path, ValueSource.skip)
continue
data[name] = res
else:
for name in object_body.keys():
if name == 'additionalProperties':
continue
if len(path) > 0:
property_path = f'{path}.{name}'
else:
property_path = name
# add array notation
# if self.check_parameter_type(path, object_body[name]) == 'array':
# property_path += '[0]'
# we omit additional properties generation
# data[name] = self.value_factory(property_path, object_body[name])
# # FIXME: should be properly handled
# if str(name).lower().__contains__("time"):
# now = datetime.datetime.now()
# date_time = now.strftime("%H:%M:%S")
# data[name] = date_time
# if str(name).lower().__contains__("date") and np.random.random() < 0.5:
# data[name] = 0
# if str(name).lower().__contains__("policy_type") and np.random.random() < 0.5:
# data[name] = 1
# if str(name).lower().__contains__("bw") and np.random.random() < 0.5:
# data[name] = np.random.randint(0, 999999)
self.value_source[path] = (data, ValueSource.random)
return data
def boolean_factory(self, path):
if path in self.ref_dict:
ref = self._build_ref(self.ref_dict[path])
self.record_source(ValueSource.reference)
self.value_source[path] = (ref, ValueSource.reference)
return ref
res = np.random.choice(['true', 'false'])
if res == 'true':
potential_target = (path, TargetType.BOOL, TargetStatus.TRUE)
else:
potential_target = (path, TargetType.BOOL, TargetStatus.FALSE)
self.potential_targets.add(potential_target)
self.value_source[path] = (res, ValueSource.random)
return res
def number_factory(self, path, number_body={}):
if self.should_use_example(path, number_body):
val = self.use_example(path, number_body)
self.record_source(ValueSource.example)
self.value_source[path] = (val, ValueSource.example)
return val
if path in self.ref_dict:
ref = self._build_ref(self.ref_dict[path])
self.record_source(ValueSource.reference)
self.value_source[path] = (ref, ValueSource.reference)
return ref
if number_body.__contains__("enum"):
self.record_source(ValueSource.enum)
enum = np.random.choice(number_body["enum"])
potential_target = (path, TargetType.ENUM, enum)
self.potential_targets.add(potential_target)
self.value_source[path] = (enum, ValueSource.enum)
return enum
if self.should_use_dictionary_value(path):
value = self.runtime_dictionary.generate_value_from_dictionary(path, self.method, number_body)
if isinstance(value, float):
self.record_source(ValueSource.dictionary)
self.value_source[path] = (value, ValueSource.dictionary)
return value
# bypass for enum
if np.random.random() < 0.5:
res = np.random.randint(0, 2)
self.value_source[path] = (res, ValueSource.random)
return res
if number_body.__contains__("minimum") and number_body.__contains__("maximum"):
if np.random.random() < 0.5:
res = np.random.randint(number_body["minimum"], number_body["maximum"], dtype=np.int64)
potential_target = (path, TargetType.NUM, TargetStatus.MIDDLE)
self.potential_targets.add(potential_target)
self.value_source[path] = (res, ValueSource.middle)
self.record_source(ValueSource.middle)
else:
res = np.random.choice([number_body["minimum"], number_body["maximum"]])
if res == number_body['minimum']:
potential_target = (path, TargetType.NUM, TargetStatus.MIN)
self.record_source(ValueSource.min)
self.value_source[path] = (res, ValueSource.min)
self.value_source[path] = (res, ValueSource.min)
else:
potential_target = (path, TargetType.NUM, TargetStatus.MAX)
self.record_source(ValueSource.max)
self.value_source[path] = (res, ValueSource.max)
self.potential_targets.add(potential_target)
self.value_source[path] = (res, ValueSource.max)
return res
elif number_body.__contains__("minimum"):
if np.random.random() < 0.2:
res = number_body["minimum"]
potential_target = (path, TargetType.NUM, TargetStatus.MIN)
self.potential_targets.add(potential_target)
self.value_source[path] = (res, ValueSource.min)
self.record_source(ValueSource.min)
else:
res = np.random.randint(0, 999999)
self.value_source[path] = (res, ValueSource.middle)
self.record_source(ValueSource.middle)
return res
elif number_body.__contains__("maximum"):
if np.random.random() < 0.2:
res = number_body["maximum"]
potential_target = (path, TargetType.NUM, TargetStatus.MAX)
self.potential_targets.add(potential_target)
self.value_source[path] = (res, ValueSource.max)
self.record_source(ValueSource.max)
else:
res = np.random.randint(0, 999999)
self.value_source[path] = (res, ValueSource.middle)
self.record_source(ValueSource.middle)
return res
else:
res = np.random.randint(0, 999999)
self.value_source[path] = (res, ValueSource.middle)
self.record_source(ValueSource.middle)
return res
def integer_factory(self, path, integer_body={}):
if self.should_use_example(path, integer_body):
val = self.use_example(path, integer_body)
self.record_source(ValueSource.example)
self.value_source[path] = (val, ValueSource.example)
return val
if path in self.ref_dict:
ref = self._build_ref(self.ref_dict[path])
self.record_source(ValueSource.reference)
self.value_source[path] = (ref, ValueSource.reference)
return ref
if integer_body.__contains__("enum"):
self.record_source(ValueSource.enum)
enum = np.random.choice(integer_body["enum"])
potential_target = (path, TargetType.ENUM, enum)
self.potential_targets.add(potential_target)
self.value_source[path] = (enum, ValueSource.enum)
return enum
if self.should_use_dictionary_value(path):
value = self.runtime_dictionary.generate_value_from_dictionary(path, self.method, integer_body)
if isinstance(value, int):
self.record_source(ValueSource.reference)
self.value_source[path] = (value, ValueSource.reference)
return value
# bypass for enum
if np.random.random() < 0.5:
res = np.random.randint(0, 2)
self.value_source[path] = (res, ValueSource.random)
self.record_source(ValueSource.random)
return res
if integer_body.__contains__("minimum") and integer_body.__contains__("maximum"):
if np.random.random() < 0.5:
res = np.random.randint(integer_body["minimum"], integer_body["maximum"], dtype=np.int64)
potential_target = (path, TargetType.NUM, TargetStatus.MIDDLE)
self.potential_targets.add(potential_target)
self.value_source[path] = (res, ValueSource.middle)
self.record_source(ValueSource.middle)
else:
res = np.random.choice([integer_body["minimum"], integer_body["maximum"]])
if res == integer_body['minimum']:
potential_target = (path, TargetType.NUM, TargetStatus.MIN)
self.value_source[path] = (res, ValueSource.min)
self.record_source(ValueSource.min)
else:
potential_target = (path, TargetType.NUM, TargetStatus.MAX)
self.value_source[path] = (res, ValueSource.max)
self.record_source(ValueSource.max)
self.potential_targets.add(potential_target)
self.value_source[path] = (res, ValueSource.random)
return res
elif integer_body.__contains__("minimum"):
if np.random.random() < 0.2:
res = integer_body["minimum"]
potential_target = (path, TargetType.NUM, TargetStatus.MIN)
self.potential_targets.add(potential_target)
self.value_source[path] = (res, ValueSource.min)
self.record_source(ValueSource.min)
else:
res = np.random.randint(0, 999999)
self.value_source[path] = (res, ValueSource.middle)
self.record_source(ValueSource.middle)
self.value_source[path] = (res, ValueSource.random)
return res
elif integer_body.__contains__("maximum"):
if np.random.random() < 0.2:
res = integer_body["maximum"]
potential_target = (path, TargetType.NUM, TargetStatus.MAX)
self.potential_targets.add(potential_target)
self.value_source[path] = (res, ValueSource.max)
self.record_source(ValueSource.max)
else:
res = np.random.randint(0, 999999)
self.value_source[path] = (res, ValueSource.middle)
self.record_source(ValueSource.middle)
return res
else:
res = np.random.randint(0, 999999)
self.value_source[path] = (res, ValueSource.random)
self.record_source(ValueSource.random)
return res
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