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-2021-40 | null | Pillow before 8.1.1 allows attackers to cause a denial of service (memory consumption) because the reported size of a contained image is not properly checked for a BLP container, and thus an attempted memory allocation can be very large. | {'GHSA-f4w8-cv6p-x6r5', 'CVE-2021-27921'} | 2021-03-23T19:49:00Z | 2021-03-03T09:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZTSY25UJU7NJUFHH3HWT575LT4TDFWBZ/', 'https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/S7G44Z33J4BNI2DPDROHWGVG2U7ZH5JU/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/TQQY6472RX4J2SUJENWDZAWKTJJGP2ML/', 'https://github.com/advisories/GHSA-f4w8-cv6p-x6r5'} | null |
PyPI | GHSA-43jf-985q-588j | Multiple `CHECK`-fails in `function.cc` in TensowFlow | ### Impact
A malicious user can cause a denial of service by altering a `SavedModel` such that [assertions in `function.cc`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/function.cc) would be falsified and crash the Python interpreter.
### Patches
We have patched the issue in GitHub commits [dcc21c7bc972b10b6fb95c2fb0f4ab5a59680ec2](https://github.com/tensorflow/tensorflow/commit/dcc21c7bc972b10b6fb95c2fb0f4ab5a59680ec2) and [3d89911481ba6ebe8c88c1c0b595412121e6c645](https://github.com/tensorflow/tensorflow/commit/3d89911481ba6ebe8c88c1c0b595412121e6c645).
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-2022-23586'} | 2022-03-03T05:14:05.260639Z | 2022-02-09T23:27:08Z | MODERATE | null | {'CWE-617'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-43jf-985q-588j', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/function.cc', 'https://github.com/tensorflow/tensorflow/commit/dcc21c7bc972b10b6fb95c2fb0f4ab5a59680ec2', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/3d89911481ba6ebe8c88c1c0b595412121e6c645', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23586'} | null |
PyPI | GHSA-r6v3-hpxj-r8rv | Code Injection in PyXDG | A code injection issue was discovered in PyXDG before 0.26 via crafted Python code in a Category element of a Menu XML document in a .menu file. XDG_CONFIG_DIRS must be set up to trigger xdg.Menu.parse parsing within the directory containing this file. This is due to a lack of sanitization in xdg/Menu.py before an eval call. | {'CVE-2019-12761'} | 2022-03-03T05:14:11.617272Z | 2019-06-07T20:56:27Z | HIGH | null | {'CWE-94'} | {'https://nvd.nist.gov/vuln/detail/CVE-2019-12761', 'https://lists.debian.org/debian-lts-announce/2021/08/msg00003.html', 'https://gist.github.com/dhondta/b45cd41f4186110a354dc7272916feba', 'https://lists.debian.org/debian-lts-announce/2019/06/msg00006.html', 'https://snyk.io/vuln/SNYK-PYTHON-PYXDG-174562'} | null |
PyPI | PYSEC-2021-176 | null | TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.ImmutableConst`(https://www.tensorflow.org/api_docs/python/tf/raw_ops/ImmutableConst) with a `dtype` of `tf.resource` or `tf.variant` results in a segfault in the implementation as code assumes that the tensor contents are pure scalars. We have patched the issue in 4f663d4b8f0bec1b48da6fa091a7d29609980fa4 and will release TensorFlow 2.5.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. If using `tf.raw_ops.ImmutableConst` in code, you can prevent the segfault by inserting a filter for the `dtype` argument. | {'GHSA-g4h2-gqm3-c9wq', 'CVE-2021-29539'} | 2021-08-27T03:22:28.395200Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g4h2-gqm3-c9wq', 'https://github.com/tensorflow/tensorflow/commit/4f663d4b8f0bec1b48da6fa091a7d29609980fa4'} | null |
PyPI | PYSEC-2014-27 | null | registerConfiglet.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to execute Python code via unspecified vectors, related to the admin interface. | {'CVE-2012-5485'} | 2021-09-01T08:44:28.919312Z | 2014-09-30T14:55:00Z | null | null | null | {'https://plone.org/products/plone-hotfix/releases/20121106', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://plone.org/products/plone/security/advisories/20121106/01', 'http://rhn.redhat.com/errata/RHSA-2014-1194.html'} | null |
PyPI | PYSEC-2021-526 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of the `SVDF` TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/7f283ff806b2031f407db64c4d3edcda8fb9f9f5/tensorflow/lite/kernels/svdf.cc#L99-L102). An attacker can craft a model such that `params->rank` would be 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. | {'CVE-2021-29598', 'GHSA-pmpr-55fj-r229'} | 2021-12-09T06:34:58.584252Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pmpr-55fj-r229', 'https://github.com/tensorflow/tensorflow/commit/6841e522a3e7d48706a02e8819836e809f738682'} | null |
PyPI | PYSEC-2020-176 | null | PyYAML 5.1 through 5.1.2 has insufficient restrictions on the load and load_all functions because of a class deserialization issue, e.g., Popen is a class in the subprocess module. NOTE: this issue exists because of an incomplete fix for CVE-2017-18342. | {'CVE-2019-20477', 'GHSA-3pqx-4fqf-j49f'} | 2020-03-01T00:15:00Z | 2020-02-19T04:15:00Z | null | null | null | {'https://www.exploit-db.com/download/47655', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/33VBUY73AA6CTTYL3LRWHNFDULV7PFPN/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/52N5XS73Z5S4ZN7I7R56ICCPCTKCUV4H/', 'https://github.com/advisories/GHSA-3pqx-4fqf-j49f', 'https://github.com/yaml/pyyaml/blob/master/CHANGES'} | null |
PyPI | GHSA-36vm-xw34-x4pj | CHECK-fail in `tf.raw_ops.IRFFT` | ### Impact
An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.IRFFT`:
```python
import tensorflow as tf
values = [-10.0] * 130
values[0] = -9.999999999999995
inputs = tf.constant(values, shape=[10, 13], dtype=tf.float32)
inputs = tf.cast(inputs, dtype=tf.complex64)
fft_length = tf.constant([0], shape=[1], dtype=tf.int32)
tf.raw_ops.IRFFT(input=inputs, fft_length=fft_length)
```
The above example causes Eigen code to operate on an empty matrix. This triggers on an assertion and causes program termination.
### Patches
We have patched the issue in GitHub commit [1c56f53be0b722ca657cbc7df461ed676c8642a2](https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2).
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 Yakun Zhang and Ying Wang of Baidu X-Team. | {'CVE-2021-29562'} | 2022-03-03T05:13:05.634583Z | 2021-05-21T14:25:02Z | LOW | null | {'CWE-617'} | {'https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-36vm-xw34-x4pj', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29562'} | null |
PyPI | GHSA-3j5x-7ccf-ppgm | Cross-site scripting in recommender-xblock | Recommender before 1.3.1 allows XSS. | {'CVE-2018-20858'} | 2021-08-17T21:16:29Z | 2019-08-21T16:15:33Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2018-20858', 'https://github.com/edx/RecommenderXBlock/pull/2', 'https://groups.google.com/forum/#!topic/openedx-announce/SF8Sn6MuUTg'} | null |
PyPI | PYSEC-2020-82 | null | libImaging/SgiRleDecode.c in Pillow before 6.2.2 has an SGI buffer overflow. | {'CVE-2020-5311'} | 2020-07-10T17:06:00Z | 2020-01-03T01:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2MMU3WT2X64GS5WHDPKKC2WZA7UIIQ3A/', 'https://pillow.readthedocs.io/en/stable/releasenotes/6.2.2.html', 'https://usn.ubuntu.com/4272-1/', 'https://github.com/python-pillow/Pillow/commit/a79b65c47c7dc6fe623aadf09aa6192fc54548f3', 'https://access.redhat.com/errata/RHSA-2020:0580', 'https://access.redhat.com/errata/RHSA-2020:0566', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3DUMIBUYGJRAVJCTFUWBRLVQKOUTVX5P/', 'https://www.debian.org/security/2020/dsa-4631'} | null |
PyPI | PYSEC-2019-130 | null | typed_ast 1.3.0 and 1.3.1 has a handle_keywordonly_args out-of-bounds read. An attacker with the ability to cause a Python interpreter to parse Python source (but not necessarily execute it) may be able to crash the interpreter process. This could be a concern, for example, in a web-based service that parses (but does not execute) Python code. (This issue also affected certain Python 3.8.0-alpha prereleases.) | {'CVE-2019-19274', 'GHSA-m3jw-62m7-jjcm'} | 2020-03-14T02:15:00Z | 2019-11-26T15:15:00Z | null | null | null | {'https://github.com/python/typed_ast/commit/156afcb26c198e162504a57caddfe0acd9ed7dce', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/LG5H4Q6LFVRX7SFXLBEJMNQFI4T5SCEA/', 'https://bugs.python.org/issue36495', 'https://github.com/python/typed_ast/commit/dc317ac9cff859aa84eeabe03fb5004982545b3b', 'https://github.com/advisories/GHSA-m3jw-62m7-jjcm', 'https://github.com/python/cpython/commit/dcfcd146f8e6fc5c2fc16a4c192a0c5f5ca8c53c', 'https://github.com/python/cpython/commit/a4d78362397fc3bced6ea80fbc7b5f4827aec55e'} | null |
PyPI | GHSA-7r87-cj48-wj45 | Potential Captcha Validate Bypass in flask-session-captcha | ### Impact
flask-session-captcha is a package which allows users to extend Flask by adding an image based captcha stored in a server side session.
The `captcha.validate()` function would return `None` if passed no value (e.g. by submitting a request with an empty form).
If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed.
Sample vulnerable code:
```python
if captcha.validate() == False:
... # abort
else:
... # do stuff
```
### Patches
A new version (1.2.1) is available that fixes the issue.
### Workarounds
Users can workaround the issue by not explicitly checking that the value is False.
Checking the return value less explicitly should still work.
```python
if not captcha.validate():
... # abort
else:
... # do stuff
```
```python
if captcha.validate():
... # do stuff
else:
... # abort
```
### References
https://github.com/Tethik/flask-session-captcha/pull/27
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [the github repo](https://github.com/Tethik/flask-session-captcha)
| {'CVE-2022-24880'} | 2022-04-27T18:31:59.848285Z | 2022-04-26T21:19:52Z | MODERATE | null | {'CWE-394', 'CWE-253', 'CWE-754'} | {'https://github.com/Tethik/flask-session-captcha/commit/2811ae23a38d33b620fb7a07de8837c6d65c13e4', 'https://nvd.nist.gov/vuln/detail/CVE-2022-24880', 'https://github.com/Tethik/flask-session-captcha/releases/tag/v1.2.1', 'https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45', 'https://github.com/Tethik/flask-session-captcha/pull/27', 'https://github.com/Tethik/flask-session-captcha'} | null |
PyPI | PYSEC-2022-50 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. 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-23hm-7w47-xw72', 'CVE-2022-21726'} | 2022-03-09T00:17:30.059421Z | 2022-02-03T11:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/dequantize_op.cc#L92-L153', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-23hm-7w47-xw72', 'https://github.com/tensorflow/tensorflow/commit/23968a8bf65b009120c43b5ebcceaf52dbc9e943'} | null |
PyPI | PYSEC-2020-199 | null | The safe_eval function in Ansible before 1.5.4 does not properly restrict the code subset, which allows remote attackers to execute arbitrary code via crafted instructions. | {'CVE-2014-4657'} | 2021-07-02T02:41:33.107799Z | 2020-02-20T15:15:00Z | null | null | null | {'https://www.securityfocus.com/bid/68232', 'https://github.com/ansible/ansible/blob/release1.5.5/CHANGELOG.md'} | null |
PyPI | GHSA-3xv8-3j54-hgrp | Out-of-bounds read in Pillow | In libImaging/PcxDecode.c in Pillow before 6.2.3 and 7.x before 7.0.1, an out-of-bounds read can occur when reading PCX files where state->shuffle is instructed to read beyond state->buffer. | {'CVE-2020-10378'} | 2022-03-03T05:13:25.261642Z | 2021-11-03T18:04:53Z | MODERATE | null | {'CWE-125'} | {'https://github.com/python-pillow/Pillow/commits/master/src/libImaging', 'https://github.com/python-pillow/Pillow/pull/4538', 'https://github.com/python-pillow/Pillow/commit/6a83e4324738bb0452fbe8074a995b1c73f08de7#diff-9478f2787e3ae9668a15123b165c23ac', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/HOKHNWV2VS5GESY7IBD237E7C6T3I427/', 'https://usn.ubuntu.com/4430-1/', 'https://github.com/python-pillow/Pillow', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10378', 'https://pillow.readthedocs.io/en/stable/releasenotes/6.2.3.html', 'https://github.com/pypa/advisory-db/blob/7872b0a91b4d980f749e6d75a81f8cc1af32829f/vulns/pillow/PYSEC-2020-77.yaml', 'https://usn.ubuntu.com/4430-2/', 'https://pillow.readthedocs.io/en/stable/releasenotes/7.1.0.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/BEBCPE4F2VHTIT6EZA2YZQZLPVDEBJGD/'} | null |
PyPI | GHSA-pmpr-55fj-r229 | Division by zero in TFLite's implementation of `SVDF` | ### Impact
The implementation of the `SVDF` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/7f283ff806b2031f407db64c4d3edcda8fb9f9f5/tensorflow/lite/kernels/svdf.cc#L99-L102):
```cc
const int rank = params->rank;
...
TF_LITE_ENSURE_EQ(context, num_filters % rank, 0);
```
An attacker can craft a model such that `params->rank` would be 0.
### Patches
We have patched the issue in GitHub commit [6841e522a3e7d48706a02e8819836e809f738682](https://github.com/tensorflow/tensorflow/commit/6841e522a3e7d48706a02e8819836e809f738682).
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-2021-29598'} | 2022-03-03T05:13:07.745732Z | 2021-05-21T14:27:58Z | LOW | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pmpr-55fj-r229', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29598', 'https://github.com/tensorflow/tensorflow/commit/6841e522a3e7d48706a02e8819836e809f738682'} | null |
PyPI | PYSEC-2021-463 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedMul` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/87cf4d3ea9949051e50ca3f071fc909538a51cd0/tensorflow/core/kernels/quantized_mul_op.cc#L287-L290) assumes that the 4 arguments are always valid scalars and tries to access the numeric value directly. 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. 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-2021-29535', 'GHSA-m3f9-w3p3-p669'} | 2021-12-09T06:34:48.800365Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m3f9-w3p3-p669', 'https://github.com/tensorflow/tensorflow/commit/efea03b38fb8d3b81762237dc85e579cc5fc6e87'} | null |
PyPI | PYSEC-2021-199 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.IRFFT`. 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-2021-29562', 'GHSA-36vm-xw34-x4pj'} | 2021-08-27T03:22:32.482991Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-36vm-xw34-x4pj'} | null |
PyPI | PYSEC-2021-414 | null | TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SplitV` can trigger a segfault is an attacker supplies negative arguments. This occurs whenever `size_splits` contains more than one value and at least one value is negative. 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-cpf4-wx82-gxp6', 'CVE-2021-41222'} | 2021-11-13T06:52:45.470098Z | 2021-11-05T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/25d622ffc432acc736b14ca3904177579e733cc6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cpf4-wx82-gxp6'} | null |
PyPI | PYSEC-2022-108 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `UnravelIndex` is vulnerable to a division by zero caused by an integer overflow bug. 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-34f9-hjfq-rr8j', 'CVE-2022-21729'} | 2022-03-09T00:18:23.531782Z | 2022-02-03T13:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/58b34c6c8250983948b5a781b426f6aa01fd47af', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-34f9-hjfq-rr8j', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/unravel_index_op.cc#L36-L135'} | null |
PyPI | PYSEC-2022-27 | null | twisted is an event-driven networking engine written in Python. In affected versions twisted exposes cookies and authorization headers when following cross-origin redirects. This issue is present in the `twited.web.RedirectAgent` and `twisted.web. BrowserLikeRedirectAgent` functions. Users are advised to upgrade. There are no known workarounds. | {'GHSA-92x2-jw7w-xvvx', 'CVE-2022-21712'} | 2022-02-15T06:31:29.205025Z | 2022-02-07T22:15:00Z | null | null | null | {'https://pypi.org/project/Twisted/', 'https://github.com/twisted/twisted/commit/af8fe78542a6f2bf2235ccee8158d9c88d31e8e2', 'https://github.com/twisted/twisted/releases/tag/twisted-22.1.0', 'https://github.com/twisted/twisted/security/advisories/GHSA-92x2-jw7w-xvvx', 'https://nvd.nist.gov/vuln/detail/CVE-2022-21712'} | null |
PyPI | PYSEC-2019-147 | null | In Apache Airflow 1.8.2 and earlier, an authenticated user can execute code remotely on the Airflow webserver by creating a special object. | {'GHSA-8fg4-j562-mjrc', 'CVE-2017-15720'} | 2021-07-05T00:01:17.000324Z | 2019-01-23T17:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-8fg4-j562-mjrc', 'https://lists.apache.org/thread.html/ade4d54ebf614f68dc81a08891755e60ea58ba88e0209233eeea5f57@%3Cdev.airflow.apache.org%3E'} | null |
PyPI | PYSEC-2016-2 | null | Cross-site scripting (XSS) vulnerability in the dismissChangeRelatedObjectPopup function in contrib/admin/static/admin/js/admin/RelatedObjectLookups.js in Django before 1.8.14, 1.9.x before 1.9.8, and 1.10.x before 1.10rc1 allows remote attackers to inject arbitrary web script or HTML via vectors involving unsafe usage of Element.innerHTML. | {'CVE-2016-6186'} | 2021-09-01T08:35:44.164135Z | 2016-08-05T15:59:00Z | null | null | null | {'http://rhn.redhat.com/errata/RHSA-2016-1595.html', 'https://github.com/django/django/commit/f68e5a99164867ab0e071a936470958ed867479d', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DMLLFAUT4J4IP4P2KI4NOVWRMHA22WUJ/', 'https://github.com/django/django/commit/d03bf6fe4e9bf5b07de62c1a271c4b41a7d3d158', 'http://rhn.redhat.com/errata/RHSA-2016-1596.html', 'http://www.securityfocus.com/archive/1/538947/100/0/threaded', 'http://seclists.org/fulldisclosure/2016/Jul/53', 'http://www.securityfocus.com/bid/92058', 'http://www.securitytracker.com/id/1036338', 'http://packetstormsecurity.com/files/137965/Django-3.3.0-Script-Insertion.html', 'http://www.ubuntu.com/usn/USN-3039-1', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/KHHPN6MISX5I6UTXQHYLPTLEEUE6WDXW/', 'http://www.vulnerability-lab.com/get_content.php?id=1869', 'https://www.exploit-db.com/exploits/40129/', 'https://www.djangoproject.com/weblog/2016/jul/18/security-releases/', 'http://rhn.redhat.com/errata/RHSA-2016-1594.html', 'http://www.debian.org/security/2016/dsa-3622'} | null |
PyPI | PYSEC-2018-73 | null | By linking to a specific url in Plone 2.5-5.1rc1 with a parameter, an attacker could send you to his own website. On its own this is not so bad: the attacker could more easily link directly to his own website instead. But in combination with another attack, you could be sent to the Plone login form and login, then get redirected to the specific url, and then get a second redirect to the attacker website. (The specific url can be seen by inspecting the hotfix code, but we don't want to make it too easy for attackers by spelling it out here.) | {'CVE-2017-1000484', 'GHSA-xvwv-6wvx-px9x'} | 2021-08-25T04:30:17.052846Z | 2018-01-03T20:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-xvwv-6wvx-px9x', 'https://plone.org/security/hotfix/20171128/an-open-redirection-when-calling-a-specific-url'} | null |
PyPI | PYSEC-2010-13 | null | MoinMoin 1.7.x before 1.7.3 and 1.8.x before 1.8.3 checks parent ACLs in certain inappropriate circumstances during processing of hierarchical ACLs, which allows remote attackers to bypass intended access restrictions by requesting an item, a different vulnerability than CVE-2008-6603. | {'CVE-2009-4762'} | 2010-05-27T05:47:00Z | 2010-03-29T20:30:00Z | null | null | null | {'http://www.securityfocus.com/bid/35277', 'http://hg.moinmo.in/moin/1.8/rev/897cdbe9e8f2', 'http://www.debian.org/security/2010/dsa-2014', 'http://moinmo.in/SecurityFixes', 'http://hg.moinmo.in/moin/1.7/rev/897cdbe9e8f2', 'http://secunia.com/advisories/39887', 'http://www.vupen.com/english/advisories/2010/1208', 'http://ubuntu.com/usn/usn-941-1', 'http://www.vupen.com/english/advisories/2010/0600'} | null |
PyPI | PYSEC-2021-802 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a division by zero error in LSH [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/lsh_projection.cc#L118). We have patched the issue in GitHub commit 0575b640091680cfb70f4dd93e70658de43b94f9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick thiscommit 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-2021-37691', 'GHSA-27qf-jwm8-g7f3'} | 2021-12-09T06:35:40.308304Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/0575b640091680cfb70f4dd93e70658de43b94f9', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-27qf-jwm8-g7f3'} | null |
PyPI | GHSA-8rh6-h94m-vj54 | Incorrect Comparison in cvxopt | Incomplete string comparison vulnerability exits in cvxopt.org cvxop <= 1.2.6 in APIs (cvxopt.cholmod.diag, cvxopt.cholmod.getfactor, cvxopt.cholmod.solve, cvxopt.cholmod.spsolve), which allows attackers to conduct Denial of Service attacks by construct fake Capsule objects. | {'CVE-2021-41500'} | 2022-03-03T05:12:30.492737Z | 2022-01-07T00:01:11Z | HIGH | null | {'CWE-697'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-41500', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/CXTPM3DGVYTYQ54OFCMXZVWVOMR7JM2D/', 'https://github.com/cvxopt/cvxopt', 'https://github.com/cvxopt/cvxopt/issues/193', 'https://github.com/cvxopt/cvxopt/commit/d5a21cf1da62e4269176384b1ff62edac5579f94'} | null |
PyPI | PYSEC-2020-101 | null | The command-line "safety" package for Python has a potential security issue. There are two Python characteristics that allow malicious code to “poison-pill” command-line Safety package detection routines by disguising, or obfuscating, other malicious or non-secure packages. This vulnerability is considered to be of low severity because the attack makes use of an existing Python condition, not the Safety tool itself. This can happen if: You are running Safety in a Python environment that you don’t trust. You are running Safety from the same Python environment where you have your dependencies installed. Dependency packages are being installed arbitrarily or without proper verification. Users can mitigate this issue by doing any of the following: Perform a static analysis by installing Docker and running the Safety Docker image: $ docker run --rm -it pyupio/safety check -r requirements.txt Run Safety against a static dependencies list, such as the requirements.txt file, in a separate, clean Python environment. Run Safety from a Continuous Integration pipeline. Use PyUp.io, which runs Safety in a controlled environment and checks Python for dependencies without any need to install them. Use PyUp's Online Requirements Checker. | {'CVE-2020-5252', 'GHSA-7q25-qrjw-6fg2'} | 2020-03-30T16:16:00Z | 2020-03-23T23:15:00Z | null | null | null | {'https://github.com/akoumjian/python-safety-vuln', 'https://pyup.io/posts/patched-vulnerability/', 'https://github.com/pyupio/safety/security/advisories/GHSA-7q25-qrjw-6fg2'} | null |
PyPI | GHSA-x823-j7c4-vpc5 | Cross-site scripting in sickrage | In SiCKRAGE, versions 9.3.54.dev1 to 10.0.11.dev1 are vulnerable to Reflected Cross-Site-Scripting (XSS) due to user input not being validated properly in the `quicksearch` feature. Therefore, an attacker can steal a user's sessionID to masquerade as a victim user, to carry out any actions in the context of the user. | {'CVE-2021-25926'} | 2022-03-03T05:13:33.888255Z | 2021-04-20T16:31:43Z | MODERATE | null | {'CWE-79'} | {'https://github.com/SiCKRAGE/SiCKRAGE/commit/9f42426727e16609ad3d1337f6637588b8ed28e4', 'https://nvd.nist.gov/vuln/detail/CVE-2021-25926', 'https://www.whitesourcesoftware.com/vulnerability-database/CVE-2021-25926,'} | null |
PyPI | PYSEC-2021-551 | null | TensorFlow is an end-to-end open source platform for machine learning. Sending invalid argument for `row_partition_types` of `tf.raw_ops.RaggedTensorToTensor` API results in a null pointer dereference and undefined behavior. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L328) accesses the first element of a user supplied list of values without validating that the provided list is not empty. We have patched the issue in GitHub commit 301ae88b331d37a2a16159b65b255f4f9eb39314. 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-hwr7-8gxx-fj5p', 'CVE-2021-37638'} | 2021-12-09T06:35:02.233432Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/301ae88b331d37a2a16159b65b255f4f9eb39314', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hwr7-8gxx-fj5p'} | null |
PyPI | PYSEC-2014-50 | null | The error pages in Plone before 4.2.3 and 4.3 before beta 1 allow remote attackers to obtain random numbers and derive the PRNG state for password resets via unspecified vectors. NOTE: this identifier was SPLIT per ADT2 due to different vulnerability types. CVE-2012-6661 was assigned for the PRNG reseeding issue in Zope. | {'CVE-2012-5508'} | 2021-09-01T08:44:31.321280Z | 2014-11-03T22:55:00Z | null | null | null | {'https://bugs.launchpad.net/zope2/+bug/1071067', 'https://plone.org/products/plone/security/advisories/20121106/24', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://plone.org/products/plone-hotfix/releases/20121124'} | null |
PyPI | PYSEC-2021-101 | null | The dashboard component of StackLift LocalStack 0.12.6 allows attackers to inject arbitrary shell commands via the functionName parameter. | {'CVE-2021-32090', 'GHSA-hpr6-f4vq-mxch'} | 2021-06-22T04:54:56.080124Z | 2021-05-07T05:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-hpr6-f4vq-mxch', 'https://portswigger.net/daily-swig/localstack-zero-day-vulnerabilities-chained-to-achieve-remote-takeover-of-local-instances', 'https://blog.sonarsource.com/hack-the-stack-with-localstack'} | null |
PyPI | GHSA-8vj2-vxx3-667w | Arbitrary expression injection in Pillow | PIL.ImageMath.eval in Pillow before 9.0.0 allows evaluation of arbitrary expressions, such as ones that use the Python exec method `ImageMath.eval("exec(exit())")`.
While Pillow 9.0.0 restricted top-level builtins available to PIL.ImageMath.eval(), it did not prevent builtins available to lambda expressions. These are now also restricted in 9.0.1. | {'CVE-2022-22817'} | 2022-03-11T23:47:55.666690Z | 2022-01-12T20:07:33Z | CRITICAL | null | {'CWE-74'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-22817', 'https://lists.debian.org/debian-lts-announce/2022/01/msg00018.html', 'https://pillow.readthedocs.io/en/stable/releasenotes/9.0.0.html#restrict-builtins-available-to-imagemath-eval', 'https://github.com/python-pillow/Pillow/commit/8531b01d6cdf0b70f256f93092caa2a5d91afc11', 'https://github.com/python-pillow/Pillow', 'https://pillow.readthedocs.io/en/stable/releasenotes/9.0.1.html#security', 'https://www.debian.org/security/2022/dsa-5053'} | null |
PyPI | PYSEC-2020-228 | null | An insecure-credentials flaw was found in all openstack-cinder versions before openstack-cinder 14.1.0, all openstack-cinder 15.x.x versions before openstack-cinder 15.2.0 and all openstack-cinder 16.x.x versions before openstack-cinder 16.1.0. When using openstack-cinder with the Dell EMC ScaleIO or VxFlex OS backend storage driver, credentials for the entire backend are exposed in the ``connection_info`` element in all Block Storage v3 Attachments API calls containing that element. This flaw enables an end-user to create a volume, make an API call to show the attachment detail information, and retrieve a username and password that may be used to connect to another user's volume. Additionally, these credentials are valid for the ScaleIO or VxFlex OS Management API, should an attacker discover the Management API endpoint. Source: OpenStack project | {'CVE-2020-10755'} | 2021-08-27T03:21:56.949334Z | 2020-06-10T17:15:00Z | null | null | null | {'https://wiki.openstack.org/wiki/OSSN/OSSN-0086', 'https://usn.ubuntu.com/4420-1/', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-10755'} | null |
PyPI | PYSEC-2021-228 | null | TensorFlow is an end-to-end open source platform for machine learning. TFlite graphs must not have loops between nodes. However, this condition was not checked and an attacker could craft models that would result in infinite loop during evaluation. In certain cases, the infinite loop would be replaced by stack overflow due to too many recursive calls. For example, the `While` implementation(https://github.com/tensorflow/tensorflow/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc) could be tricked into a scneario where both the body and the loop subgraphs are the same. Evaluating one of the subgraphs means calling the `Eval` function for the other and this quickly exhaust all stack space. 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. 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-2021-29591', 'GHSA-cwv3-863g-39vx'} | 2021-08-27T03:22:37.582991Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4', 'https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cwv3-863g-39vx'} | null |
PyPI | PYSEC-2021-678 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by controlling the values of `num_segments` tensor argument for `UnsortedSegmentJoin`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a2a607db15c7cd01d754d37e5448d72a13491bdb/tensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L93) assumes that the `num_segments` tensor is a valid scalar. Since the tensor is empty the `CHECK` involved in `.scalar<T>()()` that checks that the number of elements is exactly 1 will be invalidated and this would result in process termination. 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-2021-29552', 'GHSA-jhq9-wm9m-cf89'} | 2021-12-09T06:35:23.792052Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jhq9-wm9m-cf89', 'https://github.com/tensorflow/tensorflow/commit/704866eabe03a9aeda044ec91a8d0c83fc1ebdbe'} | null |
PyPI | PYSEC-2021-37 | null | An issue was discovered in Pillow before 8.1.1. In TiffDecode.c, there is an out-of-bounds read in TiffreadRGBATile via invalid tile boundaries. | {'CVE-2021-25291', 'GHSA-mvg9-xffr-p774'} | 2021-03-22T14:09:00Z | 2021-03-19T04:15:00Z | null | null | null | {'https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html', 'https://github.com/advisories/GHSA-mvg9-xffr-p774'} | null |
PyPI | PYSEC-2021-382 | null | qutebrowser is an open source keyboard-focused browser with a minimal GUI. Starting with qutebrowser v1.7.0, the Windows installer for qutebrowser registers a `qutebrowserurl:` URL handler. With certain applications, opening a specially crafted `qutebrowserurl:...` URL can lead to execution of qutebrowser commands, which in turn allows arbitrary code execution via commands such as `:spawn` or `:debug-pyeval`. Only Windows installs where qutebrowser is registered as URL handler are affected. The issue has been fixed in qutebrowser v2.4.0. The fix also adds additional hardening for potential similar issues on Linux (by adding the new --untrusted-args flag to the .desktop file), though no such vulnerabilities are known. | {'CVE-2021-41146', 'GHSA-vw27-fwjf-5qxm'} | 2021-10-28T05:27:07.120992Z | 2021-10-21T18:15:00Z | null | null | null | {'https://github.com/qutebrowser/qutebrowser/commit/8f46ba3f6dc7b18375f7aa63c48a1fe461190430', 'https://github.com/qutebrowser/qutebrowser/security/advisories/GHSA-vw27-fwjf-5qxm'} | null |
PyPI | GHSA-6f89-8j54-29xf | Heap buffer overflow in `FractionalAvgPoolGrad` | ### Impact
The implementation of `tf.raw_ops.FractionalAvgPoolGrad` is vulnerable to a heap buffer overflow:
```python
import tensorflow as tf
orig_input_tensor_shape = tf.constant([1, 3, 2, 3], shape=[4], dtype=tf.int64)
out_backprop = tf.constant([2], shape=[1, 1, 1, 1], dtype=tf.int64)
row_pooling_sequence = tf.constant([1], shape=[1], dtype=tf.int64)
col_pooling_sequence = tf.constant([1], shape=[1], dtype=tf.int64)
tf.raw_ops.FractionalAvgPoolGrad(
orig_input_tensor_shape=orig_input_tensor_shape, out_backprop=out_backprop,
row_pooling_sequence=row_pooling_sequence,
col_pooling_sequence=col_pooling_sequence, overlapping=False)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/dcba796a28364d6d7f003f6fe733d82726dda713/tensorflow/core/kernels/fractional_avg_pool_op.cc#L216) fails to validate that the pooling sequence arguments have enough elements as required by the `out_backprop` tensor shape.
### Patches
We have patched the issue in GitHub commit [12c727cee857fa19be717f336943d95fca4ffe4f](https://github.com/tensorflow/tensorflow/commit/12c727cee857fa19be717f336943d95fca4ffe4f).
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-2021-29578'} | 2022-03-03T05:12:50.602818Z | 2021-05-21T14:26:21Z | LOW | null | {'CWE-787', 'CWE-119'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6f89-8j54-29xf', 'https://github.com/tensorflow/tensorflow/commit/12c727cee857fa19be717f336943d95fca4ffe4f', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29578'} | null |
PyPI | PYSEC-2021-697 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. 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-2021-29571', 'GHSA-whr9-vfh2-7hm6'} | 2021-12-09T06:35:27.008570Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6'} | null |
PyPI | GHSA-jqmc-fxxp-r589 | Deserialization of Untrusted Data in Tendenci | Tendenci 12.0.10 allows unrestricted deserialization in apps\helpdesk\views\staff.py. | {'CVE-2020-14942'} | 2022-03-03T05:12:54.288360Z | 2021-06-18T18:31:05Z | HIGH | null | {'CWE-502'} | {'https://github.com/tendenci/tendenci/issues/867', 'https://nvd.nist.gov/vuln/detail/CVE-2020-14942'} | null |
PyPI | PYSEC-2017-40 | null | Sanic before 0.5.1 allows reading arbitrary files with directory traversal, as demonstrated by the /static/..%2f substring. | {'CVE-2017-16762'} | 2021-07-05T00:01:27.045850Z | 2017-11-10T09:29:00Z | null | null | null | {'https://github.com/channelcat/sanic/releases/tag/0.5.1', 'https://github.com/channelcat/sanic/issues/633'} | null |
PyPI | PYSEC-2019-110 | null | An issue was discovered in Pillow before 6.2.0. When reading specially crafted invalid image files, the library can either allocate very large amounts of memory or take an extremely long period of time to process the image. | {'CVE-2019-16865', 'GHSA-j7mj-748x-7p78'} | 2020-02-18T16:15:00Z | 2019-10-04T22:15:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2020:0681', 'https://usn.ubuntu.com/4272-1/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/LYDXD7EE4YAEVSTNIFZKNVPRVJX5ZOG3/', 'https://access.redhat.com/errata/RHSA-2020:0683', 'https://access.redhat.com/errata/RHSA-2020:0578', 'https://access.redhat.com/errata/RHSA-2020:0580', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/EMJBUZQGQ2Q7HXYCQVRLU7OXNC7CAWWU/', 'https://access.redhat.com/errata/RHSA-2020:0694', 'https://access.redhat.com/errata/RHSA-2020:0566', 'https://github.com/advisories/GHSA-j7mj-748x-7p78', 'https://www.debian.org/security/2020/dsa-4631', 'https://pillow.readthedocs.io/en/latest/releasenotes/6.2.0.html'} | null |
PyPI | PYSEC-2022-70 | null | Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. 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-9c78-vcq7-7vxq', 'CVE-2022-23561'} | 2022-03-09T00:17:32.561735Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq'} | null |
PyPI | PYSEC-2012-5 | null | CRLF injection vulnerability in the tornado.web.RequestHandler.set_header function in Tornado before 2.2.1 allows remote attackers to inject arbitrary HTTP headers and conduct HTTP response splitting attacks via crafted input. | {'CVE-2012-2374'} | 2021-07-05T00:01:27.298545Z | 2012-05-23T20:55:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2012/05/18/6', 'http://www.tornadoweb.org/documentation/releases/v2.2.1.html', 'http://openwall.com/lists/oss-security/2012/05/18/12', 'http://www.securityfocus.com/bid/53612', 'http://secunia.com/advisories/49185'} | null |
PyPI | GHSA-4hvf-hxvg-f67v | Read and Write outside of bounds in TensorFlow | ### Impact
An attacker can craft a TFLite model that would allow limited reads and writes outside of arrays in TFLite. This exploits missing validation in [the conversion from sparse tensors to dense tensors](https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/kernels/internal/utils/sparsity_format_converter.cc#L252-L293).
### Patches
We have patched the issue in GitHub commit [6364463d6f5b6254cac3d6aedf999b6a96225038](https://github.com/tensorflow/tensorflow/commit/6364463d6f5b6254cac3d6aedf999b6a96225038).
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.
### Attribution
This vulnerability has been reported by Wang Xuan of Qihoo 360 AIVul Team. | {'CVE-2022-23560'} | 2022-03-03T05:13:30.212098Z | 2022-02-09T23:53:30Z | HIGH | null | {'CWE-787', 'CWE-125'} | {'https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/kernels/internal/utils/sparsity_format_converter.cc#L252-L293', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23560', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4hvf-hxvg-f67v', 'https://github.com/tensorflow/tensorflow/', 'https://github.com/tensorflow/tensorflow/commit/6364463d6f5b6254cac3d6aedf999b6a96225038'} | null |
PyPI | PYSEC-2018-110 | null | Ajenti version version 2 contains a Input Validation vulnerability in ID string on Get-values POST request that can result in Server Crashing. This attack appear to be exploitable via An attacker can freeze te server by sending a giant string to the ID parameter .. | {'CVE-2018-1000081'} | 2022-02-17T09:17:11.010349Z | 2018-03-13T15:29:00Z | null | null | null | {'https://pypi.org/project/ajenti-panel', 'https://medium.com/stolabs/security-issues-on-ajenti-d2b7526eaeee', 'https://nvd.nist.gov/vuln/detail/CVE-2018-1000081'} | null |
PyPI | GHSA-fpcv-j2q9-vqhw | Moderate severity vulnerability that affects mayan-edms | An issue was discovered in Mayan EDMS before 3.0.2. The Appearance app sets window.location directly, leading to XSS. | {'CVE-2018-16405'} | 2022-03-03T05:13:40.184748Z | 2018-09-06T03:24:50Z | MODERATE | null | {'CWE-79'} | {'https://github.com/advisories/GHSA-fpcv-j2q9-vqhw', 'https://gitlab.com/mayan-edms/mayan-edms/issues/494', 'https://gitlab.com/mayan-edms/mayan-edms', 'https://gitlab.com/mayan-edms/mayan-edms/blob/master/HISTORY.rst', 'https://nvd.nist.gov/vuln/detail/CVE-2018-16405', 'https://gitlab.com/mayan-edms/mayan-edms/commit/9ebe80595afe4fdd1e2c74358d6a9421f4ce130e'} | null |
PyPI | PYSEC-2021-443 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixDiag*` operations(https://github.com/tensorflow/tensorflow/blob/4c4f420e68f1cfaf8f4b6e8e3eb857e9e4c3ff33/tensorflow/core/kernels/linalg/matrix_diag_op.cc#L195-L197) does not validate that the tensor arguments are non-empty. 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-2021-29515', 'GHSA-hc6c-75p4-hmq4'} | 2021-12-09T06:34:45.694528Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a7116dd3913c4a4afd2a3a938573aa7c785fdfc6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hc6c-75p4-hmq4'} | null |
PyPI | PYSEC-2021-156 | null | TensorFlow is an end-to-end open source platform for machine learning. The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/kernels/sparse_cross_op.cc#L114-L116) is tricked to consider a tensor of type `tstring` which in fact contains integral elements. Fixing the type confusion by preventing mixing `DT_STRING` and `DT_INT64` types solves this issue. 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-772j-h9xw-ffp5', 'CVE-2021-29519'} | 2021-08-27T03:22:24.765492Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b1cc5e5a50e7cee09f2c6eb48eb40ee9c4125025', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-772j-h9xw-ffp5'} | null |
PyPI | PYSEC-2021-506 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalAvgPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/dcba796a28364d6d7f003f6fe733d82726dda713/tensorflow/core/kernels/fractional_avg_pool_op.cc#L216) fails to validate that the pooling sequence arguments have enough elements as required by the `out_backprop` tensor shape. 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-2021-29578', 'GHSA-6f89-8j54-29xf'} | 2021-12-09T06:34:55.459344Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6f89-8j54-29xf', 'https://github.com/tensorflow/tensorflow/commit/12c727cee857fa19be717f336943d95fca4ffe4f'} | null |
PyPI | PYSEC-2020-156 | null | flaskparser.py in Webargs 5.x through 5.5.2 doesn't check that the Content-Type header is application/json when receiving JSON input. If the request body is valid JSON, it will accept it even if the content type is application/x-www-form-urlencoded. This allows for JSON POST requests to be made across domains, leading to CSRF. | {'CVE-2020-7965', 'GHSA-fjq3-5pxw-4wj4'} | 2020-02-03T16:36:00Z | 2020-01-29T15:15:00Z | null | null | null | {'https://webargs.readthedocs.io/en/latest/changelog.html', 'https://github.com/advisories/GHSA-fjq3-5pxw-4wj4'} | null |
PyPI | GHSA-wv5p-gmmv-wh9v | Insertion of Sensitive Information into Log File in ansible | A flaw was found in ansible module where credentials are disclosed in the console log by default and not protected by the security feature when using the bitbucket_pipeline_variable module. This flaw allows an attacker to steal bitbucket_pipeline credentials. The highest threat from this vulnerability is to confidentiality. | {'CVE-2021-20178'} | 2022-03-03T05:12:38.557348Z | 2021-06-01T21:53:29Z | MODERATE | null | {'CWE-532'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-20178', 'https://bugzilla.redhat.com/show_bug.cgi?id=1914774', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/HIU7QZUV73U6ZQ65VJWSFBTCALVXLH55/', 'https://github.com/ansible/ansible/blob/v2.9.18/changelogs/CHANGELOG-v2.9.rst#security-fixes', 'https://github.com/ansible-collections/community.general/pull/1635,', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FUQ2QKAQA5OW2TY3ACZZMFIAJ2EQTG37/'} | null |
PyPI | PYSEC-2008-2 | null | The administration application in Django 0.91, 0.95, and 0.96 stores unauthenticated HTTP POST requests and processes them after successful authentication occurs, which allows remote attackers to conduct cross-site request forgery (CSRF) attacks and delete or modify data via unspecified requests. | {'CVE-2008-3909'} | 2021-07-15T02:22:07.826825Z | 2008-09-04T17:41:00Z | null | null | null | {'https://www.redhat.com/archives/fedora-package-announce/2008-September/msg00091.html', 'http://secunia.com/advisories/31961', 'http://osvdb.org/47906', 'https://www.redhat.com/archives/fedora-package-announce/2008-September/msg00131.html', 'https://bugzilla.redhat.com/show_bug.cgi?id=460966', 'http://www.debian.org/security/2008/dsa-1640', 'http://www.vupen.com/english/advisories/2008/2533', 'http://www.openwall.com/lists/oss-security/2008/09/03/4', 'http://www.djangoproject.com/weblog/2008/sep/02/security/', 'http://secunia.com/advisories/31837'} | null |
PyPI | PYSEC-2021-855 | null | Incomplete string comparison in the numpy.core component in NumPy1.9.x, which allows attackers to fail the APIs via constructing specific string objects. | {'CVE-2021-34141'} | 2021-12-22T21:28:25.894913Z | 2021-12-17T19:15:00Z | null | null | null | {'https://github.com/numpy/numpy/issues/18993'} | null |
PyPI | GHSA-9w8r-397f-prfh | Infinite Loop in Pygments | An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword. | {'CVE-2021-20270'} | 2022-03-03T05:13:12.625772Z | 2021-04-20T16:35:47Z | HIGH | null | {'CWE-835'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-20270', 'https://lists.debian.org/debian-lts-announce/2021/05/msg00003.html', 'https://www.oracle.com/security-alerts/cpuoct2021.html', 'https://lists.debian.org/debian-lts-announce/2021/05/msg00006.html', 'https://bugzilla.redhat.com/show_bug.cgi?id=1922136', 'https://www.debian.org/security/2021/dsa-4889'} | null |
PyPI | PYSEC-2018-24 | null | Python Cryptographic Authority pyopenssl version Before 17.5.0 contains a CWE - 401 : Failure to Release Memory Before Removing Last Reference vulnerability in PKCS #12 Store that can result in Denial of service if memory runs low or is exhausted. This attack appear to be exploitable via Depends upon calling application, however it could be as simple as initiating a TLS connection. Anything that would cause the calling application to reload certificates from a PKCS #12 store.. This vulnerability appears to have been fixed in 17.5.0. | {'CVE-2018-1000808', 'GHSA-2rcm-phc9-3945'} | 2021-06-10T06:50:57.188381Z | 2018-10-08T15:29:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2019:0085', 'https://github.com/advisories/GHSA-2rcm-phc9-3945', 'https://usn.ubuntu.com/3813-1/', 'https://github.com/pyca/pyopenssl/pull/723', 'http://lists.opensuse.org/opensuse-security-announce/2019-04/msg00014.html'} | null |
PyPI | GHSA-3hxh-8cp2-g4hg | Use after free and segfault in shape inference functions | ### Impact
When running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault.
`ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types.
### Patches
We have patched the issue in GitHub commit [ee119d4a498979525046fba1c3dd3f13a039fbb1](https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1).
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. | {'CVE-2021-37690'} | 2022-03-03T05:11:34.622229Z | 2021-08-25T14:39:22Z | MODERATE | null | {'CWE-416'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37690', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg', 'https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1'} | null |
PyPI | PYSEC-2021-60 | null | Tenable for Jira Cloud is an open source project designed to pull Tenable.io vulnerability data, then generate Jira Tasks and sub-tasks based on the vulnerabilities' current state. It published in pypi as "tenable-jira-cloud". In tenable-jira-cloud before version 1.1.21, it is possible to run arbitrary commands through the yaml.load() method. This could allow an attacker with local access to the host to run arbitrary code by running the application with a specially crafted YAML configuration file. This is fixed in version 1.1.21 by using yaml.safe_load() instead of yaml.load(). | {'GHSA-8278-88vv-x98r', 'CVE-2021-21371'} | 2021-03-18T20:38:00Z | 2021-03-10T22:15:00Z | null | null | null | {'https://github.com/tenable/integration-jira-cloud/security/advisories/GHSA-8278-88vv-x98r', 'https://github.com/tenable/integration-jira-cloud/commit/f8c2095fd529e664e7fa25403a0a4a85bb3907d0', 'https://pyyaml.docsforge.com/master/documentation/#loading-yaml', 'https://pypi.org/project/tenable-jira-cloud/'} | null |
PyPI | PYSEC-2021-785 | 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 segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. 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-7ghq-fvr3-pj2x', 'CVE-2021-37674'} | 2021-12-09T06:35:38.809791Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7ghq-fvr3-pj2x', 'https://github.com/tensorflow/tensorflow/commit/136b51f10903e044308cf77117c0ed9871350475'} | null |
PyPI | PYSEC-2020-290 | null | In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15210', 'GHSA-x9j7-x98r-r4w2'} | 2021-12-09T06:34:43.437178Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x9j7-x98r-r4w2', 'https://github.com/tensorflow/tensorflow/commit/d58c96946b2880991d63d1dacacb32f0a4dfa453', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | GHSA-hhvc-g5hv-48c6 | Write to immutable memory region in TensorFlow | ### Impact
The `tf.raw_ops.ImmutableConst` operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the memory area:
```python
>>> import tensorflow as tf
>>> with open('/tmp/test.txt','w') as f: f.write('a'*128)
>>> tf.raw_ops.ImmutableConst(dtype=tf.string,shape=2,
memory_region_name='/tmp/test.txt')
```
If the file is too small, TensorFlow properly returns an error as the memory area has fewer bytes than what is needed for the tensor it creates. However, as soon as there are enough bytes, the above snippet causes a segmentation fault.
This is because the alocator used to return the buffer data is not marked as returning an opaque handle since the [needed virtual method](https://github.com/tensorflow/tensorflow/blob/c1e1fc899ad5f8c725dcbb6470069890b5060bc7/tensorflow/core/framework/typed_allocator.h#L78-L85) is [not overriden](https://github.com/tensorflow/tensorflow/blob/acdf3c04fcfa767ae8d109b9e1f727ef050dba4d/tensorflow/core/kernels/immutable_constant_op.cc).
### Patches
We have patched the issue in GitHub commit [c1e1fc899ad5f8c725dcbb6470069890b5060bc7](https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.
### 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-2020-26268'} | 2022-03-03T05:12:48.750740Z | 2020-12-10T19:07:28Z | LOW | null | {'CWE-471'} | {'https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hhvc-g5hv-48c6', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26268'} | null |
PyPI | PYSEC-2019-239 | null | An issue was discovered in py-lmdb 0.97. For certain values of mn_flags, mdb_cursor_set triggers a memcpy with an invalid write operation within mdb_xcursor_init1. NOTE: this outcome occurs when accessing a data.mdb file supplied by an attacker. | {'CVE-2019-16227'} | 2021-12-14T08:17:08.407956Z | 2019-09-11T15:15:00Z | null | null | null | {'https://pypi.org/project/lmdb', 'https://github.com/TeamSeri0us/pocs/tree/master/lmdb/lmdb%20memcpy%20illegal%20dst', 'https://nvd.nist.gov/vuln/detail/CVE-2019-16227'} | null |
PyPI | PYSEC-2017-17 | null | Multiple cross-site scripting (XSS) vulnerabilities in the administration pages in Kallithea before 0.2.1 allow remote attackers to inject arbitrary web script or HTML via the (1) first name or (2) last name user details, or the (3) repository, (4) repository group, or (5) user group description. | {'CVE-2015-1864'} | 2021-07-05T00:01:22.152589Z | 2017-09-19T15:29:00Z | null | null | null | {'https://kallithea-scm.org/repos/kallithea/changeset/a8f2986afc18c9221bf99f88b06e60ab83c86c55', 'http://www.securityfocus.com/bid/74184', 'http://www.openwall.com/lists/oss-security/2015/04/14/12', 'https://kallithea-scm.org/security/cve-2015-1864.html'} | null |
PyPI | PYSEC-2021-290 | 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'} | 2021-08-27T03:22:45.672870Z | 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 | GHSA-6jp6-9rf9-gc66 | Cross-site Scripting in Weblate | ### Impact
Due to improper neutralization, it was possible to perform cross-site scripting via crafted user and language names.
### Patches
The issues were fixed in the 4.11 release. The following commits are addressing it:
* f6753a1a1c63fade6ad418fbda827c6750ab0bda
* 9e19a8414337692cc90da2a91c9af5420f2952f1
* 22d577b1f1e88665a88b4569380148030e0f8389
### Workarounds
You can look for crafted user and language names to see if you were affected.
### References
* https://hackerone.com/reports/1486674
* https://hackerone.com/reports/1486718
* https://hackerone.com/reports/1485226
### For more information
If you have any questions or comments about this advisory:
* Open a topic in [discussions](https://github.com/WeblateOrg/weblate/discussions)
* Email us at [care@weblate.org](mailto:care@weblate.org) | {'CVE-2022-24710'} | 2022-03-09T21:16:52.565898Z | 2022-02-25T22:18:50Z | MODERATE | null | {'CWE-79'} | {'https://github.com/WeblateOrg/weblate/commit/9e19a8414337692cc90da2a91c9af5420f2952f1', 'https://github.com/WeblateOrg/weblate/', 'https://nvd.nist.gov/vuln/detail/CVE-2022-24710', 'https://github.com/WeblateOrg/weblate/commit/f6753a1a1c63fade6ad418fbda827c6750ab0bda', 'https://github.com/WeblateOrg/weblate/commit/22d577b1f1e88665a88b4569380148030e0f8389', 'https://github.com/WeblateOrg/weblate/security/advisories/GHSA-6jp6-9rf9-gc66'} | null |
PyPI | GHSA-fq86-3f29-px2c | `CHECK`-failures during Grappler's `IsSimplifiableReshape` in Tensorflow | ### Impact
The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a `SavedModel` such that [`IsSimplifiableReshape`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L1687-L1742) would trigger `CHECK` failures.
### Patches
We have patched the issue in GitHub commits [ebc1a2ffe5a7573d905e99bd0ee3568ee07c12c1](https://github.com/tensorflow/tensorflow/commit/ebc1a2ffe5a7573d905e99bd0ee3568ee07c12c1), [1fb27733f943295d874417630edd3b38b34ce082](https://github.com/tensorflow/tensorflow/commit/1fb27733f943295d874417630edd3b38b34ce082), and [240655511cd3e701155f944a972db71b6c0b1bb6](https://github.com/tensorflow/tensorflow/commit/240655511cd3e701155f944a972db71b6c0b1bb6).
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-2022-23581'} | 2022-03-03T05:13:59.913859Z | 2022-02-07T22:01:14Z | MODERATE | null | {'CWE-617'} | {'https://github.com/tensorflow/tensorflow/commit/ebc1a2ffe5a7573d905e99bd0ee3568ee07c12c1', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L1687-L1742', 'https://github.com/tensorflow/tensorflow/commit/240655511cd3e701155f944a972db71b6c0b1bb6', 'https://github.com/tensorflow/tensorflow/commit/1fb27733f943295d874417630edd3b38b34ce082', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23581', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fq86-3f29-px2c', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2021-455 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedConv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/00e9a4d67d76703fa1aee33dac582acf317e0e81/tensorflow/core/kernels/quantized_conv_ops.cc#L257-L259) does a division by a quantity that is controlled by the caller. 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-x4g7-fvjj-prg8', 'CVE-2021-29527'} | 2021-12-09T06:34:47.577181Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x4g7-fvjj-prg8', 'https://github.com/tensorflow/tensorflow/commit/cfa91be9863a91d5105a3b4941096044ab32036b'} | null |
PyPI | GHSA-m6h2-jx9v-58w6 | Missing Authorization in Apache Airflow | If remote logging is not used, the worker (in the case of CeleryExecutor) or the scheduler (in the case of LocalExecutor) runs a Flask logging server and is listening on a specific port and also binds on 0.0.0.0 by default. This logging server had no authentication and allows reading log files of DAG jobs. This issue affects Apache Airflow < 2.1.2. | {'CVE-2021-35936'} | 2022-03-03T05:14:12.440610Z | 2021-08-30T16:25:57Z | MODERATE | null | {'CWE-862'} | {'https://lists.apache.org/thread.html/r53d6bd7b0a66f92ddaf1313282f10fec802e71246606dd30c16536df%40%3Cusers.airflow.apache.org%3E', 'https://nvd.nist.gov/vuln/detail/CVE-2021-35936', 'https://github.com/apache/airflow'} | null |
PyPI | PYSEC-2018-106 | null | An issue was discovered in Mayan EDMS before 3.0.2. The Appearance app sets window.location directly, leading to XSS. | {'GHSA-fpcv-j2q9-vqhw', 'CVE-2018-16405'} | 2021-11-24T22:47:09.222926Z | 2018-09-03T19:29:00Z | null | null | null | {'https://gitlab.com/mayan-edms/mayan-edms/issues/494', 'https://gitlab.com/mayan-edms/mayan-edms/blob/master/HISTORY.rst', 'https://github.com/advisories/GHSA-fpcv-j2q9-vqhw', 'https://gitlab.com/mayan-edms/mayan-edms/commit/9ebe80595afe4fdd1e2c74358d6a9421f4ce130e'} | null |
PyPI | PYSEC-2022-149 | null | Tensorflow is an Open Source Machine Learning Framework. When decoding PNG images TensorFlow can produce a memory leak if the image is invalid. After calling `png::CommonInitDecode(..., &decode)`, the `decode` value contains allocated buffers which can only be freed by calling `png::CommonFreeDecode(&decode)`. However, several error case in the function implementation invoke the `OP_REQUIRES` macro which immediately terminates the execution of the function, without allowing for the memory free to occur. 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-fq6p-6334-8gr4', 'CVE-2022-23585'} | 2022-03-09T00:18:29.163401Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/image/decode_image_op.cc#L322-L416', 'https://github.com/tensorflow/tensorflow/commit/ab51e5b813573dc9f51efa335aebcf2994125ee9', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fq6p-6334-8gr4'} | null |
PyPI | PYSEC-2022-66 | null | Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would trigger a division by zero in `BiasAndClamp` implementation. There is no check that the `bias_size` is non zero. 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-gf2j-f278-xh4v', 'CVE-2022-23557'} | 2022-03-09T00:17:32.048410Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75', 'https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf2j-f278-xh4v'} | null |
PyPI | PYSEC-2019-106 | null | NLTK Downloader before 3.4.5 is vulnerable to a directory traversal, allowing attackers to write arbitrary files via a ../ (dot dot slash) in an NLTK package (ZIP archive) that is mishandled during extraction. | {'CVE-2019-14751', 'GHSA-mr7p-25v2-35wr'} | 2020-03-27T10:15:00Z | 2019-08-22T16:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-mr7p-25v2-35wr', 'https://github.com/nltk/nltk/commit/f59d7ed8df2e0e957f7f247fe218032abdbe9a10', 'https://salvatoresecurity.com/zip-slip-in-nltk-cve-2019-14751/', 'https://github.com/nltk/nltk/blob/3.4.5/ChangeLog', 'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00001.html', 'https://github.com/mssalvatore/CVE-2019-14751_PoC', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZGZSSEJH7RHH3RBUEVWWYT75QU67J7SE/', 'http://lists.opensuse.org/opensuse-security-announce/2020-03/msg00054.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QI4IJGLZQ5S7C5LNRNROHAO2P526XE3D/'} | null |
PyPI | PYSEC-2018-32 | null | urllib3 before version 1.23 does not remove the Authorization HTTP header when following a cross-origin redirect (i.e., a redirect that differs in host, port, or scheme). This can allow for credentials in the Authorization header to be exposed to unintended hosts or transmitted in cleartext. | {'GHSA-www2-v7xj-xrc6', 'CVE-2018-20060'} | 2021-06-10T06:51:03.467032Z | 2018-12-11T17:29:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2019:2272', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/XWP36YW3KSVLXDBY3QJKDYEPCIMN3VQZ/', 'https://github.com/urllib3/urllib3/issues/1316', 'https://github.com/urllib3/urllib3/pull/1346', 'https://bugzilla.redhat.com/show_bug.cgi?id=1649153', 'https://usn.ubuntu.com/3990-1/', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00039.html', 'https://github.com/advisories/GHSA-www2-v7xj-xrc6', 'https://github.com/urllib3/urllib3/blob/master/CHANGES.rst', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/BXLAXHM3Z6DUCXZ7ZXZ2EAYJXWDCZFCT/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/5SJERZEJDSUYQP7BNBXMBHRHGY26HRZD/'} | null |
PyPI | GHSA-mmq6-q8r3-48fm | Crash in `tf.strings.substr` due to `CHECK`-fail | ### Impact
An attacker can cause a denial of service via `CHECK`-fail in `tf.strings.substr` with invalid arguments:
```python
import tensorflow as tf
tf.strings.substr(input='abc', len=1, pos=[1,-1])
```
```python
import tensorflow as tf
tf.strings.substr(input='abc', len=1, pos=[1,2])
```
### Patches
We have received a patch for the issue in GitHub commit [890f7164b70354c57d40eda52dcdd7658677c09f](https://github.com/tensorflow/tensorflow/commit/890f7164b70354c57d40eda52dcdd7658677c09f).
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 in [#46900](https://github.com/tensorflow/issues/46900) and fixed in [#46974](https://github.com/tensorflow/issues/46974). | {'CVE-2021-29617'} | 2022-03-03T05:12:45.549998Z | 2021-05-21T14:28:50Z | LOW | null | {'CWE-755'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mmq6-q8r3-48fm', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29617', 'https://github.com/tensorflow/issues/46900', 'https://github.com/tensorflow/issues/46974', 'https://github.com/tensorflow/tensorflow/commit/890f7164b70354c57d40eda52dcdd7658677c09f'} | null |
PyPI | PYSEC-2022-89 | null | Tensorflow is an Open Source Machine Learning Framework. During shape inference, TensorFlow can allocate a large vector based on a value from a tensor controlled by the user. 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-2022-23580', 'GHSA-627q-g293-49q7'} | 2022-03-09T00:17:34.891439Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-627q-g293-49q7', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L788-L790', 'https://github.com/tensorflow/tensorflow/commit/1361fb7e29449629e1df94d44e0427ebec8c83c7'} | null |
PyPI | GHSA-vj42-xq3r-hr3r | Out-of-bounds reads in Pillow | In libImaging/Jpeg2KDecode.c in Pillow before 7.0.0, there are multiple out-of-bounds reads via a crafted JP2 file. | {'CVE-2020-10994'} | 2022-03-03T05:14:03.052947Z | 2020-07-27T21:52:39Z | MODERATE | null | {'CWE-125'} | {'https://github.com/python-pillow/Pillow/pull/4505', 'https://pillow.readthedocs.io/en/stable/releasenotes/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10994', 'https://github.com/python-pillow/Pillow/blob/master/docs/releasenotes/7.1.0.rst#security', 'https://github.com/python-pillow/Pillow/pull/4538', 'https://snyk.io/vuln/SNYK-PYTHON-PILLOW-574575', 'https://github.com/python-pillow/Pillow/commits/master/src/libImaging/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/HOKHNWV2VS5GESY7IBD237E7C6T3I427/', 'https://usn.ubuntu.com/4430-1/', 'https://github.com/python-pillow/Pillow', 'https://github.com/python-pillow/Pillow/commit/ff60894d697d1992147b791101ad53a8bf1352e4', 'https://usn.ubuntu.com/4430-2/', 'https://pillow.readthedocs.io/en/stable/releasenotes/7.1.0.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/BEBCPE4F2VHTIT6EZA2YZQZLPVDEBJGD/'} | null |
PyPI | GHSA-rrx2-r989-2c43 | Integer overflows in Tensorflow | ### Impact
The [implementations of `Sparse*Cwise*` ops](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc) are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service):
```python
import tensorflow as tf
import numpy as np
tf.raw_ops.SparseDenseCwiseDiv(
sp_indices=np.array([[9]]),
sp_values=np.array([5]),
sp_shape=np.array([92233720368., 92233720368]),
dense=np.array([4]))
```
We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The latter is an instance of [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md) (CVE-2021-41197) and is easily fixed by replacing a call to `TensorShape` constructor with a call to `BuildTensorShape` static helper factory.
### Patches
We have patched the issue in GitHub commits [1b54cadd19391b60b6fcccd8d076426f7221d5e8](https://github.com/tensorflow/tensorflow/commit/1b54cadd19391b60b6fcccd8d076426f7221d5e8) and [e952a89b7026b98fe8cbe626514a93ed68b7c510](https://github.com/tensorflow/tensorflow/commit/e952a89b7026b98fe8cbe626514a93ed68b7c510).
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.
### Attribution
This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia. | {'CVE-2022-23567'} | 2022-03-03T05:13:29.706090Z | 2022-02-09T23:39:33Z | MODERATE | null | {'CWE-190'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-23567', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc', 'https://github.com/tensorflow/tensorflow/commit/1b54cadd19391b60b6fcccd8d076426f7221d5e8', 'https://github.com/tensorflow/tensorflow/commit/e952a89b7026b98fe8cbe626514a93ed68b7c510', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrx2-r989-2c43'} | null |
PyPI | PYSEC-2017-6 | null | attic before 0.15 does not confirm unencrypted backups with the user, which allows remote attackers with read and write privileges for the encrypted repository to obtain potentially sensitive information by changing the manifest type byte of the repository to "unencrypted / without key file". | {'CVE-2015-4082'} | 2021-07-05T00:01:17.176184Z | 2017-08-18T16:29:00Z | null | null | null | {'https://github.com/jborg/attic/commit/78f9ad1faba7193ca7f0acccbc13b1ff6ebf9072', 'http://www.openwall.com/lists/oss-security/2015/05/31/3', 'http://www.securityfocus.com/bid/74821', 'https://github.com/jborg/attic/issues/271'} | null |
PyPI | PYSEC-2021-843 | null | TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. These 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-2021-41206', 'GHSA-pgcq-h79j-2f69'} | 2021-12-13T06:21:24.834833Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pgcq-h79j-2f69', 'https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4', 'https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07', 'https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904', 'https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a', 'https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261', 'https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d'} | null |
PyPI | PYSEC-2020-140 | null | In affected versions of TensorFlow the tf.raw_ops.DataFormatVecPermute API does not validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC. This can result in uninitialized memory accesses, read outside of bounds and even crashes. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0. | {'CVE-2020-26267', 'GHSA-c9f3-9wfr-wgh7'} | 2020-12-14T19:08:00Z | 2020-12-10T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c9f3-9wfr-wgh7', 'https://github.com/tensorflow/tensorflow/commit/ebc70b7a592420d3d2f359e4b1694c236b82c7ae'} | null |
PyPI | PYSEC-2021-510 | null | TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.Dequantize`, an attacker can trigger a read from outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/26003593aa94b1742f34dc22ce88a1e17776a67d/tensorflow/core/kernels/dequantize_op.cc#L106-L131) accesses the `min_range` and `max_range` tensors in parallel but fails to check that they have the same shape. 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-c45w-2wxr-pp53', 'CVE-2021-29582'} | 2021-12-09T06:34:56.077512Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/5899741d0421391ca878da47907b1452f06aaf1b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c45w-2wxr-pp53'} | null |
PyPI | PYSEC-2014-11 | null | pip 1.3 through 1.5.6 allows local users to cause a denial of service (prevention of package installation) by creating a /tmp/pip-build-* file for another user. | {'CVE-2014-8991'} | 2021-07-05T00:01:24.413265Z | 2014-11-24T15:59:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2014/11/20/6', 'http://www.oracle.com/technetwork/topics/security/bulletinjul2015-2511963.html', 'https://github.com/pypa/pip/pull/2122', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=725847', 'http://www.openwall.com/lists/oss-security/2014/11/19/17', 'http://www.securityfocus.com/bid/71209'} | null |
PyPI | PYSEC-2021-140 | null | An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword. | {'GHSA-9w8r-397f-prfh', 'CVE-2021-20270'} | 2021-08-27T03:22:17.263376Z | 2021-03-23T17:15:00Z | null | null | null | {'https://lists.debian.org/debian-lts-announce/2021/05/msg00003.html', 'https://github.com/advisories/GHSA-9w8r-397f-prfh', 'https://bugzilla.redhat.com/show_bug.cgi?id=1922136', 'https://lists.debian.org/debian-lts-announce/2021/05/msg00006.html', 'https://www.debian.org/security/2021/dsa-4889'} | null |
PyPI | PYSEC-2020-269 | null | TensorFlow before 1.7.0 has an integer overflow that causes an out-of-bounds read, possibly causing disclosure of the contents of process memory. This occurs in the DecodeBmp feature of the BMP decoder in core/kernels/decode_bmp_op.cc. | {'CVE-2018-21233'} | 2021-08-27T03:22:22.195752Z | 2020-05-04T15:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/49f73c55d56edffebde4bca4a407ad69c1cae433', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2018-001.md'} | null |
PyPI | GHSA-772j-h9xw-ffp5 | CHECK-fail in SparseCross due to type confusion | ### Impact
The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service:
```python
import tensorflow as tf
hashed_output = False
num_buckets = 1949315406
hash_key = 1869835877
out_type = tf.string
internal_type = tf.string
indices_1 = tf.constant([0, 6], shape=[1, 2], dtype=tf.int64)
indices_2 = tf.constant([0, 0], shape=[1, 2], dtype=tf.int64)
indices = [indices_1, indices_2]
values_1 = tf.constant([0], dtype=tf.int64)
values_2 = tf.constant([72], dtype=tf.int64)
values = [values_1, values_2]
batch_size = 4
shape_1 = tf.constant([4, 122], dtype=tf.int64)
shape_2 = tf.constant([4, 188], dtype=tf.int64)
shapes = [shape_1, shape_2]
dense_1 = tf.constant([188, 127, 336, 0], shape=[4, 1], dtype=tf.int64)
dense_2 = tf.constant([341, 470, 470, 470], shape=[4, 1], dtype=tf.int64)
dense_3 = tf.constant([188, 188, 341, 922], shape=[4, 1], dtype=tf.int64)
denses = [dense_1, dense_2, dense_3]
tf.raw_ops.SparseCross(indices=indices, values=values, shapes=shapes, dense_inputs=denses, hashed_output=hashed_output,
num_buckets=num_buckets, hash_key=hash_key, out_type=out_type, internal_type=internal_type)
```
The above code will result in a `CHECK` fail in [`tensor.cc`](https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/framework/tensor.cc#L670-L675):
```cc
void Tensor::CheckTypeAndIsAligned(DataType expected_dtype) const {
CHECK_EQ(dtype(), expected_dtype)
<< " " << DataTypeString(expected_dtype) << " expected, got "
<< DataTypeString(dtype());
...
}
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/kernels/sparse_cross_op.cc#L114-L116) is tricked to consider a tensor of type `tstring` which in fact contains integral elements:
```cc
if (DT_STRING == values_.dtype())
return Fingerprint64(values_.vec<tstring>().data()[start + n]);
return values_.vec<int64>().data()[start + n];
```
Fixing the type confusion by preventing mixing `DT_STRING` and `DT_INT64` types solves this issue.
### Patches
We have patched the issue in GitHub commit [b1cc5e5a50e7cee09f2c6eb48eb40ee9c4125025](https://github.com/tensorflow/tensorflow/commit/b1cc5e5a50e7cee09f2c6eb48eb40ee9c4125025).
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 Yakun Zhang and Ying Wang of Baidu X-Team. | {'CVE-2021-29519'} | 2022-03-03T05:13:05.642465Z | 2021-05-21T14:21:08Z | LOW | null | {'CWE-843'} | {'https://github.com/tensorflow/tensorflow/commit/b1cc5e5a50e7cee09f2c6eb48eb40ee9c4125025', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29519', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-772j-h9xw-ffp5'} | null |
PyPI | GHSA-jq4v-f5q6-mjqq | Cross-Site Scripting in lxml | An XSS vulnerability was discovered in the python `lxml` clean module versions before 4.6.3. When disabling the safe_attrs_only and forms arguments, the Cleaner class does not remove the formaction attribute allowing for JS to bypass the sanitizer. A remote attacker could exploit this flaw to run arbitrary JS code on users who interact with incorrectly sanitized HTML. This issue is patched in `lxml` 4.6.3. | {'CVE-2021-28957'} | 2022-03-03T05:13:36.582021Z | 2021-03-22T16:53:53Z | MODERATE | null | {'CWE-79'} | {'https://bugs.launchpad.net/lxml/+bug/1888153', 'https://github.com/lxml/lxml', 'https://nvd.nist.gov/vuln/detail/CVE-2021-28957', 'https://pypi.org/project/lxml', 'https://github.com/lxml/lxml/commit/a5f9cb52079dc57477c460dbe6ba0f775e14a999', 'https://security.netapp.com/advisory/ntap-20210521-0004/', 'https://www.oracle.com/security-alerts/cpuoct2021.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/XXN3QPWCTQVOGW4BMWV3AUUZZ4NRZNSQ/', 'https://www.debian.org/security/2021/dsa-4880', 'https://github.com/lxml/lxml/commit/2d01a1ba8984e0483ce6619b972832377f208a0d', 'https://github.com/lxml/lxml/pull/316', 'https://lists.debian.org/debian-lts-announce/2021/03/msg00031.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3C2R44VDUY7FJVMAVRZ2WY7XYL4SVN45/', 'https://github.com/lxml/lxml/pull/316/commits/10ec1b4e9f93713513a3264ed6158af22492f270'} | null |
PyPI | PYSEC-2022-3 | null | Storage.save in Django 2.2 before 2.2.26, 3.2 before 3.2.11, and 4.0 before 4.0.1 allows directory traversal if crafted filenames are directly passed to it. | {'CVE-2021-45452', 'GHSA-jrh2-hc4r-7jwx'} | 2022-01-05T02:16:15.695516Z | 2022-01-05T00:15:00Z | null | null | null | {'https://groups.google.com/forum/#!forum/django-announce', 'https://www.djangoproject.com/weblog/2022/jan/04/security-releases/', 'https://github.com/advisories/GHSA-jrh2-hc4r-7jwx', 'https://docs.djangoproject.com/en/4.0/releases/security/'} | null |
PyPI | PYSEC-2021-269 | null | TensorFlow is an end-to-end open source platform for machine learning. When a user does not supply arguments that determine a valid sparse tensor, `tf.raw_ops.SparseTensorSliceDataset` implementation can be made to dereference a null pointer. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L240-L251) has some argument validation but fails to consider the case when either `indices` or `values` are provided for an empty sparse tensor when the other is not. If `indices` is empty, then [code that performs validation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L260-L261) (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If `indices` as provided by the user is empty, then `indices` in the C++ code above is backed by an empty `std::vector`, hence calling `indices->dim_size(0)` results in null pointer dereferencing (same as calling `std::vector::at()` on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. 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-c5x2-p679-95wc', 'CVE-2021-37647'} | 2021-08-27T03:22:43.708163Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c5x2-p679-95wc', 'https://github.com/tensorflow/tensorflow/commit/02cc160e29d20631de3859c6653184e3f876b9d7'} | null |
PyPI | PYSEC-2021-793 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions all TFLite operations that use quantization can be made to use unitialized values. [For example](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/depthwise_conv.cc#L198-L200). The issue stems from the fact that `quantization.params` is only valid if `quantization.type` is different that `kTfLiteNoQuantization`. However, these checks are missing in large parts of the code. We have patched the issue in GitHub commits 537bc7c723439b9194a358f64d871dd326c18887, 4a91f2069f7145aab6ba2d8cfe41be8a110c18a5 and 8933b8a21280696ab119b63263babdb54c298538. 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-2021-37682', 'GHSA-4c4g-crqm-xrxw'} | 2021-12-09T06:35:39.522019Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/537bc7c723439b9194a358f64d871dd326c18887', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4c4g-crqm-xrxw', 'https://github.com/tensorflow/tensorflow/commit/8933b8a21280696ab119b63263babdb54c298538', 'https://github.com/tensorflow/tensorflow/commit/4a91f2069f7145aab6ba2d8cfe41be8a110c18a5'} | null |
PyPI | PYSEC-2021-639 | null | TensorFlow is an end-to-end open source platform for machine learning. Calling TF operations with tensors of non-numeric types when the operations expect numeric tensors result in null pointer dereferences. The conversion from Python array to C++ array(https://github.com/tensorflow/tensorflow/blob/ff70c47a396ef1e3cb73c90513da4f5cb71bebba/tensorflow/python/lib/core/ndarray_tensor.cc#L113-L169) is vulnerable to a type confusion. 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-452g-f7fp-9jf7', 'CVE-2021-29513'} | 2021-12-09T06:35:17.206359Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/030af767d357d1b4088c4a25c72cb3906abac489', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-452g-f7fp-9jf7'} | null |
PyPI | PYSEC-2021-76 | null | aiohttp is an asynchronous HTTP client/server framework for asyncio and Python. In aiohttp before version 3.7.4 there is an open redirect vulnerability. A maliciously crafted link to an aiohttp-based web-server could redirect the browser to a different website. It is caused by a bug in the `aiohttp.web_middlewares.normalize_path_middleware` middleware. This security problem has been fixed in 3.7.4. Upgrade your dependency using pip as follows "pip install aiohttp >= 3.7.4". If upgrading is not an option for you, a workaround can be to avoid using `aiohttp.web_middlewares.normalize_path_middleware` in your applications. | {'GHSA-v6wp-4m6f-gcjg', 'CVE-2021-21330'} | 2021-03-26T20:01:00Z | 2021-02-26T03:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/FU7ENI54JNEK3PHEFGCE46DGMFNTVU6L/', 'https://github.com/aio-libs/aiohttp/blob/master/CHANGES.rst#374-2021-02-25', 'https://github.com/aio-libs/aiohttp/security/advisories/GHSA-v6wp-4m6f-gcjg', 'https://pypi.org/project/aiohttp/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/JN3V7CZJRT4QFCVXB6LDPCJH7NAOFCA5/', 'https://www.debian.org/security/2021/dsa-4864', 'https://github.com/aio-libs/aiohttp/commit/2545222a3853e31ace15d87ae0e2effb7da0c96b'} | null |
PyPI | PYSEC-2021-99 | null | In Django 2.2 before 2.2.24, 3.x before 3.1.12, and 3.2 before 3.2.4, URLValidator, validate_ipv4_address, and validate_ipv46_address do not prohibit leading zero characters in octal literals. This may allow a bypass of access control that is based on IP addresses. (validate_ipv4_address and validate_ipv46_address are unaffected with Python 3.9.5+..) . | {'CVE-2021-33571', 'GHSA-p99v-5w3c-jqq9'} | 2021-06-22T04:54:55.488063Z | 2021-06-08T18:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-p99v-5w3c-jqq9', 'https://groups.google.com/g/django-announce/c/sPyjSKMi8Eo', 'https://docs.djangoproject.com/en/3.2/releases/security/', 'https://www.djangoproject.com/weblog/2021/jun/02/security-releases/'} | null |
PyPI | PYSEC-2021-286 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `BoostedTreesSparseCalculateBestFeatureSplit`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) needs to validate that each value in `stats_summary_indices` is in range. We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378. 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-2021-37664', 'GHSA-r4c4-5fpq-56wg'} | 2021-08-27T03:22:45.297527Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r4c4-5fpq-56wg', 'https://github.com/tensorflow/tensorflow/commit/e84c975313e8e8e38bb2ea118196369c45c51378'} | null |
PyPI | PYSEC-2020-286 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15206', 'GHSA-w5gh-2wr2-pm6g'} | 2021-12-09T06:34:42.621580Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g', 'https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | GHSA-8867-vpm3-g98g | Incorrect Default Permissions in keyring | Python keyring has insecure permissions on new databases allowing world-readable files to be created | {'CVE-2012-5578'} | 2022-03-03T05:13:23.014959Z | 2020-03-10T20:56:41Z | MODERATE | null | {'CWE-276'} | {'https://nvd.nist.gov/vuln/detail/CVE-2012-5578', 'https://security-tracker.debian.org/tracker/CVE-2012-5578', 'https://access.redhat.com/security/cve/cve-2012-5578', 'https://bugs.launchpad.net/ubuntu/+source/python-keyring/+bug/1031465', 'http://www.openwall.com/lists/oss-security/2012/11/27/4', 'https://github.com/jaraco/keyring/blob/master/CHANGES.rst#010', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2012-5578', 'https://bugzilla.suse.com/show_bug.cgi?id=CVE-2012-5578'} | null |
PyPI | PYSEC-2009-6 | null | Multiple cross-site scripting (XSS) vulnerabilities in action/AttachFile.py in MoinMoin 1.8.2 and earlier allow remote attackers to inject arbitrary web script or HTML via (1) an AttachFile sub-action in the error_msg function or (2) multiple vectors related to package file errors in the upload_form function, different vectors than CVE-2009-0260. | {'CVE-2009-1482'} | 2017-08-17T01:30:00Z | 2009-04-29T18:30:00Z | null | null | null | {'http://www.vupen.com/english/advisories/2009/1119', 'http://secunia.com/advisories/35024', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/50356', 'http://secunia.com/advisories/34945', 'http://moinmo.in/SecurityFixes', 'http://www.securityfocus.com/bid/34631', 'http://secunia.com/advisories/34821', 'http://www.ubuntu.com/usn/USN-774-1', 'http://hg.moinmo.in/moin/1.8/rev/5f51246a4df1', 'http://www.debian.org/security/2009/dsa-1791'} | null |
PyPI | GHSA-vcjj-9vg7-vf68 | Null pointer dereference in TFLite | ### Impact
An attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service:
```python
import tensorflow as tf
model = tf.keras.models.Sequential()
model.add(tf.keras.Input(shape=(1, 2, 3)))
model.add(tf.keras.layers.Dense(0, activation='relu'))
converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()
interpreter = tf.lite.Interpreter(model_content=tflite_model)
interpreter.allocate_tensors()
interpreter.invoke()
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L268-L285) unconditionally dereferences a pointer.
```cc
if (y4 > 1) {
// ...
} else {
for (int i0 = 0; i0 < y0; ++i0) {
const T* input2_data_ptr = nullptr;
for (int i1 = 0; i1 < y1; ++i1) {
input2_data_ptr = input2_data_reset;
for (int i2 = 0; i2 < y2; ++i2) {
scalar_broadcast_f(y3, params, *input1_data_ptr, input2_data_ptr,
output_data_ptr);
}
}
}
}
```
### Patches
We have patched the issue in GitHub commit [15691e456c7dc9bd6be203b09765b063bf4a380c](https://github.com/tensorflow/tensorflow/commit/15691e456c7dc9bd6be203b09765b063bf4a380c).
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 Yakun Zhang of Baidu Security. | {'CVE-2021-37688'} | 2021-08-24T17:57:25Z | 2021-08-25T14:39:54Z | HIGH | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow/commit/15691e456c7dc9bd6be203b09765b063bf4a380c', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vcjj-9vg7-vf68', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37688', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2019-151 | null | send_email in graphite-web/webapp/graphite/composer/views.py in Graphite through 1.1.5 is vulnerable to SSRF. The vulnerable SSRF endpoint can be used by an attacker to have the Graphite web server request any resource. The response to this SSRF request is encoded into an image file and then sent to an e-mail address that can be supplied by the attacker. Thus, an attacker can exfiltrate any information. | {'GHSA-vfj6-275q-4pvm', 'CVE-2017-18638'} | 2021-07-05T00:01:21.806042Z | 2019-10-11T23:15:00Z | null | null | null | {'https://github.com/graphite-project/graphite-web/issues/2008', 'https://lists.debian.org/debian-lts-announce/2019/10/msg00030.html', 'https://github.com/graphite-project/graphite-web/security/advisories/GHSA-vfj6-275q-4pvm', 'https://www.youtube.com/watch?v=ds4Gp4xoaeA', 'https://blog.orange.tw/2017/07/how-i-chained-4-vulnerabilities-on.html#second-bug-internal-graphite-ssrf', 'https://github.com/graphite-project/graphite-web/pull/2499'} | null |
PyPI | PYSEC-2022-31 | null | The package weblate from 0 and before 4.11.1 are vulnerable to Remote Code Execution (RCE) via argument injection when using git or mercurial repositories. Authenticated users, can change the behavior of the application in an unintended way, leading to command execution.
| {'CVE-2022-23915', 'SNYK-PYTHON-WEBLATE-2414088'} | 2022-03-04T21:31:07.631627Z | 2022-03-04T20:15:00Z | null | null | null | {'https://github.com/WeblateOrg/weblate/pull/7337', 'https://github.com/WeblateOrg/weblate/releases/tag/weblate-4.11.1', 'https://snyk.io/vuln/SNYK-PYTHON-WEBLATE-2414088', 'https://github.com/WeblateOrg/weblate/pull/7338'} | null |
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