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 | GHSA-g3rq-g295-4j3m | Regular Expression Denial of Service (ReDoS) in Jinja2 | This affects the package jinja2 from 0.0.0 and before 2.11.3. The ReDOS vulnerability of the regex is mainly due to the sub-pattern [a-zA-Z0-9._-]+.[a-zA-Z0-9._-]+ This issue can be mitigated by Markdown to format user content instead of the urlize filter, or by implementing request timeouts and limiting process memory. | {'CVE-2020-28493'} | 2022-04-18T22:02:03.718853Z | 2021-03-19T21:28:05Z | MODERATE | null | {'CWE-400'} | {'https://github.com/pallets/jinja', 'https://github.com/pallets/jinja/blob/ab81fd9c277900c85da0c322a2ff9d68a235b2e6/src/jinja2/utils.py%23L20', 'https://nvd.nist.gov/vuln/detail/CVE-2020-28493', 'https://security.gentoo.org/glsa/202107-19', 'https://github.com/pallets/jinja/pull/1343', 'https://snyk.io/vuln/SNYK-PYTHON-JINJA2-1012994', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/PVAKCOO7VBVUBM3Q6CBBTPBFNP5NDXF4/'} | null |
PyPI | PYSEC-2021-402 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference functions for `SparseCountSparseOutput` can trigger a read outside of bounds of heap allocated array. 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-m342-ff57-4jcc', 'CVE-2021-41210'} | 2021-11-13T06:52:43.758467Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m342-ff57-4jcc', 'https://github.com/tensorflow/tensorflow/commit/701cfaca222a82afbeeb17496bd718baa65a67d2'} | null |
PyPI | PYSEC-2021-117 | null | This affects the package bikeshed before 3.0.0. This can occur when an untrusted source file containing include, include-code or include-raw block is processed. The contents of arbitrary files could be disclosed in the HTML output. | {'GHSA-hf6p-4rv2-9qrp', 'SNYK-PYTHON-BIKESHED-1537647', 'CVE-2021-23423'} | 2021-08-16T10:33:00.179750Z | 2021-08-16T08:15:00Z | null | null | null | {'https://snyk.io/vuln/SNYK-PYTHON-BIKESHED-1537647', 'https://github.com/advisories/GHSA-hf6p-4rv2-9qrp', 'https://github.com/tabatkins/bikeshed/commit/b2f668fca204260b1cad28d5078e93471cb6b2dd'} | null |
PyPI | PYSEC-2014-46 | null | Cross-site scripting (XSS) vulnerability in widget_traversal.py in Plone before 4.2.3 and 4.3 before beta 1 allows remote attackers to inject arbitrary web script or HTML via unspecified vectors. | {'CVE-2012-5504'} | 2021-09-01T08:44:30.873895Z | 2014-09-30T14:55:00Z | null | null | null | {'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'https://plone.org/products/plone-hotfix/releases/20121106', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://plone.org/products/plone/security/advisories/20121106/20'} | null |
PyPI | PYSEC-2021-547 | null | TensorFlow is an end-to-end open source platform for machine learning. Passing invalid arguments (e.g., discovered via fuzzing) to `tf.raw_ops.SparseCountSparseOutput` results in segfault. 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-2021-29619', 'GHSA-wvjw-p9f5-vq28'} | 2021-12-09T06:35:01.886365Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/82e6203221865de4008445b13c69b6826d2b28d9', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wvjw-p9f5-vq28'} | null |
PyPI | PYSEC-2020-117 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments. Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1." | {'CVE-2020-15194', 'GHSA-9mqp-7v2h-2382'} | 2020-12-23T18:33:00Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/390611e0d45c5793c7066110af37c8514e6a6c54', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9mqp-7v2h-2382'} | null |
PyPI | PYSEC-2021-814 | null | TensorFlow is an open source platform for machine learning. In affected versions the implementation of `ParallelConcat` misses some input validation and can produce a division by 0. 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-7v94-64hj-m82h', 'CVE-2021-41207'} | 2021-12-09T06:35:42.190672Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7v94-64hj-m82h', 'https://github.com/tensorflow/tensorflow/commit/f2c3931113eaafe9ef558faaddd48e00a6606235'} | null |
PyPI | PYSEC-2018-65 | null | MicroPyramid Django-CRM 0.2 allows CSRF for /users/create/, /users/##/edit/, and /accounts/##/delete/ URIs. | {'CVE-2018-16552'} | 2021-08-25T04:29:58.134898Z | 2018-09-05T22:29:00Z | null | null | null | {'https://github.com/MicroPyramid/Django-CRM/issues/68'} | null |
PyPI | PYSEC-2013-1 | null | runner/connection_plugins/ssh.py in Ansible before 1.2.3, when using ControlPersist, allows local users to redirect a ssh session via a symlink attack on a socket file with a predictable name in /tmp/. | {'CVE-2013-4259'} | 2021-07-02T02:41:32.926386Z | 2013-09-16T19:14:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=998223', 'http://www.ansible.com/security', 'https://groups.google.com/forum/#!topic/ansible-project/UVDYW0HGcNg'} | null |
PyPI | PYSEC-2021-394 | null | TensorFlow is an open source platform for machine learning. In affeced versions during execution, `EinsumHelper::ParseEquation()` is supposed to set the flags in `input_has_ellipsis` vector and `*output_has_ellipsis` boolean to indicate whether there is ellipsis in the corresponding inputs and output. However, the code only changes these flags to `true` and never assigns `false`. This results in unitialized variable access if callers assume that `EinsumHelper::ParseEquation()` always sets these flags. 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. | {'CVE-2021-41201', 'GHSA-j86v-p27c-73fm'} | 2021-11-13T06:52:42.499515Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j86v-p27c-73fm', 'https://github.com/tensorflow/tensorflow/commit/f09caa532b6e1ac8d2aa61b7832c78c5b79300c6'} | null |
PyPI | PYSEC-2021-21 | null | Sydent is a reference Matrix identity server. Sydent does not limit the size of requests it receives from HTTP clients. A malicious user could send an HTTP request with a very large body, leading to memory exhaustion and denial of service. Sydent also does not limit response size for requests it makes to remote Matrix homeservers. A malicious homeserver could return a very large response, again leading to memory exhaustion and denial of service. This affects any server which accepts registration requests from untrusted clients. This issue has been patched by releases 89071a1, 0523511, f56eee3. As a workaround request sizes can be limited in an HTTP reverse-proxy. There are no known workarounds for the problem with overlarge responses. | {'CVE-2021-29430', 'GHSA-wmg4-8cp2-hpg9'} | 2021-04-22T17:19:00Z | 2021-04-15T21:15:00Z | null | null | null | {'https://github.com/matrix-org/sydent/commit/0523511d2fb40f2738f8a8549868f44b96e5dab7', 'https://github.com/matrix-org/sydent/commit/f56eee315b6c44fdd9f6aa785cc2ec744a594428', 'https://github.com/matrix-org/sydent/commit/89071a1a754c69a50deac89e6bb74002d4cda19d', 'https://github.com/matrix-org/sydent/releases/tag/v2.3.0', 'https://github.com/matrix-org/sydent/security/advisories/GHSA-wmg4-8cp2-hpg9', 'https://pypi.org/project/matrix-sydent/'} | null |
PyPI | GHSA-qfpc-5pjr-mh26 | Missing validation in shape inference for `Dequantize` | ### Impact
The shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments:
```python
import tensorflow as tf
tf.compat.v1.disable_v2_behavior()
tf.raw_ops.Dequantize(
input_tensor = tf.constant(-10.0, dtype=tf.float32),
input_tensor = tf.cast(input_tensor, dtype=tf.quint8),
min_range = tf.constant([], shape=[0], dtype=tf.float32),
max_range = tf.constant([], shape=[0], dtype=tf.float32),
mode = 'MIN_COMBINED',
narrow_range=False,
axis=-10,
dtype=tf.dtypes.float32)
```
The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values.
### Patches
We have patched the issue in GitHub commit [da857cfa0fde8f79ad0afdbc94e88b5d4bbec764](https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764).
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-2021-37677'} | 2022-03-03T05:13:56.617475Z | 2021-08-25T14:41:23Z | MODERATE | null | {'CWE-20'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37677', 'https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26'} | null |
PyPI | GHSA-844w-j86r-4x2j | Heap buffer overflow in `UnsortedSegmentSum` in TensorFlow | ### Impact
A heap buffer overflow in `UnsortedSegmentSum` can be produced when the `Index` template argument is `int32`. In this case `data_size` and `num_segments` fields are truncated from `int64` to `int32` and can produce negative numbers, resulting in accessing out of bounds heap memory.
This is unlikely to be exploitable and was detected and fixed internally. We are making the security advisory only to notify users that it is better to update to TensorFlow 1.15 or 2.0 or later as these versions already have this fixed.
### Patches
Patched by db4f9717c41bccc3ce10099ab61996b246099892 and released in all official releases after 1.15 and 2.0.
### For more information
Please consult [`SECURITY.md`](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-2019-16778'} | 2022-03-03T05:14:03.970552Z | 2019-12-16T20:17:10Z | LOW | null | {'CWE-122', 'CWE-681'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-844w-j86r-4x2j', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2019-002.md', 'https://nvd.nist.gov/vuln/detail/CVE-2019-16778', 'https://github.com/tensorflow/tensorflow/commit/db4f9717c41bccc3ce10099ab61996b246099892'} | null |
PyPI | GHSA-4298-89hc-6rfv | Open Redirect in Flask-User | This affects all versions of package Flask-User. When using the make_safe_url function, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as /////evil.com/path or \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behaviour of Werkzeug is modified using 'autocorrect_location_header=False. | {'CVE-2021-23401'} | 2022-03-03T05:13:19.971226Z | 2021-08-09T20:44:32Z | MODERATE | null | {'CWE-601'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-23401', 'https://github.com/lingthio/Flask-User', 'https://github.com/lingthio/Flask-User/blob/master/flask_user/user_manager__utils.py', 'https://snyk.io/vuln/SNYK-PYTHON-FLASKUSER-1293188'} | null |
PyPI | GHSA-9c8h-vvrj-w2p8 | Heap OOB in `RaggedGather` | ### Impact
If the arguments to `tf.raw_ops.RaggedGather` don't determine a valid ragged tensor code can trigger a read from outside of bounds of heap allocated buffers.
```python
import tensorflow as tf
tf.raw_ops.RaggedGather(
params_nested_splits = [0,0,0],
params_dense_values = [1,1],
indices = [0,0,9,0,0],
OUTPUT_RAGGED_RANK=0)
```
In debug mode, the same code triggers a `CHECK` failure.
The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/ragged_gather_op.cc#L70) directly reads the first dimension of a tensor shape before checking that said tensor has rank of at least 1 (i.e., it is not a scalar). Furthermore, the implementation does not check that the list given by `params_nested_splits` is not an empty list of tensors.
### Patches
We have patched the issue in GitHub commit [a2b743f6017d7b97af1fe49087ae15f0ac634373](https://github.com/tensorflow/tensorflow/commit/a2b743f6017d7b97af1fe49087ae15f0ac634373).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-37641'} | 2022-03-03T05:13:53.218448Z | 2021-08-25T14:43:59Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-vvrj-w2p8', 'https://github.com/tensorflow/tensorflow/commit/a2b743f6017d7b97af1fe49087ae15f0ac634373', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37641'} | null |
PyPI | GHSA-mh24-7wvg-v88g | Low severity vulnerability that affects pypiserver | CRLF Injection in pypiserver 1.2.5 and below allows attackers to set arbitrary HTTP headers and possibly conduct XSS attacks via a %0d%0a in a URI. | {'CVE-2019-6802'} | 2022-03-03T05:13:14.500131Z | 2019-01-30T20:56:26Z | MODERATE | null | {'CWE-74', 'CWE-79'} | {'https://github.com/pypiserver/pypiserver/issues/237', 'https://github.com/advisories/GHSA-mh24-7wvg-v88g', 'https://nvd.nist.gov/vuln/detail/CVE-2019-6802'} | null |
PyPI | PYSEC-2017-56 | null | Plone 3.3 through 5.1a1 allows remote attackers to obtain information about the ID of sensitive content via unspecified vectors. | {'CVE-2016-4042'} | 2021-07-25T23:34:48.613344Z | 2017-02-24T20:59:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2016/04/20/2', 'https://plone.org/security/hotfix/20160419/unauthorized-disclosure-of-site-content'} | null |
PyPI | PYSEC-2013-15 | null | The salt master in Salt (aka SaltStack) 0.11.0 through 0.17.0 does not properly drop group privileges, which makes it easier for remote attackers to gain privileges. | {'CVE-2013-6617'} | 2021-07-05T00:01:26.106423Z | 2013-11-05T18:55:00Z | null | null | null | {'http://docs.saltstack.com/topics/releases/0.17.1.html'} | null |
PyPI | PYSEC-2021-681 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.FusedBatchNorm`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/828f346274841fa7505f7020e88ca36c22e557ab/tensorflow/core/kernels/fused_batch_norm_op.cc#L295-L297) performs a division based on the last dimension of the `x` tensor. Since this is controlled by the user, an attacker can trigger a denial of service. 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-2021-29555', 'GHSA-r35g-4525-29fq'} | 2021-12-09T06:35:24.280047Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r35g-4525-29fq', 'https://github.com/tensorflow/tensorflow/commit/1a2a87229d1d61e23a39373777c056161eb4084d'} | null |
PyPI | PYSEC-2021-496 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger undefined behavior by binding to null pointer in `tf.raw_ops.ParameterizedTruncatedNormal`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3f6fe4dfef6f57e768260b48166c27d148f3015f/tensorflow/core/kernels/parameterized_truncated_normal_op.cc#L630) does not validate input arguments before accessing the first element of `shape`. If `shape` argument is empty, then `shape_tensor.flat<T>()` is an empty array. 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-4p4p-www8-8fv9', 'CVE-2021-29568'} | 2021-12-09T06:34:53.905703Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4p4p-www8-8fv9', 'https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8'} | null |
PyPI | PYSEC-2021-6 | null | In Django 2.2 before 2.2.20, 3.0 before 3.0.14, and 3.1 before 3.1.8, MultiPartParser allowed directory traversal via uploaded files with suitably crafted file names. Built-in upload handlers were not affected by this vulnerability. | {'CVE-2021-28658', 'GHSA-xgxc-v2qg-chmh'} | 2021-05-12T08:15:00Z | 2021-04-06T15:15:00Z | null | null | null | {'https://docs.djangoproject.com/en/3.1/releases/security/', 'https://www.djangoproject.com/weblog/2021/apr/06/security-releases/', 'https://groups.google.com/g/django-announce/c/ePr5j-ngdPU', 'https://github.com/advisories/GHSA-xgxc-v2qg-chmh', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ZVKYPHR3TKR2ESWXBPOJEKRO2OSJRZUE/', 'https://lists.debian.org/debian-lts-announce/2021/04/msg00008.html'} | null |
PyPI | PYSEC-2020-98 | null | Red Discord Bot Dashboard is an easy-to-use interactive web dashboard to control your Redbot. In Red Discord Bot before version 0.1.7a an RCE exploit has been discovered. This exploit allows Discord users with specially crafted Server names and Usernames/Nicknames to inject code into the webserver front-end code. By abusing this exploit, it's possible to perform destructive actions and/or access sensitive information. This high severity exploit has been fixed on version 0.1.7a. There are no workarounds, bot owners must upgrade their relevant packages (Dashboard module and Dashboard webserver) in order to patch this issue. | {'CVE-2020-26249', 'GHSA-hm45-mgqm-gjm4'} | 2020-12-10T20:15:00Z | 2020-12-09T00:15:00Z | null | null | null | {'https://github.com/Cog-Creators/Red-Dashboard/commit/99d88b840674674166ce005b784ae8e31e955ab1', 'https://github.com/Cog-Creators/Red-Dashboard/security/advisories/GHSA-hm45-mgqm-gjm4', 'https://github.com/Cog-Creators/Red-Dashboard/commit/a6b9785338003ec87fb75305e7d1cc2d40c7ab91', 'https://pypi.org/project/Red-Dashboard'} | null |
PyPI | PYSEC-2020-77 | null | In libImaging/PcxDecode.c in Pillow before 7.1.0, an out-of-bounds read can occur when reading PCX files where state->shuffle is instructed to read beyond state->buffer. | null | 2020-07-27T19:15:00Z | 2020-06-25T19:15:00Z | null | null | null | {'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#diff-9478f2787e3ae9668a15123b165c23ac/commit/6a83e4324738bb0452fbe8074a995b1c73f08de7', '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-p5xh-vx83-mxcj | HTTP Request Smuggling in Twisted | In Twisted Web through 20.3.0, there was an HTTP request splitting vulnerability. When presented with a content-length and a chunked encoding header, the content-length took precedence and the remainder of the request body was interpreted as a pipelined request. | {'CVE-2020-10109'} | 2022-04-04T21:16:55.158716Z | 2020-03-31T15:40:12Z | CRITICAL | null | {'CWE-444'} | {'https://github.com/twisted/twisted/blob/6ff2c40e42416c83203422ff70dfc49d2681c8e2/NEWS.rst#twisted-2030-2020-03-13', 'https://usn.ubuntu.com/4308-1/', 'https://security.gentoo.org/glsa/202007-24', 'https://know.bishopfox.com/advisories/twisted-version-19.10.0', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/6ISMZFZBWW4EV6ETJGXAYIXN3AT7GBPL/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/YW3NIL7VXSGJND2Q4BSXM3CFTAFU6T7D/', 'https://lists.debian.org/debian-lts-announce/2022/02/msg00021.html', 'https://usn.ubuntu.com/4308-2/', 'https://github.com/twisted/twisted', 'https://nvd.nist.gov/vuln/detail/CVE-2020-10109', 'https://github.com/twisted/twisted/commit/4a7d22e490bb8ff836892cc99a1f54b85ccb0281'} | null |
PyPI | PYSEC-2022-165 | null | The package guake before 3.8.5 are vulnerable to Exposed Dangerous Method or Function due to the exposure of execute_command and execute_command_by_uuid methods via the d-bus interface, which makes it possible for a malicious user to run an arbitrary command via the d-bus method. **Note:** Exploitation requires the user to have installed another malicious program that will be able to send dbus signals or run terminal commands. | {'CVE-2021-23556', 'GHSA-7x48-7466-3g33', 'SNYK-PYTHON-GUAKE-2386334'} | 2022-03-17T16:54:03.713303Z | 2022-03-17T12:15:00Z | null | null | null | {'https://github.com/Guake/guake/pull/2017/commits/e3d671120bfe7ba28f50e256cc5e8a629781b888', 'https://github.com/Guake/guake/issues/1796', 'https://github.com/Guake/guake/pull/2017', 'https://github.com/advisories/GHSA-7x48-7466-3g33', 'https://snyk.io/vuln/SNYK-PYTHON-GUAKE-2386334', 'https://github.com/Guake/guake/releases'} | null |
PyPI | PYSEC-2021-479 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `MatrixTriangularSolve`(https://github.com/tensorflow/tensorflow/blob/8cae746d8449c7dda5298327353d68613f16e798/tensorflow/core/kernels/linalg/matrix_triangular_solve_op_impl.h#L160-L240) fails to terminate kernel execution if one validation condition fails. 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-2021-29551', 'GHSA-vqw6-72r7-fgw7'} | 2021-12-09T06:34:51.250544Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/480641e3599775a8895254ffbc0fc45621334f68', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vqw6-72r7-fgw7'} | null |
PyPI | GHSA-7x48-7466-3g33 | Command injection in guake | Guake is a drop-down terminal for GNOME. The package guake before 3.8.5 is vulnerable to Exposed Dangerous Method or Function due to the exposure of execute_command and execute_command_by_uuid methods via the d-bus interface, which makes it possible for a malicious user to run an arbitrary command via the d-bus method. **Note:** Exploitation requires the user to have installed another malicious program that will be able to send dbus signals or run terminal commands. | {'CVE-2021-23556'} | 2022-04-05T19:00:31.638645Z | 2022-03-18T00:01:11Z | MODERATE | null | null | {'https://github.com/Guake/guake/pull/2017/commits/e3d671120bfe7ba28f50e256cc5e8a629781b888', 'https://github.com/Guake/guake/issues/1796', 'https://github.com/Guake/guake/pull/2017', 'https://github.com/pypa/advisory-database/tree/main/vulns/guake/PYSEC-2022-165.yaml', 'https://github.com/Guake/guake', 'https://nvd.nist.gov/vuln/detail/CVE-2021-23556', 'https://snyk.io/vuln/SNYK-PYTHON-GUAKE-2386334', 'https://github.com/Guake/guake/releases'} | null |
PyPI | PYSEC-2021-183 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29546', 'GHSA-m34j-p8rj-wjxq'} | 2021-08-27T03:22:29.613359Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxq', 'https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb'} | null |
PyPI | PYSEC-2019-203 | null | Splunk-SDK-Python before 1.6.6 does not properly verify untrusted TLS server certificates, which could result in man-in-the-middle attacks. | {'CVE-2019-5729', 'GHSA-f58w-649r-qjr9'} | 2021-08-27T03:22:21.751156Z | 2019-03-21T16:01:00Z | null | null | null | {'https://github.com/advisories/GHSA-f58w-649r-qjr9', 'https://www.splunk.com/view/SP-CAAAQAD'} | null |
PyPI | PYSEC-2020-300 | null | In TensorFlow release candidate versions 2.4.0rc*, the general implementation for matching filesystem paths to globbing pattern is vulnerable to an access out of bounds of the array holding the directories. There are multiple invariants and preconditions that are assumed by the parallel implementation of GetMatchingPaths but are not verified by the PRs introducing it (#40861 and #44310). Thus, we are completely rewriting the implementation to fully specify and validate these. This is patched in version 2.4.0. This issue only impacts master branch and the release candidates for TF version 2.4. The final release of the 2.4 release will be patched. | {'GHSA-9jjw-hf72-3mxw', 'CVE-2020-26269'} | 2020-12-14T17:42:00Z | 2020-12-10T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9jjw-hf72-3mxw', 'https://github.com/tensorflow/tensorflow/commit/8b5b9dc96666a3a5d27fad7179ff215e3b74b67c'} | null |
PyPI | PYSEC-2015-10 | null | Django before 1.4.21, 1.5.x through 1.6.x, 1.7.x before 1.7.9, and 1.8.x before 1.8.3 uses an incorrect regular expression, which allows remote attackers to inject arbitrary headers and conduct HTTP response splitting attacks via a newline character in an (1) email message to the EmailValidator, a (2) URL to the URLValidator, or unspecified vectors to the (3) validate_ipv4_address or (4) validate_slug validator. | {'CVE-2015-5144'} | 2021-07-05T00:01:20.182098Z | 2015-07-14T17:59:00Z | null | null | null | {'http://www.securitytracker.com/id/1032820', 'http://www.debian.org/security/2015/dsa-3305', 'http://www.ubuntu.com/usn/USN-2671-1', 'http://www.oracle.com/technetwork/topics/security/bulletinoct2015-2511968.html', 'https://www.djangoproject.com/weblog/2015/jul/08/security-releases/', 'http://lists.opensuse.org/opensuse-updates/2015-10/msg00043.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-November/172084.html', 'https://security.gentoo.org/glsa/201510-06', 'http://www.securityfocus.com/bid/75665', 'http://lists.opensuse.org/opensuse-updates/2015-10/msg00046.html'} | null |
PyPI | PYSEC-2021-750 | null | TensorFlow is an end-to-end open source platform for machine learning. When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer. Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the `tensor_name` user controlled input and immediately retrieves the tensor at the restoration index (controlled via `preferred_shard` argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read. We have patched the issue in GitHub commit 9e82dce6e6bd1f36a57e08fa85af213e2b2f2622. 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-gh6x-4whr-2qv4', 'CVE-2021-37639'} | 2021-12-09T06:35:35.665255Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/9e82dce6e6bd1f36a57e08fa85af213e2b2f2622', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gh6x-4whr-2qv4'} | null |
PyPI | GHSA-x4g7-fvjj-prg8 | Division by 0 in `QuantizedConv2D` | ### Impact
An attacker can trigger a division by 0 in `tf.raw_ops.QuantizedConv2D`:
```python
import tensorflow as tf
input = tf.zeros([1, 1, 1, 1], dtype=tf.quint8)
filter = tf.constant([], shape=[1, 0, 1, 1], dtype=tf.quint8)
min_input = tf.constant(0.0)
max_input = tf.constant(0.0001)
min_filter = tf.constant(0.0)
max_filter = tf.constant(0.0001)
strides = [1, 1, 1, 1]
padding = "SAME"
tf.raw_ops.QuantizedConv2D(input=input, filter=filter, min_input=min_input, max_input=max_input, min_filter=min_filter, max_filter=max_filter, strides=strides, padding=padding)
```
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:
```cc
const int filter_value_count = filter_width * filter_height * input_depth;
const int64 patches_per_chunk = kMaxChunkSize / (filter_value_count * sizeof(T1));
```
### Patches
We have patched the issue in GitHub commit [cfa91be9863a91d5105a3b4941096044ab32036b](https://github.com/tensorflow/tensorflow/commit/cfa91be9863a91d5105a3b4941096044ab32036b).
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-2021-29527'} | 2022-03-03T05:13:59.524394Z | 2021-05-21T14:21:59Z | LOW | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29527', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x4g7-fvjj-prg8', 'https://github.com/tensorflow/tensorflow/commit/cfa91be9863a91d5105a3b4941096044ab32036b'} | null |
PyPI | GHSA-5f5c-687x-g5qm | Classic Buffer Overflow in pyo | Buffer Overflow Vulnerability exists in ajaxsoundstudio.com in Pyo < 1.03 in the Server_debug function, which allows remote attackers to conduct DoS attacks by deliberately passing on an overlong audio file name. | {'CVE-2021-41499'} | 2022-03-03T05:12:23.220091Z | 2022-01-07T00:10:33Z | HIGH | null | {'CWE-120'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-41499', 'https://github.com/belangeo/pyo', 'https://github.com/belangeo/pyo/issues/222'} | null |
PyPI | PYSEC-2021-300 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses `yaml.unsafe_load` which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. 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-2021-37678', 'GHSA-r6jx-9g48-2r5r'} | 2021-08-27T03:22:46.598549Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/23d6383eb6c14084a8fc3bdf164043b974818012', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6jx-9g48-2r5r'} | null |
PyPI | GHSA-887w-45rq-vxgf | Moderate severity vulnerability that affects SQLAlchemy | SQLAlchemy through 1.2.17 and 1.3.x through 1.3.0b2 allows SQL Injection via the order_by parameter. | {'CVE-2019-7164'} | 2022-03-23T22:00:07.130247Z | 2019-04-16T15:50:41Z | CRITICAL | null | {'CWE-89'} | {'http://lists.opensuse.org/opensuse-security-announce/2019-08/msg00087.html', 'https://github.com/sqlalchemy/sqlalchemy/issues/4481', 'https://nvd.nist.gov/vuln/detail/CVE-2019-7164', 'https://lists.debian.org/debian-lts-announce/2021/11/msg00005.html', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00016.html', 'https://github.com/sqlalchemy/sqlalchemy/commit/30307c4616ad67c01ddae2e1e8e34fabf6028414', 'https://access.redhat.com/errata/RHSA-2019:0984', 'https://www.oracle.com/security-alerts/cpujan2021.html', 'https://github.com/advisories/GHSA-887w-45rq-vxgf', 'http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00010.html', 'https://github.com/sqlalchemy/sqlalchemy', 'https://access.redhat.com/errata/RHSA-2019:0981', 'https://lists.debian.org/debian-lts-announce/2019/03/msg00020.html'} | null |
PyPI | PYSEC-2021-615 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference functions for the `QuantizeAndDequantizeV*` operations can trigger a read outside of bounds of heap allocated array. 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. | {'CVE-2021-41205', 'GHSA-49rx-x2rw-pc6f'} | 2021-12-09T06:35:08.369063Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/7cf73a2274732c9d82af51c2bc2cf90d13cd7e6d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-49rx-x2rw-pc6f'} | null |
PyPI | GHSA-9c78-vcq7-7vxq | Out of bounds write in TFLite | ### Impact
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.
### Patches
We have patched the issue in GitHub commit [6c0b2b70eeee588591680f5b7d5d38175fd7cdf6](https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6).
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-2022-23561'} | 2022-03-03T05:13:37.705682Z | 2022-02-09T23:53:47Z | HIGH | null | {'CWE-787'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-23561', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq', 'https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | PYSEC-2021-245 | null | TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.RaggedTensorToTensor`, an attacker can exploit an undefined behavior if input arguments are empty. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L356-L360) only checks that one of the tensors is not empty, but does not check for the other ones. There are multiple `DCHECK` validations to prevent heap OOB, but these are no-op in release builds, hence they don't prevent anything. The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits 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-rgvq-pcvf-hx75', 'CVE-2021-29608'} | 2021-08-27T03:22:40.610515Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f94ef358bb3e91d517446454edff6535bcfe8e4a', 'https://github.com/tensorflow/tensorflow/commit/b761c9b652af2107cfbc33efd19be0ce41daa33e', 'https://github.com/tensorflow/tensorflow/commit/c4d7afb6a5986b04505aca4466ae1951686c80f6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rgvq-pcvf-hx75'} | null |
PyPI | PYSEC-2020-245 | null | ovirt-engine-sdk-python before 3.4.0.7 and 3.5.0.4 does not verify that the hostname of the remote endpoint matches the Common Name (CN) or subjectAltName as specified by its x.509 certificate in a TLS/SSL session. This could allow man-in-the-middle attackers to spoof remote endpoints via an arbitrary valid certificate. | {'CVE-2014-0161'} | 2021-08-27T03:22:09.942049Z | 2020-01-02T18:15:00Z | null | null | null | {'https://access.redhat.com/security/cve/cve-2014-0161', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2014-0161'} | null |
PyPI | PYSEC-2014-3 | null | The (1) FilePathField, (2) GenericIPAddressField, and (3) IPAddressField model field classes in Django before 1.4.11, 1.5.x before 1.5.6, 1.6.x before 1.6.3, and 1.7.x before 1.7 beta 2 do not properly perform type conversion, which allows remote attackers to have unspecified impact and vectors, related to "MySQL typecasting." | {'CVE-2014-0474'} | 2021-07-05T00:01:18.748183Z | 2014-04-23T15:55:00Z | null | null | null | {'http://www.ubuntu.com/usn/USN-2169-1', 'https://www.djangoproject.com/weblog/2014/apr/21/security/', 'http://rhn.redhat.com/errata/RHSA-2014-0456.html', 'http://lists.opensuse.org/opensuse-updates/2014-09/msg00023.html', 'http://secunia.com/advisories/61281', 'http://rhn.redhat.com/errata/RHSA-2014-0457.html', 'http://www.debian.org/security/2014/dsa-2934'} | null |
PyPI | GHSA-pm3h-mm62-pwm8 | XML Entity Expansion in trytond and proteus | An XML Entity Expansion (XEE) issue was discovered in Tryton Application Platform (Server) 5.x through 5.0.45, 6.x through 6.0.15, and 6.1.x and 6.2.x through 6.2.5, and Tryton Application Platform (Command Line Client (proteus)) 5.x through 5.0.11, 6.x through 6.0.4, and 6.1.x and 6.2.x through 6.2.1. An unauthenticated user can send a crafted XML-RPC message to consume all the resources of the server. | {'CVE-2022-26662'} | 2022-03-28T16:00:10.900076Z | 2022-03-11T00:02:04Z | HIGH | null | {'CWE-776'} | {'https://www.debian.org/security/2022/dsa-5098', 'https://www.debian.org/security/2022/dsa-5099', 'https://discuss.tryton.org/t/security-release-for-issue11219-and-issue11244/5059', 'https://hg.tryton.org/trytond', 'https://lists.debian.org/debian-lts-announce/2022/03/msg00016.html', 'https://lists.debian.org/debian-lts-announce/2022/03/msg00017.html', 'https://nvd.nist.gov/vuln/detail/CVE-2022-26662', 'https://bugs.tryton.org/issue11244'} | null |
PyPI | PYSEC-2018-49 | null | In PyYAML before 5.1, the yaml.load() API could execute arbitrary code if used with untrusted data. The load() function has been deprecated in version 5.1 and the 'UnsafeLoader' has been introduced for backward compatibility with the function. | {'CVE-2017-18342', 'GHSA-rprw-h62v-c2w7'} | 2021-07-05T00:01:25.530537Z | 2018-06-27T12:29:00Z | null | null | null | {'https://security.gentoo.org/glsa/202003-45', 'https://github.com/yaml/pyyaml/wiki/PyYAML-yaml.load(input)-Deprecation', 'https://github.com/advisories/GHSA-rprw-h62v-c2w7', 'https://github.com/marshmallow-code/apispec/issues/278', 'https://github.com/yaml/pyyaml/issues/193', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/JEX7IPV5P2QJITAMA5Z63GQCZA5I6NVZ/', 'https://github.com/yaml/pyyaml/blob/master/CHANGES', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/KSQQMRUQSXBSUXLCRD3TSZYQ7SEZRKCE/', 'https://github.com/yaml/pyyaml/pull/74', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/M6JCFGEIEOFMWWIXGHSELMKQDD4CV2BA/'} | null |
PyPI | PYSEC-2019-192 | null | A flaw was discovered in the python-novajoin plugin, all versions up to, excluding 1.1.1, for Red Hat OpenStack Platform. The novajoin API lacked sufficient access control, allowing any keystone authenticated user to generate FreeIPA tokens. | {'GHSA-xf8c-3cgx-fcwm', 'CVE-2019-10138'} | 2021-08-27T03:22:09.442632Z | 2019-07-30T17:15:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2019-10138', 'https://review.opendev.org/#/c/631240/', 'https://github.com/advisories/GHSA-xf8c-3cgx-fcwm'} | null |
PyPI | PYSEC-2012-14 | null | Universal Feed Parser (aka feedparser or python-feedparser) before 5.1.2 allows remote attackers to cause a denial of service (memory consumption) via a crafted XML ENTITY declaration in a non-ASCII encoded document. | {'GHSA-hjf3-r7gw-9rwg', 'CVE-2012-2921'} | 2021-08-27T03:22:03.863933Z | 2012-05-21T22:55:00Z | null | null | null | {'https://wiki.mageia.org/en/Support/Advisories/MGASA-2012-0157', 'http://freecode.com/projects/feedparser/releases/344371', 'http://secunia.com/advisories/49256', 'http://www.securityfocus.com/bid/53654', 'http://osvdb.org/81701', 'https://github.com/advisories/GHSA-hjf3-r7gw-9rwg', 'https://code.google.com/p/feedparser/source/browse/trunk/NEWS?spec=svn706&r=706', 'https://code.google.com/p/feedparser/source/detail?r=703&path=/trunk/feedparser/feedparser.py', 'http://www.mandriva.com/security/advisories?name=MDVSA-2013:118'} | null |
PyPI | PYSEC-2010-29 | null | Multiple cross-site scripting (XSS) vulnerabilities in the paste.httpexceptions implementation in Paste before 1.7.4 allow remote attackers to inject arbitrary web script or HTML via vectors involving a 404 status code, related to (1) paste.urlparser.StaticURLParser, (2) paste.urlparser.PkgResourcesParser, (3) paste.urlmap.URLMap, and (4) HTTPNotFound. | {'CVE-2010-2477'} | 2021-08-27T03:22:10.125815Z | 2010-11-06T00:00:00Z | null | null | null | {'http://marc.info/?l=oss-security&m=127785414818815&w=2', 'http://bitbucket.org/ianb/paste/changeset/fcae59df8b56', 'http://groups.google.com/group/paste-users/browse_thread/thread/3b3fff3dadd0b1e5?pli=1', 'http://pylonshq.com/articles/archives/2010/6/paste_174_released_addresses_xss_security_hole', 'http://www.ubuntu.com/usn/USN-1026-1', 'http://secunia.com/advisories/42500', 'http://marc.info/?l=oss-security&m=127792576822169&w=2', 'http://groups.google.com/group/pylons-discuss/msg/8c256dc076a408d8?dmode=source&output=gplain', 'http://www.securityfocus.com/bid/41160'} | null |
PyPI | PYSEC-2021-838 | null | Invenio-Drafts-Resources is a submission/deposit module for Invenio, a software framework for research data management. Invenio-Drafts-Resources prior to versions 0.13.7 and 0.14.6 does not properly check permissions when a record is published. The vulnerability is exploitable in a default installation of InvenioRDM. An authenticated a user is able via REST API calls to publish draft records of other users if they know the record identifier and the draft validates (e.g. all require fields filled out). An attacker is not able to modify the data in the record, and thus e.g. *cannot* change a record from restricted to public. The problem is patched in Invenio-Drafts-Resources v0.13.7 and 0.14.6, which is part of InvenioRDM v6.0.1 and InvenioRDM v7.0 respectively. | {'CVE-2021-43781', 'GHSA-xr38-w74q-r8jv'} | 2021-12-10T06:37:24.899021Z | 2021-12-06T18:15:00Z | null | null | null | {'https://github.com/inveniosoftware/invenio-drafts-resources/commit/039b0cff1ad4b952000f4d8c3a93f347108b6626', 'https://github.com/inveniosoftware/invenio-drafts-resources/security/advisories/GHSA-xr38-w74q-r8jv'} | null |
PyPI | GHSA-q6j3-c4wc-63vw | CSRF tokens leaked in URL by canned query form | ### Impact
The HTML form for a read-only canned query includes the hidden CSRF token field added in #798 for writable canned queries (#698).
This means that submitting those read-only forms exposes the CSRF token in the URL - for example on https://latest.datasette.io/fixtures/neighborhood_search submitting the form took me to:
https://latest.datasette.io/fixtures/neighborhood_search?text=down&csrftoken=CSRFTOKEN-HERE
This token could potentially leak to an attacker if the resulting page has a link to an external site on it and the user clicks the link, since the token would be exposed in the referral logs.
### Patches
A fix for this issue has been released in Datasette 0.46.
### Workarounds
You can fix this issue in a Datasette instance without upgrading by copying the [0.46 query.html template](https://raw.githubusercontent.com/simonw/datasette/0.46/datasette/templates/query.html) into a custom `templates/` directory and running Datasette with the `--template-dir=templates/` option.
### References
Issue 918 discusses this in details: https://github.com/simonw/datasette/issues/918
### For more information
Contact swillison at gmail with any questions. | null | 2022-03-03T05:14:06.391514Z | 2020-08-11T14:54:40Z | MODERATE | null | {'CWE-200'} | {'https://snyk.io/vuln/SNYK-PYTHON-DATASETTE-598229', 'https://github.com/simonw/datasette/commit/7f10f0f7664d474c1be82bf668829e3b736a3d2b', 'https://github.com/simonw/datasette', 'https://github.com/simonw/datasette/issues/918', 'https://github.com/simonw/datasette/security/advisories/GHSA-q6j3-c4wc-63vw'} | null |
PyPI | GHSA-f8xq-q7px-wg8c | Improper Neutralization of Formula Elements in a CSV File in Gradio Flagging | ### Impact
The `gradio` library has a flagging functionality which saves input/output data into a CSV file on the developer's computer. This can allow a user to save arbitrary text into the CSV file, such as commands. If a program like MS Excel opens such a file, then it automatically runs these commands, which could lead to arbitrary commands running on the user's computer.
### Patches
The problem has been patched as of `2.8.11`, which escapes the data saved to the csv with single quotes.
### Workarounds
If you are using an older version of `gradio`, don't open csv files generated by `gradio` with Excel or similar spreadsheet programs.
| {'CVE-2022-24770'} | 2022-03-18T23:16:59.966123Z | 2022-03-18T23:11:43Z | HIGH | null | {'CWE-1236'} | {'https://github.com/gradio-app/gradio', 'https://github.com/gradio-app/gradio/pull/817', 'https://github.com/gradio-app/gradio/commit/80fea89117358ee105973453fdc402398ae20239', 'https://nvd.nist.gov/vuln/detail/CVE-2022-24770', 'https://github.com/gradio-app/gradio/security/advisories/GHSA-f8xq-q7px-wg8c'} | null |
PyPI | GHSA-fqr5-qphf-vfr8 | Cross Site Scripting (XSS) in Simiki | Cross Site Scripting (XSS) in Simiki v1.6.2.1 and prior allows remote attackers to execute arbitrary code via line 54 of the component 'simiki/blob/master/simiki/generators.py'. | {'CVE-2020-19000'} | 2022-03-03T05:12:58.818641Z | 2021-09-01T18:37:01Z | MODERATE | null | {'CWE-79'} | {'https://github.com/tankywoo/simiki', 'https://github.com/tankywoo/simiki/issues/123', 'https://nvd.nist.gov/vuln/detail/CVE-2020-19000'} | null |
PyPI | PYSEC-2021-584 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.Map*` and `tf.raw_ops.OrderedMap*` operations. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L222-L248) has a check in place to ensure that `indices` is in ascending order, but does not check that `indices` is not empty. We have patched the issue in GitHub commit 532f5c5a547126c634fefd43bbad1dc6417678ac. 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-2021-37671', 'GHSA-qr82-2c78-4m8h'} | 2021-12-09T06:35:05.048687Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qr82-2c78-4m8h', 'https://github.com/tensorflow/tensorflow/commit/532f5c5a547126c634fefd43bbad1dc6417678ac'} | null |
PyPI | PYSEC-2022-132 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `AddManySparseToTensorsMap` is vulnerable to an integer overflow which results in a `CHECK`-fail when building new `TensorShape` objects (so, an assert failure based denial of service). 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 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-2022-23568', 'GHSA-6445-fm66-fvq2'} | 2022-03-09T00:18:26.728990Z | 2022-02-03T12:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a68f68061e263a88321c104a6c911fe5598050a8', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_tensors_map_ops.cc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6445-fm66-fvq2', 'https://github.com/tensorflow/tensorflow/commit/b51b82fe65ebace4475e3c54eb089c18a4403f1c'} | null |
PyPI | PYSEC-2014-85 | null | The Server.verify_request function in SimpleGeo python-oauth2 does not check the nonce, which allows remote attackers to perform replay attacks via a signed URL. | {'CVE-2013-4346'} | 2021-08-27T03:22:09.637359Z | 2014-05-20T14:55:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2013/09/12/7', 'http://www.securityfocus.com/bid/62386', 'https://github.com/simplegeo/python-oauth2/issues/129'} | null |
PyPI | GHSA-j8fq-86c5-5v2r | Remote code execution in dask | An issue was discovered in Dask (aka python-dask) through 2021.09.1. Single machine Dask clusters started with dask.distributed.LocalCluster or dask.distributed.Client (which defaults to using LocalCluster) would mistakenly configure their respective Dask workers to listen on external interfaces (typically with a randomly selected high port) rather than only on localhost. A Dask cluster created using this method (when running on a machine that has an applicable port exposed) could be used by a sophisticated attacker to achieve remote code execution. | {'CVE-2021-42343'} | 2022-03-21T20:00:06.928891Z | 2021-10-27T18:53:48Z | CRITICAL | null | {'CWE-668'} | {'https://docs.dask.org/en/latest/changelog.html', 'https://github.com/dask/distributed', 'https://github.com/dask/distributed/commit/afce4be8e05fb180e50a9d9e38465f1a82295e1b', 'https://nvd.nist.gov/vuln/detail/CVE-2021-42343', 'https://github.com/dask/distributed/security/advisories/GHSA-hwqr-f3v9-hwxr', 'https://github.com/dask/distributed/pull/5427'} | null |
PyPI | PYSEC-2020-20 | null | In Apache Airflow versions prior to 1.10.13, the Charts and Query View of the old (Flask-admin based) UI were vulnerable for SSRF attack. | {'CVE-2020-17513', 'GHSA-6r3p-fcvm-xh7c'} | 2020-12-15T15:40:00Z | 2020-12-14T10:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-6r3p-fcvm-xh7c', 'https://lists.apache.org/thread.html/rb3647269f07cc2775ca6568cbfd4994d862c842a58120d2aba9c658a%40%3Cusers.airflow.apache.org%3E'} | null |
PyPI | PYSEC-2021-357 | null | The Unicorn framework through 0.35.3 for Django allows XSS via component.name. | {'GHSA-c87f-fq5g-63r2', 'CVE-2021-42053'} | 2021-10-08T02:27:35.256995Z | 2021-10-07T06:15:00Z | null | null | null | {'https://github.com/adamghill/django-unicorn/pull/288/files', 'https://github.com/advisories/GHSA-c87f-fq5g-63r2'} | null |
PyPI | GHSA-p75j-wc34-527c | Exposure of Sensitive Information to an Unauthorized Actor in ansible | A flaw was found in ansible 2.8.0 before 2.8.4. Fields managing sensitive data should be set as such by no_log feature. Some of these fields in GCP modules are not set properly. service_account_contents() which is common class for all gcp modules is not setting no_log to True. Any sensitive data managed by that function would be leak as an output when running ansible playbooks. | {'CVE-2019-10217'} | 2022-03-03T05:13:46.669107Z | 2021-10-12T16:31:59Z | MODERATE | null | {'CWE-200'} | {'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00021.html', 'https://github.com/ansible/ansible/issues/56269', 'https://nvd.nist.gov/vuln/detail/CVE-2019-10217', 'http://lists.opensuse.org/opensuse-security-announce/2020-04/msg00026.html', 'https://github.com/ansible/ansible', 'https://github.com/ansible/ansible/pull/59427', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2019-10217'} | null |
PyPI | PYSEC-2021-707 | null | TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.CTCBeamSearchDecoder`, an attacker can trigger denial of service via segmentation faults. The implementation(https://github.com/tensorflow/tensorflow/blob/a74768f8e4efbda4def9f16ee7e13cf3922ac5f7/tensorflow/core/kernels/ctc_decoder_ops.cc#L68-L79) fails to detect cases when the input tensor is empty and proceeds to read data from a null buffer. 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-2021-29581', 'GHSA-vq2r-5xvm-3hc3'} | 2021-12-09T06:35:28.711775Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b1b323042264740c398140da32e93fb9c2c9f33e', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vq2r-5xvm-3hc3'} | null |
PyPI | GHSA-434h-p4gx-jm89 | Observable Response Discrepancy in Flask-AppBuilder | ### Impact
User enumeration in database authentication in Flask-AppBuilder <= 3.2.3. Allows for a non authenticated user to enumerate existing accounts by timing the response time from the server when you are logging in.
### Patches
Upgrade to 3.3.0
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [Flask-AppBuilder](https://github.com/dpgaspar/Flask-AppBuilder)
| {'CVE-2021-29621'} | 2022-03-03T05:13:01.517970Z | 2021-05-27T18:38:36Z | MODERATE | null | {'CWE-203'} | {'https://github.com/dpgaspar/Flask-AppBuilder/commit/780bd0e8fbf2d36ada52edb769477e0a4edae580', 'https://lists.apache.org/thread.html/r5b754118ba4e996adf03863705d34168bffec202da5c6bdc9bf3add5@%3Cannounce.apache.org%3E', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29621', 'https://pypi.org/project/Flask-AppBuilder/', 'https://github.com/dpgaspar/Flask-AppBuilder/security/advisories/GHSA-434h-p4gx-jm89', 'https://github.com/dpgaspar/Flask-AppBuilder', 'https://lists.apache.org/thread.html/r91067f953906d93aaa1c69fe2b5472754019cc6bd4f1ba81349d62a0@%3Ccommits.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/r466759f377651f0a690475d5a52564d0e786e82c08d5a5730a4f8352@%3Cannounce.apache.org%3E'} | null |
PyPI | PYSEC-2020-212 | null | Multiple cross-site scripting (XSS) vulnerabilities in Roundup before 1.4.20 allow remote attackers to inject arbitrary web script or HTML via the (1) @ok_message or (2) @error_message parameter to issue*. | {'CVE-2012-6133'} | 2021-07-05T00:01:25.863651Z | 2020-01-30T21:15:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=722672', 'https://pypi.python.org/pypi/roundup/1.4.20', 'http://www.openwall.com/lists/oss-security/2013/02/13/8', 'http://issues.roundup-tracker.org/issue2550724', 'http://www.openwall.com/lists/oss-security/2012/11/10/2'} | null |
PyPI | PYSEC-2010-4 | null | Multiple directory traversal vulnerabilities in FTPServer.py in pyftpdlib before 0.3.0 allow remote authenticated users to access arbitrary files and directories via vectors involving a symlink in a pathname to a (1) CWD, (2) DELE, (3) STOR, or (4) RETR command. | {'CVE-2008-7262'} | 2021-07-05T00:01:24.654243Z | 2010-10-19T20:00:00Z | null | null | null | {'http://code.google.com/p/pyftpdlib/source/browse/trunk/HISTORY', 'http://code.google.com/p/pyftpdlib/issues/detail?id=55'} | null |
PyPI | PYSEC-2017-95 | null | An exploitable vulnerability exists in the Databook loading functionality of Tablib 0.11.4. A yaml loaded Databook can execute arbitrary python commands resulting in command execution. An attacker can insert python into loaded yaml to trigger this vulnerability. | {'CVE-2017-2810', 'GHSA-gcr6-rf47-jrgf'} | 2021-08-27T03:22:22.103496Z | 2017-06-14T13:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-gcr6-rf47-jrgf', 'https://talosintelligence.com/vulnerability_reports/TALOS-2017-0307', 'https://security.gentoo.org/glsa/201811-18', 'http://www.securityfocus.com/bid/99076'} | null |
PyPI | PYSEC-2021-212 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-6qgm-fv6v-rfpv', 'CVE-2021-29575'} | 2021-08-27T03:22:34.716646Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6qgm-fv6v-rfpv'} | null |
PyPI | PYSEC-2019-7 | null | www/resource.py in Buildbot before 1.8.1 allows CRLF injection in the Location header of /auth/login and /auth/logout via the redirect parameter. This affects other web sites in the same domain. | {'CVE-2019-7313'} | 2019-02-06T21:48:00Z | 2019-02-03T08:29:00Z | null | null | null | {'https://github.com/buildbot/buildbot/wiki/CRLF-injection-in-Buildbot-login-and-logout-redirect-code'} | null |
PyPI | PYSEC-2021-642 | null | TensorFlow is an end-to-end open source platform for machine learning. Calling `tf.raw_ops.RaggedTensorToVariant` with arguments specifying an invalid ragged tensor results in a null pointer dereference. The implementation of `RaggedTensorToVariant` operations(https://github.com/tensorflow/tensorflow/blob/904b3926ed1c6c70380d5313d282d248a776baa1/tensorflow/core/kernels/ragged_tensor_to_variant_op.cc#L39-L40) does not validate that the ragged tensor argument is non-empty. Since `batched_ragged` contains no elements, `batched_ragged.splits` is a null vector, thus `batched_ragged.splits(0)` will result in dereferencing `nullptr`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-84mw-34w6-2q43', 'CVE-2021-29516'} | 2021-12-09T06:35:17.688674Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-84mw-34w6-2q43', 'https://github.com/tensorflow/tensorflow/commit/b055b9c474cd376259dde8779908f9eeaf097d93'} | null |
PyPI | GHSA-2jc8-4r6g-282j | Moderate severity vulnerability that affects python-gnupg | The shell_quote function in python-gnupg 0.3.5 does not properly escape characters, which allows context-dependent attackers to execute arbitrary code via shell metacharacters in unspecified vectors, as demonstrated using "\" (backslash) characters to form multi-command sequences, a different vulnerability than CVE-2014-1927. NOTE: this vulnerability exists because of an incomplete fix for CVE-2013-7323. | {'CVE-2014-1928'} | 2020-06-16T20:52:26Z | 2018-11-06T23:13:02Z | MODERATE | null | {'CWE-20'} | {'http://seclists.org/oss-sec/2014/q1/246', 'https://github.com/advisories/GHSA-2jc8-4r6g-282j', 'http://secunia.com/advisories/56616', 'https://code.google.com/p/python-gnupg/issues/detail?id=98', 'http://seclists.org/oss-sec/2014/q1/294', 'http://secunia.com/advisories/59031', 'http://www.debian.org/security/2014/dsa-2946', 'https://nvd.nist.gov/vuln/detail/CVE-2014-1928', 'https://code.google.com/p/python-gnupg/'} | null |
PyPI | GHSA-2xwp-m7mq-7q3r | CLI does not correctly implement strict mode | In the affected versions, the AWS Encryption CLI operated in "discovery mode" even when "strict mode" was specified. Although decryption only succeeded if the user had permission to decrypt with at least one of the CMKs, decryption could be successful using a CMK that was not included in the user-defined set when the CLI was operating in "strict mode."
Affected users should upgrade to Encryption CLI v1.8.x or v2.1.x as soon as possible. | null | 2022-03-03T05:12:12.871982Z | 2020-10-28T17:05:38Z | LOW | null | {'CWE-326'} | {'https://github.com/aws/aws-encryption-sdk-cli/commit/7d21b8051cab9e52e056fe427d2bff19cf146460', 'https://github.com/aws/aws-encryption-sdk-cli/security/advisories/GHSA-2xwp-m7mq-7q3r'} | null |
PyPI | GHSA-6v6p-p97v-g2p7 | Out-of-bounds Write in OpenCV | OpenCV (Open Source Computer Vision Library) through 3.3 (corresponding to OpenCV-Python and OpenCV-Contrib-Python 3.3.0.9) has an invalid write in the cv::RLByteStream::getBytes function in modules/imgcodecs/src/bitstrm.cpp when reading an image file by using cv::imread, as demonstrated by the 2-opencv-heapoverflow-fseek test case. | {'CVE-2017-12603'} | 2022-03-03T05:13:26.905438Z | 2021-10-12T22:01:44Z | HIGH | null | {'CWE-787'} | {'https://lists.debian.org/debian-lts-announce/2021/10/msg00028.html', 'https://github.com/opencv/opencv/issues/9309', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00030.html', 'https://security.gentoo.org/glsa/201712-02', 'https://github.com/xiaoqx/pocs/blob/master/opencv.md', 'https://github.com/opencv/opencv/pull/9376', 'https://nvd.nist.gov/vuln/detail/CVE-2017-12603', 'https://github.com/opencv/opencv-python'} | null |
PyPI | PYSEC-2019-184 | null | Ladon since 0.6.1 (since ebef0aae48af78c159b6fce81bc6f5e7e0ddb059) is affected by: XML External Entity (XXE). The impact is: Information Disclosure, reading files and reaching internal network endpoints. The component is: SOAP request handlers. For instance: https://bitbucket.org/jakobsg/ladon/src/42944fc012a3a48214791c120ee5619434505067/src/ladon/interfaces/soap.py#lines-688. The attack vector is: Send a specially crafted SOAP call. | {'CVE-2019-1010268', 'GHSA-vg35-vc9f-q7x2'} | 2021-08-27T03:22:05.932908Z | 2019-07-18T17:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-vg35-vc9f-q7x2', 'https://bitbucket.org/jakobsg/ladon/src/42944fc012a3a48214791c120ee5619434505067/src/ladon/interfaces/soap.py#lines-688', 'https://www.exploit-db.com/exploits/43113'} | null |
PyPI | GHSA-xrqm-fpgr-6hhx | Overflow/crash in `tf.range` | ### Impact
While calculating the size of the output within the `tf.range` kernel, there is a conditional statement of type `int64 = condition ? int64 : double`. Due to C++ implicit conversion rules, both branches of the condition will be cast to `double` and the result would be truncated before the assignment. This result in overflows:
```python
import tensorflow as tf
tf.sparse.eye(num_rows=9223372036854775807, num_columns=None)
```
Similarly, `tf.range` would result in crashes due to overflows if the start or end point are too large.
```python
import tensorflow as tf
tf.range(start=-1e+38, limit=1)
```
### Patches
We have patched the issue in GitHub commits [6d94002a09711d297dbba90390d5482b76113899](https://github.com/tensorflow/tensorflow/commit/6d94002a09711d297dbba90390d5482b76113899) (merging [#51359](https://github.com/tensorflow/tensorflow/pull/51359)) and [1b0e0ec27e7895b9985076eab32445026ae5ca94](https://github.com/tensorflow/tensorflow/commit/1b0e0ec27e7895b9985076eab32445026ae5ca94) (merging [#51711](https://github.com/tensorflow/tensorflow/pull/51711)).
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.
### 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 externally via [GitHub issue](https://github.com/tensorflow/tensorflow/issues/46912), [GitHub issue](https://github.com/tensorflow/tensorflow/issues/46899) and [GitHub issue](https://github.com/tensorflow/tensorflow/issues/46889).
| {'CVE-2021-41202'} | 2022-03-03T05:14:05.060099Z | 2021-11-10T19:13:16Z | MODERATE | null | {'CWE-681'} | {'https://github.com/tensorflow/tensorflow/commit/1b0e0ec27e7895b9985076eab32445026ae5ca94', 'https://github.com/tensorflow/tensorflow/issues/46889', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xrqm-fpgr-6hhx', 'https://github.com/tensorflow/tensorflow/issues/46912', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41202', 'https://github.com/tensorflow/tensorflow/commit/6d94002a09711d297dbba90390d5482b76113899'} | null |
PyPI | PYSEC-2020-36 | null | Django 1.11 before 1.11.29, 2.2 before 2.2.11, and 3.0 before 3.0.4 allows SQL Injection if untrusted data is used as a tolerance parameter in GIS functions and aggregates on Oracle. By passing a suitably crafted tolerance to GIS functions and aggregates on Oracle, it was possible to break escaping and inject malicious SQL. | {'CVE-2020-9402', 'GHSA-3gh2-xw74-jmcw'} | 2020-07-14T17:28:00Z | 2020-03-05T15:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-3gh2-xw74-jmcw', 'https://security.netapp.com/advisory/ntap-20200327-0004/', 'https://www.djangoproject.com/weblog/2020/mar/04/security-releases/', 'https://security.gentoo.org/glsa/202004-17', 'https://docs.djangoproject.com/en/3.0/releases/security/', 'https://groups.google.com/forum/#!topic/django-announce/fLUh_pOaKrY', 'https://www.debian.org/security/2020/dsa-4705', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/4A2AP4T7RKPBCLTI2NNQG3T6MINDUUMZ/', 'https://usn.ubuntu.com/4296-1/'} | null |
PyPI | PYSEC-2020-2 | null | An archive traversal flaw was found in all ansible-engine versions 2.9.x prior to 2.9.7, when running ansible-galaxy collection install. When extracting a collection .tar.gz file, the directory is created without sanitizing the filename. An attacker could take advantage to overwrite any file within the system. | {'GHSA-3c67-gc48-983w', 'CVE-2020-10691'} | 2020-05-21T14:49:00Z | 2020-04-30T17:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-3c67-gc48-983w', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-10691', 'https://github.com/ansible/ansible/pull/68596'} | null |
PyPI | PYSEC-2014-93 | null | PyWBEM 0.7 and earlier uses a separate connection to validate X.509 certificates, which allows man-in-the-middle attackers to spoof a peer via an arbitrary certificate. | {'CVE-2013-6418'} | 2021-08-27T03:22:18.674694Z | 2014-05-05T17:06:00Z | null | null | null | {'https://www.suse.com/support/update/announcement/2014/suse-su-20140580-1.html', 'http://secunia.com/advisories/58327', 'http://www.securityfocus.com/bid/64544', 'http://seclists.org/oss-sec/2013/q4/531', 'http://sourceforge.net/p/pywbem/mailman/message/31757312/', 'https://bugzilla.redhat.com/show_bug.cgi?id=1039801', 'http://sourceforge.net/p/pywbem/code/627/', 'http://www.oracle.com/technetwork/topics/security/bulletinjan2016-2867206.html'} | null |
PyPI | PYSEC-2022-124 | null | Tensorflow is an Open Source Machine Learning Framework. 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. The fix is 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. Users are advised to upgrade as soon as possible. | {'GHSA-4hvf-hxvg-f67v', 'CVE-2022-23560'} | 2022-03-09T00:18:25.643457Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4hvf-hxvg-f67v', 'https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/kernels/internal/utils/sparsity_format_converter.cc#L252-L293', 'https://github.com/tensorflow/tensorflow/commit/6364463d6f5b6254cac3d6aedf999b6a96225038'} | null |
PyPI | PYSEC-2021-592 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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-2021-37679', 'GHSA-g8wg-cjwc-xhhp'} | 2021-12-09T06:35:05.737030Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g8wg-cjwc-xhhp', 'https://github.com/tensorflow/tensorflow/commit/4e2565483d0ffcadc719bd44893fb7f609bb5f12'} | null |
PyPI | PYSEC-2021-438 | null | django-helpdesk is vulnerable to Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') | {'GHSA-2v5j-q74q-r53f', 'CVE-2021-3994'} | 2021-12-02T21:26:01.187346Z | 2021-12-01T11:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-2v5j-q74q-r53f', 'https://huntr.dev/bounties/be7f211d-4bfd-44fd-91e8-682329906fbd', 'https://github.com/django-helpdesk/django-helpdesk/commit/a22eb0673fe0b7784f99c6b5fd343b64a6700f06'} | null |
PyPI | GHSA-62gx-355r-9fhg | Session operations in eager mode lead to null pointer dereferences | ### Impact
In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference:
```python
import tensorflow as tf
tf.raw_ops.GetSessionTensor(handle=['\x12\x1a\x07'],dtype=4)
```
```python
import tensorflow as tf
tf.raw_ops.DeleteSessionTensor(handle=['\x12\x1a\x07'])
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid:
```cc
OP_REQUIRES_OK(ctx, ctx->session_state()->GetTensor(name, &val));
```
Thus, in eager mode, `ctx->session_state()` is nullptr and the call of the member function is undefined behavior.
### Patches
We have patched the issue in GitHub commit [ff70c47a396ef1e3cb73c90513da4f5cb71bebba](https://github.com/tensorflow/tensorflow/commit/ff70c47a396ef1e3cb73c90513da4f5cb71bebba).
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-2021-29518'} | 2022-03-03T05:13:04.427750Z | 2021-05-21T14:21:05Z | LOW | null | {'CWE-476'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29518', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-62gx-355r-9fhg', 'https://github.com/tensorflow/tensorflow/commit/ff70c47a396ef1e3cb73c90513da4f5cb71bebba'} | null |
PyPI | PYSEC-2015-7 | null | ModelMultipleChoiceField in Django 1.6.x before 1.6.10 and 1.7.x before 1.7.3, when show_hidden_initial is set to True, allows remote attackers to cause a denial of service by submitting duplicate values, which triggers a large number of SQL queries. | {'CVE-2015-0222'} | 2021-07-05T00:01:19.802913Z | 2015-01-16T16:59:00Z | null | null | null | {'https://www.djangoproject.com/weblog/2015/jan/13/security/', 'http://ubuntu.com/usn/usn-2469-1', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-January/148485.html', 'http://advisories.mageia.org/MGASA-2015-0026.html', 'http://secunia.com/advisories/62285', 'http://lists.opensuse.org/opensuse-updates/2015-04/msg00001.html', 'http://secunia.com/advisories/62309', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-January/148608.html', 'http://lists.fedoraproject.org/pipermail/package-announce/2015-January/148696.html', 'http://lists.opensuse.org/opensuse-updates/2015-09/msg00035.html', 'http://www.mandriva.com/security/advisories?name=MDVSA-2015:109'} | null |
PyPI | PYSEC-2020-341 | null | An exploitable vulnerability exists in the configuration-loading functionality of the jw.util package before 2.3 for Python. When loading a configuration with FromString or FromStream with YAML, one can execute arbitrary Python code, resulting in OS command execution, because safe_load is not used. | {'CVE-2020-13388', 'GHSA-h72c-w3q3-55qq'} | 2022-01-05T02:16:25.743194Z | 2020-05-22T17:15:00Z | null | null | null | {'https://joel-malwarebenchmark.github.io', 'https://github.com/advisories/GHSA-h72c-w3q3-55qq', 'https://joel-malwarebenchmark.github.io/blog/2020/04/27/cve-2020-13388-jw-util-vulnerability/', 'https://security.netapp.com/advisory/ntap-20200528-0002/'} | null |
PyPI | PYSEC-2011-12 | null | Directory traversal vulnerability in Django 1.1.x before 1.1.4 and 1.2.x before 1.2.5 on Windows might allow remote attackers to read or execute files via a / (slash) character in a key in a session cookie, related to session replays. | {'GHSA-7g9h-c88w-r7h2', 'CVE-2011-0698'} | 2021-07-15T02:22:08.473566Z | 2011-02-14T21:00:00Z | null | null | null | {'http://www.mandriva.com/security/advisories?name=MDVSA-2011:031', 'https://github.com/advisories/GHSA-7g9h-c88w-r7h2', 'http://www.vupen.com/english/advisories/2011/0372', 'http://secunia.com/advisories/43230', 'http://www.djangoproject.com/weblog/2011/feb/08/security/', 'http://www.securityfocus.com/bid/46296', 'http://www.vupen.com/english/advisories/2011/0439', 'http://openwall.com/lists/oss-security/2011/02/09/6'} | null |
PyPI | GHSA-393f-2jr3-cp69 | CHECK-fail in DrawBoundingBoxes | ### Impact
An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`:
```python
import tensorflow as tf
images = tf.fill([53, 0, 48, 1], 0.)
boxes = tf.fill([53, 31, 4], 0.)
boxes = tf.Variable(boxes)
boxes[0, 0, 0].assign(3.90621)
tf.raw_ops.DrawBoundingBoxes(images=images, boxes=boxes)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`.
```cc
const int64 max_box_row_clamp = std::min<int64>(max_box_row, height - 1);
...
CHECK_GE(max_box_row_clamp, 0);
```
In this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution.
### Patches
We have patched the issue in GitHub commit [b432a38fe0e1b4b904a6c222cbce794c39703e87](https://github.com/tensorflow/tensorflow/commit/b432a38fe0e1b4b904a6c222cbce794c39703e87).
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-2021-29533'} | 2022-03-03T05:13:02.902950Z | 2021-05-21T14:22:21Z | LOW | null | {'CWE-754'} | {'https://github.com/tensorflow/tensorflow/commit/b432a38fe0e1b4b904a6c222cbce794c39703e87', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-393f-2jr3-cp69', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29533'} | null |
PyPI | PYSEC-2021-711 | null | TensorFlow is an end-to-end open source platform for machine learning. The TFLite computation for size of output after padding, `ComputeOutSize`(https://github.com/tensorflow/tensorflow/blob/0c9692ae7b1671c983569e5d3de5565843d500cf/tensorflow/lite/kernels/padding.h#L43-L55), does not check that the `stride` argument is not 0 before doing the division. Users can craft special models such that `ComputeOutSize` is called with `stride` set to 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-mv78-g7wq-mhp4', 'CVE-2021-29585'} | 2021-12-09T06:35:29.363788Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mv78-g7wq-mhp4', 'https://github.com/tensorflow/tensorflow/commit/49847ae69a4e1a97ae7f2db5e217c77721e37948'} | null |
PyPI | PYSEC-2021-341 | null | Incorrect Access Control in Lin-CMS-Flask v0.1.1 allows remote attackers to obtain sensitive information and/or gain privileges due to the application not invalidating a user's authentication token upon logout, which allows for replaying packets. | {'CVE-2020-18701'} | 2022-03-16T02:19:50.092963Z | 2021-08-16T18:15:00Z | null | null | null | {'https://github.com/TaleLin/lin-cms-flask/issues/30'} | null |
PyPI | PYSEC-2006-3 | null | Cross-site request forgery (CSRF) vulnerability in Edgewall Trac 0.10 and earlier allows remote attackers to perform unauthorized actions as other users via unknown vectors. | {'CVE-2006-5878'} | 2021-07-16T01:31:34.062903Z | 2006-11-14T19:07:00Z | null | null | null | {'http://www.vupen.com/english/advisories/2006/4422', 'http://secunia.com/advisories/23357', 'http://security.gentoo.org/glsa/glsa-200612-14.xml', 'http://secunia.com/advisories/22789', 'http://trac.edgewall.org/ticket/4049', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/30146', 'http://trac.edgewall.org/wiki/ChangeLog', 'http://secunia.com/advisories/22868', 'http://www.debian.org/security/2006/dsa-1209'} | null |
PyPI | PYSEC-2021-654 | 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.QuantizedMul`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55900e961ed4a23b438392024912154a2c2f5e85/tensorflow/core/kernels/quantized_mul_op.cc#L188-L198) 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. | {'CVE-2021-29528', 'GHSA-6f84-42vf-ppwp'} | 2021-12-09T06:35:19.582800Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/a1b11d2fdd1e51bfe18bb1ede804f60abfa92da6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6f84-42vf-ppwp'} | null |
PyPI | PYSEC-2021-204 | null | TensorFlow is an end-to-end open source platform for machine learning. Due to lack of validation in `tf.raw_ops.SparseDenseCwiseMul`, an attacker can trigger denial of service via `CHECK`-fails or accesses to outside the bounds of heap allocated data. Since the implementation(https://github.com/tensorflow/tensorflow/blob/38178a2f7a681a7835bb0912702a134bfe3b4d84/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L68-L80) only validates the rank of the input arguments but no constraints between dimensions(https://www.tensorflow.org/api_docs/python/tf/raw_ops/SparseDenseCwiseMul), an attacker can abuse them to trigger internal `CHECK` assertions (and cause program termination, denial of service) or to write to memory outside of bounds of heap allocated tensor buffers. 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-2021-29567', 'GHSA-wp3c-xw9g-gpcg'} | 2021-08-27T03:22:33.334705Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/7ae2af34087fb4b5c8915279efd03da3b81028bc', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wp3c-xw9g-gpcg'} | null |
PyPI | GHSA-4c4g-crqm-xrxw | Use of unitialized value in TFLite | ### Impact
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):
```cc
const auto* affine_quantization =
reinterpret_cast<TfLiteAffineQuantization*>(
filter->quantization.params);
```
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.
### Patches
We have patched the issue in GitHub commits [537bc7c723439b9194a358f64d871dd326c18887](https://github.com/tensorflow/tensorflow/commit/537bc7c723439b9194a358f64d871dd326c18887),
[4a91f2069f7145aab6ba2d8cfe41be8a110c18a5](https://github.com/tensorflow/tensorflow/commit/4a91f2069f7145aab6ba2d8cfe41be8a110c18a5) and [8933b8a21280696ab119b63263babdb54c298538](https://github.com/tensorflow/tensorflow/commit/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.
### 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-2021-37682'} | 2021-08-24T16:41:39Z | 2021-08-25T14:40:32Z | MODERATE | null | {'CWE-908'} | {'https://github.com/tensorflow/tensorflow/commit/537bc7c723439b9194a358f64d871dd326c18887', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37682', 'https://github.com/tensorflow/tensorflow', '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-2017-83 | null | Scrapy 1.4 allows remote attackers to cause a denial of service (memory consumption) via large files because arbitrarily many files are read into memory, which is especially problematic if the files are then individually written in a separate thread to a slow storage resource, as demonstrated by interaction between dataReceived (in core/downloader/handlers/http11.py) and S3FilesStore. | {'CVE-2017-14158'} | 2022-03-01T15:19:56.850925Z | 2017-09-05T17:29:00Z | null | null | null | {'http://blog.csdn.net/wangtua/article/details/75228728', 'https://github.com/scrapy/scrapy/issues/482'} | null |
PyPI | GHSA-mjcr-rqjg-rhg3 | Implementation trusts the "me" field returned by the authorization server without verifying it | ### Impact
A malicious user can sign in as a user with any IndieAuth identifier. This is because the implementation does not verify that the final `"me"` URL value returned by the authorization server belongs to the same domain as the initial value entered by the user.
### Patches
Version 1.1 fixes this issue.
### Workarounds
There is no workaround. Upgrade to 1.1 immediately.
### References
- [Security Considerations: Differing User Profile URLs](https://indieauth.spec.indieweb.org/#differing-user-profile-urls-li-1) in the IndieAuth specification.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [simonw/datasette-indieauth](https://github.com/simonw/datasette-indieauth/issues) | null | 2022-03-21T20:04:49Z | 2020-11-24T21:21:04Z | CRITICAL | null | {'CWE-290'} | {'https://github.com/simonw/datasette-indieauth/commit/376c8804c6b0811852049229a24336fe5eb6a439', 'https://pypi.org/project/datasette-indieauth/', 'https://github.com/simonw/datasette-indieauth', 'https://github.com/simonw/datasette-indieauth/security/advisories/GHSA-mjcr-rqjg-rhg3'} | null |
PyPI | PYSEC-2020-204 | null | Ansible before 1.6.7 does not prevent inventory data with "{{" and "lookup" substrings, and does not prevent remote data with "{{" substrings, which allows remote attackers to execute arbitrary code via (1) crafted lookup('pipe') calls or (2) crafted Jinja2 data. | {'CVE-2014-4966'} | 2021-07-02T02:41:33.333300Z | 2020-02-18T15:15:00Z | null | null | null | {'http://www.ocert.org/advisories/ocert-2014-004.html', 'https://github.com/ansible/ansible/commit/62a1295a3e08cb6c3e9f1b2a1e6e5dcaeab32527'} | null |
PyPI | PYSEC-2016-16 | null | The password hasher in contrib/auth/hashers.py in Django before 1.8.10 and 1.9.x before 1.9.3 allows remote attackers to enumerate users via a timing attack involving login requests. | {'CVE-2016-2513'} | 2021-07-15T02:22:10.225115Z | 2016-04-08T15:59:00Z | null | null | null | {'http://www.ubuntu.com/usn/USN-2915-3', 'http://www.securitytracker.com/id/1035152', 'https://github.com/django/django/commit/67b46ba7016da2d259c1ecc7d666d11f5e1cfaab', 'http://rhn.redhat.com/errata/RHSA-2016-0506.html', 'http://rhn.redhat.com/errata/RHSA-2016-0505.html', 'http://www.ubuntu.com/usn/USN-2915-1', 'http://www.debian.org/security/2016/dsa-3544', 'http://www.ubuntu.com/usn/USN-2915-2', 'http://www.oracle.com/technetwork/topics/security/bulletinapr2016-2952098.html', 'http://rhn.redhat.com/errata/RHSA-2016-0504.html', 'http://www.securityfocus.com/bid/83878', 'https://www.djangoproject.com/weblog/2016/mar/01/security-releases/', 'http://rhn.redhat.com/errata/RHSA-2016-0502.html'} | null |
PyPI | PYSEC-2021-480 | 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'} | 2021-12-09T06:34:51.420468Z | 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-2021-195 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-mqh2-9wrp-vx84', 'CVE-2021-29558'} | 2021-08-27T03:22:31.758663Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mqh2-9wrp-vx84', 'https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31'} | null |
PyPI | PYSEC-2022-173 | null | An issue was discovered in SaltStack Salt in versions before 3002.8, 3003.4, 3004.1. Job publishes and file server replies are susceptible to replay attacks, which can result in an attacker replaying job publishes causing minions to run old jobs. File server replies can also be re-played. A sufficient craft attacker could gain root access on minion under certain scenarios. | {'CVE-2022-22936'} | 2022-03-29T18:37:44.021549Z | 2022-03-29T17:15:00Z | null | null | null | {'https://saltproject.io/security_announcements/salt-security-advisory-release/,', 'https://github.com/saltstack/salt/releases,', 'https://repo.saltproject.io/'} | null |
PyPI | PYSEC-2020-61 | null | In lookatme (python/pypi package) versions prior to 2.3.0, the package automatically loaded the built-in "terminal" and "file_loader" extensions. Users that use lookatme to render untrusted markdown may have malicious shell commands automatically run on their system. This is fixed in version 2.3.0. As a workaround, the `lookatme/contrib/terminal.py` and `lookatme/contrib/file_loader.py` files may be manually deleted. Additionally, it is always recommended to be aware of what is being rendered with lookatme. | {'GHSA-c84h-w6cr-5v8q', 'CVE-2020-15271'} | 2020-11-13T16:40:00Z | 2020-10-26T18:15:00Z | null | null | null | {'https://pypi.org/project/lookatme/#history', 'https://github.com/d0c-s4vage/lookatme/security/advisories/GHSA-c84h-w6cr-5v8q', 'https://github.com/d0c-s4vage/lookatme/commit/72fe36b784b234548d49dae60b840c37f0eb8d84', 'https://github.com/d0c-s4vage/lookatme/pull/110', 'https://github.com/d0c-s4vage/lookatme/releases/tag/v2.3.0'} | null |
PyPI | PYSEC-2019-25 | null | invenio-communities before 1.0.0a20 allows XSS. | {'GHSA-mfv8-q39f-mgfg', 'CVE-2019-1020005'} | 2019-08-01T16:59:00Z | 2019-07-29T15:15:00Z | null | null | null | {'https://github.com/inveniosoftware/invenio-communities/security/advisories/GHSA-mfv8-q39f-mgfg'} | null |
PyPI | GHSA-hr84-fqvp-48mm | Segfault in SparseCountSparseOutput | ### Impact
Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken.
```python
import tensorflow as tf
indices = tf.constant([], shape=[0, 0], dtype=tf.int64)
values = tf.constant([], shape=[0, 0], dtype=tf.int64)
dense_shape = tf.constant([-100, -100, -100], shape=[3], dtype=tf.int64)
weights = tf.constant([], shape=[0, 0], dtype=tf.int64)
tf.raw_ops.SparseCountSparseOutput(indices=indices, values=values, dense_shape=dense_shape, weights=weights, minlength=79, maxlength=96, binary_output=False)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., [`std::vector<absl::flat_hash_map<int64,T>>`](https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure.
```cc
bool is_1d = shape.NumElements() == 1;
int num_batches = is_1d ? 1 : shape.flat<int64>()(0);
...
auto per_batch_counts = BatchedMap<W>(num_batches);
```
If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`.
Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue.
### Patches
We have patched the issue in GitHub commit [c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5](https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.
### 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-2021-29521'} | 2022-03-03T05:13:33.495080Z | 2021-05-21T14:21:16Z | LOW | null | {'CWE-131'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hr84-fqvp-48mm', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29521', 'https://github.com/tensorflow/tensorflow/commit/c57c0b9f3a4f8684f3489dd9a9ec627ad8b599f5'} | null |
PyPI | PYSEC-2018-3 | null | An issue was discovered in Django 2.1 before 2.1.2, in which unprivileged users can read the password hashes of arbitrary accounts. The read-only password widget used by the Django Admin to display an obfuscated password hash was bypassed if a user has only the "view" permission (new in Django 2.1), resulting in display of the entire password hash to those users. This may result in a vulnerability for sites with legacy user accounts using insecure hashes. | {'CVE-2018-16984', 'GHSA-6mx3-3vqg-hpp2'} | 2021-06-10T06:50:43.349902Z | 2018-10-02T18:29:00Z | null | null | null | {'http://www.securitytracker.com/id/1041749', 'https://security.netapp.com/advisory/ntap-20190502-0009/', 'https://www.djangoproject.com/weblog/2018/oct/01/security-release/', 'https://github.com/advisories/GHSA-6mx3-3vqg-hpp2'} | null |
PyPI | PYSEC-2021-746 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of sparse reduction operations in TensorFlow can trigger accesses outside of bounds of heap allocated data. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_reduce_op.cc#L217-L228) fails to validate that each reduction group does not overflow and that each corresponding index does not point to outside the bounds of the input tensor. We have patched the issue in GitHub commit 87158f43f05f2720a374f3e6d22a7aaa3a33f750. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-cgfm-62j4-v4rf', 'CVE-2021-37635'} | 2021-12-09T06:35:35.309422Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cgfm-62j4-v4rf', 'https://github.com/tensorflow/tensorflow/commit/87158f43f05f2720a374f3e6d22a7aaa3a33f750'} | null |
PyPI | PYSEC-2020-316 | null | In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | {'CVE-2020-15201', 'GHSA-p5f8-gfw5-33w4'} | 2021-12-09T06:35:13.253783Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4'} | null |
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