ecosystem stringclasses 14 values | vuln_id stringlengths 10 19 | summary stringlengths 4 267 ⌀ | details stringlengths 9 13.5k | aliases stringlengths 17 144 ⌀ | modified_date stringdate 2010-05-27 05:47:00 2022-05-10 08:46:52 | published_date stringdate 2005-12-31 05:00:00 2022-05-10 08:46:50 | severity stringclasses 5 values | score float64 0 10 ⌀ | cwe_id stringclasses 988 values | refs stringlengths 30 17.7k ⌀ | introduced stringlengths 75 4.26k ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|
PyPI | PYSEC-2021-131 | null | Synapse is a Matrix reference homeserver written in python (pypi package matrix-synapse). Matrix is an ecosystem for open federated Instant Messaging and VoIP. In Synapse before version 1.25.0, requests to user provided domains were not restricted to external IP addresses when calculating the key validity for third-party invite events and sending push notifications. This could cause Synapse to make requests to internal infrastructure. The type of request was not controlled by the user, although limited modification of request bodies was possible. For the most thorough protection server administrators should remove the deprecated `federation_ip_range_blacklist` from their settings after upgrading to Synapse v1.25.0 which will result in Synapse using the improved default IP address restrictions. See the new `ip_range_blacklist` and `ip_range_whitelist` settings if more specific control is necessary. | {'GHSA-v936-j8gp-9q3p', 'CVE-2021-21273'} | 2021-08-27T03:22:06.569635Z | 2021-02-26T18:15:00Z | null | null | null | {'https://github.com/matrix-org/synapse/releases/tag/v1.25.0', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-v936-j8gp-9q3p', 'https://github.com/matrix-org/synapse/pull/8821', 'https://github.com/matrix-org/synapse/commit/30fba6210834a4ecd91badf0c8f3eb278b72e746'} | null |
PyPI | GHSA-h72c-w3q3-55qq | OS Command Injection in jw.util | 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'} | 2022-03-03T05:13:11.235861Z | 2021-06-02T21:45:12Z | HIGH | null | {'CWE-78'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-13388', 'https://joel-malwarebenchmark.github.io', '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-2021-561 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the code for `tf.raw_ops.SaveV2` does not properly validate the inputs and an attacker can trigger a null pointer dereference. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/save_restore_v2_ops.cc) uses `ValidateInputs` to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above. However, the validation uses `OP_REQUIRES` which translates to setting the `Status` object of the current `OpKernelContext` to an error status, followed by an empty `return` statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in `Compute` that follows the call to `ValidateInputs`. This is equivalent to lacking the validation. We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986. 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-2021-37648', 'GHSA-wp77-4gmm-7cq8'} | 2021-12-09T06:35:03.096515Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wp77-4gmm-7cq8', 'https://github.com/tensorflow/tensorflow/commit/9728c60e136912a12d99ca56e106b7cce7af5986'} | null |
PyPI | PYSEC-2014-60 | null | The object manager implementation (objectmanager.py) in Plone 2.1 through 4.1, 4.2.x through 4.2.5, and 4.3.x through 4.3.1 does not properly restrict access to internal methods, which allows remote attackers to obtain sensitive information via a crafted request. | {'CVE-2013-4196'} | 2021-07-25T23:34:46.895458Z | 2014-03-11T19:37:00Z | null | null | null | {'http://plone.org/products/plone-hotfix/releases/20130618', 'http://seclists.org/oss-sec/2013/q3/261', 'https://bugzilla.redhat.com/show_bug.cgi?id=978475', 'http://plone.org/products/plone/security/advisories/20130618-announcement'} | null |
PyPI | PYSEC-2022-138 | null | Tensorflow is an Open Source Machine Learning Framework. There is a typo in TensorFlow's `SpecializeType` which results in heap OOB read/write. Due to a typo, `arg` is initialized to the `i`th mutable argument in a loop where the loop index is `j`. Hence it is possible to assign to `arg` from outside the vector of arguments. Since this is a mutable proto value, it allows both read and write to outside of bounds data. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range. | {'GHSA-77gp-3h4r-6428', 'CVE-2022-23574'} | 2022-03-09T00:18:27.547711Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/full_type_util.cc#L81-L102', 'https://github.com/tensorflow/tensorflow/commit/0657c83d08845cc434175934c642299de2c0f042', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-77gp-3h4r-6428'} | null |
PyPI | PYSEC-2021-424 | null | Matrix is an ecosystem for open federated Instant Messaging and Voice over IP. In versions 1.41.0 and prior, unauthorised users can access the name, avatar, topic and number of members of a room if they know the ID of the room. This vulnerability is limited to homeservers where the vulnerable homeserver is in the room and untrusted users are permitted to create groups (communities). By default, only homeserver administrators can create groups. However, homeserver administrators can already access this information in the database or using the admin API. As a result, only homeservers where the configuration setting `enable_group_creation` has been set to `true` are impacted. Server administrators should upgrade to 1.41.1 or higher to patch the vulnerability. There are two potential workarounds. Server administrators can set `enable_group_creation` to `false` in their homeserver configuration (this is the default value) to prevent creation of groups by non-administrators. Administrators that are using a reverse proxy could, with partial loss of group functionality, block the endpoints `/_matrix/client/r0/groups/{group_id}/rooms` and `/_matrix/client/unstable/groups/{group_id}/rooms`. | {'CVE-2021-39163', 'GHSA-jj53-8fmw-f2w2'} | 2021-11-16T03:58:44.500451Z | 2021-08-31T16:15:00Z | null | null | null | {'https://github.com/matrix-org/synapse/releases/tag/v1.41.1', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2VHDEPCZ22GJFMZCWA2XZAGPOEV72POF/', 'https://github.com/matrix-org/synapse/security/advisories/GHSA-jj53-8fmw-f2w2', 'https://github.com/matrix-org/synapse/commit/cb35df940a', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/PXT7ID7DNBRN2TVTETU3SYQHJKEG6PXN/'} | null |
PyPI | PYSEC-2022-17 | null | Gerapy is a distributed crawler management framework. Prior to version 0.9.9, an authenticated user could execute arbitrary commands. This issue is fixed in version 0.9.9. There are no known workarounds. | {'GHSA-756h-r2c9-qp5j', 'CVE-2021-32849'} | 2022-02-02T21:26:17.207117Z | 2022-01-26T22:15:00Z | null | null | null | {'https://github.com/Gerapy/Gerapy/issues/217', 'https://lgtm.com/projects/g/Gerapy/Gerapy?mode=tree&ruleFocus=1505994646253', 'https://github.com/Gerapy/Gerapy/issues/197', 'https://securitylab.github.com/advisories/GHSL-2021-076-gerapy/', 'https://github.com/Gerapy/Gerapy/security/advisories/GHSA-756h-r2c9-qp5j'} | null |
PyPI | PYSEC-2019-177 | null | An error-handling flaw was found in python-ecdsa before version 0.13.3. During signature decoding, malformed DER signatures could raise unexpected exceptions (or no exceptions at all), which could lead to a denial of service. | {'CVE-2019-14853', 'GHSA-2mrj-435v-c2cr', 'GHSA-pwfw-mgfj-7g3g'} | 2021-08-27T03:22:03.507805Z | 2019-11-26T13:15:00Z | null | null | null | {'https://www.debian.org/security/2019/dsa-4588', 'https://github.com/advisories/GHSA-pwfw-mgfj-7g3g', 'https://github.com/warner/python-ecdsa/releases/tag/python-ecdsa-0.13.3', 'https://github.com/advisories/GHSA-2mrj-435v-c2cr', 'https://seclists.org/bugtraq/2019/Dec/33', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2019-14853'} | null |
PyPI | GHSA-5f2r-qp73-37mr | `CHECK`-failures during Grappler's `SafeToRemoveIdentity` in Tensorflow | ### Impact
The Grappler optimizer in TensorFlow can be used to cause a denial of service by altering a `SavedModel` such that [`SafeToRemoveIdentity`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/dependency_optimizer.cc#L59-L98) would trigger `CHECK` failures.
### Patches
We have patched the issue in GitHub commit [92dba16749fae36c246bec3f9ba474d9ddeb7662](https://github.com/tensorflow/tensorflow/commit/92dba16749fae36c246bec3f9ba474d9ddeb7662).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. | {'CVE-2022-23579'} | 2022-03-03T05:13:50.267333Z | 2022-02-10T00:33:29Z | MODERATE | null | {'CWE-617'} | {'https://nvd.nist.gov/vuln/detail/CVE-2022-23579', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/dependency_optimizer.cc#L59-L98', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5f2r-qp73-37mr', 'https://github.com/tensorflow/tensorflow/commit/92dba16749fae36c246bec3f9ba474d9ddeb7662', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | GHSA-mvg9-xffr-p774 | Out of bounds read in Pillow | An issue was discovered in Pillow before 8.1.1. In TiffDecode.c, there is an out-of-bounds read in TiffreadRGBATile via invalid tile boundaries. | {'CVE-2021-25291'} | 2022-03-03T05:14:07.810296Z | 2021-03-29T16:35:57Z | HIGH | null | {'CWE-125'} | {'https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html', 'https://security.gentoo.org/glsa/202107-33', 'https://github.com/python-pillow/Pillow/commit/cbdce6c5d054fccaf4af34b47f212355c64ace7a', 'https://github.com/python-pillow/Pillow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-25291'} | null |
PyPI | PYSEC-2017-66 | null | The checkPassword function in python-kerberos does not authenticate the KDC it attempts to communicate with, which allows remote attackers to cause a denial of service (bad response), or have other unspecified impact by performing a man-in-the-middle attack. | {'CVE-2015-3206'} | 2021-07-25T23:34:51.016854Z | 2017-08-25T18:29:00Z | null | null | null | {'https://github.com/apple/ccs-pykerberos/issues/31', 'https://bugzilla.redhat.com/show_bug.cgi?id=1223802', 'https://pypi.python.org/pypi/kerberos', 'http://www.securityfocus.com/bid/74760', 'http://www.openwall.com/lists/oss-security/2015/05/21/3'} | null |
PyPI | GHSA-5gqf-456p-4836 | Reference binding to nullptr in `SdcaOptimizer` | ### Impact
The implementation of `tf.raw_ops.SdcaOptimizer` triggers undefined behavior due to dereferencing a null pointer:
```python
import tensorflow as tf
sparse_example_indices = [tf.constant((0), dtype=tf.int64), tf.constant((0), dtype=tf.int64)]
sparse_feature_indices = [tf.constant([], shape=[0, 0, 0, 0], dtype=tf.int64), tf.constant((0), dtype=tf.int64)]
sparse_feature_values = []
dense_features = []
dense_weights = []
example_weights = tf.constant((0.0), dtype=tf.float32)
example_labels = tf.constant((0.0), dtype=tf.float32)
sparse_indices = [tf.constant((0), dtype=tf.int64), tf.constant((0), dtype=tf.int64)]
sparse_weights = [tf.constant((0.0), dtype=tf.float32), tf.constant((0.0), dtype=tf.float32)]
example_state_data = tf.constant([0.0, 0.0, 0.0, 0.0], shape=[1, 4], dtype=tf.float32)
tf.raw_ops.SdcaOptimizer(
sparse_example_indices=sparse_example_indices,
sparse_feature_indices=sparse_feature_indices,
sparse_feature_values=sparse_feature_values, dense_features=dense_features,
example_weights=example_weights, example_labels=example_labels,
sparse_indices=sparse_indices, sparse_weights=sparse_weights,
dense_weights=dense_weights, example_state_data=example_state_data,
loss_type="logistic_loss", l1=0.0, l2=0.0, num_loss_partitions=1,
num_inner_iterations=1, adaptative=False)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/60a45c8b6192a4699f2e2709a2645a751d435cc3/tensorflow/core/kernels/sdca_internal.cc) does not validate that the user supplied arguments satisfy all [constraints expected by the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SdcaOptimizer).
### Patches
We have patched the issue in GitHub commit [f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb](https://github.com/tensorflow/tensorflow/commit/f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb).
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-2021-29572'} | 2022-03-03T05:13:10.211775Z | 2021-05-21T14:25:31Z | LOW | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5gqf-456p-4836', 'https://github.com/tensorflow/tensorflow/commit/f7cc8755ac6683131fdfa7a8a121f9d7a9dec6fb', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29572'} | null |
PyPI | PYSEC-2019-78 | null | A vulnerability was found in ceilometer before version 12.0.0.0rc1. An Information Exposure in ceilometer-agent prints sensitive configuration data to log files without DEBUG logging being activated. | {'CVE-2019-3830'} | 2020-10-22T14:44:00Z | 2019-03-26T18:29:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2019:0919', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2019-3830'} | null |
PyPI | GHSA-6r3p-fcvm-xh7c | SSRF vulnerability in Arache Airflow | 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'} | 2022-03-03T05:13:51.061684Z | 2020-12-17T21:00:58Z | MODERATE | null | {'CWE-918'} | {'https://lists.apache.org/thread.html/rb3647269f07cc2775ca6568cbfd4994d862c842a58120d2aba9c658a%40%3Cusers.airflow.apache.org%3E', 'https://nvd.nist.gov/vuln/detail/CVE-2020-17513'} | null |
PyPI | PYSEC-2011-18 | null | Cross-site scripting (XSS) vulnerability in feedparser.py in Universal Feed Parser (aka feedparser or python-feedparser) before 5.0 allows remote attackers to inject arbitrary web script or HTML via vectors involving nested CDATA stanzas. | {'CVE-2009-5065'} | 2021-08-27T03:22:03.724216Z | 2011-04-11T18:55:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-updates/2011-04/msg00026.html', 'http://secunia.com/advisories/44074', 'http://www.mandriva.com/security/advisories?name=MDVSA-2011:082', 'https://bugzilla.novell.com/show_bug.cgi?id=680074', 'http://code.google.com/p/feedparser/issues/detail?id=195', 'https://bugzilla.redhat.com/show_bug.cgi?id=684877', 'http://support.novell.com/security/cve/CVE-2009-5065.html', 'http://www.securityfocus.com/bid/47177'} | null |
PyPI | PYSEC-2013-25 | null | The Python client in Apache Qpid before 2.2 does not verify that the server hostname matches a domain name in the subject's Common Name (CN) or subjectAltName field of the X.509 certificate, which allows man-in-the-middle attackers to spoof SSL servers via an arbitrary valid certificate. | {'CVE-2013-1909'} | 2021-07-25T23:34:52.564224Z | 2013-08-23T16:55:00Z | null | null | null | {'http://rhn.redhat.com/errata/RHSA-2013-1024.html', 'http://secunia.com/advisories/54137', 'https://issues.apache.org/jira/browse/QPID-4918', 'http://qpid.apache.org/releases/qpid-0.22/release-notes.html', 'http://svn.apache.org/viewvc?view=revision&revision=1460013', 'http://secunia.com/advisories/53968'} | null |
PyPI | PYSEC-2021-11 | null | django-registration is a user registration package for Django. The django-registration package provides tools for implementing user-account registration flows in the Django web framework. In django-registration prior to 3.1.2, the base user-account registration view did not properly apply filters to sensitive data, with the result that sensitive data could be included in error reports rather than removed automatically by Django. Triggering this requires: A site is using django-registration < 3.1.2, The site has detailed error reports (such as Django's emailed error reports to site staff/developers) enabled and a server-side error (HTTP 5xx) occurs during an attempt by a user to register an account. Under these conditions, recipients of the detailed error report will see all submitted data from the account-registration attempt, which may include the user's proposed credentials (such as a password). | {'GHSA-58c7-px5v-82hh', 'CVE-2021-21416'} | 2021-04-06T18:40:00Z | 2021-04-01T22:15:00Z | null | null | null | {'https://github.com/ubernostrum/django-registration/security/advisories/GHSA-58c7-px5v-82hh'} | null |
PyPI | GHSA-8w3x-457r-wg53 | Out-of-bounds Write in OpenCV | OpenCV (Open Source Computer Vision Library) through 3.3 (corresponding to opencv-python and opencv-contrib-python through 3.3.0.9) has an out-of-bounds write error in the function FillColorRow1 in utils.cpp when reading an image file by using cv::imread. | {'CVE-2017-12597'} | 2022-03-03T05:13:24.769844Z | 2021-10-12T22:00:41Z | HIGH | null | {'CWE-787'} | {'https://nvd.nist.gov/vuln/detail/CVE-2017-12597', 'https://github.com/opencv/opencv-python/releases/tag/11', '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-python/releases/tag/9', 'https://github.com/opencv/opencv/pull/9376', 'https://github.com/opencv/opencv-python'} | null |
PyPI | GHSA-vqhp-cxgc-6wmm | regular expression denial-of-service (ReDoS) in Bleach | ### Impact
`bleach.clean` behavior parsing style attributes could result in a regular expression denial of service (ReDoS).
Calls to ``bleach.clean`` with an allowed tag with an allowed ``style`` attribute are vulnerable to ReDoS. For example, ``bleach.clean(..., attributes={'a': ['style']})``.
### Patches
3.1.4
### Workarounds
* do not whitelist the style attribute in `bleach.clean` calls
* limit input string length
### References
* https://bugzilla.mozilla.org/show_bug.cgi?id=1623633
* https://www.regular-expressions.info/redos.html
* https://blog.r2c.dev/posts/finding-python-redos-bugs-at-scale-using-dlint-and-r2c/
* https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-6817
### Credits
* Reported by schwag09 of r2c
### For more information
If you have any questions or comments about this advisory:
* Open an issue at https://github.com/mozilla/bleach/issues
* Email us at security@mozilla.org | {'CVE-2020-6817'} | 2022-03-03T05:13:01.828284Z | 2020-03-30T19:45:56Z | HIGH | null | {'CWE-400'} | {'https://snyk.io/vuln/SNYK-PYTHON-BLEACH-561754', 'https://github.com/mozilla/bleach/security/advisories/GHSA-vqhp-cxgc-6wmm', 'https://github.com/mozilla/bleach/releases/tag/v3.1.4', 'https://nvd.nist.gov/vuln/detail/CVE-2020-6817', 'https://bugzilla.mozilla.org/show_bug.cgi?id=1623633'} | null |
PyPI | GHSA-vmjw-c2vp-p33c | Crash in NMS ops caused by integer conversion to unsigned | ### Impact
An attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0:
```python
import tensorflow as tf
tf.raw_ops.NonMaxSuppressionV5(
boxes=[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]],
scores=[1.0,2.0,3.0],
max_output_size=-1,
iou_threshold=0.5,
score_threshold=0.5,
soft_nms_sigma=1.0,
pad_to_max_output_size=True)
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`:
```cc
const int output_size = max_output_size.scalar<int>()();
// ...
std::vector<int> selected;
// ...
if (pad_to_max_output_size) {
selected.resize(output_size, 0);
// ...
}
```
However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to usigned. If the attacker supplies a negative value, this conversion results in a crash.
A similar issue occurs in `CombinedNonMaxSuppression`:
```python
import tensorflow as tf
tf.raw_ops.NonMaxSuppressionV5(
boxes=[[[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]],[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]],[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]]]],
scores=[[[1.0,2.0,3.0],[1.0,2.0,3.0],[1.0,2.0,3.0]]],
max_output_size_per_class=-1,
max_total_size=10,
iou_threshold=score_threshold=0.5,
pad_per_class=True,
clip_boxes=True)
```
### Patches
We have patched the issue in GitHub commit [3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d](https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d) and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58](https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### 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-2021-37669'} | 2022-03-03T05:14:08.140626Z | 2021-08-25T14:42:03Z | MODERATE | null | {'CWE-681'} | {'https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58', 'https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vmjw-c2vp-p33c', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37669', 'https://github.com/tensorflow/tensorflow/'} | null |
PyPI | GHSA-wm2m-xrrp-j74c | HTTP Request Smuggling in netius | netius prior to 1.17.58 is vulnerable to HTTP Request Smuggling. HTTP pipelining issues and request smuggling attacks might be possible due to incorrect Transfer encoding header parsing which could allow for CL:TE or TE:TE attacks. | {'CVE-2020-7655'} | 2022-03-03T05:12:37.803031Z | 2021-06-18T18:31:40Z | MODERATE | null | {'CWE-444'} | {'https://nvd.nist.gov/vuln/detail/CVE-2020-7655', 'https://snyk.io/vuln/SNYK-PYTHON-NETIUS-569141'} | null |
PyPI | PYSEC-2017-89 | null | Mercurial prior to 4.3 did not adequately sanitize hostnames passed to ssh, leading to possible shell-injection attacks. | {'CVE-2017-1000116'} | 2021-08-27T03:22:07.062416Z | 2017-10-05T01:29:00Z | null | null | null | {'https://access.redhat.com/errata/RHSA-2017:2489', 'https://www.mercurial-scm.org/wiki/WhatsNew#Mercurial_4.3_.2F_4.3.1_.282017-08-10.29', 'http://www.debian.org/security/2017/dsa-3963', 'http://www.securityfocus.com/bid/100290', 'https://security.gentoo.org/glsa/201709-18'} | null |
PyPI | PYSEC-2014-76 | null | Zope before 2.13.19, as used in Plone before 4.2.3 and 4.3 before beta 1, does not reseed the pseudo-random number generator (PRNG), which makes it easier for remote attackers to guess the value via unspecified vectors. NOTE: this issue was SPLIT from CVE-2012-5508 due to different vulnerability types (ADT2). | {'GHSA-48vv-2pmq-9fvv', 'CVE-2012-6661'} | 2021-07-25T23:34:59.010626Z | 2014-11-03T22:55:00Z | null | null | null | {'https://bugs.launchpad.net/zope2/+bug/1071067', 'https://plone.org/products/plone/security/advisories/20121106/24', 'https://github.com/plone/Products.CMFPlone/blob/4.2.3/docs/CHANGES.txt', 'http://www.openwall.com/lists/oss-security/2012/11/10/1', 'https://github.com/advisories/GHSA-48vv-2pmq-9fvv', 'https://plone.org/products/plone-hotfix/releases/20121124'} | null |
PyPI | PYSEC-2021-577 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `BoostedTreesSparseCalculateBestFeatureSplit`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/stats_ops.cc) needs to validate that each value in `stats_summary_indices` is in range. We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37664', 'GHSA-r4c4-5fpq-56wg'} | 2021-12-09T06:35:04.439609Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r4c4-5fpq-56wg', 'https://github.com/tensorflow/tensorflow/commit/e84c975313e8e8e38bb2ea118196369c45c51378'} | null |
PyPI | PYSEC-2021-127 | null | Apache Superset up to and including 0.38.0 allowed the creation of a Markdown component on a Dashboard page for describing chart's related information. Abusing this functionality, a malicious user could inject javascript code executing unwanted action in the context of the user's browser. The javascript code will be automatically executed (Stored XSS) when a legitimate user surfs on the dashboard page. The vulnerability is exploitable creating a “div” section and embedding in it a “svg” element with javascript code. | {'CVE-2021-27907'} | 2021-08-27T03:21:55.702415Z | 2021-03-05T12:15:00Z | null | null | null | {'https://lists.apache.org/thread.html/r09293fb09f1d617f0d2180c42210e739e2211f8da9bc5c1873bea67a@%3Cdev.superset.apache.org%3E', 'https://lists.apache.org/thread.html/r09293fb09f1d617f0d2180c42210e739e2211f8da9bc5c1873bea67a%40%3Cdev.superset.apache.org%3E'} | null |
PyPI | PYSEC-2018-55 | null | gunicorn version 19.4.5 contains a CWE-113: Improper Neutralization of CRLF Sequences in HTTP Headers vulnerability in "process_headers" function in "gunicorn/http/wsgi.py" that can result in an attacker causing the server to return arbitrary HTTP headers. This vulnerability appears to have been fixed in 19.5.0. | {'GHSA-32pc-xphx-q4f6', 'CVE-2018-1000164'} | 2021-07-15T02:22:14.592267Z | 2018-04-18T19:29:00Z | null | null | null | {'https://lists.debian.org/debian-lts-announce/2018/04/msg00022.html', 'https://github.com/benoitc/gunicorn/issues/1227', 'https://www.debian.org/security/2018/dsa-4186', 'https://github.com/advisories/GHSA-32pc-xphx-q4f6', 'https://usn.ubuntu.com/4022-1/', 'https://epadillas.github.io/2018/04/02/http-header-splitting-in-gunicorn-19.4.5'} | null |
PyPI | PYSEC-2020-127 | null | In eager mode, TensorFlow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1 does not set the session state. Hence, calling `tf.raw_ops.GetSessionHandle` or `tf.raw_ops.GetSessionHandleV2` results in a null pointer dereference In linked snippet, in eager mode, `ctx->session_state()` returns `nullptr`. Since code immediately dereferences this, we get a segmentation fault. The issue is patched in commit 9a133d73ae4b4664d22bd1aa6d654fec13c52ee1, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'GHSA-q8gv-q7wr-9jf8', 'CVE-2020-15204'} | 2020-10-29T16:15:00Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q8gv-q7wr-9jf8', 'https://github.com/tensorflow/tensorflow/commit/9a133d73ae4b4664d22bd1aa6d654fec13c52ee1', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html'} | null |
PyPI | GHSA-ch4f-829c-v5pw | Division by 0 in `ResourceScatterDiv` | ### Impact
The implementation of `tf.raw_ops.ResourceScatterDiv` is vulnerable to a division by 0 error:
```python
import tensorflow as tf
v= tf.Variable([1,2,3])
tf.raw_ops.ResourceScatterDiv(
resource=v.handle,
indices=[1],
updates=[0])
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/resource_variable_ops.cc#L865) uses a common class for all binary operations but fails to treat the division by 0 case separately.
### Patches
We have patched the issue in GitHub commit [4aacb30888638da75023e6601149415b39763d76](https://github.com/tensorflow/tensorflow/commit/4aacb30888638da75023e6601149415b39763d76).
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-2021-37642'} | 2022-03-03T05:13:41.042235Z | 2021-08-25T14:43:56Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ch4f-829c-v5pw', 'https://github.com/tensorflow/tensorflow/commit/4aacb30888638da75023e6601149415b39763d76', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37642'} | null |
PyPI | PYSEC-2021-824 | null | TensorFlow is an open source platform for machine learning. In affected versions the process of building the control flow graph for a TensorFlow model is vulnerable to a null pointer exception when nodes that should be paired are not. This occurs because the code assumes that the first node in the pairing (e.g., an `Enter` node) always exists when encountering the second node (e.g., an `Exit` node). When this is not the case, `parent` is `nullptr` so dereferencing it causes a crash. 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-2021-41217', 'GHSA-5crj-c72x-m7gq'} | 2021-12-09T06:35:43.751303Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/05cbebd3c6bb8f517a158b0155debb8df79017ff', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5crj-c72x-m7gq'} | null |
PyPI | PYSEC-2019-161 | null | python-keystoneclient version 0.2.3 to 0.2.5 has middleware memcache signing bypass | {'GHSA-9vg3-cf92-h2h7', 'CVE-2013-2167'} | 2021-07-25T23:34:52.007420Z | 2019-12-10T15:15:00Z | null | null | null | {'http://www.openwall.com/lists/oss-security/2013/06/19/5', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2013-2167', 'https://bugs.gentoo.org/show_bug.cgi?id=CVE-2013-2167', 'http://rhn.redhat.com/errata/RHSA-2013-0992.html', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/85492', 'https://github.com/advisories/GHSA-9vg3-cf92-h2h7', 'http://www.securityfocus.com/bid/60680', 'https://security-tracker.debian.org/tracker/CVE-2013-2167', 'http://lists.fedoraproject.org/pipermail/package-announce/2013-August/113944.html', 'https://access.redhat.com/security/cve/cve-2013-2167'} | null |
PyPI | PYSEC-2021-432 | null | Nanopb is a small code-size Protocol Buffers implementation in ansi C. In Nanopb before versions 0.3.9.8 and 0.4.5, decoding a specifically formed message can cause invalid `free()` or `realloc()` calls if the message type contains an `oneof` field, and the `oneof` directly contains both a pointer field and a non-pointer field. If the message data first contains the non-pointer field and then the pointer field, the data of the non-pointer field is incorrectly treated as if it was a pointer value. Such message data rarely occurs in normal messages, but it is a concern when untrusted data is parsed. This has been fixed in versions 0.3.9.8 and 0.4.5. See referenced GitHub Security Advisory for more information including workarounds. | {'CVE-2021-21401', 'GHSA-7mv5-5mxh-qg88'} | 2021-11-24T22:47:12.152718Z | 2021-03-23T18:15:00Z | null | null | null | {'https://github.com/nanopb/nanopb/issues/647', 'https://github.com/nanopb/nanopb/commit/e2f0ccf939d9f82931d085acb6df8e9a182a4261', 'https://github.com/nanopb/nanopb/security/advisories/GHSA-7mv5-5mxh-qg88', 'https://github.com/nanopb/nanopb/blob/c9124132a604047d0ef97a09c0e99cd9bed2c818/CHANGELOG.txt#L1'} | null |
PyPI | PYSEC-2014-99 | null | Multiple cross-site scripting (XSS) vulnerabilities in the respond_error function in routing.py in Eugene Pankov Ajenti before 1.2.21.7 allow remote attackers to inject arbitrary web script or HTML via the PATH_INFO to (1) resources.js or (2) resources.css in ajenti:static/, related to the traceback page. | {'CVE-2014-4301'} | 2021-12-13T06:35:03.086455Z | 2014-06-18T14:55:00Z | null | null | null | {'http://www.securityfocus.com/bid/68047', 'https://github.com/Eugeny/ajenti/commit/d3fc5eb142ff16d55d158afb050af18d5ff09120', 'http://secunia.com/advisories/59177', 'https://www.netsparker.com/critical-xss-vulnerabilities-in-ajenti'} | null |
PyPI | PYSEC-2020-8 | null | A flaw was found in Ansible Engine when a file is moved using atomic_move primitive as the file mode cannot be specified. This sets the destination files world-readable if the destination file does not exist and if the file exists, the file could be changed to have less restrictive permissions before the move. This could lead to the disclosure of sensitive data. All versions in 2.7.x, 2.8.x and 2.9.x branches are believed to be vulnerable. | {'CVE-2020-1736', 'GHSA-x7jh-595q-wq82'} | 2020-09-08T17:15:00Z | 2020-03-16T16:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-x7jh-595q-wq82', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2NYYQP2XJB2TTRP6AKWVMBSPB2DFJNKD/', 'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1736', 'https://github.com/ansible/ansible/issues/67794', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/BPNZWBAUP4ZHUR6PO7U6ZXEKNCX62KZ7/', 'https://security.gentoo.org/glsa/202006-11'} | null |
PyPI | PYSEC-2021-598 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions TFLite's [`expand_dims.cc`](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/expand_dims.cc#L36-L50) contains a vulnerability which allows reading one element outside of bounds of heap allocated data. If `axis` is a large negative value (e.g., `-100000`), then after the first `if` it would still be negative. The check following the `if` statement will pass and the `for` loop would read one element before the start of `input_dims.data` (when `i = 0`). We have patched the issue in GitHub commit d94ffe08a65400f898241c0374e9edc6fa8ed257. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'CVE-2021-37685', 'GHSA-c545-c4f9-rf6v'} | 2021-12-09T06:35:06.268797Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/d94ffe08a65400f898241c0374e9edc6fa8ed257', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c545-c4f9-rf6v'} | null |
PyPI | PYSEC-2018-9 | null | ** DISPUTED ** OpenStack Keystone through 14.0.1 has a user enumeration vulnerability because invalid usernames have much faster responses than valid ones for a POST /v3/auth/tokens request. NOTE: the vendor's position is that this is a hardening opportunity, and not necessarily an issue that should have an OpenStack Security Advisory. | {'CVE-2018-20170'} | 2021-06-10T06:51:56.696140Z | 2018-12-17T07:29:00Z | null | null | null | {'https://bugs.launchpad.net/keystone/+bug/1795800'} | null |
PyPI | GHSA-gjh6-wvhq-h4qx | Cross-site Scripting in FreeTAKServer-UI | FreeTAKServer-UI v1.9.8 was discovered to contain a stored cross-site scripting (XSS) vulnerability via the Callsign parameter. | {'CVE-2022-25507'} | 2022-03-29T19:15:16.162314Z | 2022-03-12T00:00:37Z | MODERATE | null | {'CWE-79'} | {'https://github.com/FreeTAKTeam/UI', 'https://github.com/FreeTAKTeam/UI/issues/28', 'https://nvd.nist.gov/vuln/detail/CVE-2022-25507'} | null |
PyPI | GHSA-hjf3-r7gw-9rwg | Moderate severity vulnerability that affects feedparser | 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. | {'CVE-2012-2921'} | 2022-03-03T05:13:08.972804Z | 2018-07-24T20:00:41Z | MODERATE | null | null | {'https://nvd.nist.gov/vuln/detail/CVE-2012-2921', '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-2017-31 | null | Salt before 2014.7.6 does not verify certificates when connecting via the aliyun, proxmox, and splunk modules. | {'CVE-2015-4017'} | 2021-07-05T00:01:26.252043Z | 2017-08-25T18:29:00Z | null | null | null | {'https://docs.saltstack.com/en/latest/topics/releases/2014.7.6.html', 'http://www.openwall.com/lists/oss-security/2015/05/19/2', 'https://groups.google.com/forum/#!topic/salt-users/8Kv1bytGD6c', 'https://bugzilla.redhat.com/show_bug.cgi?id=1222960'} | null |
PyPI | PYSEC-2020-259 | null | In Twisted Web through 19.10.0, there was an HTTP request splitting vulnerability. When presented with two content-length headers, it ignored the first header. When the second content-length value was set to zero, the request body was interpreted as a pipelined request. | {'GHSA-h96w-mmrf-2h6v', 'CVE-2020-10108'} | 2021-08-27T03:22:49.614366Z | 2020-03-12T13:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-h96w-mmrf-2h6v', 'https://usn.ubuntu.com/4308-1/', 'https://security.gentoo.org/glsa/202007-24', 'https://know.bishopfox.com/advisories', '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://usn.ubuntu.com/4308-2/', 'https://www.oracle.com/security-alerts/cpuoct2020.html'} | null |
PyPI | PYSEC-2021-609 | null | TensorFlow is an open source platform for machine learning. In affected versions if `tf.image.resize` is called with a large input argument then the TensorFlow process will crash due to a `CHECK`-failure caused by an overflow. The number of elements in the output tensor is too much for the `int64_t` type and the overflow is detected via a `CHECK` statement. This aborts the process. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41199', 'GHSA-5hx2-qx8j-qjqm'} | 2021-12-09T06:35:07.452136Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/e5272d4204ff5b46136a1ef1204fc00597e21837', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5hx2-qx8j-qjqm', 'https://github.com/tensorflow/tensorflow/issues/46914'} | null |
PyPI | PYSEC-2021-46 | null | before_upstream_connection in AuthPlugin in http/proxy/auth.py in proxy.py before 2.3.1 accepts incorrect Proxy-Authorization header data because of a boolean confusion (and versus or). | {'CVE-2021-3116'} | 2021-01-14T15:09:00Z | 2021-01-11T05:15:00Z | null | null | null | {'https://cardaci.xyz/advisories/2021/01/10/proxy.py-2.3.0-broken-basic-authentication/', 'https://pypi.org/project/proxy.py/2.3.1/#history', 'https://github.com/abhinavsingh/proxy.py/pull/482/commits/9b00093288237f5073c403f2c4f62acfdfa8ed46'} | null |
PyPI | PYSEC-2021-259 | null | TensorFlow is an end-to-end open source platform for machine learning. It is possible to trigger a null pointer dereference in TensorFlow by passing an invalid input to `tf.raw_ops.CompressElement`. The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/data/compression_utils.cc#L34) was accessing the size of a buffer obtained from the return of a separate function call before validating that said buffer is valid. We have patched the issue in GitHub commit 5dc7f6981fdaf74c8c5be41f393df705841fb7c5. 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-2021-37637', 'GHSA-c9qf-r67m-p7cg'} | 2021-08-27T03:22:42.844418Z | 2021-08-12T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/5dc7f6981fdaf74c8c5be41f393df705841fb7c5', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c9qf-r67m-p7cg'} | null |
PyPI | GHSA-c6fm-rgw4-8q73 | Moderate severity vulnerability that affects CoAPthon3 | The Serialize.deserialize() method in CoAPthon3 1.0 and 1.0.1 mishandles certain exceptions, leading to a denial of service in applications that use this library (e.g., the standard CoAP server, CoAP client, example collect CoAP server and client) when they receive crafted CoAP messages. | {'CVE-2018-12679'} | 2022-03-03T05:12:11.093194Z | 2019-04-08T15:18:57Z | HIGH | null | {'CWE-502'} | {'https://github.com/Tanganelli/CoAPthon3', 'https://nvd.nist.gov/vuln/detail/CVE-2018-12679', 'https://github.com/advisories/GHSA-c6fm-rgw4-8q73', 'https://github.com/Tanganelli/CoAPthon3/issues/16'} | null |
PyPI | PYSEC-2020-84 | null | libImaging/FliDecode.c in Pillow before 6.2.2 has an FLI buffer overflow. | {'CVE-2020-5313', 'GHSA-hj69-c76v-86wr'} | 2020-02-18T16:15:00Z | 2020-01-03T01:15:00Z | null | null | null | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2MMU3WT2X64GS5WHDPKKC2WZA7UIIQ3A/', 'https://github.com/python-pillow/Pillow/commit/a09acd0decd8a87ccce939d5ff65dab59e7d365b', 'https://pillow.readthedocs.io/en/stable/releasenotes/6.2.2.html', 'https://usn.ubuntu.com/4272-1/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3DUMIBUYGJRAVJCTFUWBRLVQKOUTVX5P/', 'https://www.debian.org/security/2020/dsa-4631', 'https://github.com/advisories/GHSA-hj69-c76v-86wr'} | null |
PyPI | PYSEC-2021-170 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. 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`. 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. 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-393f-2jr3-cp69', 'CVE-2021-29533'} | 2021-08-27T03:22:27.240459Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b432a38fe0e1b4b904a6c222cbce794c39703e87', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-393f-2jr3-cp69'} | null |
PyPI | PYSEC-2021-520 | null | TensorFlow is an end-to-end open source platform for machine learning. The fix for CVE-2020-15209(https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209) missed the case when the target shape of `Reshape` operator is given by the elements of a 1-D tensor. As such, the fix for the vulnerability(https://github.com/tensorflow/tensorflow/blob/9c1dc920d8ffb4893d6c9d27d1f039607b326743/tensorflow/lite/core/subgraph.cc#L1062-L1074) allowed passing a null-buffer-backed tensor with a 1D shape. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29592', 'GHSA-jjr8-m8g8-p6wv'} | 2021-12-09T06:34:57.625576Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jjr8-m8g8-p6wv', 'https://github.com/tensorflow/tensorflow/commit/f8378920345f4f4604202d4ab15ef64b2aceaa16'} | null |
PyPI | PYSEC-2014-21 | null | IPython Notebook 0.12 through 1.x before 1.2 does not validate the origin of websocket requests, which allows remote attackers to execute arbitrary code by leveraging knowledge of the kernel id and a crafted page. | {'CVE-2014-3429'} | 2021-11-10T21:26:51.333186Z | 2014-08-07T11:13:00Z | null | null | null | {'http://permalink.gmane.org/gmane.comp.python.ipython.devel/13198', 'http://lists.opensuse.org/opensuse-updates/2014-08/msg00039.html', 'http://seclists.org/oss-sec/2014/q3/152', 'http://www.mandriva.com/security/advisories?name=MDVSA-2015:160', 'https://github.com/ipython/ipython/pull/4845', 'http://advisories.mageia.org/MGASA-2014-0320.html', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/94497', 'http://lambdaops.com/cross-origin-websocket-hijacking-of-ipython', 'https://bugzilla.redhat.com/show_bug.cgi?id=1119890'} | null |
PyPI | GHSA-j7mj-748x-7p78 | DOS attack in Pillow when processing specially crafted image files | An issue was discovered in Pillow before 6.2.0. When reading specially crafted invalid image files, the library can either allocate very large amounts of memory or take an extremely long period of time to process the image. | {'CVE-2019-16865'} | 2022-03-03T05:13:58.873995Z | 2019-10-22T14:40:42Z | HIGH | null | {'CWE-770'} | {'https://access.redhat.com/errata/RHSA-2020:0681', 'https://usn.ubuntu.com/4272-1/', 'https://access.redhat.com/errata/RHSA-2020:0683', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/LYDXD7EE4YAEVSTNIFZKNVPRVJX5ZOG3/', 'https://access.redhat.com/errata/RHSA-2020:0578', 'https://access.redhat.com/errata/RHSA-2020:0580', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/EMJBUZQGQ2Q7HXYCQVRLU7OXNC7CAWWU/', 'https://access.redhat.com/errata/RHSA-2020:0694', 'https://access.redhat.com/errata/RHSA-2020:0566', 'https://www.debian.org/security/2020/dsa-4631', 'https://github.com/python-pillow/Pillow/issues/4123', 'https://pillow.readthedocs.io/en/latest/releasenotes/6.2.0.html', 'https://nvd.nist.gov/vuln/detail/CVE-2019-16865'} | null |
PyPI | PYSEC-2021-465 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `QuantizedResizeBilinear` by passing in invalid thresholds for the quantization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/50711818d2e61ccce012591eeb4fdf93a8496726/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L705-L706) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly. 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-8c89-2vwr-chcq', 'CVE-2021-29537'} | 2021-12-09T06:34:49.104886Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f6c40f0c6cbf00d46c7717a26419f2062f2f8694', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8c89-2vwr-chcq'} | null |
PyPI | PYSEC-2022-56 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-c582-c96p-r5cq', 'CVE-2022-21732'} | 2022-03-09T00:17:30.817713Z | 2022-02-03T12:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c582-c96p-r5cq', 'https://github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e'} | null |
PyPI | PYSEC-2019-136 | null | Waitress through version 1.3.1 implemented a "MAY" part of the RFC7230 which states: "Although the line terminator for the start-line and header fields is the sequence CRLF, a recipient MAY recognize a single LF as a line terminator and ignore any preceding CR." Unfortunately if a front-end server does not parse header fields with an LF the same way as it does those with a CRLF it can lead to the front-end and the back-end server parsing the same HTTP message in two different ways. This can lead to a potential for HTTP request smuggling/splitting whereby Waitress may see two requests while the front-end server only sees a single HTTP message. This issue is fixed in Waitress 1.4.0. | {'GHSA-pg36-wpm5-g57p', 'CVE-2019-16785'} | 2020-02-25T17:15:00Z | 2019-12-20T23:15:00Z | null | null | null | {'https://docs.pylonsproject.org/projects/waitress/en/latest/#security-fixes', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/LYEOTGWJZVKPRXX2HBNVIYWCX73QYPM5/', 'https://access.redhat.com/errata/RHSA-2020:0720', 'https://github.com/Pylons/waitress/security/advisories/GHSA-pg36-wpm5-g57p', 'https://github.com/Pylons/waitress/commit/8eba394ad75deaf9e5cd15b78a3d16b12e6b0eba', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/GVDHR2DNKCNQ7YQXISJ45NT4IQDX3LJ7/'} | null |
PyPI | PYSEC-2019-24 | null | invenio-app before 1.1.1 allows host header injection. | {'GHSA-94mf-xfg5-r247', 'CVE-2019-1020006'} | 2019-08-01T16:12:00Z | 2019-07-29T15:15:00Z | null | null | null | {'https://github.com/inveniosoftware/invenio-app/security/advisories/GHSA-94mf-xfg5-r247'} | null |
PyPI | PYSEC-2021-317 | null | The package pillow from 0 and before 8.3.2 are vulnerable to Regular Expression Denial of Service (ReDoS) via the getrgb function. | {'CVE-2021-23437', 'GHSA-98vv-pw6r-q6q4', 'SNYK-PYTHON-PILLOW-1319443'} | 2021-09-03T18:35:52.828411Z | 2021-09-03T16:15:00Z | null | null | null | {'https://pillow.readthedocs.io/en/stable/releasenotes/8.3.2.html', 'https://snyk.io/vuln/SNYK-PYTHON-PILLOW-1319443', 'https://github.com/python-pillow/Pillow/commit/9e08eb8f78fdfd2f476e1b20b7cf38683754866b', 'https://github.com/advisories/GHSA-98vv-pw6r-q6q4'} | null |
PyPI | GHSA-jff3-mwp3-f8cw | Exposure of Sensitive Information to an Unauthorized Actor in Products.GenericSetup | ### Impact
_What kind of vulnerability is it? Who is impacted?_
Information disclosure vulnerability - anonymous visitors may view log and snapshot files generated by the Generic Setup Tool.
### Patches
_Has the problem been patched? What versions should users upgrade to?_
The problem has been fixed in version 2.1.1. Depending on how you have installed Products.GenericSetup, you should change the buildout version pin to 2.1.1 and re-run the buildout, or if you used pip simply do pip install `"Products.GenericSetup>=2.1.1"`
### Workarounds
_Is there a way for users to fix or remediate the vulnerability without upgrading?_
Visit the ZMI Security tab at `portal_setup/manage_access` and click on the link _Access contents information_. On the next page, uncheck the box _Also use roles acquired from folders containing this objects_ at the bottom and check the boxes for _Manager_ and _Owner_. Then click on _Save Changes_. Return to the ZMI Security tab at `portal_setup/manage_access` and scroll down to the link _View_. Click on _View_, uncheck the box _Also use roles acquired from folders containing this objects_ at the bottom and check the boxes for _Manager_ and _Owner_. Then click on _Save Changes_.
### References
_Are there any links users can visit to find out more?_
- [GHSA-jff3-mwp3-f8cw](https://github.com/zopefoundation/Products.GenericSetup/security/advisories/GHSA-jff3-mwp3-f8cw)
- [Products.GenericSetup on PyPI](https://pypi.org/project/Products.GenericSetup/)
- [Definition of information disclosure at MITRE](https://cwe.mitre.org/data/definitions/200.html)
### For more information
If you have any questions or comments about this advisory:
* Open an issue in the [Products.GenericSetup issue tracker](https://github.com/zopefoundation/Products.GenericSetup/issues)
* Email us at [security@plone.org](mailto:security@plone.org) | {'CVE-2021-21360'} | 2022-03-03T05:13:45.084029Z | 2021-03-09T00:38:31Z | LOW | null | {'CWE-200'} | {'https://pypi.org/project/Products.GenericSetup/', 'http://www.openwall.com/lists/oss-security/2021/05/21/1', 'https://github.com/zopefoundation/Products.GenericSetup/commit/700319512b3615b3871a1f24e096cf66dc488c57', 'https://github.com/zopefoundation/Products.GenericSetup/security/advisories/GHSA-jff3-mwp3-f8cw', 'http://www.openwall.com/lists/oss-security/2021/05/22/1', 'https://nvd.nist.gov/vuln/detail/CVE-2021-21360'} | null |
PyPI | PYSEC-2018-2 | null | django.middleware.common.CommonMiddleware in Django 1.11.x before 1.11.15 and 2.0.x before 2.0.8 has an Open Redirect. | {'GHSA-5hg3-6c2f-f3wr', 'CVE-2018-14574'} | 2021-06-10T06:51:09.426505Z | 2018-08-03T17:29:00Z | null | null | null | {'http://www.securityfocus.com/bid/104970', 'https://www.debian.org/security/2018/dsa-4264', 'https://www.djangoproject.com/weblog/2018/aug/01/security-releases/', 'https://github.com/advisories/GHSA-5hg3-6c2f-f3wr', 'http://www.securitytracker.com/id/1041403', 'https://access.redhat.com/errata/RHSA-2019:0265', 'https://usn.ubuntu.com/3726-1/'} | null |
PyPI | PYSEC-2021-747 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseDenseCwiseDiv` is vulnerable to a division by 0 error. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L56) uses a common class for all binary operations but fails to treat the division by 0 case separately. We have patched the issue in GitHub commit d9204be9f49520cdaaeb2541d1dc5187b23f31d9. 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-2021-37636', 'GHSA-hp4c-x6r7-6555'} | 2021-12-09T06:35:35.406311Z | 2021-08-12T18:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hp4c-x6r7-6555'} | null |
PyPI | PYSEC-2020-317 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'CVE-2020-15202', 'GHSA-h6fg-mjxg-hqq4'} | 2021-12-09T06:35:13.455948Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ca8c013b5e97b1373b3bb1c97ea655e69f31a575', 'https://github.com/tensorflow/tensorflow/commit/27b417360cbd671ef55915e4bb6bb06af8b8a832', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4'} | null |
PyPI | GHSA-8r8j-xvfj-36f9 | Code injection in ymlref | ymlref allows code injection. | {'CVE-2018-20133'} | 2022-03-24T22:16:56.564588Z | 2018-12-19T19:25:14Z | CRITICAL | null | {'CWE-94'} | {'https://github.com/dexter2206/ymlref', 'https://nvd.nist.gov/vuln/detail/CVE-2018-20133', 'https://github.com/dexter2206/ymlref/issues/2'} | null |
PyPI | PYSEC-2019-214 | null | A malicious admin user could edit the state of objects in the Airflow metadata database to execute arbitrary javascript on certain page views. | {'GHSA-8p7v-2jvj-v54r', 'CVE-2019-0216'} | 2021-11-16T03:58:43.132049Z | 2019-04-10T20:29:00Z | null | null | null | {'https://github.com/advisories/GHSA-8p7v-2jvj-v54r', 'https://lists.apache.org/thread.html/2de387213d45bc626d27554a1bde7b8c67d08720901f82a50b6f4231@%3Cdev.airflow.apache.org%3E', 'http://www.securityfocus.com/bid/107869', 'http://www.openwall.com/lists/oss-security/2019/04/10/6'} | null |
PyPI | PYSEC-2011-1 | null | django.contrib.sessions in Django before 1.2.7 and 1.3.x before 1.3.1, when session data is stored in the cache, uses the root namespace for both session identifiers and application-data keys, which allows remote attackers to modify a session by triggering use of a key that is equal to that session's identifier. | {'GHSA-x88j-93vc-wpmp', 'CVE-2011-4136'} | 2021-07-05T00:01:17.786807Z | 2011-10-19T10:55:00Z | null | null | null | {'https://www.djangoproject.com/weblog/2011/sep/09/', 'http://openwall.com/lists/oss-security/2011/09/13/2', 'http://www.debian.org/security/2011/dsa-2332', 'https://hermes.opensuse.org/messages/14700881', 'https://github.com/advisories/GHSA-x88j-93vc-wpmp', 'http://openwall.com/lists/oss-security/2011/09/11/1', 'https://bugzilla.redhat.com/show_bug.cgi?id=737366', 'http://secunia.com/advisories/46614', 'https://www.djangoproject.com/weblog/2011/sep/10/127/'} | null |
PyPI | GHSA-c4rh-4376-gff4 | Improper certificate management in AWS IoT Device SDK v2 | The AWS IoT Device SDK v2 for Java, Python, C++ and Node.js appends a user supplied Certificate Authority (CA) to the root CAs instead of overriding it on Unix systems. TLS handshakes will thus succeed if the peer can be verified either from the user-supplied CA or the system’s default trust-store. Attackers with access to a host’s trust stores or are able to compromise a certificate authority already in the host's trust store (note: the attacker must also be able to spoof DNS in this case) may be able to use this issue to bypass CA pinning. An attacker could then spoof the MQTT broker, and either drop traffic and/or respond with the attacker's data, but they would not be able to forward this data on to the MQTT broker because the attacker would still need the user's private keys to authenticate against the MQTT broker. The 'aws_tls_ctx_options_override_default_trust_store_*' function within the aws-c-io submodule has been updated to override the default trust store. This corrects this issue. This issue affects: Amazon Web Services AWS IoT Device SDK v2 for Java versions prior to 1.5.0 on Linux/Unix. Amazon Web Services AWS IoT Device SDK v2 for Python versions prior to 1.6.1 on Linux/Unix. Amazon Web Services AWS IoT Device SDK v2 for C++ versions prior to 1.12.7 on Linux/Unix. Amazon Web Services AWS IoT Device SDK v2 for Node.js versions prior to 1.5.3 on Linux/Unix. Amazon Web Services AWS-C-IO 0.10.4 on Linux/Unix. | {'CVE-2021-40830'} | 2022-03-03T05:13:15.678455Z | 2021-11-24T21:12:04Z | MODERATE | null | {'CWE-295'} | {'https://github.com/aws/aws-iot-device-sdk-java-v2', 'https://github.com/aws/aws-iot-device-sdk-java-v2/commit/67950ad2a02f2f9355c310b69dc9226b017f32f2', 'https://nvd.nist.gov/vuln/detail/CVE-2021-40830', 'https://github.com/aws/aws-iot-device-sdk-js-v2/commit/53a36e3ac203291494120604d416b6de59177cac', 'https://github.com/aws/aws-iot-device-sdk-python-v2', 'https://github.com/aws/aws-iot-device-sdk-js-v2', 'https://github.com/aws/aws-iot-device-sdk-python-v2/commit/0450ce68add7e3d05c6d781ecdac953c299c053a', 'https://github.com/aws/aws-iot-device-sdk-cpp-v2', 'https://github.com/awslabs/aws-c-io/'} | null |
PyPI | GHSA-j28r-j54m-gpc4 | Code Injection in SLO Generator | SLO generator allows for loading of YAML files that if crafted in a specific format can allow for code execution within the context of the SLO Generator. We recommend upgrading SLO Generator past https://github.com/google/slo-generator/pull/173 | {'CVE-2021-22557'} | 2022-03-03T05:13:48.445259Z | 2021-10-05T17:53:59Z | MODERATE | null | {'CWE-94'} | {'https://github.com/google/slo-generator/pull/173', '://github.com/google/slo-generator', 'http://packetstormsecurity.com/files/164426/Google-SLO-Generator-2.0.0-Code-Execution.html', 'https://github.com/google/slo-generator/releases/tag/v2.0.1', 'https://nvd.nist.gov/vuln/detail/CVE-2021-22557'} | null |
PyPI | PYSEC-2020-252 | null | The Scalyr Agent before 2.1.10 has Missing SSL Certificate Validation because, in some circumstances, native Python code is used that lacks a comparison of the hostname to commonName and subjectAltName. | {'CVE-2020-24715'} | 2021-08-27T03:22:21.152325Z | 2020-08-27T22:15:00Z | null | null | null | {'https://scalyr-static.s3.amazonaws.com/technical-details/index.html'} | null |
PyPI | GHSA-ccgm-3xw4-h5p8 | Improper Restriction of XML External Entity Reference in pikepdf | models/metadata.py in the pikepdf package 1.3.0 through 2.9.2 for Python allows XXE when parsing XMP metadata entries. | {'CVE-2021-29421'} | 2022-03-03T05:13:15.711071Z | 2021-04-20T16:30:03Z | HIGH | null | {'CWE-611'} | {'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/36P4HTLBJPO524WMQWW57N3QRF4RFSJG/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3QFLBBYGEDNXJ7FS6PIWTVI4T4BUPGEQ/', 'https://github.com/pikepdf/pikepdf/commit/3f38f73218e5e782fe411ccbb3b44a793c0b343a', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29421'} | null |
PyPI | PYSEC-2021-252 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `ParseAttrValue`(https://github.com/tensorflow/tensorflow/blob/c22d88d6ff33031aa113e48aa3fc9aa74ed79595/tensorflow/core/framework/attr_value_util.cc#L397-L453) can be tricked into stack overflow due to recursion by giving in a specially crafted input. 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-qw5h-7f53-xrp6', 'CVE-2021-29615'} | 2021-08-27T03:22:41.882183Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qw5h-7f53-xrp6', 'https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1'} | null |
PyPI | PYSEC-2021-602 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70) unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. 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-wf5p-c75w-w3wh', 'CVE-2021-37689'} | 2021-12-09T06:35:06.599796Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/d6b57f461b39fd1aa8c1b870f1b974aac3554955', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-wf5p-c75w-w3wh'} | null |
PyPI | GHSA-53qw-q765-4fww | Denial-of-service in Django | An issue was discovered in Django 2.2 before 2.2.26, 3.2 before 3.2.11, and 4.0 before 4.0.1. UserAttributeSimilarityValidator incurred significant overhead in evaluating a submitted password that was artificially large in relation to the comparison values. In a situation where access to user registration was unrestricted, this provided a potential vector for a denial-of-service attack. | {'CVE-2021-45115'} | 2022-03-03T05:13:19.042457Z | 2022-01-12T19:20:53Z | HIGH | null | {'CWE-400'} | {'https://github.com/django/django', 'https://groups.google.com/forum/#!forum/django-announce', 'https://nvd.nist.gov/vuln/detail/CVE-2021-45115', 'https://www.djangoproject.com/weblog/2022/jan/04/security-releases/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/B4SQG2EAF4WCI2SLRL6XRDJ3RPK3ZRDV/', 'https://security.netapp.com/advisory/ntap-20220121-0005/', 'https://docs.djangoproject.com/en/4.0/releases/security/'} | null |
PyPI | GHSA-v768-w7m9-2vmm | Reference binding to nullptr in shape inference | ### Impact
An attacker can cause undefined behavior via binding a reference to null pointer in `tf.raw_ops.SparseFillEmptyRows`:
```python
import tensorflow as tf
tf.compat.v1.disable_v2_behavior()
tf.raw_ops.SparseFillEmptyRows(
indices = tf.constant([], shape=[0, 0], dtype=tf.int64),
values = tf.constant([], shape=[0], dtype=tf.int64),
dense_shape = tf.constant([], shape=[0], dtype=tf.int64),
default_value = 0)
```
The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/sparse_ops.cc#L608-L634) does not validate that the input arguments are not empty tensors.
### Patches
We have patched the issue in GitHub commit [578e634b4f1c1c684d4b4294f9e5281b2133b3ed](https://github.com/tensorflow/tensorflow/commit/578e634b4f1c1c684d4b4294f9e5281b2133b3ed).
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-2021-37676'} | 2022-03-03T05:14:01.276269Z | 2021-08-25T14:41:26Z | HIGH | null | {'CWE-824'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/578e634b4f1c1c684d4b4294f9e5281b2133b3ed', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37676', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v768-w7m9-2vmm'} | null |
PyPI | GHSA-rvmq-4x66-q7j3 | Remote code execution in Apache Airflow | An issue was found in Apache Airflow versions 1.10.10 and below. A remote code/command injection vulnerability was discovered in one of the example DAGs shipped with Airflow which would allow any authenticated user to run arbitrary commands as the user running airflow worker/scheduler (depending on the executor in use). If you already have examples disabled by setting load_examples=False in the config then you are not vulnerable. | {'CVE-2020-11978'} | 2022-03-03T05:12:54.520849Z | 2020-07-27T16:57:33Z | HIGH | null | {'CWE-78', 'CWE-77'} | {'http://packetstormsecurity.com/files/162908/Apache-Airflow-1.10.10-Remote-Code-Execution.html', 'https://nvd.nist.gov/vuln/detail/CVE-2020-11978', 'https://lists.apache.org/thread.html/r7255cf0be3566f23a768e2a04b40fb09e52fcd1872695428ba9afe91%40%3Cusers.airflow.apache.org%3E'} | null |
PyPI | GHSA-m9mq-p2f9-cfqv | Critical severity vulnerability that affects bleach | An issue was discovered in Bleach 2.1.x before 2.1.3. Attributes that have URI values weren't properly sanitized if the values contained character entities. Using character entities, it was possible to construct a URI value with a scheme that was not allowed that would slide through unsanitized. | {'CVE-2018-7753'} | 2022-03-07T20:47:08.254480Z | 2019-01-04T17:46:30Z | CRITICAL | null | {'CWE-20'} | {'https://github.com/mozilla/bleach', 'https://bugs.debian.org/892252', 'https://github.com/advisories/GHSA-m9mq-p2f9-cfqv', 'https://github.com/mozilla/bleach/commit/c5df5789ec3471a31311f42c2d19fc2cf21b35ef', 'https://nvd.nist.gov/vuln/detail/CVE-2018-7753', 'https://github.com/mozilla/bleach/releases/tag/v2.1.3'} | null |
PyPI | PYSEC-2016-17 | null | Django 1.8.x before 1.8.16, 1.9.x before 1.9.11, and 1.10.x before 1.10.3 use a hardcoded password for a temporary database user created when running tests with an Oracle database, which makes it easier for remote attackers to obtain access to the database server by leveraging failure to manually specify a password in the database settings TEST dictionary. | {'CVE-2016-9013'} | 2021-07-15T02:22:10.369344Z | 2016-12-09T20:59:00Z | null | null | null | {'http://www.securitytracker.com/id/1037159', 'http://www.securityfocus.com/bid/94069', 'http://www.debian.org/security/2017/dsa-3835', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/QXDKJYHN74BWY3P7AR2UZDVJREQMRE6S/', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/OG5ROMUPS6C7BXELD3TAUUH7OBYV56WQ/', 'http://www.ubuntu.com/usn/USN-3115-1', 'https://www.djangoproject.com/weblog/2016/nov/01/security-releases/'} | null |
PyPI | PYSEC-2021-481 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can read data outside of bounds of heap allocated buffer in `tf.raw_ops.QuantizeAndDequantizeV3`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/11ff7f80667e6490d7b5174aa6bf5e01886e770f/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L237) does not validate the value of user supplied `axis` attribute before using it to index in the array backing the `input` argument. 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-2021-29553', 'GHSA-h9px-9vqg-222h'} | 2021-12-09T06:34:51.614588Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h9px-9vqg-222h', 'https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387'} | null |
PyPI | PYSEC-2021-194 | 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.SparseMatMul`. The division by 0 occurs deep in Eigen code because the `b` tensor is empty. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-xw93-v57j-fcgh', 'CVE-2021-29557'} | 2021-08-27T03:22:31.559796Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/7f283ff806b2031f407db64c4d3edcda8fb9f9f5', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xw93-v57j-fcgh'} | null |
PyPI | PYSEC-2022-172 | null | An issue was discovered in SaltStack Salt in versions before 3002.8, 3003.4, 3004.1. A minion authentication denial of service can cause a MiTM attacker to force a minion process to stop by impersonating a master. | {'CVE-2022-22935'} | 2022-03-29T18:37:43.967592Z | 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-2020-60 | null | A stored cross-site scripting (XSS) vulnerability affects the Web UI in Locust before 1.3.2, if the installation violates the usage expectations by exposing this UI to outside users. | {'CVE-2020-28364'} | 2020-11-17T20:37:00Z | 2020-11-09T21:15:00Z | null | null | null | {'https://docs.locust.io/en/stable/changelog.html'} | null |
PyPI | PYSEC-2015-6 | null | The django.views.static.serve view in Django before 1.4.18, 1.6.x before 1.6.10, and 1.7.x before 1.7.3 reads files an entire line at a time, which allows remote attackers to cause a denial of service (memory consumption) via a long line in a file. | {'CVE-2015-0221'} | 2021-07-05T00:01:19.682404Z | 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://secunia.com/advisories/62718', 'http://www.mandriva.com/security/advisories?name=MDVSA-2015:036', 'http://secunia.com/advisories/62309', 'http://lists.opensuse.org/opensuse-updates/2015-04/msg00001.html', '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 | GHSA-gfr2-qpxh-qj9m | Path Traversal in Ansible | A flaw was found in the Ansible Engine when the fetch module is used. An attacker could intercept the module, inject a new path, and then choose a new destination path on the controller node. All versions in 2.7.x, 2.8.x and 2.9.x branches are believed to be vulnerable. | {'CVE-2020-1735'} | 2022-05-05T22:01:59.656750Z | 2021-04-07T20:35:24Z | MODERATE | null | {'CWE-22'} | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1735', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WQVOQD4VAIXXTVQAJKTN7NUGTJFE2PCB/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-1735', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MRRYUU5ZBLPBXCYG6CFP35D64NP2UB2S/', 'https://github.com/ansible/ansible', 'https://github.com/ansible/ansible/blob/stable-2.9/changelogs/CHANGELOG-v2.9.rst#security-fixes-7', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DKPA4KC3OJSUFASUYMG66HKJE7ADNGFW/', 'https://github.com/ansible/ansible/issues/67793', 'https://security.gentoo.org/glsa/202006-11'} | null |
PyPI | PYSEC-2020-340 | null | In Mozilla Bleach before 3.1.4, `bleach.clean` behavior parsing style attributes could result in a regular expression denial of service (ReDoS). | {'CVE-2020-6817', 'GHSA-vqhp-cxgc-6wmm', 'SNYK-PYTHON-BLEACH-561754'} | 2022-01-05T02:16:12.945364Z | 2020-03-30T19:45:00Z | null | null | null | {'https://snyk.io/vuln/SNYK-PYTHON-BLEACH-561754', 'https://github.com/mozilla/bleach/security/advisories/GHSA-vqhp-cxgc-6wmm', 'https://github.com/mozilla/bleach/releases/tag/v3.1.4', 'https://blog.r2c.dev/posts/finding-python-redos-bugs-at-scale-using-dlint-and-r2c/', 'https://bugzilla.mozilla.org/show_bug.cgi?id=1623633'} | null |
PyPI | PYSEC-2021-710 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK`-fail in caused by an integer overflow in constructing a new tensor shape. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/0908c2f2397c099338b901b067f6495a5b96760b/tensorflow/core/kernels/sparse_split_op.cc#L66-L70) builds a dense shape without checking that the dimensions would not result in overflow. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows. 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-xvjm-fvxx-q3hv', 'CVE-2021-29584'} | 2021-12-09T06:35:29.199701Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xvjm-fvxx-q3hv', 'https://github.com/tensorflow/tensorflow/commit/4c0ee937c0f61c4fc5f5d32d9bb4c67428012a60'} | null |
PyPI | PYSEC-2011-13 | null | Unspecified vulnerability in Plone 2.5 through 4.0, as used in Conga, luci, and possibly other products, allows remote attackers to obtain administrative access, read or create arbitrary content, and change the site skin via unknown vectors. | {'CVE-2011-0720'} | 2021-07-25T23:34:43.059075Z | 2011-02-03T17:00:00Z | null | null | null | {'http://www.redhat.com/support/errata/RHSA-2011-0394.html', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/65099', 'http://secunia.com/advisories/43914', 'http://www.redhat.com/support/errata/RHSA-2011-0393.html', 'http://www.securitytracker.com/id?1025258', 'http://secunia.com/advisories/43146', 'http://plone.org/products/plone/security/advisories/cve-2011-0720', 'http://www.vupen.com/english/advisories/2011/0796', 'http://www.securityfocus.com/bid/46102', 'http://osvdb.org/70753'} | null |
PyPI | PYSEC-2021-340 | null | Cross Site Scripting (XSS) in Lin-CMS-Flask v0.1.1 allows remote attackers to execute arbitrary code by entering scripts in the the 'Username' parameter of the in component 'app/api/cms/user.py'. | {'CVE-2020-18699'} | 2022-03-16T02:19:50.038358Z | 2021-08-16T18:15:00Z | null | null | null | {'https://github.com/TaleLin/lin-cms-flask/issues/28'} | null |
PyPI | GHSA-6p5r-g9mq-ggh2 | Reference binding to nullptr in `MatrixSetDiagV*` ops | ### Impact
An attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixSetDiagV*`:
```python
import tensorflow as tf
tf.raw_ops.MatrixSetDiagV3(
input=[1,2,3],
diagonal=[1,1],
k=[],
align='RIGHT_LEFT')
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong:
```cc
auto& diag_index = context->input(1);
...
lower_diag_index = diag_index.flat<int32>()(0);
```
### Patches
We have patched the issue in GitHub commit [ff8894044dfae5568ecbf2ed514c1a37dc394f1b](https://github.com/tensorflow/tensorflow/commit/ff8894044dfae5568ecbf2ed514c1a37dc394f1b).
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-2021-37658'} | 2022-03-03T05:14:20.827120Z | 2021-08-25T14:42:49Z | HIGH | null | {'CWE-824'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/ff8894044dfae5568ecbf2ed514c1a37dc394f1b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6p5r-g9mq-ggh2', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37658'} | null |
PyPI | PYSEC-2006-2 | null | Trac before 0.9.6 does not disable the "raw" or "include" commands when providing untrusted users with restructured text (reStructuredText) functionality from docutils, which allows remote attackers to read arbitrary files, perform cross-site scripting (XSS) attacks, or cause a denial of service via unspecified vectors. NOTE: this might be related to CVE-2006-3458. | {'CVE-2006-3695'} | 2021-07-16T01:31:33.987147Z | 2006-07-21T14:03:00Z | null | null | null | {'http://secunia.com/advisories/21534', 'http://www.debian.org/security/2006/dsa-1152', 'http://securitytracker.com/id?1016457', 'http://www.vupen.com/english/advisories/2006/2729', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/27708', 'http://secunia.com/advisories/20958', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/27706', 'http://trac.edgewall.org/wiki/ChangeLog', 'http://www.securityfocus.com/bid/18323'} | null |
PyPI | PYSEC-2021-655 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in `tf.raw_ops.QuantizedResizeBilinear` by manipulating input values so that float rounding results in off-by-one error in accessing image elements. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L62-L66) computes two integers (representing the upper and lower bounds for interpolation) by ceiling and flooring a floating point value. For some values of `in`, `interpolation->upper[i]` might be smaller than `interpolation->lower[i]`. This is an issue if `interpolation->upper[i]` is capped at `in_size-1` as it means that `interpolation->lower[i]` points outside of the image. Then, in the interpolation code(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L245-L264), this would result in heap buffer overflow. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-jfp7-4j67-8r3q', 'CVE-2021-29529'} | 2021-12-09T06:35:19.746209Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/f851613f8f0fb0c838d160ced13c134f778e3ce7', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jfp7-4j67-8r3q'} | null |
PyPI | PYSEC-2021-205 | 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'} | 2021-08-27T03:22:33.499981Z | 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 | GHSA-c9f3-9wfr-wgh7 | Lack of validation in data format attributes in TensorFlow | ### Impact
The `tf.raw_ops.DataFormatVecPermute` API does not validate the `src_format` and `dst_format` attributes. [The code](https://github.com/tensorflow/tensorflow/blob/304b96815324e6a73d046df10df6626d63ac12ad/tensorflow/core/kernels/data_format_ops.cc) assumes that these two arguments define a permutation of `NHWC`.
However, these assumptions are not checked and this can result in uninitialized memory accesses, read outside of bounds and even crashes.
```python
>>> import tensorflow as tf
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='1234', dst_format='1234')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 757100143], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='HHHH', dst_format='WWWW')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,4], src_format='H', dst_format='W')
<tf.Tensor: shape=(2,), dtype=int32, numpy=array([4, 32701], dtype=int32)>
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
src_format='1234', dst_format='1253')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 2, 939037184, 3], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
src_format='1234', dst_format='1223')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 32701, 2, 3], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
src_format='1224', dst_format='1423')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([1, 4, 3, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4], src_format='1234', dst_format='432')
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([4, 3, 2, 32701], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[1,2,3,4],
src_format='12345678', dst_format='87654321')
munmap_chunk(): invalid pointer
Aborted
...
>>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]],
src_format='12345678', dst_format='87654321')
<tf.Tensor: shape=(4, 2), dtype=int32, numpy=
array([[71364624, 0],
[71365824, 0],
[ 560, 0],
[ 48, 0]], dtype=int32)>
...
>>> tf.raw_ops.DataFormatVecPermute(x=[[1,5],[2,6],[3,7],[4,8]],
src_format='12345678', dst_format='87654321')
free(): invalid next size (fast)
Aborted
```
A similar issue occurs in `tf.raw_ops.DataFormatDimMap`, for the same reasons:
```python
>>> tf.raw_ops.DataFormatDimMap(x=[[1,5],[2,6],[3,7],[4,8]], src_format='1234',
>>> dst_format='8765')
<tf.Tensor: shape=(4, 2), dtype=int32, numpy=
array([[1954047348, 1954047348],
[1852793646, 1852793646],
[1954047348, 1954047348],
[1852793632, 1852793632]], dtype=int32)>
```
### Patches
We have patched the issue in GitHub commit [ebc70b7a592420d3d2f359e4b1694c236b82c7ae](https://github.com/tensorflow/tensorflow/commit/ebc70b7a592420d3d2f359e4b1694c236b82c7ae) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2020-26267'} | 2022-03-03T05:13:36.799741Z | 2020-12-10T19:07:26Z | LOW | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c9f3-9wfr-wgh7', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26267', 'https://github.com/tensorflow/tensorflow/commit/ebc70b7a592420d3d2f359e4b1694c236b82c7ae'} | null |
PyPI | PYSEC-2017-82 | null | The salt-ssh minion code in SaltStack Salt 2016.11 before 2016.11.4 copied over configuration from the Salt Master without adjusting permissions, which might leak credentials to local attackers on configured minions (clients). | {'CVE-2017-8109'} | 2021-08-25T04:30:30.228761Z | 2017-04-25T17:59:00Z | null | null | null | {'https://github.com/saltstack/salt/pull/40609/commits/6e34c2b5e5e849302af7ccd00509929c3809c658', 'https://docs.saltstack.com/en/latest/topics/releases/2016.11.4.html', 'https://bugzilla.suse.com/show_bug.cgi?id=1035912', 'https://github.com/saltstack/salt/issues/40075', 'http://www.securityfocus.com/bid/98095', 'https://github.com/saltstack/salt/pull/40609'} | null |
PyPI | PYSEC-2020-205 | null | Multiple argument injection vulnerabilities in Ansible before 1.6.7 allow remote attackers to execute arbitrary code by leveraging access to an Ansible managed host and providing a crafted fact, as demonstrated by a fact with (1) a trailing " src=" clause, (2) a trailing " temp=" clause, or (3) a trailing " validate=" clause accompanied by a shell command. | {'CVE-2014-4967'} | 2021-07-02T02:41:33.376176Z | 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 | GHSA-4fg4-p75j-w5xj | Heap out of bounds in `QuantizedBatchNormWithGlobalNormalization` | ### Impact
An attacker can cause a segfault and denial of service via accessing data outside of bounds in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`:
```python
import tensorflow as tf
t = tf.constant([1], shape=[1, 1, 1, 1], dtype=tf.quint8)
t_min = tf.constant([], shape=[0], dtype=tf.float32)
t_max = tf.constant([], shape=[0], dtype=tf.float32)
m = tf.constant([1], shape=[1], dtype=tf.quint8)
m_min = tf.constant([], shape=[0], dtype=tf.float32)
m_max = tf.constant([], shape=[0], dtype=tf.float32)
v = tf.constant([1], shape=[1], dtype=tf.quint8)
v_min = tf.constant([], shape=[0], dtype=tf.float32)
v_max = tf.constant([], shape=[0], dtype=tf.float32)
beta = tf.constant([1], shape=[1], dtype=tf.quint8)
beta_min = tf.constant([], shape=[0], dtype=tf.float32)
beta_max = tf.constant([], shape=[0], dtype=tf.float32)
gamma = tf.constant([1], shape=[1], dtype=tf.quint8)
gamma_min = tf.constant([], shape=[0], dtype=tf.float32)
gamma_max = tf.constant([], shape=[0], dtype=tf.float32)
tf.raw_ops.QuantizedBatchNormWithGlobalNormalization(
t=t, t_min=t_min, t_max=t_max, m=m, m_min=m_min, m_max=m_max,
v=v, v_min=v_min, v_max=v_max, beta=beta, beta_min=beta_min,
beta_max=beta_max, gamma=gamma, gamma_min=gamma_min,
gamma_max=gamma_max, out_type=tf.qint32,
variance_epsilon=0.1, scale_after_normalization=True)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc#L176-L189) assumes the inputs are not empty:
```cc
const float input_min = context->input(1).flat<float>()(0);
const float input_max = context->input(2).flat<float>()(0);
...
const float mean_min = context->input(4).flat<float>()(0);
const float mean_max = context->input(5).flat<float>()(0);
...
const float var_min = context->input(7).flat<float>()(0);
const float var_max = context->input(8).flat<float>()(0);
...
const float beta_min = context->input(10).flat<float>()(0);
const float beta_max = context->input(11).flat<float>()(0);
...
const float gamma_min = context->input(13).flat<float>()(0);
const float gamma_max = context->input(14).flat<float>()(0);
```
If any of these inputs is empty, `.flat<T>()` is an empty buffer, so accessing the element at index 0 is accessing data outside of bounds.
### Patches
We have patched the issue in GitHub commit [d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b](https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b).
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-2021-29547'} | 2022-03-03T05:14:19.780476Z | 2021-05-21T14:23:31Z | LOW | null | {'CWE-125'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29547', 'https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4fg4-p75j-w5xj'} | null |
PyPI | GHSA-j86v-p27c-73fm | Unitialized access in `EinsumHelper::ParseEquation` | ### Impact
During execution, [`EinsumHelper::ParseEquation()`](https://github.com/tensorflow/tensorflow/blob/e0b6e58c328059829c3eb968136f17aa72b6c876/tensorflow/core/kernels/linalg/einsum_op_impl.h#L126-L181) 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`.
```cc
for (int i = 0; i < num_inputs; ++i) {
input_label_counts->at(i).resize(num_labels);
for (const int label : input_labels->at(i)) {
if (label != kEllipsisLabel)
input_label_counts->at(i)[label] += 1;
else
input_has_ellipsis->at(i) = true;
}
}
output_label_counts->resize(num_labels);
for (const int label : *output_labels) {
if (label != kEllipsisLabel)
output_label_counts->at(label) += 1;
else
*output_has_ellipsis = true;
}
```
This results in unitialized variable access if callers assume that `EinsumHelper::ParseEquation()` always sets these flags.
### Patches
We have patched the issue in GitHub commit [f09caa532b6e1ac8d2aa61b7832c78c5b79300c6](https://github.com/tensorflow/tensorflow/commit/f09caa532b6e1ac8d2aa61b7832c78c5b79300c6).
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. | {'CVE-2021-41201'} | 2022-03-03T05:12:12.386786Z | 2021-11-10T19:17:43Z | HIGH | null | {'CWE-824'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j86v-p27c-73fm', 'https://github.com/tensorflow/tensorflow/commit/f09caa532b6e1ac8d2aa61b7832c78c5b79300c6', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41201'} | null |
PyPI | GHSA-cfpj-3q4c-jhvr | Division by zero in TFLite | ### Impact
The implementation of fully connected layers in TFLite is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/fully_connected.cc#L226):
```cc
const int batch_size = input_size / filter->dims->data[1];
```
An attacker can craft a model such that `filter->dims->data[1]` is 0.
### Patches
We have patched the issue in GitHub commit [718721986aa137691ee23f03638867151f74935f](https://github.com/tensorflow/tensorflow/commit/718721986aa137691ee23f03638867151f74935f).
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. Concurrently, it has also been reported by Yakun Zhang of Baidu Security. | {'CVE-2021-37680'} | 2021-08-24T16:24:24Z | 2021-08-25T14:40:38Z | MODERATE | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-37680', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cfpj-3q4c-jhvr', 'https://github.com/tensorflow/tensorflow/commit/718721986aa137691ee23f03638867151f74935f', 'https://github.com/tensorflow/tensorflow'} | null |
PyPI | PYSEC-2019-185 | null | An issue was discovered in Matrix Sydent before 1.0.3 and Synapse before 0.99.3.1. Random number generation is mishandled, which makes it easier for attackers to predict a Sydent authentication token or a Synapse random ID. | {'CVE-2019-11842'} | 2021-08-27T03:22:06.320363Z | 2019-05-09T18:29:00Z | null | null | null | {'https://matrix.org/blog/2019/05/03/security-updates-sydent-1-0-3-synapse-0-99-3-1-and-riot-android-0-9-0-0-8-99-0-8-28-a/'} | null |
PyPI | PYSEC-2020-37 | null | In django-basic-auth-ip-whitelist before 0.3.4, a potential timing attack exists on websites where the basic authentication is used or configured, i.e. BASIC_AUTH_LOGIN and BASIC_AUTH_PASSWORD is set. Currently the string comparison between configured credentials and the ones provided by users is performed through a character-by-character string comparison. This enables a possibility that attacker may time the time it takes the server to validate different usernames and password, and use this knowledge to work out the valid credentials. This attack is understood not to be realistic over the Internet. However, it may be achieved from within local networks where the website is hosted, e.g. from inside a data centre where a website's server is located. Sites protected by IP address whitelisting only are unaffected by this vulnerability. This vulnerability has been fixed on version 0.3.4 of django-basic-auth-ip-whitelist. Update to version 0.3.4 as soon as possible and change basic authentication username and password configured on a Django project using this package. A workaround without upgrading to version 0.3.4 is to stop using basic authentication and use the IP whitelisting component only. It can be achieved by not setting BASIC_AUTH_LOGIN and BASIC_AUTH_PASSWORD in Django project settings. | {'GHSA-m38j-pmg3-v5x5', 'CVE-2020-4071'} | 2020-07-09T14:11:00Z | 2020-06-24T13:15:00Z | null | null | null | {'https://github.com/tm-kn/django-basic-auth-ip-whitelist/security/advisories/GHSA-m38j-pmg3-v5x5', 'https://groups.google.com/forum/#!msg/django-developers/iAaq0pvHXuA/fpUuwjK3i2wJ'} | null |
PyPI | GHSA-f2j6-wrhh-v25m | High severity vulnerability that affects paramiko | Paramiko version 2.4.1, 2.3.2, 2.2.3, 2.1.5, 2.0.8, 1.18.5, 1.17.6 contains a Incorrect Access Control vulnerability in SSH server that can result in RCE. This attack appear to be exploitable via network connectivity. | {'CVE-2018-1000805'} | 2022-04-07T15:17:06.612829Z | 2018-10-10T16:10:10Z | HIGH | null | {'CWE-863', 'CWE-732'} | {'https://github.com/paramiko/paramiko/issues/1283', 'https://usn.ubuntu.com/3796-2/', 'https://access.redhat.com/errata/RHSA-2018:3347', 'https://github.com/paramiko/paramiko', 'https://access.redhat.com/errata/RHSA-2018:3505', 'https://usn.ubuntu.com/3796-1/', 'https://access.redhat.com/errata/RHSA-2018:3406', 'https://herolab.usd.de/wp-content/uploads/sites/4/usd20180023.txt', 'https://lists.debian.org/debian-lts-announce/2018/10/msg00018.html', 'https://lists.debian.org/debian-lts-announce/2021/12/msg00025.html', 'https://usn.ubuntu.com/3796-3/', 'https://nvd.nist.gov/vuln/detail/CVE-2018-1000805', 'https://access.redhat.com/errata/RHBA-2018:3497', 'https://github.com/advisories/GHSA-f2j6-wrhh-v25m'} | null |
PyPI | PYSEC-2014-92 | null | python-gnupg 0.3.5 and 0.3.6 allows context-dependent attackers to have an unspecified impact via vectors related to "option injection through positional arguments." NOTE: this vulnerability exists because of an incomplete fix for CVE-2013-7323. | {'CVE-2014-1929', 'GHSA-vcr5-xr9h-mvc5'} | 2021-08-27T03:22:18.219373Z | 2014-10-25T21:55:00Z | null | null | null | {'https://github.com/advisories/GHSA-vcr5-xr9h-mvc5', 'http://secunia.com/advisories/59031', 'http://www.debian.org/security/2014/dsa-2946', 'http://seclists.org/oss-sec/2014/q1/335', 'http://seclists.org/oss-sec/2014/q1/245'} | null |
PyPI | PYSEC-2020-3 | null | An Improper Output Neutralization for Logs flaw was found in Ansible when using the uri module, where sensitive data is exposed to content and json output. This flaw allows an attacker to access the logs or outputs of performed tasks to read keys used in playbooks from other users within the uri module. The highest threat from this vulnerability is to data confidentiality. | {'GHSA-785x-qw4v-6872', 'CVE-2020-14330'} | 2021-10-11T15:32:06.056476Z | 2020-09-11T18:15:00Z | null | null | null | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-14330', 'https://github.com/advisories/GHSA-785x-qw4v-6872', 'https://github.com/ansible/ansible/issues/68400'} | null |
PyPI | PYSEC-2022-125 | null | Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause a write outside of bounds of an array in TFLite. In fact, the attacker can override the linked list used by the memory allocator. This can be leveraged for an arbitrary write primitive under certain conditions. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-9c78-vcq7-7vxq', 'CVE-2022-23561'} | 2022-03-09T00:18:25.786755Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/6c0b2b70eeee588591680f5b7d5d38175fd7cdf6', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c78-vcq7-7vxq'} | null |
PyPI | PYSEC-2021-593 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of fully connected layers in TFLite is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/fully_connected.cc#L226). We have patched the issue in GitHub commit 718721986aa137691ee23f03638867151f74935f. 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-2021-37680', 'GHSA-cfpj-3q4c-jhvr'} | 2021-12-09T06:35:05.816233Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cfpj-3q4c-jhvr', 'https://github.com/tensorflow/tensorflow/commit/718721986aa137691ee23f03638867151f74935f'} | null |
PyPI | PYSEC-2021-439 | null | In Django 2.2 before 2.2.25, 3.1 before 3.1.14, and 3.2 before 3.2.10, HTTP requests for URLs with trailing newlines could bypass upstream access control based on URL paths. | {'CVE-2021-44420', 'GHSA-v6rh-hp5x-86rv'} | 2021-12-08T02:30:49.294438Z | 2021-12-08T00:15:00Z | null | null | null | {'https://groups.google.com/forum/#!forum/django-announce', 'https://docs.djangoproject.com/en/3.2/releases/security/', 'https://www.djangoproject.com/weblog/2021/dec/07/security-releases/', 'https://github.com/advisories/GHSA-v6rh-hp5x-86rv', 'https://www.openwall.com/lists/oss-security/2021/12/07/1'} | null |
PyPI | PYSEC-2021-356 | null | nltk is vulnerable to Inefficient Regular Expression Complexity | {'CVE-2021-3828', 'GHSA-2ww3-fxvq-293j'} | 2021-10-01T22:29:03.465380Z | 2021-09-27T13:15:00Z | null | null | null | {'https://github.com/nltk/nltk/commit/277711ab1dec729e626b27aab6fa35ea5efbd7e6', 'https://huntr.dev/bounties/d19aed43-75bc-4a03-91a0-4d0bb516bc32', 'https://github.com/advisories/GHSA-2ww3-fxvq-293j'} | null |
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