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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PyPI | PYSEC-2022-60 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `SparseTensorSliceDataset` has an undefined behavior: under certain condition it can be made to dereference a `nullptr` value. The 3 input arguments to `SparseTensorSliceDataset` represent a sparse tensor. However, there are some preconditions that these arguments must satisfy but these are not validated in the implementation. 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-pfjj-m3jj-9jc9', 'CVE-2022-21736'} | 2022-03-09T00:17:31.305252Z | 2022-02-03T12:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/965b97e4a9650495cda5a8c210ef6684b4b9eceb', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pfjj-m3jj-9jc9', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc#L227-L292'} | null | {'https://github.com/tensorflow/tensorflow/commit/965b97e4a9650495cda5a8c210ef6684b4b9eceb'} | {'https://github.com/tensorflow/tensorflow/commit/965b97e4a9650495cda5a8c210ef6684b4b9eceb'} |
PyPI | GHSA-5xvc-vgmp-jgc3 | Improper Access Control in jupyterhub-firstuseauthenticator | ### Impact
When JupyterHub is used with FirstUseAuthenticator, the vulnerability allows unauthorized access to any user's account if `create_users=True` and the username is known or guessed.
### Patches
Upgrade to jupyterhub-firstuseauthenticator to 1.0, or apply patch https://github.com/jupyterhub/firstuseauthenticator/pull/38.patch
### Workarounds
If you cannot upgrade, there is no complete workaround, but it can be mitigated.
If you cannot upgrade yet, you can disable user creation with `c.FirstUseAuthenticator.create_users = False`, which will only allow login with fully normalized usernames for already existing users prior to jupyterhub-firstuserauthenticator 1.0. If any users have never logged in with their normalized username (i.e. lowercase), they will still be vulnerable until you can patch or upgrade. | {'CVE-2021-41194'} | 2022-03-22T18:16:53.507087Z | 2021-10-28T23:13:57Z | CRITICAL | null | {'CWE-284'} | {'https://github.com/jupyterhub/firstuseauthenticator/pull/38', 'https://github.com/jupyterhub/firstuseauthenticator/pull/38/commits/32b21898fb2b53b1a2e36270de6854ad70e9e9bf', 'https://github.com/jupyterhub/firstuseauthenticator/pull/38.patch', 'https://github.com/jupyterhub/firstuseauthenticator/security/advisories/GHSA-5xvc-vgmp-jgc3', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41194', 'https://github.com/jupyterhub/firstuseauthenticator', 'https://github.com/jupyterhub/firstuseauthenticator/pull/38/commits/9e200d974e0cb85d828a6afedb8ab90a37878f28'} | null | {'https://github.com/jupyterhub/firstuseauthenticator/pull/38/commits/9e200d974e0cb85d828a6afedb8ab90a37878f28', 'https://github.com/jupyterhub/firstuseauthenticator/pull/38/commits/32b21898fb2b53b1a2e36270de6854ad70e9e9bf'} | {'https://github.com/jupyterhub/firstuseauthenticator/pull/38/commits/9e200d974e0cb85d828a6afedb8ab90a37878f28', 'https://github.com/jupyterhub/firstuseauthenticator/pull/38/commits/32b21898fb2b53b1a2e36270de6854ad70e9e9bf'} |
PyPI | PYSEC-2021-453 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b40060c9f697b044e3107917c797ba052f4506ab/tensorflow/core/kernels/conv_grad_input_ops.h#L625-L655) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-xm2v-8rrw-w9pm', 'CVE-2021-29525'} | 2021-12-09T06:34:47.241877Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xm2v-8rrw-w9pm', 'https://github.com/tensorflow/tensorflow/commit/2be2cdf3a123e231b16f766aa0e27d56b4606535'} | null | {'https://github.com/tensorflow/tensorflow/commit/2be2cdf3a123e231b16f766aa0e27d56b4606535'} | {'https://github.com/tensorflow/tensorflow/commit/2be2cdf3a123e231b16f766aa0e27d56b4606535'} |
PyPI | GHSA-3p4q-x8f3-p7vq | Moderate severity vulnerability that affects notebook | Jupyter Notebook before 5.7.2 allows XSS via a crafted directory name because notebook/static/tree/js/notebooklist.js handles certain URLs unsafely. | {'CVE-2018-19352'} | 2022-03-03T05:14:08.823743Z | 2018-11-21T22:19:22Z | MODERATE | null | {'CWE-79'} | {'https://nvd.nist.gov/vuln/detail/CVE-2018-19352', 'https://pypi.org/project/notebook/#history', 'https://github.com/jupyter/notebook', 'https://github.com/jupyter/notebook/blob/master/docs/source/changelog.rst', 'https://github.com/jupyter/notebook/commit/288b73e1edbf527740e273fcc69b889460871648', 'https://github.com/advisories/GHSA-3p4q-x8f3-p7vq'} | null | {'https://github.com/jupyter/notebook/commit/288b73e1edbf527740e273fcc69b889460871648'} | {'https://github.com/jupyter/notebook/commit/288b73e1edbf527740e273fcc69b889460871648'} |
PyPI | PYSEC-2014-17 | null | The parser cache functionality in parsergenerator.py in RPLY (aka python-rply) before 0.7.1 allows local users to spoof cache data by pre-creating a temporary rply-*.json file with a predictable name. | {'CVE-2014-1604'} | 2021-07-05T00:01:25.895879Z | 2014-01-28T00:55:00Z | null | null | null | {'http://secunia.com/advisories/56429', 'http://www.osvdb.org/102202', 'http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=735263', 'http://www.openwall.com/lists/oss-security/2014/01/18/4', 'https://github.com/alex/rply/commit/fc9bbcd25b0b4f09bbd6339f710ad24c129d5d7c', 'http://www.openwall.com/lists/oss-security/2014/01/17/8', 'https://exchange.xforce.ibmcloud.com/vulnerabilities/90593'} | null | {'https://github.com/alex/rply/commit/fc9bbcd25b0b4f09bbd6339f710ad24c129d5d7c'} | {'https://github.com/alex/rply/commit/fc9bbcd25b0b4f09bbd6339f710ad24c129d5d7c'} |
PyPI | GHSA-pw4v-gr34-2553 | Denial of service (via resource exhaustion) due to improper input validation | ### Impact
Missing input validation of some parameters on the endpoints used to confirm third-party identifiers could cause excessive use of disk space and memory leading to resource exhaustion.
### Patches
Fixed by 3175fd3.
### For more information
If you have any questions or comments about this advisory, email us at security@matrix.org. | {'CVE-2021-29433'} | 2022-03-03T05:14:01.787497Z | 2021-04-16T19:53:37Z | MODERATE | null | {'CWE-20', 'CWE-400'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29433', 'https://pypi.org/project/matrix-sydent/', 'https://github.com/matrix-org/sydent/security/advisories/GHSA-pw4v-gr34-2553', 'https://github.com/matrix-org/sydent/commit/3175fd358ebc2c310eab7a3dbf296ce2bd54c1da'} | null | {'https://github.com/matrix-org/sydent/commit/3175fd358ebc2c310eab7a3dbf296ce2bd54c1da'} | {'https://github.com/matrix-org/sydent/commit/3175fd358ebc2c310eab7a3dbf296ce2bd54c1da'} |
PyPI | PYSEC-2021-516 | null | TensorFlow is an end-to-end open source platform for machine learning. The optimized implementation of the `TransposeConv` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L5221-L5222). An attacker can craft a model such that `stride_{h,w}` values are 0. Code calling this function must validate these arguments. 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-vfr4-x8j2-3rf9', 'CVE-2021-29588'} | 2021-12-09T06:34:57.029977Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/801c1c6be5324219689c98e1bd3e0ca365ee834d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vfr4-x8j2-3rf9'} | null | {'https://github.com/tensorflow/tensorflow/commit/801c1c6be5324219689c98e1bd3e0ca365ee834d'} | {'https://github.com/tensorflow/tensorflow/commit/801c1c6be5324219689c98e1bd3e0ca365ee834d'} |
PyPI | PYSEC-2018-34 | null | (1) core/tests/test_memmap.py, (2) core/tests/test_multiarray.py, (3) f2py/f2py2e.py, and (4) lib/tests/test_io.py in NumPy before 1.8.1 allow local users to write to arbitrary files via a symlink attack on a temporary file. | {'CVE-2014-1859'} | 2021-06-29T22:52:17.858494Z | 2018-01-08T19:29:00Z | null | null | null | {'https://exchange.xforce.ibmcloud.com/vulnerabilities/91317', 'https://github.com/numpy/numpy/blob/maintenance/1.8.x/doc/release/1.8.1-notes.rst', 'http://www.openwall.com/lists/oss-security/2014/02/08/3', 'http://lists.fedoraproject.org/pipermail/package-announce/2014-February/128358.html', 'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=737778', 'http://lists.fedoraproject.org/pipermail/package-announce/2014-February/128781.html', 'https://github.com/numpy/numpy/commit/0bb46c1448b0d3f5453d5182a17ea7ac5854ee15', 'https://bugzilla.redhat.com/show_bug.cgi?id=1062009', 'http://www.securityfocus.com/bid/65440', 'https://github.com/numpy/numpy/pull/4262'} | null | {'https://github.com/numpy/numpy/commit/0bb46c1448b0d3f5453d5182a17ea7ac5854ee15'} | {'https://github.com/numpy/numpy/commit/0bb46c1448b0d3f5453d5182a17ea7ac5854ee15'} |
PyPI | PYSEC-2020-146 | null | TUF (aka The Update Framework) 0.7.2 through 0.12.1 allows Uncontrolled Resource Consumption. | {'CVE-2020-6173', 'GHSA-2828-9vh6-9m6j'} | 2020-01-21T19:55:00Z | 2020-01-14T19:15:00Z | null | null | null | {'https://github.com/theupdateframework/tuf/issues/973', 'https://github.com/advisories/GHSA-2828-9vh6-9m6j', 'https://github.com/theupdateframework/tuf/commits/develop'} | null | {'https://github.com/theupdateframework/tuf/commits/develop'} | {'https://github.com/theupdateframework/tuf/commits/develop'} |
PyPI | PYSEC-2021-845 | null | TensorFlow is an open source platform for machine learning. In affected versions several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or `CHECK`-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41206', 'GHSA-pgcq-h79j-2f69'} | 2021-12-13T06:20:24.360595Z | 2021-11-05T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pgcq-h79j-2f69', 'https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4', 'https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a', 'https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261', 'https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d', 'https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07'} | null | {'https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a', 'https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904', 'https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07', 'https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261', 'https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4', 'https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d'} | {'https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4', 'https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07', 'https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a', 'https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d', 'https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904', 'https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261'} |
PyPI | PYSEC-2022-5 | null | nltk is vulnerable to Inefficient Regular Expression Complexity | {'GHSA-rqjh-jp2r-59cj', 'CVE-2021-3842'} | 2022-01-12T23:31:32.837727Z | 2022-01-04T15:15:00Z | null | null | null | {'https://github.com/advisories/GHSA-rqjh-jp2r-59cj', 'https://github.com/nltk/nltk/commit/2a50a3edc9d35f57ae42a921c621edc160877f4d', 'https://huntr.dev/bounties/761a761e-2be2-430a-8d92-6f74ffe9866a'} | null | {'https://github.com/nltk/nltk/commit/2a50a3edc9d35f57ae42a921c621edc160877f4d'} | {'https://github.com/nltk/nltk/commit/2a50a3edc9d35f57ae42a921c621edc160877f4d'} |
PyPI | GHSA-j3mj-fhpq-qqjj | Reachable Assertion in Tensorflow | ### Impact
When decoding a tensor from protobuf, a TensorFlow process can encounter cases where a `CHECK` assertion is invalidated based on user controlled arguments, if the tensors have an invalid `dtype` and 0 elements or an invalid shape. This allows attackers to cause denial of services in TensorFlow processes.
### Patches
We have patched the issue in GitHub commit [5b491cd5e41ad63735161cec9c2a568172c8b6a3](https://github.com/tensorflow/tensorflow/commit/5b491cd5e41ad63735161cec9c2a568172c8b6a3).
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-2022-23571'} | 2022-03-03T05:13:41.114572Z | 2022-02-09T23:28:57Z | MODERATE | null | {'CWE-617'} | {'https://github.com/tensorflow/tensorflow/commit/5b491cd5e41ad63735161cec9c2a568172c8b6a3', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-j3mj-fhpq-qqjj', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23571', 'https://github.com/tensorflow/tensorflow/'} | null | {'https://github.com/tensorflow/tensorflow/commit/5b491cd5e41ad63735161cec9c2a568172c8b6a3'} | {'https://github.com/tensorflow/tensorflow/commit/5b491cd5e41ad63735161cec9c2a568172c8b6a3'} |
PyPI | GHSA-p3w6-jcg4-52xh | High severity vulnerability that affects django-rest-registration | ## Misusing the Django Signer API leads to predictable signatures used in verification emails
### Impact
The vulnerability is a high severity one. Anyone using Django REST Registration library versions `0.2.*` - `0.4.*` with e-mail verification option (which is recommended, but needs [additional configuration](https://django-rest-registration.readthedocs.io/en/latest/quickstart.html#preferred-configuration)) is affected.
In the worst case, the attacker can take over any Django user by resetting his/her password without even receiving the reset password verification link, just by guessing the signature from publicly available data (more detailed description below).
### Patches
The problem has been patched in version `0.5.0`. All library users should upgrade to version `0.5.0` or higher.
The fix will invalidate all previously generated signatures , and in consequence, all verification links in previously sent verification e-mails. Therefore semi-major version `0.5.0` was released instead of version `0.4.6` to mark that incompatibility.
### Workarounds
The easiest way way is to disable the verification options by using something like the minimal configuration described [here](https://django-rest-registration.readthedocs.io/en/latest/quickstart.html#minimal-configuration). This will unfortunately disable checking whether the given e-mail is valid and make unable to users who registered an account but didn't verify it before config change.
Less harsh way is to temporarily disable just the the reset password functionality:
```python
REST_REGISTRATION = {
# ...
'RESET_PASSWORD_VERIFICATION_ENABLED': False,
# ...
}
```
Which should disallow the worst case, which is account takeover by an attacker. The attacker can still use the register-email endpoint to change the email to its own (but it is less critical than resetting the password in this case).
If one already set `'RESET_PASSWORD_VERIFICATION_ONE_TIME_USE'` setting key to `True` in `REST_REGISTRATION` Django setting (which is not the default setting) then it should mitigate the security issue in case of password reset (in this case, the signature is much harder to guess by the attacker). But even in this case upgrade to newest version is highly recommended.
### Technical description
After the code [was refactored](https://github.com/apragacz/django-rest-registration/commit/b6d921e9decc9bb36a4c6d58bc607471aa824a2e) to use the [official Signer class](https://docs.djangoproject.com/en/dev/topics/signing/) the salt
was passed wrongly as secret key, replacing the `SECRET_KEY` set in
Django settings file. This leads to the Django `SECRET_KEY` not being used by the signer object. The secret key of the signer ends to be the salt which in most cases is a static string which is publicly available.
In consequence this allows, with verification enabled, to guess
the signature contained in the verification link (which is sent in a verification e-mail) by a potential attacker very easily.
The bug went unnoticed for very long time so multiple versions are affected:
this bug affects versions `0.2.*`, `0.3.*`, `0.4.*`; version `0.1.*` is not affected.
Recently released version `0.5.0` contains the [fix](https://github.com/apragacz/django-rest-registration/commit/26d094fab65ea8c2694fdfb6a3ab95a7808b62d5) which correctly passes the salt to the Signer constructor as keyword argument instead as a positonal argument. It also contains additonal test so this problem should not reappear in the future.
### Thanks
I'd like to thank @peterthomassen from https://desec.io DNS security project for finding the bug. I'd like also to thank his employer, SSE (https://www.securesystems.de) for funding his work.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [GitHub issues project page](https://github.com/apragacz/django-rest-registration/issues)
* Email @apragacz, author of the library | {'CVE-2019-13177'} | 2022-03-21T21:31:54.619518Z | 2019-07-02T15:43:41Z | CRITICAL | null | {'CWE-347'} | {'https://github.com/apragacz/django-rest-registration/security/advisories/GHSA-p3w6-jcg4-52xh', 'https://nvd.nist.gov/vuln/detail/CVE-2019-13177', 'https://github.com/advisories/GHSA-p3w6-jcg4-52xh', 'https://github.com/apragacz/django-rest-registration/commit/26d094fab65ea8c2694fdfb6a3ab95a7808b62d5', 'https://github.com/apragacz/django-rest-registration/releases/tag/0.5.0', 'https://github.com/apragacz/django-rest-registration'} | null | {'https://github.com/apragacz/django-rest-registration/commit/26d094fab65ea8c2694fdfb6a3ab95a7808b62d5'} | {'https://github.com/apragacz/django-rest-registration/commit/26d094fab65ea8c2694fdfb6a3ab95a7808b62d5'} |
PyPI | PYSEC-2020-280 | null | In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. | {'CVE-2020-15200', 'GHSA-x7rp-74x2-mjf3'} | 2021-12-09T06:34:41.630526Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x7rp-74x2-mjf3', 'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1'} | null | {'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02'} | {'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02'} |
PyPI | PYSEC-2021-280 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixSetDiagV*`. 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. We have patched the issue in GitHub 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. | {'CVE-2021-37658', 'GHSA-6p5r-g9mq-ggh2'} | 2021-08-27T03:22:44.725554Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ff8894044dfae5568ecbf2ed514c1a37dc394f1b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6p5r-g9mq-ggh2'} | null | {'https://github.com/tensorflow/tensorflow/commit/ff8894044dfae5568ecbf2ed514c1a37dc394f1b'} | {'https://github.com/tensorflow/tensorflow/commit/ff8894044dfae5568ecbf2ed514c1a37dc394f1b'} |
PyPI | PYSEC-2022-118 | null | Tensorflow is an Open Source Machine Learning Framework. The implementation of `QuantizedMaxPool` has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'GHSA-3mw4-6rj6-74g5', 'CVE-2022-21739'} | 2022-03-09T00:18:24.872174Z | 2022-02-03T14:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559', 'https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3mw4-6rj6-74g5'} | null | {'https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559'} | {'https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559'} |
PyPI | PYSEC-2021-404 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `tf.ragged.cross` can trigger a read outside of bounds of heap allocated array. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'GHSA-fr77-rrx3-cp7g', 'CVE-2021-41212'} | 2021-11-13T06:52:43.991676Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fr77-rrx3-cp7g', 'https://github.com/tensorflow/tensorflow/commit/fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8'} | null | {'https://github.com/tensorflow/tensorflow/commit/fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8'} | {'https://github.com/tensorflow/tensorflow/commit/fa6b7782fbb14aa08d767bc799c531f5e1fb3bb8'} |
PyPI | GHSA-8q59-q68h-6hv4 | Improper Input Validation in PyYAML | A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747. | {'CVE-2020-14343'} | 2022-04-22T18:30:50.414390Z | 2021-03-25T21:26:26Z | CRITICAL | null | {'CWE-20'} | {'https://www.oracle.com/security-alerts/cpuapr2022.html', 'https://nvd.nist.gov/vuln/detail/CVE-2020-14343', 'https://pypi.org/project/PyYAML/', 'https://github.com/yaml/pyyaml/commit/a001f2782501ad2d24986959f0239a354675f9dc', 'https://github.com/yaml/pyyaml', 'https://github.com/yaml/pyyaml/issues/420#issuecomment-663673966', 'https://bugzilla.redhat.com/show_bug.cgi?id=1860466'} | null | {'https://github.com/yaml/pyyaml/commit/a001f2782501ad2d24986959f0239a354675f9dc'} | {'https://github.com/yaml/pyyaml/commit/a001f2782501ad2d24986959f0239a354675f9dc'} |
PyPI | PYSEC-2021-812 | null | TensorFlow is an open source platform for machine learning. In affected versions during TensorFlow's Grappler optimizer phase, constant folding might attempt to deep copy a resource tensor. This results in a segfault, as these tensors are supposed to not change. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'GHSA-786j-5qwq-r36x', 'CVE-2021-41204'} | 2021-12-09T06:35:41.878388Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-786j-5qwq-r36x', 'https://github.com/tensorflow/tensorflow/commit/7731e8dfbe4a56773be5dc94d631611211156659'} | null | {'https://github.com/tensorflow/tensorflow/commit/7731e8dfbe4a56773be5dc94d631611211156659'} | {'https://github.com/tensorflow/tensorflow/commit/7731e8dfbe4a56773be5dc94d631611211156659'} |
PyPI | GHSA-8ch4-58qp-g3mp | Observable Timing Discrepancy in aaugustin websockets library | The aaugustin websockets library before 9.1 for Python has an Observable Timing Discrepancy on servers when HTTP Basic Authentication is enabled with basic_auth_protocol_factory(credentials=...). An attacker may be able to guess a password via a timing attack. | {'CVE-2021-33880'} | 2022-04-22T16:01:59.328330Z | 2021-06-11T17:43:14Z | MODERATE | null | {'CWE-203', 'CWE-208'} | {'https://www.oracle.com/security-alerts/cpuapr2022.html', 'https://www.oracle.com/security-alerts/cpujan2022.html', 'https://github.com/aaugustin/websockets/', 'https://github.com/aaugustin/websockets/commit/547a26b685d08cac0aa64e5e65f7867ac0ea9bc0', 'https://nvd.nist.gov/vuln/detail/CVE-2021-33880'} | null | {'https://github.com/aaugustin/websockets/commit/547a26b685d08cac0aa64e5e65f7867ac0ea9bc0'} | {'https://github.com/aaugustin/websockets/commit/547a26b685d08cac0aa64e5e65f7867ac0ea9bc0'} |
PyPI | PYSEC-2021-111 | null | `projen` is a project generation tool that synthesizes project configuration files such as `package.json`, `tsconfig.json`, `.gitignore`, GitHub Workflows, `eslint`, `jest`, and more, from a well-typed definition written in JavaScript. Users of projen's `NodeProject` project type (including any project type derived from it) include a `.github/workflows/rebuild-bot.yml` workflow that may allow any GitHub user to trigger execution of un-trusted code in the context of the "main" repository (as opposed to that of a fork). In some situations, such untrusted code may potentially be able to commit to the "main" repository. The rebuild-bot workflow is triggered by comments including `@projen rebuild` on pull-request to trigger a re-build of the projen project, and updating the pull request with the updated files. This workflow is triggered by an `issue_comment` event, and thus always executes with a `GITHUB_TOKEN` belonging to the repository into which the pull-request is made (this is in contrast with workflows triggered by `pull_request` events, which always execute with a `GITHUB_TOKEN` belonging to the repository from which the pull-request is made). Repositories that do not have branch protection configured on their default branch (typically `main` or `master`) could possibly allow an untrusted user to gain access to secrets configured on the repository (such as NPM tokens, etc). Branch protection prohibits this escalation, as the managed `GITHUB_TOKEN` would not be able to modify the contents of a protected branch and affected workflows must be defined on the default branch. | {'CVE-2021-21423', 'GHSA-gg2g-m5wc-vccq'} | 2021-07-08T03:14:29.411085Z | 2021-04-06T19:15:00Z | null | null | null | {'https://www.npmjs.com/package/projen', 'https://github.com/projen/projen/commit/36030c6a4b1acd0054673322612e7c70e9446643', 'https://github.com/projen/projen/security/advisories/GHSA-gg2g-m5wc-vccq'} | null | {'https://github.com/projen/projen/commit/36030c6a4b1acd0054673322612e7c70e9446643'} | {'https://github.com/projen/projen/commit/36030c6a4b1acd0054673322612e7c70e9446643'} |
PyPI | PYSEC-2021-541 | null | TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `tf.raw_ops.CTCLoss` allows an attacker to trigger an OOB read from heap. The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-vvg4-vgrv-xfr7', 'CVE-2021-29613'} | 2021-12-09T06:35:00.939983Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/4504a081af71514bb1828048363e6540f797005b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vvg4-vgrv-xfr7', 'https://github.com/tensorflow/tensorflow/commit/14607c0707040d775e06b6817325640cb4b5864c'} | null | {'https://github.com/tensorflow/tensorflow/commit/14607c0707040d775e06b6817325640cb4b5864c', 'https://github.com/tensorflow/tensorflow/commit/4504a081af71514bb1828048363e6540f797005b'} | {'https://github.com/tensorflow/tensorflow/commit/4504a081af71514bb1828048363e6540f797005b', 'https://github.com/tensorflow/tensorflow/commit/14607c0707040d775e06b6817325640cb4b5864c'} |
PyPI | GHSA-vcg8-98q8-g7mj | Exposure of Sensitive Information to an Unauthorized Actor and Insecure Temporary File in Ansible | A flaw was found in Ansible Engine when using Ansible Vault for editing encrypted files. When a user executes "ansible-vault edit", another user on the same computer can read the old and new secret, as it is created in a temporary file with mkstemp and the returned file descriptor is closed and the method write_data is called to write the existing secret in the file. This method will delete the file before recreating it insecurely. All versions in 2.7.x, 2.8.x and 2.9.x branches are believed to be vulnerable. | {'CVE-2020-1740'} | 2022-03-03T05:13:18.887783Z | 2021-04-07T21:47:31Z | LOW | null | {'CWE-200', 'CWE-377'} | {'https://bugzilla.redhat.com/show_bug.cgi?id=CVE-2020-1740', 'https://security.gentoo.org/glsa/202006-11', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/MRRYUU5ZBLPBXCYG6CFP35D64NP2UB2S/', 'https://github.com/ansible/ansible/issues/67798', 'https://github.com/ansible/ansible', 'https://lists.debian.org/debian-lts-announce/2020/05/msg00005.html', 'https://github.com/ansible/ansible/commit/28f9fbdb5e281976e33f443193047068afb97a9b', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/WQVOQD4VAIXXTVQAJKTN7NUGTJFE2PCB/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-1740', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/DKPA4KC3OJSUFASUYMG66HKJE7ADNGFW/'} | null | {'https://github.com/ansible/ansible/commit/28f9fbdb5e281976e33f443193047068afb97a9b'} | {'https://github.com/ansible/ansible/commit/28f9fbdb5e281976e33f443193047068afb97a9b'} |
PyPI | PYSEC-2021-668 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow by passing crafted inputs to `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L171-L185) fails to consider corner cases where input would be split in such a way that the generated tokens should only contain padding elements. If input is such that `num_tokens` is 0, then, for `data_start_index=0` (when left padding is present), the marked line would result in reading `data[-1]`. 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-2021-29542', 'GHSA-4hrh-9vmp-2jgg'} | 2021-12-09T06:35:22.008829Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4hrh-9vmp-2jgg'} | null | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b'} | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b'} |
PyPI | PYSEC-2021-392 | 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'} | 2021-11-13T06:52:42.174686Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5hx2-qx8j-qjqm', 'https://github.com/tensorflow/tensorflow/commit/e5272d4204ff5b46136a1ef1204fc00597e21837', 'https://github.com/tensorflow/tensorflow/issues/46914'} | null | {'https://github.com/tensorflow/tensorflow/commit/e5272d4204ff5b46136a1ef1204fc00597e21837'} | {'https://github.com/tensorflow/tensorflow/commit/e5272d4204ff5b46136a1ef1204fc00597e21837'} |
PyPI | PYSEC-2021-238 | null | TensorFlow is an end-to-end open source platform for machine learning. The TFLite implementation of concatenation is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/7b7352a724b690b11bfaae2cd54bc3907daf6285/tensorflow/lite/kernels/concatenation.cc#L70-L76). An attacker can craft a model such that the dimensions of one of the concatenation input overflow the values of `int`. TFLite uses `int` to represent tensor dimensions, whereas TF uses `int64`. Hence, valid TF models can trigger an integer overflow when converted to TFLite format. 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-2021-29601', 'GHSA-9c84-4hx6-xmm4'} | 2021-08-27T03:22:39.383979Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c84-4hx6-xmm4', 'https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73'} | null | {'https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73'} | {'https://github.com/tensorflow/tensorflow/commit/4253f96a58486ffe84b61c0415bb234a4632ee73'} |
PyPI | PYSEC-2021-687 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from `tf.raw_ops.LoadAndRemapMatrix`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the `ckpt_path` is always a valid scalar. However, an attacker can send any other tensor as the first argument of `LoadAndRemapMatrix`. This would cause the rank `CHECK` in `scalar<T>()()` to trigger and terminate the process. 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-2021-29561', 'GHSA-gvm4-h8j3-rjrq'} | 2021-12-09T06:35:25.291953Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gvm4-h8j3-rjrq', 'https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4'} | null | {'https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4'} | {'https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4'} |
PyPI | GHSA-m8qc-mf6p-pfq9 | Link Following in rply | python-rply before 0.7.4 insecurely creates temporary files. | {'CVE-2014-1938'} | 2022-03-03T05:13:33.531617Z | 2020-03-11T20:56:34Z | MODERATE | null | {'CWE-59'} | {'https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=737627', 'https://nvd.nist.gov/vuln/detail/CVE-2014-1938', 'http://www.openwall.com/lists/oss-security/2014/02/11/1', 'https://github.com/alex/rply/commit/76d268a38c627bf4aebebcd064f5b6d380eb8b20', 'https://security-tracker.debian.org/tracker/CVE-2014-1938', 'https://github.com/alex/rply/issues/42'} | null | {'https://github.com/alex/rply/commit/76d268a38c627bf4aebebcd064f5b6d380eb8b20'} | {'https://github.com/alex/rply/commit/76d268a38c627bf4aebebcd064f5b6d380eb8b20'} |
PyPI | PYSEC-2021-869 | null | archivy is vulnerable to Cross-Site Request Forgery (CSRF) | {'CVE-2021-4162', 'GHSA-9236-8w7q-rmrv'} | 2022-01-13T03:02:27.086269Z | 2021-12-25T12:15:00Z | null | null | null | {'https://github.com/archivy/archivy/commit/796c3ae318eea183fc88c87ec5a27355b0f6a99d', 'https://huntr.dev/bounties/e204a768-2129-4b6f-abad-e436309c7c32', 'https://github.com/advisories/GHSA-9236-8w7q-rmrv'} | null | {'https://github.com/archivy/archivy/commit/796c3ae318eea183fc88c87ec5a27355b0f6a99d'} | {'https://github.com/archivy/archivy/commit/796c3ae318eea183fc88c87ec5a27355b0f6a99d'} |
PyPI | GHSA-r82c-j4mq-5xfw | Update bitlyshortener to >=0.5.0 to prevent generating some invalid short URLs | ### Impact
Due to a sudden upstream breaking change by Bitly, versions of `bitlyshortener` <0.5.0 can generate an invalid short URL when a vanity domain exists.
### Patches
Upgrading `bitlyshortener` to 0.5.0 or newer will prevent the generation of any such invalid short URLs.
### References
* [Release notes](https://github.com/impredicative/bitlyshortener/releases) | null | 2022-03-03T05:13:06.521725Z | 2020-10-27T19:19:56Z | HIGH | null | {'CWE-601'} | {'https://github.com/impredicative/bitlyshortener/releases/tag/0.5.0', 'https://pypi.org/project/bitlyshortener/', 'https://github.com/impredicative/bitlyshortener/commit/3d412feb77f3daf6f71536463734c2119a55968d', 'https://github.com/impredicative/bitlyshortener/security/advisories/GHSA-r82c-j4mq-5xfw'} | null | {'https://github.com/impredicative/bitlyshortener/commit/3d412feb77f3daf6f71536463734c2119a55968d'} | {'https://github.com/impredicative/bitlyshortener/commit/3d412feb77f3daf6f71536463734c2119a55968d'} |
PyPI | PYSEC-2018-18 | null | Jupyter Notebook before 5.7.2 allows XSS via a crafted directory name because notebook/static/tree/js/notebooklist.js handles certain URLs unsafely. | {'GHSA-3p4q-x8f3-p7vq', 'CVE-2018-19352'} | 2021-06-10T06:52:01.452566Z | 2018-11-18T17:29:00Z | null | null | null | {'https://github.com/jupyter/notebook/commit/288b73e1edbf527740e273fcc69b889460871648', 'https://pypi.org/project/notebook/#history', 'https://github.com/jupyter/notebook/blob/master/docs/source/changelog.rst', 'https://github.com/advisories/GHSA-3p4q-x8f3-p7vq'} | null | {'https://github.com/jupyter/notebook/commit/288b73e1edbf527740e273fcc69b889460871648'} | {'https://github.com/jupyter/notebook/commit/288b73e1edbf527740e273fcc69b889460871648'} |
PyPI | PYSEC-2021-490 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.IRFFT`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29562', 'GHSA-36vm-xw34-x4pj'} | 2021-12-09T06:34:52.986581Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-36vm-xw34-x4pj', 'https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2'} | null | {'https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2'} | {'https://github.com/tensorflow/tensorflow/commit/1c56f53be0b722ca657cbc7df461ed676c8642a2'} |
PyPI | GHSA-p5f8-gfw5-33w4 | Heap buffer overflow in Tensorflow | ### Impact
The `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, this code is prone to heap buffer overflow:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L248-L251
If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large.
### Patches
We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release.
We recommend users to upgrade to TensorFlow 2.3.1.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2020-15201'} | 2021-08-26T15:13:48Z | 2020-09-25T18:28:34Z | MODERATE | null | {'CWE-20', 'CWE-787', 'CWE-122'} | {'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4', 'https://nvd.nist.gov/vuln/detail/CVE-2020-15201', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1'} | null | {'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02'} | {'https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02'} |
PyPI | PYSEC-2021-185 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the op's contract(https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizedBatchNormWithGlobalNormalization). 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-2021-29548', 'GHSA-p45v-v4pw-77jr'} | 2021-08-27T03:22:29.986611Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p45v-v4pw-77jr'} | null | {'https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b'} | {'https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b'} |
PyPI | PYSEC-2020-71 | null | In openapi-python-client before version 0.5.3, clients generated with a maliciously crafted OpenAPI Document can generate arbitrary Python code. Subsequent execution of this malicious client is arbitrary code execution. | {'CVE-2020-15142', 'GHSA-9x4c-63pf-525f'} | 2020-08-20T18:11:00Z | 2020-08-14T17:15:00Z | null | null | null | {'https://github.com/triaxtec/openapi-python-client/blob/main/CHANGELOG.md#053---2020-08-13', 'https://pypi.org/project/openapi-python-client/', 'https://github.com/triaxtec/openapi-python-client/security/advisories/GHSA-9x4c-63pf-525f', 'https://github.com/triaxtec/openapi-python-client/commit/f7a56aae32cba823a77a84a1f10400799b19c19a'} | null | {'https://github.com/triaxtec/openapi-python-client/commit/f7a56aae32cba823a77a84a1f10400799b19c19a'} | {'https://github.com/triaxtec/openapi-python-client/commit/f7a56aae32cba823a77a84a1f10400799b19c19a'} |
PyPI | PYSEC-2021-756 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, as these are also affected and still in supported range. | {'CVE-2021-37645', 'GHSA-9w2p-5mgw-p94c'} | 2021-12-09T06:35:36.218671Z | 2021-08-12T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9w2p-5mgw-p94c'} | null | {'https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1'} | {'https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1'} |
PyPI | GHSA-26j7-6w8w-7922 | Division by zero in optimized pooling implementations in TFLite | ### Impact
Optimized pooling implementations in TFLite fail to check that the stride arguments are not 0 before calling [`ComputePaddingHeightWidth`](https://github.com/tensorflow/tensorflow/blob/3f24ccd932546416ec906a02ddd183b48a1d2c83/tensorflow/lite/kernels/pooling.cc#L90).
Since users can craft special models which will have `params->stride_{height,width}` be zero, this will result in a division by zero.
### Patches
We have patched the issue in GitHub commit [5f7975d09eac0f10ed8a17dbb6f5964977725adc](https://github.com/tensorflow/tensorflow/commit/5f7975d09eac0f10ed8a17dbb6f5964977725adc).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-29586'} | 2022-03-03T05:13:45.088991Z | 2021-05-21T14:26:43Z | LOW | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29586', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-26j7-6w8w-7922', 'https://github.com/tensorflow/tensorflow/commit/5f7975d09eac0f10ed8a17dbb6f5964977725adc'} | null | {'https://github.com/tensorflow/tensorflow/commit/5f7975d09eac0f10ed8a17dbb6f5964977725adc'} | {'https://github.com/tensorflow/tensorflow/commit/5f7975d09eac0f10ed8a17dbb6f5964977725adc'} |
PyPI | GHSA-278g-rq84-9hmg | `CHECK`-fail in `MapStage` | ### Impact
An attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.MapStage`:
```python
import tensorflow as tf
tf.raw_ops.MapStage(
key=tf.constant([], shape=[0, 0, 0, 0], dtype=tf.int64),
indices=tf.constant((0), dtype=tf.int32),
values=[tf.constant((0), dtype=tf.int32)],
dtypes=[tf.int32,
tf.int64],
capacity=0,
memory_limit=0,
container='',
shared_name='')
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/map_stage_op.cc#L513) does not check that the `key` input is a valid non-empty tensor.
### Patches
We have patched the issue in GitHub commit [d7de67733925de196ec8863a33445b73f9562d1d](https://github.com/tensorflow/tensorflow/commit/d7de67733925de196ec8863a33445b73f9562d1d).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### 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-2021-37673'} | 2022-03-03T05:13:08.313939Z | 2021-08-25T14:41:36Z | MODERATE | null | {'CWE-20'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37673', 'https://github.com/tensorflow/tensorflow/commit/d7de67733925de196ec8863a33445b73f9562d1d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-278g-rq84-9hmg'} | null | {'https://github.com/tensorflow/tensorflow/commit/d7de67733925de196ec8863a33445b73f9562d1d'} | {'https://github.com/tensorflow/tensorflow/commit/d7de67733925de196ec8863a33445b73f9562d1d'} |
PyPI | PYSEC-2020-306 | null | In Tensorflow before versions 2.2.1 and 2.3.1, if a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition. However, this `status` argument is not properly checked. Hence, code following these methods will bind references to null pointers. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. | {'GHSA-q8qj-fc9q-cphr', 'CVE-2020-15191'} | 2021-12-09T06:35:12.260463Z | 2020-09-25T19:15:00Z | null | null | null | {'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q8qj-fc9q-cphr', 'https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1'} | null | {'https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8'} | {'https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8'} |
PyPI | GHSA-9g8h-pjm4-q92p | Out-of-bounds Write in OpenCV. | In OpenCV 3.3.1 (corresponding with OpenCV-Python 3.3.1.11), a heap-based buffer overflow happens in cv::Jpeg2KDecoder::readComponent8u in modules/imgcodecs/src/grfmt_jpeg2000.cpp when parsing a crafted image file. | {'CVE-2018-5268'} | 2022-03-03T05:13:11.150261Z | 2021-10-12T22:23:41Z | MODERATE | null | {'CWE-787'} | {'http://www.securityfocus.com/bid/106945', 'https://lists.debian.org/debian-lts-announce/2021/10/msg00028.html', 'https://github.com/opencv/opencv/issues/10541', 'https://nvd.nist.gov/vuln/detail/CVE-2018-5268', 'https://github.com/opencv/opencv/pull/10566/commits/435a3e337bd9d4e11af61cf8b8afca067bf1a8aa', 'https://lists.debian.org/debian-lts-announce/2018/04/msg00019.html', 'https://github.com/opencv/opencv-python', 'https://lists.debian.org/debian-lts-announce/2018/07/msg00030.html'} | null | {'https://github.com/opencv/opencv/pull/10566/commits/435a3e337bd9d4e11af61cf8b8afca067bf1a8aa'} | {'https://github.com/opencv/opencv/pull/10566/commits/435a3e337bd9d4e11af61cf8b8afca067bf1a8aa'} |
PyPI | GHSA-4fjv-pmhg-3rfg | Multiple cryptographic issues in Python oic | ### Impact
* Client implementations using this library
### Issues
1) The IdToken signature algorithm was not checked automatically, but only if the expected algorithm was passed in as a kwarg.
2) JWA `none` algorithm was allowed in all flows.
3) `oic.consumer.Consumer.parse_authz` returns an unverified IdToken. The verification of the token was left to the discretion of the implementator.
4) `iat` claim was not checked for sanity (i.e. it could be in the future)
### Patches
1) IdToken signature is now always checked.
2) JWA `none` algorithm is now allowed only if using the `response_type` `code`
3) IdToken verification is now done automatically.
4) `iat` claim is now checked for sanity. | {'CVE-2020-26244'} | 2022-03-03T05:13:09.226121Z | 2020-12-04T16:47:12Z | MODERATE | null | {'CWE-325', 'CWE-347'} | {'https://github.com/OpenIDC/pyoidc/security/advisories/GHSA-4fjv-pmhg-3rfg', 'https://github.com/OpenIDC/pyoidc/commit/62f8d753fa17c8b1f29f8be639cf0b33afb02498', 'https://github.com/OpenIDC/pyoidc/releases/tag/1.2.1', 'https://nvd.nist.gov/vuln/detail/CVE-2020-26244', 'https://pypi.org/project/oic/'} | null | {'https://github.com/OpenIDC/pyoidc/commit/62f8d753fa17c8b1f29f8be639cf0b33afb02498'} | {'https://github.com/OpenIDC/pyoidc/commit/62f8d753fa17c8b1f29f8be639cf0b33afb02498'} |
PyPI | PYSEC-2021-613 | null | TensorFlow is an open source platform for machine learning. In affected versions an attacker can trigger undefined behavior, integer overflows, segfaults and `CHECK`-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. The fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'CVE-2021-41203', 'GHSA-7pxj-m4jf-r6h2'} | 2021-12-09T06:35:08.067216Z | 2021-11-05T21:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/e8dc63704c88007ee4713076605c90188d66f3d2', 'https://github.com/tensorflow/tensorflow/commit/b619c6f865715ca3b15ef1842b5b95edbaa710ad', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7pxj-m4jf-r6h2', 'https://github.com/tensorflow/tensorflow/commit/368af875869a204b4ac552b9ddda59f6a46a56ec', 'https://github.com/tensorflow/tensorflow/commit/abcced051cb1bd8fb05046ac3b6023a7ebcc4578'} | null | {'https://github.com/tensorflow/tensorflow/commit/e8dc63704c88007ee4713076605c90188d66f3d2', 'https://github.com/tensorflow/tensorflow/commit/abcced051cb1bd8fb05046ac3b6023a7ebcc4578', 'https://github.com/tensorflow/tensorflow/commit/b619c6f865715ca3b15ef1842b5b95edbaa710ad', 'https://github.com/tensorflow/tensorflow/commit/368af875869a204b4ac552b9ddda59f6a46a56ec'} | {'https://github.com/tensorflow/tensorflow/commit/e8dc63704c88007ee4713076605c90188d66f3d2', 'https://github.com/tensorflow/tensorflow/commit/abcced051cb1bd8fb05046ac3b6023a7ebcc4578', 'https://github.com/tensorflow/tensorflow/commit/b619c6f865715ca3b15ef1842b5b95edbaa710ad', 'https://github.com/tensorflow/tensorflow/commit/368af875869a204b4ac552b9ddda59f6a46a56ec'} |
PyPI | PYSEC-2021-243 | null | TensorFlow is an end-to-end open source platform for machine learning. A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of `Split_V`(https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99). If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the `SizeOfDimension` function(https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/kernel_util.h#L148-L150) will access data outside the bounds of the tensor shape 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. | {'CVE-2021-29606', 'GHSA-h4pc-gx2w-f2xv'} | 2021-08-27T03:22:40.241160Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h4pc-gx2w-f2xv', 'https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412'} | null | {'https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412'} | {'https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412'} |
PyPI | GHSA-89px-ww3j-g2mm | 2FA bypass in Wagtail through new device path | ## 2FA bypass through new device path
### Impact
If someone gains access to someone's Wagtail login credentials, they can log into the CMS and bypass the 2FA check by changing the URL. They can then add a new device and gain full access to the CMS.
### Patches
This problem has been patched in version 1.3.0.
### Workarounds
There is no workaround at the moment.
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [github.com/labd/wagtail-2fa](https://github.com/labd/wagtail-2fa)
* Email us at [security@labdigital.nl](mailto:security@labdigital.nl) | {'CVE-2019-16766'} | 2022-03-03T05:13:37.620316Z | 2019-11-29T17:05:59Z | HIGH | null | {'CWE-290', 'CWE-304'} | {'https://github.com/advisories/GHSA-89px-ww3j-g2mm', 'https://github.com/labd/wagtail-2fa/commit/a6711b29711729005770ff481b22675b35ff5c81', 'https://github.com/labd/wagtail-2fa/security/advisories/GHSA-89px-ww3j-g2mm', 'https://nvd.nist.gov/vuln/detail/CVE-2019-16766', 'https://github.com/labd/wagtail-2fa/commit/13b12995d35b566df08a17257a23863ab6efb0ca'} | null | {'https://github.com/labd/wagtail-2fa/commit/a6711b29711729005770ff481b22675b35ff5c81', 'https://github.com/labd/wagtail-2fa/commit/13b12995d35b566df08a17257a23863ab6efb0ca'} | {'https://github.com/labd/wagtail-2fa/commit/a6711b29711729005770ff481b22675b35ff5c81', 'https://github.com/labd/wagtail-2fa/commit/13b12995d35b566df08a17257a23863ab6efb0ca'} |
PyPI | GHSA-hj69-c76v-86wr | Out-of-bounds Read in Pillow | libImaging/FliDecode.c in Pillow before 6.2.2 has an FLI buffer overflow. | {'CVE-2020-5313'} | 2022-03-03T05:13:50.761817Z | 2020-04-01T16:36:00Z | HIGH | null | {'CWE-125'} | {'https://github.com/python-pillow/Pillow/commit/a09acd0decd8a87ccce939d5ff65dab59e7d365b', 'https://github.com/python-pillow/Pillow/blob/master/CHANGES.rst#622-2020-01-02', 'https://usn.ubuntu.com/4272-1/', 'https://www.debian.org/security/2020/dsa-4631', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/2MMU3WT2X64GS5WHDPKKC2WZA7UIIQ3A/', 'https://pillow.readthedocs.io/en/stable/releasenotes/6.2.2.html', 'https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/3DUMIBUYGJRAVJCTFUWBRLVQKOUTVX5P/', 'https://nvd.nist.gov/vuln/detail/CVE-2020-5313'} | null | {'https://github.com/python-pillow/Pillow/commit/a09acd0decd8a87ccce939d5ff65dab59e7d365b'} | {'https://github.com/python-pillow/Pillow/commit/a09acd0decd8a87ccce939d5ff65dab59e7d365b'} |
PyPI | GHSA-4ppp-gpcr-7qf6 | HTTP Request Smuggling: Content-Length Sent Twice in Waitress | ### Impact
Waitress would header fold a double `Content-Length` header and due to being unable to cast the now comma separated value to an integer would set the `Content-Length` to 0 internally.
So a request with:
```
Content-Length: 10
Content-Length: 10
```
would get transformed to:
```
Content-Length: 10, 10
```
Which would Waitress would then internally set to `Content-Lenght: 0`.
Waitress would then treat the request as having no body, thereby treating the body of the request as a new request in HTTP pipelining.
### Patches
This issue is fixed in Waitress 1.4.0. This brings a range of changes to harden Waitress against potential HTTP request confusions, and may change the behaviour of Waitress behind non-conformist proxies.
The Pylons Project recommends upgrading as soon as possible, while validating that the changes in Waitress don't cause any changes in behavior.
### Workarounds
Various reverse proxies may have protections against sending potentially bad HTTP requests to the backend, and or hardening against potential issues like this. If the reverse proxy doesn't use HTTP/1.1 for connecting to the backend issues are also somewhat mitigated, as HTTP pipelining does not exist in HTTP/1.0 and Waitress will close the connection after every single request (unless the Keep Alive header is explicitly sent... so this is not a fool proof security method).
### Issues/more security issues:
* open an issue at https://github.com/Pylons/waitress/issues (if not sensitive or security related)
* email the Pylons Security mailing list: pylons-project-security@googlegroups.com (if security related) | null | 2022-03-24T18:01:51.171462Z | 2019-12-20T23:04:35Z | CRITICAL | null | {'CWE-444'} | {'https://github.com/Pylons/waitress', 'https://github.com/Pylons/waitress/commit/575994cd42e83fd772a5f7ec98b2c56751bd3f65', 'https://github.com/Pylons/waitress/security/advisories/GHSA-4ppp-gpcr-7qf6'} | null | {'https://github.com/Pylons/waitress/commit/575994cd42e83fd772a5f7ec98b2c56751bd3f65'} | {'https://github.com/Pylons/waitress/commit/575994cd42e83fd772a5f7ec98b2c56751bd3f65'} |
PyPI | GHSA-h4pc-gx2w-f2xv | Heap OOB read in TFLite | ### Impact
A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of [`Split_V`](https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99):
```cc
const int input_size = SizeOfDimension(input, axis_value);
```
If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the [`SizeOfDimension` function](https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/kernel_util.h#L148-L150) will access data outside the bounds of the tensor shape array:
```cc
inline int SizeOfDimension(const TfLiteTensor* t, int dim) {
return t->dims->data[dim];
}
```
### Patches
We have patched the issue in GitHub commit [ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412](https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412).
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-29606'} | 2022-03-03T05:13:05.178287Z | 2021-05-21T14:28:24Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h4pc-gx2w-f2xv', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29606', 'https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412'} | null | {'https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412'} | {'https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412'} |
PyPI | PYSEC-2020-26 | null | Synopsys hub-rest-api-python (aka blackduck on PyPI) version 0.0.25 - 0.0.52 does not validate SSL certificates in certain cases. | {'GHSA-f248-v4qh-x2r6', 'CVE-2020-27589'} | 2021-09-01T06:49:41.380049Z | 2020-11-06T14:15:00Z | null | null | null | {'https://github.com/blackducksoftware/hub-rest-api-python/pull/113/commits/273b27d0de1004389dd8cf43c40b1197c787e7cd', 'https://pypi.org/project/blackduck/', 'https://community.synopsys.com/s/question/0D52H00005JCZAXSA5/announcement-black-duck-defect-identified', 'https://github.com/blackducksoftware/hub-rest-api-python', 'https://github.com/advisories/GHSA-f248-v4qh-x2r6', 'https://www.optiv.com/explore-optiv-insights/source-zero/certificate-validation-disabled-black-duck-api-wrapper'} | null | {'https://github.com/blackducksoftware/hub-rest-api-python/pull/113/commits/273b27d0de1004389dd8cf43c40b1197c787e7cd'} | {'https://github.com/blackducksoftware/hub-rest-api-python/pull/113/commits/273b27d0de1004389dd8cf43c40b1197c787e7cd'} |
PyPI | PYSEC-2021-428 | null | nbdime provides tools for diffing and merging of Jupyter Notebooks. In affected versions a stored cross-site scripting (XSS) issue exists within the Jupyter-owned nbdime project. It appears that when reading the file name and path from disk, the extension does not sanitize the string it constructs before returning it to be displayed. The diffNotebookCheckpoint function within nbdime causes this issue. When attempting to display the name of the local notebook (diffNotebookCheckpoint), nbdime appears to simply append .ipynb to the name of the input file. The NbdimeWidget is then created, and the base string is passed through to the request API function. From there, the frontend simply renders the HTML tag and anything along with it. Users are advised to patch to the most recent version of the affected product. | {'CVE-2021-41134', 'GHSA-p6rw-44q7-3fw4'} | 2021-11-16T21:20:29.137127Z | 2021-11-03T18:15:00Z | null | null | null | {'https://github.com/jupyter/nbdime/security/advisories/GHSA-p6rw-44q7-3fw4', 'https://github.com/jupyter/nbdime/commit/e44a5cc7677f24b45ebafc756db49058c2f750ea'} | null | {'https://github.com/jupyter/nbdime/commit/e44a5cc7677f24b45ebafc756db49058c2f750ea'} | {'https://github.com/jupyter/nbdime/commit/e44a5cc7677f24b45ebafc756db49058c2f750ea'} |
PyPI | GHSA-4cfr-gjfx-fj3x | Cobbler before 3.3.0 allows arbitrary file write operations via upload_log_data. | Cobbler before 3.3.0 allows arbitrary file write operations via upload_log_data. | {'CVE-2021-40324'} | 2022-03-03T05:14:01.052844Z | 2021-10-05T17:53:11Z | HIGH | null | {'CWE-434'} | {'https://github.com/cobbler/cobbler/commit/d8f60bbf14a838c8c8a1dba98086b223e35fe70a', 'https://github.com/cobbler/cobbler', 'https://nvd.nist.gov/vuln/detail/CVE-2021-40324', 'https://github.com/cobbler/cobbler/releases/tag/v3.3.0'} | null | {'https://github.com/cobbler/cobbler/commit/d8f60bbf14a838c8c8a1dba98086b223e35fe70a'} | {'https://github.com/cobbler/cobbler/commit/d8f60bbf14a838c8c8a1dba98086b223e35fe70a'} |
PyPI | PYSEC-2021-582 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`. However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to unsigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`. We have patched the issue in GitHub commit 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-vmjw-c2vp-p33c', 'CVE-2021-37669'} | 2021-12-09T06:35:04.885089Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vmjw-c2vp-p33c', 'https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58', 'https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d'} | null | {'https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d', 'https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58'} | {'https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58', 'https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d'} |
PyPI | PYSEC-2022-134 | null | Tensorflow is an Open Source Machine Learning Framework. When decoding a tensor from protobuf, TensorFlow might do a null-dereference if attributes of some mutable arguments to some operations are missing from the proto. This is guarded by a `DCHECK`. However, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the dereferencing of the null pointer, whereas in the second case it results in a crash due to the assertion failure. 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. | {'CVE-2022-23570', 'GHSA-9p77-mmrw-69c7'} | 2022-03-09T00:18:26.999978Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/8a513cec4bec15961fbfdedcaa5376522980455c', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9p77-mmrw-69c7', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/full_type_util.cc#L104-L106'} | null | {'https://github.com/tensorflow/tensorflow/commit/8a513cec4bec15961fbfdedcaa5376522980455c'} | {'https://github.com/tensorflow/tensorflow/commit/8a513cec4bec15961fbfdedcaa5376522980455c'} |
PyPI | GHSA-7xwj-5r4v-429p | NPE in TFLite | ### Impact
The implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313):
```cc
TfLiteTensor* state = GetVariableInput(context, node, kStateTensor);
// ...
GetTensorData<float>(state)
```
The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor.
```cc
TfLiteTensor* GetVariableInput(TfLiteContext* context, const TfLiteNode* node,
int index) {
TfLiteTensor* tensor = GetMutableInput(context, node, index);
return tensor->is_variable ? tensor : nullptr;
}
```
Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception.
### Patches
We have patched the issue in GitHub commit [5b048e87e4e55990dae6b547add4dae59f4e1c76](https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76).
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-2021-37681'} | 2021-08-24T16:30:14Z | 2021-08-25T14:40:35Z | HIGH | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37681', 'https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7xwj-5r4v-429p'} | null | {'https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76'} | {'https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76'} |
PyPI | PYSEC-2021-351 | null | ESPHome is a system to control the ESP8266/ESP32. Anyone with web_server enabled and HTTP basic auth configured on version 2021.9.1 or older is vulnerable to an issue in which `web_server` allows over-the-air (OTA) updates without checking user defined basic auth username & password. This issue is patched in version 2021.9.2. As a workaround, one may disable or remove `web_server`. | {'CVE-2021-41104', 'GHSA-48mj-p7x2-5jfm'} | 2021-09-30T23:26:26.067991Z | 2021-09-28T16:15:00Z | null | null | null | {'https://github.com/esphome/esphome/commit/2234f6aacf8cc653307fed80f3750317a82c4f83', 'https://github.com/esphome/esphome/pull/2409/commits/207cde1667d8c799a197b78ca8a5a14de8d5ca1e', 'https://github.com/esphome/esphome/releases/tag/2021.9.2', 'https://github.com/esphome/esphome/security/advisories/GHSA-48mj-p7x2-5jfm'} | null | {'https://github.com/esphome/esphome/commit/2234f6aacf8cc653307fed80f3750317a82c4f83', 'https://github.com/esphome/esphome/pull/2409/commits/207cde1667d8c799a197b78ca8a5a14de8d5ca1e'} | {'https://github.com/esphome/esphome/commit/2234f6aacf8cc653307fed80f3750317a82c4f83', 'https://github.com/esphome/esphome/pull/2409/commits/207cde1667d8c799a197b78ca8a5a14de8d5ca1e'} |
PyPI | PYSEC-2021-701 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-6qgm-fv6v-rfpv', 'CVE-2021-29575'} | 2021-12-09T06:35:27.716876Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6qgm-fv6v-rfpv', 'https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23'} | null | {'https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23'} | {'https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23'} |
PyPI | PYSEC-2021-214 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.AvgPool3DGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/d80ffba9702dc19d1fac74fc4b766b3fa1ee976b/tensorflow/core/kernels/pooling_ops_3d.cc#L376-L450) assumes that the `orig_input_shape` and `grad` tensors have similar first and last dimensions but does not check that this assumption is validated. 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-v6r6-84gr-92rm', 'CVE-2021-29577'} | 2021-08-27T03:22:35.059356Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/6fc9141f42f6a72180ecd24021c3e6b36165fe0d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v6r6-84gr-92rm'} | null | {'https://github.com/tensorflow/tensorflow/commit/6fc9141f42f6a72180ecd24021c3e6b36165fe0d'} | {'https://github.com/tensorflow/tensorflow/commit/6fc9141f42f6a72180ecd24021c3e6b36165fe0d'} |
PyPI | PYSEC-2021-644 | null | TensorFlow is an end-to-end open source platform for machine learning. In eager mode (default in TF 2.0 and later), session operations are invalid. However, users could still call the raw ops associated with them and trigger a null pointer dereference. The implementation(https://github.com/tensorflow/tensorflow/blob/eebb96c2830d48597d055d247c0e9aebaea94cd5/tensorflow/core/kernels/session_ops.cc#L104) dereferences the session state pointer without checking if it is valid. Thus, in eager mode, `ctx->session_state()` is nullptr and the call of the member function is undefined behavior. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-62gx-355r-9fhg', 'CVE-2021-29518'} | 2021-12-09T06:35:18.016615Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-62gx-355r-9fhg', 'https://github.com/tensorflow/tensorflow/commit/ff70c47a396ef1e3cb73c90513da4f5cb71bebba'} | null | {'https://github.com/tensorflow/tensorflow/commit/ff70c47a396ef1e3cb73c90513da4f5cb71bebba'} | {'https://github.com/tensorflow/tensorflow/commit/ff70c47a396ef1e3cb73c90513da4f5cb71bebba'} |
PyPI | GHSA-wrp6-9w7f-3wxg | calibre-web is vulnerable to Cross-site Scripting | calibre-web is vulnerable to Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') | {'CVE-2021-4170'} | 2022-03-03T05:14:13.530442Z | 2022-01-21T23:55:34Z | HIGH | null | {'CWE-79'} | {'https://github.com/janeczku/calibre-web/', 'https://github.com/janeczku/calibre-web/commit/7ad419dc8c12180e842a82118f4866ac3d074bc5', 'https://nvd.nist.gov/vuln/detail/CVE-2021-4170', 'https://huntr.dev/bounties/ff395101-e392-401d-ab4f-579c63fbf6a0'} | null | {'https://github.com/janeczku/calibre-web/commit/7ad419dc8c12180e842a82118f4866ac3d074bc5'} | {'https://github.com/janeczku/calibre-web/commit/7ad419dc8c12180e842a82118f4866ac3d074bc5'} |
PyPI | GHSA-cw7p-q79f-m2v7 | incomplete JupyterHub logout with simultaneous JupyterLab sessions | ### Impact
Users of JupyterLab with JupyterHub who have multiple JupyterLab tabs open in the same browser session, may see incomplete logout from the single-user server, as fresh credentials (for the single-user server only, not the Hub) reinstated after logout, if another active JupyterLab session is open while the logout takes place.
### Patches
Upgrade to JupyterHub 1.5. For distributed deployments, it is jupyterhub in the _user_ environment that needs patching. There are no patches necessary in the Hub environment.
### Workarounds
The only workaround is to make sure that only one JupyterLab tab is open when you log out. | {'CVE-2021-41247'} | 2022-03-03T05:13:51.884212Z | 2021-11-08T18:02:37Z | LOW | null | {'CWE-613'} | {'https://github.com/jupyterhub/jupyterhub/commit/5ac9e7f73a6e1020ffddc40321fc53336829fe27', 'https://github.com/jupyterhub/jupyterhub/security/advisories/GHSA-cw7p-q79f-m2v7', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41247', 'https://github.com/jupyterhub/jupyterhub'} | null | {'https://github.com/jupyterhub/jupyterhub/commit/5ac9e7f73a6e1020ffddc40321fc53336829fe27'} | {'https://github.com/jupyterhub/jupyterhub/commit/5ac9e7f73a6e1020ffddc40321fc53336829fe27'} |
PyPI | GHSA-42fp-4hm3-j8r7 | Moderate severity vulnerability that affects moin | Cross-site scripting (XSS) vulnerability in the link dialogue in GUI editor in MoinMoin before 1.9.10 allows remote attackers to inject arbitrary web script or HTML via unspecified vectors. | {'CVE-2017-5934'} | 2022-03-03T05:13:32.296666Z | 2019-01-04T17:46:08Z | MODERATE | null | {'CWE-79'} | {'https://github.com/moinwiki/moin-1.9/commit/70955a8eae091cc88fd9a6e510177e70289ec024', 'https://nvd.nist.gov/vuln/detail/CVE-2017-5934', 'https://lists.debian.org/debian-lts-announce/2018/10/msg00007.html', 'https://usn.ubuntu.com/3794-1/', 'https://www.debian.org/security/2018/dsa-4318', 'http://lists.opensuse.org/opensuse-security-announce/2018-10/msg00024.html', 'https://github.com/moinwiki/moin-1.9', 'https://github.com/advisories/GHSA-42fp-4hm3-j8r7', 'http://moinmo.in/SecurityFixes'} | null | {'https://github.com/moinwiki/moin-1.9/commit/70955a8eae091cc88fd9a6e510177e70289ec024'} | {'https://github.com/moinwiki/moin-1.9/commit/70955a8eae091cc88fd9a6e510177e70289ec024'} |
PyPI | PYSEC-2021-828 | null | TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain values. 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-2021-41221', 'GHSA-cqv6-3phm-hcwx'} | 2021-12-09T06:35:44.302427Z | 2021-11-05T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cqv6-3phm-hcwx', 'https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6'} | null | {'https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6'} | {'https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6'} |
PyPI | PYSEC-2022-122 | null | Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would cause an integer overflow in `TfLiteIntArrayCreate`. The `TfLiteIntArrayGetSizeInBytes` returns an `int` instead of a `size_t. An attacker can control model inputs such that `computed_size` overflows the size of `int` datatype. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | {'CVE-2022-23558', 'GHSA-9gwq-6cwj-47h3'} | 2022-03-09T00:18:25.380350Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9gwq-6cwj-47h3', 'https://github.com/tensorflow/tensorflow/commit/a1e1511dde36b3f8aa27a6ec630838e7ea40e091', 'https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/c/common.c#L53-L60', 'https://github.com/tensorflow/tensorflow/blob/ca6f96b62ad84207fbec580404eaa7dd7403a550/tensorflow/lite/c/common.c#L24-L33'} | null | {'https://github.com/tensorflow/tensorflow/commit/a1e1511dde36b3f8aa27a6ec630838e7ea40e091'} | {'https://github.com/tensorflow/tensorflow/commit/a1e1511dde36b3f8aa27a6ec630838e7ea40e091'} |
PyPI | GHSA-2wmv-37vq-52g5 | FPE in `tf.raw_ops.UnravelIndex` | ### Impact
An attacker can cause denial of service in applications serving models using `tf.raw_ops.UnravelIndex` by triggering a division by 0:
```python
import tensorflow as tf
tf.raw_ops.UnravelIndex(indices=-1, dims=[1,0,2])
```
The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/unravel_index_op.cc#L36) does not check that the tensor subsumed by `dims` is not empty. Hence, if one element of `dims` is 0, the implementation does a division by 0.
### Patches
We have patched the issue in GitHub commit [a776040a5e7ebf76eeb7eb923bf1ae417dd4d233](https://github.com/tensorflow/tensorflow/commit/a776040a5e7ebf76eeb7eb923bf1ae417dd4d233).
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
### 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-2021-37668'} | 2022-03-03T05:14:06.445606Z | 2021-08-25T14:42:06Z | MODERATE | null | {'CWE-369'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2wmv-37vq-52g5', 'https://github.com/tensorflow/tensorflow/commit/a776040a5e7ebf76eeb7eb923bf1ae417dd4d233', 'https://nvd.nist.gov/vuln/detail/CVE-2021-37668'} | null | {'https://github.com/tensorflow/tensorflow/commit/a776040a5e7ebf76eeb7eb923bf1ae417dd4d233'} | {'https://github.com/tensorflow/tensorflow/commit/a776040a5e7ebf76eeb7eb923bf1ae417dd4d233'} |
PyPI | PYSEC-2021-594 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of SVDF in TFLite is [vulnerable to a null pointer error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/svdf.cc#L300-L313). The [`GetVariableInput` function](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L115-L119) can return a null pointer but `GetTensorData` assumes that the argument is always a valid tensor. Furthermore, because `GetVariableInput` calls [`GetMutableInput`](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/kernel_util.cc#L82-L90) which might return `nullptr`, the `tensor->is_variable` expression can also trigger a null pointer exception. We have patched the issue in GitHub commit 5b048e87e4e55990dae6b547add4dae59f4e1c76. 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-2021-37681', 'GHSA-7xwj-5r4v-429p'} | 2021-12-09T06:35:05.896757Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7xwj-5r4v-429p'} | null | {'https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76'} | {'https://github.com/tensorflow/tensorflow/commit/5b048e87e4e55990dae6b547add4dae59f4e1c76'} |
PyPI | PYSEC-2020-30 | null | A buffer overflow in the patching routine of bsdiff4 before 1.2.0 allows an attacker to write to heap memory (beyond allocated bounds) via a crafted patch file. | {'CVE-2020-15904'} | 2020-07-31T16:15:00Z | 2020-07-22T23:15:00Z | null | null | null | {'https://github.com/ilanschnell/bsdiff4/commit/49a4cee2feef7deaf9d89e5e793a8824930284d7', 'https://github.com/ilanschnell/bsdiff4/blob/master/CHANGELOG.txt'} | null | {'https://github.com/ilanschnell/bsdiff4/commit/49a4cee2feef7deaf9d89e5e793a8824930284d7'} | {'https://github.com/ilanschnell/bsdiff4/commit/49a4cee2feef7deaf9d89e5e793a8824930284d7'} |
PyPI | PYSEC-2013-29 | null | The Crypto.Random.atfork function in PyCrypto before 2.6.1 does not properly reseed the pseudo-random number generator (PRNG) before allowing a child process to access it, which makes it easier for context-dependent attackers to obtain sensitive information by leveraging a race condition in which a child process is created and accesses the PRNG within the same rate-limit period as another process. | {'CVE-2013-1445'} | 2021-08-27T03:22:16.634811Z | 2013-10-26T17:55:00Z | null | null | null | {'https://github.com/dlitz/pycrypto/commit/19dcf7b15d61b7dc1a125a367151de40df6ef175', 'http://www.debian.org/security/2013/dsa-2781', 'http://www.openwall.com/lists/oss-security/2013/10/17/3'} | null | {'https://github.com/dlitz/pycrypto/commit/19dcf7b15d61b7dc1a125a367151de40df6ef175'} | {'https://github.com/dlitz/pycrypto/commit/19dcf7b15d61b7dc1a125a367151de40df6ef175'} |
PyPI | GHSA-hhx9-p69v-cx2j | Authentication bypass in Apache Airflow | "The previous default setting for Airflow's Experimental API was to allow all API requests without authentication, but this poses security risks to users who miss this fact. From Airflow 1.10.11 the default has been changed to deny all requests by default and is documented at https://airflow.apache.org/docs/1.10.11/security.html#api-authentication. Note this change fixes it for new installs but existing users need to change their config to default `[api]auth_backend = airflow.api.auth.backend.deny_all` as mentioned in the Updating Guide: https://github.com/apache/airflow/blob/1.10.11/UPDATING.md#experimental-api-will-deny-all-request-by-default" | {'CVE-2020-13927'} | 2022-03-03T05:13:29.653716Z | 2021-04-30T17:34:13Z | CRITICAL | null | {'CWE-287'} | {'https://airflow.apache.org/docs/apache-airflow/1.10.11/security.html#api-authentication', 'http://packetstormsecurity.com/files/162908/Apache-Airflow-1.10.10-Remote-Code-Execution.html', 'https://github.com/apache/airflow/pull/9611/commits/c8053e166d45ad519c0a1cd4480e025a759c176e', 'https://nvd.nist.gov/vuln/detail/CVE-2020-13927', 'https://lists.apache.org/thread.html/r23a81b247aa346ff193670be565b2b8ea4b17ddbc7a35fc099c1aadd%40%3Cdev.airflow.apache.org%3E', 'https://github.com/apache/airflow/releases/tag/1.10.11'} | null | {'https://github.com/apache/airflow/pull/9611/commits/c8053e166d45ad519c0a1cd4480e025a759c176e'} | {'https://github.com/apache/airflow/pull/9611/commits/c8053e166d45ad519c0a1cd4480e025a759c176e'} |
PyPI | PYSEC-2021-717 | null | TensorFlow is an end-to-end open source platform for machine learning. TFlite graphs must not have loops between nodes. However, this condition was not checked and an attacker could craft models that would result in infinite loop during evaluation. In certain cases, the infinite loop would be replaced by stack overflow due to too many recursive calls. For example, the `While` implementation(https://github.com/tensorflow/tensorflow/blob/106d8f4fb89335a2c52d7c895b7a7485465ca8d9/tensorflow/lite/kernels/while.cc) could be tricked into a scneario where both the body and the loop subgraphs are the same. Evaluating one of the subgraphs means calling the `Eval` function for the other and this quickly exhaust all stack space. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. Please consult our security guide(https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. | {'CVE-2021-29591', 'GHSA-cwv3-863g-39vx'} | 2021-12-09T06:35:30.563708Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cwv3-863g-39vx', 'https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4', 'https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743'} | null | {'https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4', 'https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743'} | {'https://github.com/tensorflow/tensorflow/commit/c6173f5fe66cdbab74f4f869311fe6aae2ba35f4', 'https://github.com/tensorflow/tensorflow/commit/9c1dc920d8ffb4893d6c9d27d1f039607b326743'} |
PyPI | GHSA-4p4p-www8-8fv9 | Reference binding to null in `ParameterizedTruncatedNormal` | ### Impact
An attacker can trigger undefined behavior by binding to null pointer in `tf.raw_ops.ParameterizedTruncatedNormal`:
```python
import tensorflow as tf
shape = tf.constant([], shape=[0], dtype=tf.int32)
means = tf.constant((1), dtype=tf.float32)
stdevs = tf.constant((1), dtype=tf.float32)
minvals = tf.constant((1), dtype=tf.float32)
maxvals = tf.constant((1), dtype=tf.float32)
tf.raw_ops.ParameterizedTruncatedNormal(
shape=shape, means=means, stdevs=stdevs, minvals=minvals, maxvals=maxvals)
```
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`:
```cc
int32 num_batches = shape_tensor.flat<int32>()(0);
```
If `shape` argument is empty, then `shape_tensor.flat<T>()` is an empty array.
### Patches
We have patched the issue in GitHub commit [5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8](https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8).
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-2021-29568'} | 2022-03-03T05:12:41.657056Z | 2021-05-21T14:25:19Z | LOW | null | {'CWE-824'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29568', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4p4p-www8-8fv9', 'https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8'} | null | {'https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8'} | {'https://github.com/tensorflow/tensorflow/commit/5e52ef5a461570cfb68f3bdbbebfe972cb4e0fd8'} |
PyPI | PYSEC-2020-202 | null | Ansible before 1.5.5 constructs filenames containing user and password fields on the basis of deb lines in sources.list, which might allow local users to obtain sensitive credential information in opportunistic circumstances by leveraging existence of a file that uses the "deb http://user:pass@server:port/" format. | {'CVE-2014-4660'} | 2021-07-02T02:41:33.239912Z | 2020-02-20T03:15:00Z | null | null | null | {'https://github.com/ansible/ansible/commit/c4b5e46054c74176b2446c82d4df1a2610eddc08', 'https://www.openwall.com/lists/oss-security/2014/06/26/19', 'https://github.com/ansible/ansible/blob/release1.5.5/CHANGELOG.md', 'https://www.securityfocus.com/bid/68231', 'https://security-tracker.debian.org/tracker/CVE-2014-4660'} | null | {'https://github.com/ansible/ansible/commit/c4b5e46054c74176b2446c82d4df1a2610eddc08'} | {'https://github.com/ansible/ansible/commit/c4b5e46054c74176b2446c82d4df1a2610eddc08'} |
PyPI | PYSEC-2021-652 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263) does a division by a quantity that is controlled by the caller. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-4vf2-4xcg-65cx', 'CVE-2021-29526'} | 2021-12-09T06:35:19.249421Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/b12aa1d44352de21d1a6faaf04172d8c2508b42b', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4vf2-4xcg-65cx'} | null | {'https://github.com/tensorflow/tensorflow/commit/b12aa1d44352de21d1a6faaf04172d8c2508b42b'} | {'https://github.com/tensorflow/tensorflow/commit/b12aa1d44352de21d1a6faaf04172d8c2508b42b'} |
PyPI | PYSEC-2021-202 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.SparseFillEmptyRows`. This is because of missing validation(https://github.com/tensorflow/tensorflow/blob/fdc82089d206e281c628a93771336bf87863d5e8/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L230-L231) that was covered under a `TODO`. If the `dense_shape` tensor is empty, then `dense_shape_t.vec<>()` would cause a null pointer dereference in the implementation of the op. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-r6pg-pjwc-j585', 'CVE-2021-29565'} | 2021-08-27T03:22:32.984830Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/faa76f39014ed3b5e2c158593b1335522e573c7f', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6pg-pjwc-j585'} | null | {'https://github.com/tensorflow/tensorflow/commit/faa76f39014ed3b5e2c158593b1335522e573c7f'} | {'https://github.com/tensorflow/tensorflow/commit/faa76f39014ed3b5e2c158593b1335522e573c7f'} |
PyPI | GHSA-2ww3-fxvq-293j | Inefficient Regular Expression in nltk | nltk is contains an Inefficient Regular Expression and is vulnerable to regular expression denial of service attacks. | {'CVE-2021-3828'} | 2022-04-26T18:17:15.373864Z | 2021-09-29T17:14:53Z | HIGH | null | {'CWE-697', 'CWE-1333'} | {'https://github.com/nltk/nltk/pull/2816', 'https://nvd.nist.gov/vuln/detail/CVE-2021-3828', 'https://huntr.dev/bounties/d19aed43-75bc-4a03-91a0-4d0bb516bc32', 'https://github.com/nltk/nltk/commit/277711ab1dec729e626b27aab6fa35ea5efbd7e6', 'https://github.com/nltk/nltk'} | null | {'https://github.com/nltk/nltk/commit/277711ab1dec729e626b27aab6fa35ea5efbd7e6'} | {'https://github.com/nltk/nltk/commit/277711ab1dec729e626b27aab6fa35ea5efbd7e6'} |
PyPI | PYSEC-2021-486 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow in `tf.raw_ops.SparseSplit`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/699bff5d961f0abfde8fa3f876e6d241681fbef8/tensorflow/core/util/sparse/sparse_tensor.h#L528-L530) accesses an array element based on a user controlled offset. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-mqh2-9wrp-vx84', 'CVE-2021-29558'} | 2021-12-09T06:34:52.373382Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mqh2-9wrp-vx84'} | null | {'https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31'} | {'https://github.com/tensorflow/tensorflow/commit/8ba6fa29cd8bf9cef9b718dc31c78c73081f5b31'} |
PyPI | GHSA-m34j-p8rj-wjxq | Division by 0 in `QuantizedBiasAdd` | ### Impact
An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`:
```python
import tensorflow as tf
input_tensor = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8)
bias = tf.constant([], shape=[0], dtype=tf.quint8)
min_input = tf.constant(-10.0, dtype=tf.float32)
max_input = tf.constant(-10.0, dtype=tf.float32)
min_bias = tf.constant(-10.0, dtype=tf.float32)
max_bias = tf.constant(-10.0, dtype=tf.float32)
tf.raw_ops.QuantizedBiasAdd(input=input_tensor, bias=bias, min_input=min_input,
max_input=max_input, min_bias=min_bias,
max_bias=max_bias, out_type=tf.qint32)
```
This is because the [implementation of the Eigen kernel](https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero:
```cc
template <typename T1, typename T2, typename T3>
void QuantizedAddUsingEigen(const Eigen::ThreadPoolDevice& device,
const Tensor& input, float input_min,
float input_max, const Tensor& smaller_input,
float smaller_input_min, float smaller_input_max,
Tensor* output, float* output_min,
float* output_max) {
...
const int64 input_element_count = input.NumElements();
const int64 smaller_input_element_count = smaller_input.NumElements();
...
bcast[0] = input_element_count / smaller_input_element_count;
...
}
```
This integral division by 0 is undefined behavior.
### Patches
We have patched the issue in GitHub commit [67784700869470d65d5f2ef20aeb5e97c31673cb](https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb).
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-2021-29546'} | 2022-03-03T05:13:15.068960Z | 2021-05-21T14:23:28Z | LOW | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-29546', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxq', 'https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb'} | null | {'https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb'} | {'https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb'} |
PyPI | GHSA-fh37-cx83-q542 | Improper Authentication in Apache Airflow | The lineage endpoint of the deprecated Experimental API was not protected by authentication in Airflow 2.0.0. This allowed unauthenticated users to hit that endpoint. This is low-severity issue as the attacker needs to be aware of certain parameters to pass to that endpoint and even after can just get some metadata about a DAG and a Task. This issue only affects Apache Airflow 2.0.0. | {'CVE-2021-26697'} | 2022-03-03T05:12:19.674223Z | 2021-06-18T18:30:11Z | MODERATE | null | {'CWE-287', 'CWE-269'} | {'https://lists.apache.org/thread.html/re21fec81baea7a6d73b0b5d31efd07cc02c61f832e297f65bb19b519@%3Cdev.airflow.apache.org%3E', 'https://lists.apache.org/thread.html/re21fec81baea7a6d73b0b5d31efd07cc02c61f832e297f65bb19b519@%3Cusers.airflow.apache.org%3E', 'http://www.openwall.com/lists/oss-security/2021/02/17/2', 'https://nvd.nist.gov/vuln/detail/CVE-2021-26697', 'https://lists.apache.org/thread.html/re21fec81baea7a6d73b0b5d31efd07cc02c61f832e297f65bb19b519%40%3Cusers.airflow.apache.org%3E', 'https://github.com/apache/airflow/commit/21cedff205e7d62675949fda2aa4616d77232b76', 'https://lists.apache.org/thread.html/r36111262a59219a3e2704c71e97cf84937dae5ba7a1da99499e5d8f9@%3Cannounce.apache.org%3E'} | null | {'https://github.com/apache/airflow/commit/21cedff205e7d62675949fda2aa4616d77232b76'} | {'https://github.com/apache/airflow/commit/21cedff205e7d62675949fda2aa4616d77232b76'} |
PyPI | PYSEC-2021-469 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a dereference of a null pointer in `tf.raw_ops.StringNGrams`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L67-L74) does not fully validate the `data_splits` argument. This would result in `ngrams_data`(https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L106-L110) to be a null pointer when the output would be computed to have 0 or negative size. Later writes to the output tensor would then cause a null pointer dereference. 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-2021-29541', 'GHSA-xqfj-35wv-m3cr'} | 2021-12-09T06:34:49.747683Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xqfj-35wv-m3cr', 'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b'} | null | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b'} | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b'} |
PyPI | PYSEC-2021-193 | 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.Reverse`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/36229ea9e9451dac14a8b1f4711c435a1d84a594/tensorflow/core/kernels/reverse_op.cc#L75-L76) performs a division based on the first dimension of the tensor 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. | {'GHSA-fxqh-cfjm-fp93', 'CVE-2021-29556'} | 2021-08-27T03:22:31.368222Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/4071d8e2f6c45c1955a811fee757ca2adbe462c1', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxqh-cfjm-fp93'} | null | {'https://github.com/tensorflow/tensorflow/commit/4071d8e2f6c45c1955a811fee757ca2adbe462c1'} | {'https://github.com/tensorflow/tensorflow/commit/4071d8e2f6c45c1955a811fee757ca2adbe462c1'} |
PyPI | GHSA-xqfj-35wv-m3cr | Null pointer dereference in `StringNGrams` | ### Impact
An attacker can trigger a dereference of a null pointer in `tf.raw_ops.StringNGrams`:
```python
import tensorflow as tf
data=tf.constant([''] * 11, shape=[11], dtype=tf.string)
splits = [0]*115
splits.append(3)
data_splits=tf.constant(splits, shape=[116], dtype=tf.int64)
tf.raw_ops.StringNGrams(data=data, data_splits=data_splits, separator=b'Ss',
ngram_widths=[7,6,11],
left_pad='ABCDE', right_pad=b'ZYXWVU',
pad_width=50, preserve_short_sequences=True)
```
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L67-L74) does not fully validate the `data_splits` argument. This would result in [`ngrams_data`](https://github.com/tensorflow/tensorflow/blob/1cdd4da14282210cc759e468d9781741ac7d01bf/tensorflow/core/kernels/string_ngrams_op.cc#L106-L110) to be a null pointer when the output would be computed to have 0 or negative size.
Later writes to the output tensor would then cause a null pointer dereference.
### Patches
We have patched the issue in GitHub commit [ba424dd8f16f7110eea526a8086f1a155f14f22b](https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b).
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-2021-29541'} | 2022-03-03T05:13:08.273193Z | 2021-05-21T14:23:12Z | LOW | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xqfj-35wv-m3cr', 'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29541'} | null | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b'} | {'https://github.com/tensorflow/tensorflow/commit/ba424dd8f16f7110eea526a8086f1a155f14f22b'} |
PyPI | PYSEC-2022-175 | null | Insecure Temporary File in GitHub repository horovod/horovod prior to 0.24.0. | {'CVE-2022-0315', 'GHSA-47wv-vhj2-g66m'} | 2022-03-31T20:31:44.168006Z | 2022-03-24T09:15:00Z | null | null | null | {'https://huntr.dev/bounties/7e50397b-dd63-4bb5-b56d-704094a7da45', 'https://github.com/advisories/GHSA-47wv-vhj2-g66m', 'https://github.com/horovod/horovod/commit/b96ecae4dc69fc0a83c7c2d3f1dde600c20a1b41'} | null | {'https://github.com/horovod/horovod/commit/b96ecae4dc69fc0a83c7c2d3f1dde600c20a1b41'} | {'https://github.com/horovod/horovod/commit/b96ecae4dc69fc0a83c7c2d3f1dde600c20a1b41'} |
PyPI | PYSEC-2020-310 | null | In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the implementation of `SparseFillEmptyRowsGrad` uses a double indexing pattern. It is possible for `reverse_index_map(i)` to be an index outside of bounds of `grad_values`, thus resulting in a heap buffer overflow. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. | {'GHSA-63xm-rx5p-xvqr', 'CVE-2020-15195'} | 2021-12-09T06:35:12.907152Z | 2020-09-25T19:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-63xm-rx5p-xvqr', 'https://github.com/tensorflow/tensorflow/commit/390611e0d45c5793c7066110af37c8514e6a6c54', 'http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html', 'https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1'} | null | {'https://github.com/tensorflow/tensorflow/commit/390611e0d45c5793c7066110af37c8514e6a6c54'} | {'https://github.com/tensorflow/tensorflow/commit/390611e0d45c5793c7066110af37c8514e6a6c54'} |
PyPI | PYSEC-2021-310 | 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. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/lite/kernels/internal/optimized/optimized_ops.h#L268-L285) unconditionally dereferences a pointer. We have patched the issue in GitHub commit 15691e456c7dc9bd6be203b09765b063bf4a380c. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. | {'GHSA-vcjj-9vg7-vf68', 'CVE-2021-37688'} | 2021-08-27T03:22:47.519318Z | 2021-08-12T22:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vcjj-9vg7-vf68', 'https://github.com/tensorflow/tensorflow/commit/15691e456c7dc9bd6be203b09765b063bf4a380c'} | null | {'https://github.com/tensorflow/tensorflow/commit/15691e456c7dc9bd6be203b09765b063bf4a380c'} | {'https://github.com/tensorflow/tensorflow/commit/15691e456c7dc9bd6be203b09765b063bf4a380c'} |
PyPI | PYSEC-2021-740 | null | TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.io.decode_raw` produces incorrect results and crashes the Python interpreter when combining `fixed_length` and wider datatypes. The implementation of the padded version(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc) is buggy due to a confusion about pointer arithmetic rules. First, the code computes(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L61) the width of each output element by dividing the `fixed_length` value to the size of the type argument. The `fixed_length` argument is also used to determine the size needed for the output tensor(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L63-L79). This is followed by reencoding code(https://github.com/tensorflow/tensorflow/blob/1d8903e5b167ed0432077a3db6e462daf781d1fe/tensorflow/core/kernels/decode_padded_raw_op.cc#L85-L94). The erroneous code is the last line above: it is moving the `out_data` pointer by `fixed_length * sizeof(T)` bytes whereas it only copied at most `fixed_length` bytes from the input. This results in parts of the input not being decoded into the output. Furthermore, because the pointer advance is far wider than desired, this quickly leads to writing to outside the bounds of the backing data. This OOB write leads to interpreter crash in the reproducer mentioned here, but more severe attacks can be mounted too, given that this gadget allows writing to periodically placed locations in memory. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-8pmx-p244-g88h', 'CVE-2021-29614'} | 2021-12-09T06:35:34.396130Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8pmx-p244-g88h'} | null | {'https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d'} | {'https://github.com/tensorflow/tensorflow/commit/698e01511f62a3c185754db78ebce0eee1f0184d'} |
PyPI | GHSA-374m-jm66-3vj8 | Heap OOB in `SparseBinCount` | ### Impact
The [implementation](https://github.com/tensorflow/tensorflow/blob/e71b86d47f8bc1816bf54d7bddc4170e47670b97/tensorflow/core/kernels/bincount_op.cc#L353-L417) of `SparseBinCount` is vulnerable to a heap OOB:
```python
import tensorflow as tf
tf.raw_ops.SparseBincount(
indices=[[0],[1],[2]]
values=[0,-10000000]
dense_shape=[1,1]
size=[1]
weights=[3,2,1]
binary_output=False)
```
This is because of missing validation between the elements of the `values` argument and the shape of the sparse output:
```cc
for (int64_t i = 0; i < indices_mat.dimension(0); ++i) {
const int64_t batch = indices_mat(i, 0);
const Tidx bin = values(i);
...
out(batch, bin) = ...;
}
```
### Patches
We have patched the issue in GitHub commit [f410212e373eb2aec4c9e60bf3702eba99a38aba](https://github.com/tensorflow/tensorflow/commit/f410212e373eb2aec4c9e60bf3702eba99a38aba).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-41226'} | 2022-03-03T05:14:12.215771Z | 2021-11-10T18:41:47Z | HIGH | null | {'CWE-125'} | {'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/commit/f410212e373eb2aec4c9e60bf3702eba99a38aba', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-374m-jm66-3vj8', 'https://nvd.nist.gov/vuln/detail/CVE-2021-41226'} | null | {'https://github.com/tensorflow/tensorflow/commit/f410212e373eb2aec4c9e60bf3702eba99a38aba'} | {'https://github.com/tensorflow/tensorflow/commit/f410212e373eb2aec4c9e60bf3702eba99a38aba'} |
PyPI | GHSA-gfp2-w5jm-955q | OMERO.web exposes some unnecessary session information in the page | ### Background
OMERO.web loads various information about the current user such as their id, name and the groups they are in, and these are available on the main webclient pages. Some additional information being loaded is not used by the webclient and is being removed in this release.
### Impact
OMERO.web before 5.9.0
### Patches
5.9.0
### Workarounds
No workaround
### References
### For more information
If you have any questions or comments about this advisory:
* Open an issue in [omero-web](https://github.com/ome/omero-web)
* Email us at [security](mailto:security@openmicroscopy.org.uk) | {'CVE-2021-21376'} | 2022-03-03T05:13:29.883008Z | 2021-03-23T15:26:34Z | MODERATE | null | {'CWE-200'} | {'https://github.com/ome/omero-web/commit/952f8e5d28532fbb14fb665982211329d137908c', 'https://www.openmicroscopy.org/security/advisories/2021-SV1/', 'https://pypi.org/project/omero-web/', 'https://github.com/ome/omero-web/security/advisories/GHSA-gfp2-w5jm-955q', 'https://github.com/ome/omero-web/blob/master/CHANGELOG.md#590-march-2021', 'https://nvd.nist.gov/vuln/detail/CVE-2021-21376'} | null | {'https://github.com/ome/omero-web/commit/952f8e5d28532fbb14fb665982211329d137908c'} | {'https://github.com/ome/omero-web/commit/952f8e5d28532fbb14fb665982211329d137908c'} |
PyPI | PYSEC-2021-255 | null | TensorFlow is an end-to-end open source platform for machine learning. Passing a complex argument to `tf.transpose` at the same time as passing `conjugate=True` argument results in a crash. 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-xqfj-cr6q-pc8w', 'CVE-2021-29618'} | 2021-08-27T03:22:42.358462Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/issues/46973', 'https://github.com/tensorflow/tensorflow/commit/1dc6a7ce6e0b3e27a7ae650bfc05b195ca793f88', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xqfj-cr6q-pc8w', 'https://github.com/tensorflow/issues/42105'} | null | {'https://github.com/tensorflow/tensorflow/commit/1dc6a7ce6e0b3e27a7ae650bfc05b195ca793f88'} | {'https://github.com/tensorflow/tensorflow/commit/1dc6a7ce6e0b3e27a7ae650bfc05b195ca793f88'} |
PyPI | GHSA-9crf-c6qr-r273 | Integer division by 0 in `tf.raw_ops.AllToAll` | ### Impact
The [shape inference code for `AllToAll`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/tpu_cross_replica_ops.cc#L25-L74) can be made to execute a division by 0:
```python
import tensorflow as tf
@tf.function
def func():
return tf.raw_ops.AllToAll(
input=[0.0, 0.1652, 0.6543],
group_assignment=[1, -1],
concat_dimension=0,
split_dimension=0,
split_count=0)
func()
```
This occurs whenever the `split_count` argument is 0:
```cc
TF_RETURN_IF_ERROR(c->GetAttr("split_count", &split_count));
...
for (int32_t i = 0; i < rank; ++i) {
...
dims[i] = c->MakeDim(c->Value(dims[i]) / split_count);
...
}
```
### Patches
We have patched the issue in GitHub commit [a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc](https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
### Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360. | {'CVE-2021-41218'} | 2022-03-03T05:13:16.433441Z | 2021-11-10T18:52:24Z | MODERATE | null | {'CWE-369'} | {'https://nvd.nist.gov/vuln/detail/CVE-2021-41218', 'https://github.com/tensorflow/tensorflow', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9crf-c6qr-r273', 'https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc'} | null | {'https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc'} | {'https://github.com/tensorflow/tensorflow/commit/a8ad3e5e79c75f36edb81e0ba3f3c0c5442aeddc'} |
PyPI | PYSEC-2021-605 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions under certain conditions, Go code can trigger a segfault in string deallocation. For string tensors, `C.TF_TString_Dealloc` is called during garbage collection within a finalizer function. However, tensor structure isn't checked until encoding to avoid a performance penalty. The current method for dealloc assumes that encoding succeeded, but segfaults when a string tensor is garbage collected whose encoding failed (e.g., due to mismatched dimensions). To fix this, the call to set the finalizer function is deferred until `NewTensor` returns and, if encoding failed for a string tensor, deallocs are determined based on bytes written. We have patched the issue in GitHub commit 8721ba96e5760c229217b594f6d2ba332beedf22. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, which is the other affected version. | {'CVE-2021-37692', 'GHSA-cmgw-8vpc-rc59'} | 2021-12-09T06:35:06.839358Z | 2021-08-12T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cmgw-8vpc-rc59', 'https://github.com/tensorflow/tensorflow/commit/8721ba96e5760c229217b594f6d2ba332beedf22', 'https://github.com/tensorflow/tensorflow/pull/50508'} | null | {'https://github.com/tensorflow/tensorflow/commit/8721ba96e5760c229217b594f6d2ba332beedf22'} | {'https://github.com/tensorflow/tensorflow/commit/8721ba96e5760c229217b594f6d2ba332beedf22'} |
PyPI | PYSEC-2020-255 | null | In affected versions of TensorFlow the tf.raw_ops.ImmutableConst operation returns a constant tensor created from a memory mapped file which is assumed immutable. However, if the type of the tensor is not an integral type, the operation crashes the Python interpreter as it tries to write to the memory area. If the file is too small, TensorFlow properly returns an error as the memory area has fewer bytes than what is needed for the tensor it creates. However, as soon as there are enough bytes, the above snippet causes a segmentation fault. This is because the allocator used to return the buffer data is not marked as returning an opaque handle since the needed virtual method is not overridden. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0. | {'CVE-2020-26268', 'GHSA-hhvc-g5hv-48c6'} | 2021-08-27T03:22:22.907995Z | 2020-12-10T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hhvc-g5hv-48c6', 'https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7'} | null | {'https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7'} | {'https://github.com/tensorflow/tensorflow/commit/c1e1fc899ad5f8c725dcbb6470069890b5060bc7'} |
PyPI | PYSEC-2017-102 | null | Radicale before 1.1.2 and 2.x before 2.0.0rc2 is prone to timing oracles and simple brute-force attacks when using the htpasswd authentication method. | {'CVE-2017-8342'} | 2021-12-14T08:18:58.722697Z | 2017-04-30T15:59:00Z | null | null | null | {'https://pypi.org/project/radicale', 'https://bugs.debian.org/861514', 'https://nvd.nist.gov/vuln/detail/CVE-2017-8342', 'https://github.com/Kozea/Radicale/commit/059ba8dec1f22ccbeab837e288b3833a099cee2d', 'https://github.com/Kozea/Radicale/blob/1.1.2/NEWS.rst', 'https://lists.debian.org/debian-lts-announce/2020/04/msg00019.html', 'https://github.com/Kozea/Radicale/commit/190b1dd795f0c552a4992445a231da760211183b'} | null | {'https://github.com/Kozea/Radicale/commit/059ba8dec1f22ccbeab837e288b3833a099cee2d', 'https://github.com/Kozea/Radicale/commit/190b1dd795f0c552a4992445a231da760211183b'} | {'https://github.com/Kozea/Radicale/commit/059ba8dec1f22ccbeab837e288b3833a099cee2d', 'https://github.com/Kozea/Radicale/commit/190b1dd795f0c552a4992445a231da760211183b'} |
PyPI | GHSA-v542-8q9x-cffc | Exposure of Sensitive Information to an Unauthorized Actor | Django Channels 3.x before 3.0.3 allows remote attackers to obtain sensitive information from a different request scope. The legacy channels.http.AsgiHandler class, used for handling HTTP type requests in an ASGI environment prior to Django 3.0, did not correctly separate request scopes in Channels 3.0. In many cases this would result in a crash but, with correct timing, responses could be sent to the wrong client, resulting in potential leakage of session identifiers and other sensitive data. Note that this affects only the legacy Channels provided class, and not Django's similar ASGIHandler, available from Django 3.0. | {'CVE-2020-35681'} | 2022-03-03T05:13:58.617865Z | 2021-03-19T21:29:02Z | HIGH | null | {'CWE-200'} | {'https://github.com/django/channels/releases', 'https://channels.readthedocs.io/en/stable/releases/index.html', 'https://github.com/django/channels/commit/e85874d9630474986a6937430eac52db79a2a022', 'https://nvd.nist.gov/vuln/detail/CVE-2020-35681', 'https://channels.readthedocs.io/en/stable/releases/3.0.3.html'} | null | {'https://github.com/django/channels/commit/e85874d9630474986a6937430eac52db79a2a022'} | {'https://github.com/django/channels/commit/e85874d9630474986a6937430eac52db79a2a022'} |
PyPI | GHSA-9px9-73fg-3fqp | Null pointer dereference in Grappler's `IsConstant` | ### Impact
Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a `SavedModel` file (fixing the first one would trigger the same dereference in the second place):
First, during [constant folding](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L3466-L3497), the `GraphDef` might not have the required nodes for the binary operation:
```cc
NodeDef* mul_left_child = node_map_->GetNode(node->input(0));
NodeDef* mul_right_child = node_map_->GetNode(node->input(1));
// One child must be constant, and the second must be Conv op.
const bool left_child_is_constant = IsReallyConstant(*mul_left_child);
const bool right_child_is_constant = IsReallyConstant(*mul_right_child);
```
If a node is missing, the correposning `mul_*child` would be null, and the dereference in the subsequent line would be incorrect.
We have a similar issue during [`IsIdentityConsumingSwitch`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/mutable_graph_view.cc#L59-L74):
```cc
NodeDef* input_node = graph.GetNode(tensor_id.node());
return IsSwitch(*input_node);
```
### Patches
We have patched the issue in GitHub commits [0a365c029e437be0349c31f8d4c9926b69fa3fa1](https://github.com/tensorflow/tensorflow/commit/0a365c029e437be0349c31f8d4c9926b69fa3fa1) and [045deec1cbdebb27d817008ad5df94d96a08b1bf](https://github.com/tensorflow/tensorflow/commit/045deec1cbdebb27d817008ad5df94d96a08b1bf).
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-2022-23589'} | 2022-03-03T05:13:46.368917Z | 2022-02-09T23:29:14Z | MODERATE | null | {'CWE-476'} | {'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/mutable_graph_view.cc#L59-L74', 'https://github.com/tensorflow/tensorflow/', 'https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/optimizers/constant_folding.cc#L3466-L3497', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9px9-73fg-3fqp', 'https://github.com/tensorflow/tensorflow/commit/045deec1cbdebb27d817008ad5df94d96a08b1bf', 'https://nvd.nist.gov/vuln/detail/CVE-2022-23589', 'https://github.com/tensorflow/tensorflow/commit/0a365c029e437be0349c31f8d4c9926b69fa3fa1'} | null | {'https://github.com/tensorflow/tensorflow/commit/045deec1cbdebb27d817008ad5df94d96a08b1bf', 'https://github.com/tensorflow/tensorflow/commit/0a365c029e437be0349c31f8d4c9926b69fa3fa1'} | {'https://github.com/tensorflow/tensorflow/commit/045deec1cbdebb27d817008ad5df94d96a08b1bf', 'https://github.com/tensorflow/tensorflow/commit/0a365c029e437be0349c31f8d4c9926b69fa3fa1'} |
PyPI | GHSA-qw5h-7f53-xrp6 | Stack overflow in `ParseAttrValue` with nested tensors | ### Impact
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.
### Patches
We have patched the issue in GitHub commit [e07e1c3d26492c06f078c7e5bf2d138043e199c1](https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1).
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. | {'CVE-2021-29615'} | 2022-03-03T05:13:40.155128Z | 2021-05-21T14:28:45Z | LOW | null | {'CWE-674'} | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qw5h-7f53-xrp6', 'https://nvd.nist.gov/vuln/detail/CVE-2021-29615', 'https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1'} | null | {'https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1'} | {'https://github.com/tensorflow/tensorflow/commit/e07e1c3d26492c06f078c7e5bf2d138043e199c1'} |
PyPI | PYSEC-2021-672 | null | TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'CVE-2021-29546', 'GHSA-m34j-p8rj-wjxq'} | 2021-12-09T06:35:22.808181Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxq', 'https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb'} | null | {'https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb'} | {'https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb'} |
PyPI | PYSEC-2021-222 | null | TensorFlow is an end-to-end open source platform for machine learning. The TFLite computation for size of output after padding, `ComputeOutSize`(https://github.com/tensorflow/tensorflow/blob/0c9692ae7b1671c983569e5d3de5565843d500cf/tensorflow/lite/kernels/padding.h#L43-L55), does not check that the `stride` argument is not 0 before doing the division. Users can craft special models such that `ComputeOutSize` is called with `stride` set to 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range. | {'GHSA-mv78-g7wq-mhp4', 'CVE-2021-29585'} | 2021-08-27T03:22:36.517027Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/commit/49847ae69a4e1a97ae7f2db5e217c77721e37948', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mv78-g7wq-mhp4'} | null | {'https://github.com/tensorflow/tensorflow/commit/49847ae69a4e1a97ae7f2db5e217c77721e37948'} | {'https://github.com/tensorflow/tensorflow/commit/49847ae69a4e1a97ae7f2db5e217c77721e37948'} |
PyPI | PYSEC-2021-737 | null | TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseReshape` results in a denial of service based on a `CHECK`-failure. The implementation(https://github.com/tensorflow/tensorflow/blob/e87b51ce05c3eb172065a6ea5f48415854223285/tensorflow/core/kernels/sparse_reshape_op.cc#L40) has no validation that the input arguments specify a valid sparse tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are the only affected versions. | {'GHSA-9rpc-5v9q-5r7f', 'CVE-2021-29611'} | 2021-12-09T06:35:33.881511Z | 2021-05-14T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9rpc-5v9q-5r7f', 'https://github.com/tensorflow/tensorflow/commit/1d04d7d93f4ed3854abf75d6b712d72c3f70d6b6'} | null | {'https://github.com/tensorflow/tensorflow/commit/1d04d7d93f4ed3854abf75d6b712d72c3f70d6b6'} | {'https://github.com/tensorflow/tensorflow/commit/1d04d7d93f4ed3854abf75d6b712d72c3f70d6b6'} |
PyPI | PYSEC-2022-102 | null | Tensorflow is an Open Source Machine Learning Framework. The `simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. The fix will be included in TensorFlow 2.8.0. This is the only affected version. | {'GHSA-gwcx-jrx4-92w2', 'CVE-2022-23593'} | 2022-03-09T00:17:36.413722Z | 2022-02-04T23:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gwcx-jrx4-92w2', 'https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/mlir/tfrt/jit/transforms/tf_cpurt_symbolic_shape_optimization.cc#L149-L205', 'https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a'} | null | {'https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a'} | {'https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a'} |
PyPI | PYSEC-2016-8 | null | Pillow before 3.3.2 allows context-dependent attackers to obtain sensitive information by using the "crafted image file" approach, related to an "Integer Overflow" issue affecting the Image.core.map_buffer in map.c component. | {'GHSA-rwr3-c2q8-gm56', 'CVE-2016-9189'} | 2021-07-05T00:01:24.104078Z | 2016-11-04T10:59:00Z | null | null | null | {'http://pillow.readthedocs.io/en/3.4.x/releasenotes/3.3.2.html', 'http://www.securityfocus.com/bid/94234', 'https://security.gentoo.org/glsa/201612-52', 'https://github.com/python-pillow/Pillow/issues/2105', 'http://www.debian.org/security/2016/dsa-3710', 'https://github.com/advisories/GHSA-rwr3-c2q8-gm56', 'https://github.com/python-pillow/Pillow/pull/2146/commits/c50ebe6459a131a1ea8ca531f10da616d3ceaa0f'} | null | {'https://github.com/python-pillow/Pillow/pull/2146/commits/c50ebe6459a131a1ea8ca531f10da616d3ceaa0f'} | {'https://github.com/python-pillow/Pillow/pull/2146/commits/c50ebe6459a131a1ea8ca531f10da616d3ceaa0f'} |
PyPI | PYSEC-2021-808 | null | TensorFlow is an open source platform for machine learning. In affected versions if `tf.summary.create_file_writer` is called with non-scalar arguments code crashes due to a `CHECK`-fail. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range. | {'GHSA-gh8h-7j2j-qv4f', 'CVE-2021-41200'} | 2021-12-09T06:35:41.245758Z | 2021-11-05T20:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/issues/46909', 'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gh8h-7j2j-qv4f', 'https://github.com/tensorflow/tensorflow/commit/874bda09e6702cd50bac90b453b50bcc65b2769e'} | null | {'https://github.com/tensorflow/tensorflow/commit/874bda09e6702cd50bac90b453b50bcc65b2769e'} | {'https://github.com/tensorflow/tensorflow/commit/874bda09e6702cd50bac90b453b50bcc65b2769e'} |
PyPI | PYSEC-2021-275 | null | TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a crash via a floating point exception in `tf.raw_ops.ResourceGather`. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L725-L731) computes the value of a value, `batch_size`, and then divides by it without checking that this value is not 0. We have patched the issue in GitHub commit ac117ee8a8ea57b73d34665cdf00ef3303bc0b11. 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-qjj8-32p7-h289', 'CVE-2021-37653'} | 2021-08-27T03:22:44.260808Z | 2021-08-12T18:15:00Z | null | null | null | {'https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qjj8-32p7-h289', 'https://github.com/tensorflow/tensorflow/commit/ac117ee8a8ea57b73d34665cdf00ef3303bc0b11'} | null | {'https://github.com/tensorflow/tensorflow/commit/ac117ee8a8ea57b73d34665cdf00ef3303bc0b11'} | {'https://github.com/tensorflow/tensorflow/commit/ac117ee8a8ea57b73d34665cdf00ef3303bc0b11'} |
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