Headline
GHSA-5889-7v45-q28m: Incomplete validation in signal ops leads to crashes
Impact
The tf.compat.v1.signal.rfft2d and tf.compat.v1.signal.rfft3d lack input validation and under certain condition can result in crashes (due to CHECK-failures).
Patches
We have patched the issue in GitHub commit 0a8a781e597b18ead006d19b7d23d0a369e9ad73 (merging GitHub PR #55274).
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported externally via a GitHub issue.
Package
pip tensorflow (pip )
Affected versions
< 2.6.4
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
Patched versions
2.6.4
2.7.2
2.8.1
Package
pip tensorflow-cpu (pip )
Affected versions
< 2.6.4
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
Patched versions
2.6.4
2.7.2
2.8.1
Package
pip tensorflow-gpu (pip )
Affected versions
< 2.6.4
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
Patched versions
2.6.4
2.7.2
2.8.1
Description
Impact
The tf.compat.v1.signal.rfft2d and tf.compat.v1.signal.rfft3d lack input validation and under certain condition can result in crashes (due to CHECK-failures).
Patches
We have patched the issue in GitHub commit 0a8a781e597b18ead006d19b7d23d0a369e9ad73 (merging GitHub PR #55274).
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported externally via a GitHub issue.
References
- GHSA-5889-7v45-q28m
- https://nvd.nist.gov/vuln/detail/CVE-2022-29213
- tensorflow/tensorflow#55263
- tensorflow/tensorflow#55274
- tensorflow/tensorflow@0a8a781
- https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4
- https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2
- https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1
- https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0
mihaimaruseac published the maintainer security advisory
May 17, 2022
Related news
The Western Digital My Cloud Web App [https://os5.mycloud.com/] uses a weak SSLContext when attempting to configure port forwarding rules. This was enabled to maintain compatibility with old or outdated home routers. By using an "SSL" context instead of "TLS" or specifying stronger validation, deprecated or insecure protocols are permitted. As a result, a local user with no privileges can exploit this vulnerability and jeopardize the integrity, confidentiality and authenticity of information transmitted. The scope of impact cannot extend to other components and no user input is required to exploit this vulnerability.
Implemented protections on AWS credentials that were not properly protected.
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the `tf.compat.v1.signal.rfft2d` and `tf.compat.v1.signal.rfft3d` lack input validation and under certain condition can result in crashes (due to `CHECK`-failures). Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.