medium
6.6
CWE
416
Advisory Published
Advisory Published
Updated

CVE-2021-37690: Use after free and segfault in shape inference functions in TensorFlow

First published: Thu Aug 12 2021(Updated: )

### Impact When running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. ### Patches We have patched the issue in GitHub commit [ee119d4a498979525046fba1c3dd3f13a039fbb1](https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

Credit: security-advisories@github.com security-advisories@github.com

Affected SoftwareAffected VersionHow to fix
Google TensorFlow>=2.3.0<2.3.4
Google TensorFlow>=2.4.0<2.4.3
Google TensorFlow=2.5.0
Google TensorFlow=2.6.0-rc0
Google TensorFlow=2.6.0-rc1
Google TensorFlow=2.6.0-rc2
pip/tensorflow-gpu=2.5.0
2.5.1
pip/tensorflow-gpu>=2.4.0<2.4.3
2.4.3
pip/tensorflow-gpu<2.3.4
2.3.4
pip/tensorflow-cpu=2.5.0
2.5.1
pip/tensorflow-cpu>=2.4.0<2.4.3
2.4.3
pip/tensorflow-cpu<2.3.4
2.3.4
pip/tensorflow=2.5.0
2.5.1
pip/tensorflow>=2.4.0<2.4.3
2.4.3
pip/tensorflow<2.3.4
2.3.4

Remedy

https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1

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Reference Links

Frequently Asked Questions

  • What is the severity of CVE-2021-37690?

    CVE-2021-37690 has been classified with a medium severity level due to its potential impact on data integrity.

  • How do I fix CVE-2021-37690?

    To remediate CVE-2021-37690, upgrade TensorFlow to version 2.5.1 or later, or use versions 2.4.3 and 2.3.4 as appropriate.

  • What versions of TensorFlow are affected by CVE-2021-37690?

    CVE-2021-37690 affects TensorFlow versions from 2.3.0 up to and including 2.6.0-rc2.

  • What is the nature of the vulnerability in CVE-2021-37690?

    CVE-2021-37690 relates to improper handling of shapes in certain shape functions which can lead to memory issues.

  • Is CVE-2021-37690 a remote code execution vulnerability?

    CVE-2021-37690 is not classified as a remote code execution vulnerability, but it may affect the stability of the application.

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