CVE-2022-35973

Advisory

TensorFlow 2.7.4, 2.8.3 and 2.9.2 include a fix for CVE-2022-35973: Segfault in 'QuantizedMatMul'.
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v

Affected package

Affected versions

Fixed versions

Vulnerability changelog

TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue. See CVE-2022-35973.


CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v
MISC:https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48: https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48

Resources

• https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-35973
• https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v