CVE-2022-35973

Segfault in `QuantizedMatMul` in TensorFlow

Description

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.

Category

5.9
CVSS
Severity: Medium
CVSS 3.1 •
EPSS 0.15%
Third-Party Advisory github.com Third-Party Advisory github.com
Affected: tensorflow tensorflow
Published at:
Updated at:

References

Link Tags
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v third party advisory patch
https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48 third party advisory patch

Frequently Asked Questions

What is the severity of CVE-2022-35973?
CVE-2022-35973 has been scored as a medium severity vulnerability.
How to fix CVE-2022-35973?
To fix CVE-2022-35973, make sure you are using an up-to-date version of the affected component(s) by checking the vendor release notes. As for now, there are no other specific guidelines available.
Is CVE-2022-35973 being actively exploited in the wild?
As for now, there are no information to confirm that CVE-2022-35973 is being actively exploited. According to its EPSS score, there is a ~0% probability that this vulnerability will be exploited by malicious actors in the next 30 days.
What software or system is affected by CVE-2022-35973?
CVE-2022-35973 affects tensorflow tensorflow.
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