Vulnerability · Published Sep 16, 2022 · Assigned by GitHub_M
CVE-2022-35973Segfault in `QuantizedMatMul` in TensorFlow
Medium 5.9
In plain English
A medium-severity improper input validation in tensorflow from tensorflow. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.5% (higher than 44% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.
Official 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.
Affected packages & fixed versions
| Ecosystem | Package | Fixed in | Advisory |
|---|---|---|---|
| PyPI | tensorflow | 2.7.2, 2.8.1, 2.9.1 | PYSEC-2026-3119 |
| PyPI | tensorflow | 2.7.2 | GHSA-689c-r7h2-fv9v |
| PyPI | tensorflow | 2.8.1 | GHSA-689c-r7h2-fv9v |
| PyPI | tensorflow | 2.9.1 | GHSA-689c-r7h2-fv9v |
| PyPI | tensorflow-cpu | 2.8.1 | GHSA-689c-r7h2-fv9v |
| PyPI | tensorflow-cpu | 2.7.2, 2.8.1, 2.9.1 | PYSEC-2026-3285 |
| PyPI | tensorflow-cpu | 2.7.2 | GHSA-689c-r7h2-fv9v |
| PyPI | tensorflow-cpu | 2.9.1 | GHSA-689c-r7h2-fv9v |
| PyPI | tensorflow-gpu | 2.7.2, 2.8.1, 2.9.1 | PYSEC-2026-959 |
| PyPI | tensorflow-gpu | 2.7.2 | GHSA-689c-r7h2-fv9v |
| PyPI | tensorflow-gpu | 2.8.1 | GHSA-689c-r7h2-fv9v |
| PyPI | tensorflow-gpu | 2.9.1 | GHSA-689c-r7h2-fv9v |
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| tensorflow | tensorflow | < 2.7.2>= 2.8.0, < 2.8.1>= 2.9.0, < 2.9.1 |
Weakness: CWE-20 · Vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H