CVE-2022-35973
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.
Does this matter?
High impact if exploited, but EPSS currently rates exploitation as unlikely (0.45%). Schedule it in the normal patch cycle and watch for a rise in EPSS or a public exploit.
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.
- CVSS 3.1
- 7.5 HIGHCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
- EPSS
- 0.45% probability · 38th percentile
- CISA KEV
- Not listed
- Weakness
- CWE-20
- Affected
- google/tensorflow
- Source
- security-advisories@github.com
References
- https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9vPatch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48Patch, Third Party Advisory
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9vPatch, Third Party Advisory
Source: NVD record, EPSS from FIRST.org, KEV from CISA. Refreshed daily.