Vulnerabilities > CVE-2022-35973 - Unspecified vulnerability in Google Tensorflow
Attack vector
NETWORK Attack complexity
LOW Privileges required
NONE Confidentiality impact
NONE Integrity impact
NONE Availability impact
HIGH Summary
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.
Vulnerable Configurations
| Part | Description | Count |
|---|---|---|
| Application | 17 |
References
- https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48
- https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v