Vulnerability Details CVE-2022-35973
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.
Exploit prediction scoring system (EPSS) score
EPSS Score 0.002
EPSS Ranking 41.6%
CVSS Severity
CVSS v3 Score 5.9
References
- https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v
- https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v
Products affected by CVE-2022-35973
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cpe:2.3:a:google:tensorflow:2.10
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cpe:2.3:a:google:tensorflow:2.7.0
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cpe:2.3:a:google:tensorflow:2.7.1
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cpe:2.3:a:google:tensorflow:2.8.0
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cpe:2.3:a:google:tensorflow:2.9.0