CVE-2022-35973

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Summary

CVECVE-2022-35973
StatePUBLIC
Assigner[email protected]
Source PriorityCVE Program / NVD first with legacy fallback
Published2022-09-16 21:15:00 UTC
Updated2022-09-20 19:12:00 UTC
DescriptionTensorFlow 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.

Risk And Classification

Problem Types: NVD-CWE-noinfo

NVD Known Affected Configurations (CPE 2.3)

TypeVendorProductVersionUpdateEditionLanguage
Application Google Tensorflow All All All All
Application Google Tensorflow 2.10 rc0 All All
Application Google Tensorflow 2.10 rc1 All All
Application Google Tensorflow 2.10 rc2 All All
Application Google Tensorflow 2.10 rc3 All All

References

ReferenceSourceLinkTags
Fix tf.raw_ops. QuantizedMatMul vulnerability from non scalar min/max… · tensorflow/tensorflow@aca766a · GitHub MISC github.com
Segfault in `QuantizedMatMul` · Advisory · tensorflow/tensorflow · GitHub CONFIRM github.com
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NVD vulnerability detail NVD nvd.nist.gov canonical, analysis

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