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CVE-2022-35974 Detail

Description

TensorFlow is an open source platform for machine learning. If `QuantizeDownAndShrinkRange` is given nonscalar inputs for `input_min` or `input_max`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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.


Metrics

NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 4.0 Severity and Vector Strings:

NIST CVSS score
NIST: NVD
N/A
NVD assessment not yet provided.

References to Advisories, Solutions, and Tools

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Hyperlink Resource
https://github.com/tensorflow/tensorflow/commit/73ad1815ebcfeb7c051f9c2f7ab5024380ca8613 Patch  Third Party Advisory 
https://github.com/tensorflow/tensorflow/commit/73ad1815ebcfeb7c051f9c2f7ab5024380ca8613 Patch  Third Party Advisory 
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vgvh-2pf4-jr2x Patch  Third Party Advisory 
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vgvh-2pf4-jr2x Patch  Third Party Advisory 

Weakness Enumeration

CWE-ID CWE Name Source
NVD-CWE-noinfo Insufficient Information cwe source acceptance level NIST  
CWE-20 Improper Input Validation GitHub, Inc.  

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Change History

3 change records found show changes

Quick Info

CVE Dictionary Entry:
CVE-2022-35974
NVD Published Date:
09/16/2022
NVD Last Modified:
11/21/2024
Source:
GitHub, Inc.