Upstream information

CVE-2022-35973 at MITRE

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.

SUSE information

Overall state of this security issue: Does not affect SUSE products

This issue is currently rated as having critical severity.

CVSS v3 Scores
  National Vulnerability Database
Base Score 7.5
Vector CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Attack Vector Network
Attack Complexity Low
Privileges Required None
User Interaction None
Scope Unchanged
Confidentiality Impact None
Integrity Impact None
Availability Impact High
CVSSv3 Version 3.1
SUSE Bugzilla entry: 1203507 [NEW]

No SUSE Security Announcements cross referenced.

List of released packages

Product(s) Fixed package version(s) References
openSUSE Tumbleweed
  • tensorflow-lite >= 2.10.0-1.1
  • tensorflow-lite-devel >= 2.10.0-1.1
Patchnames:
openSUSE-Tumbleweed-2024-12355


SUSE Timeline for this CVE

CVE page created: Sat Sep 17 09:33:47 2022
CVE page last modified: Tue Sep 3 19:26:12 2024