Vulnerability Details : CVE-2022-35969

TensorFlow is an open source platform for machine learning. The implementation of `Conv2DBackpropInput` requires `input_sizes` to be 4-dimensional. Otherwise, it gives a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c. 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.
Published 2022-09-16 21:15:09
Updated 2022-09-20 19:58:03
Source GitHub, Inc.
View at NVD,   CVE.org
Vulnerability category: Denial of service

Products affected by CVE-2022-35969

Exploit prediction scoring system (EPSS) score for CVE-2022-35969

EPSS FAQ
0.08%
Probability of exploitation activity in the next 30 days EPSS Score History
~ 34 %
Percentile, the proportion of vulnerabilities that are scored at or less

CVSS scores for CVE-2022-35969

Base Score Base Severity CVSS Vector Exploitability Score Impact Score Score Source First Seen
7.5
 HIGH CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
3.9
3.6
 NIST
5.9
 MEDIUM CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
2.2
3.6
 GitHub, Inc.

CWE ids for CVE-2022-35969

  • The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary.
    Assigned by:
    • nvd@nist.gov (Primary)
    • security-advisories@github.com (Secondary)

References for CVE-2022-35969

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