Vulnerability Details : CVE-2022-35985

TensorFlow is an open source platform for machine learning. If `LRNGrad` is given an `output_image` input tensor that is not 4-D, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. 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 22:15:11
Updated 2022-09-20 14:53:56
Source GitHub, Inc.
View at NVD,   CVE.org
Vulnerability category: Denial of service

Products affected by CVE-2022-35985

Exploit prediction scoring system (EPSS) score for CVE-2022-35985

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-2022-35985

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-2022-35985

  • 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: security-advisories@github.com (Primary)

References for CVE-2022-35985

Jump to
This web site uses cookies for managing your session, storing preferences, website analytics and additional purposes described in our privacy policy.
By using this web site you are agreeing to CVEdetails.com terms of use!
Accept Close