Vulnerability Details : CVE-2022-35990

TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient` receives input `min` or `max` of rank other than 1, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. 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 22:15:12
Updated 2022-09-20 14:55:02
Source GitHub, Inc.
View at NVD,   CVE.org
Vulnerability category: Denial of service

Exploit prediction scoring system (EPSS) score for CVE-2022-35990

Probability of exploitation activity in the next 30 days: 0.08%

Percentile, the proportion of vulnerabilities that are scored at or less: ~ 34 % EPSS Score History EPSS FAQ

CVSS scores for CVE-2022-35990

Base Score Base Severity CVSS Vector Exploitability Score Impact Score Score Source
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-2022-35990

  • 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-2022-35990

Products affected by CVE-2022-35990

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