CVE-2022-35979 is a denial-of-service vulnerability affecting TensorFlow, specifically versions prior to 2.10.0, 2.9.1, 2.8.1, and 2.7.2. It arises when non-scalar inputs are provided to the min_features or max_features arguments of QuantizedRelu or QuantizedRelu6 operations, leading to a segfault. The vulnerability has a CVSS score of 7.5 (High), indicating it can be exploited remotely with low complexity and no user interaction, resulting in a complete loss of availability. There are no known workarounds. Currently, there is no evidence of active exploitation, nor is there publicly available exploit code in Metasploit, Nuclei, or ExploitDB. Community discussion and media coverage for this CVE are minimal.
| Vendor | Product | Version(s) | CPE |
|---|---|---|---|
< 2.7.2CPE matchmatch criteria | cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* | ||
>= 2.8.0, < 2.8.1CPE matchmatch criteria | cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* | ||
>= 2.9.0, < 2.9.1CPE matchmatch criteria | cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* | ||
2.10CPE matchmatch criteria | cpe:2.3:a:google:tensorflow:2.10:rc0:*:*:*:*:*:* | ||
2.10CPE matchmatch criteria | cpe:2.3:a:google:tensorflow:2.10:rc1:*:*:*:*:*:* |
CVSS version used by this source: 3.1
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
The average CVE in this peer group has 0.0 Twitter, 0.0 Reddit, 0.1 Bluesky, 0.1 Mastodon, and 0.4 GitHub mentions.
No media coverage found for this CVE.
The average CVE in this peer group has 0.1 InfoSec Media, 0.0 Vendor Blog, and 0.0 Security Researcher mentions.