PT-2022-23072 · Google · Tensorflow

Neophytos Christou · Published 2022-09-16 · Updated 2024-03-06 · CVE-2022-35973

Positive Technologies (AI Summary)

CVSS v3.1

5.9

Medium

Base vector

AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

Name of the Vulnerable Software and Affected Versions TensorFlow versions prior to 2.10.0 TensorFlow versions 2.9.1, 2.8.1, and 2.7.2

Description The issue arises when QuantizedMatMul is given nonscalar input for: min a, max a, min b, or max b. This can trigger a segfault, leading to a denial of service attack.

Recommendations For TensorFlow versions prior to 2.10.0, update to version 2.10.0 or later. For TensorFlow versions 2.9.1, 2.8.1, and 2.7.2, update to the respective patched versions. As a temporary workaround, consider avoiding the use of QuantizedMatMul with nonscalar input for min a, max a, min b, or max b until a patch is available.

Exploit

Fix

RCE

Weakness Enumeration

CWE-20

Related Identifiers

BIT-TENSORFLOW-2022-35973

CVE-2022-35973

GHSA-689C-R7H2-FV9V

OPENSUSE-SU-2024:12355-1

Affected Products

Tensorflow

References · 10

• 🔥 https://github.com/CVEProject/cvelistV5/tree/main/cves/2022/35xxx/CVE-2022-35973.json · Exploit
• https://github.com/tensorflow/tensorflow/commit/aca766ac7693bf29ed0df55ad6bfcc78f35e7f48 · Patch
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-689c-r7h2-fv9v · Patch
• https://nvd.nist.gov/vuln/detail/CVE-2022-35973 · Security Note
• https://osv.dev/vulnerability/CVE-2022-35973 · Vendor Advisory
• https://osv.dev/vulnerability/BIT-tensorflow-2022-35973 · Vendor Advisory
• https://osv.dev/vulnerability/GHSA-689c-r7h2-fv9v · Vendor Advisory
• https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0 · Note
• https://github.com/tensorflow/tensorflow · Note
• https://t.me/cibsecurity/49986 · Telegram Post