PT-2022-23085 · Google · Tensorflow

Di Jin · Published 2022-09-16 · Updated 2024-03-06 · CVE-2022-35987

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 2.9.0 through 2.9.0 TensorFlow versions 2.8.0 through 2.8.0 TensorFlow versions 2.7.0 through 2.7.1

Description The DenseBincount function in TensorFlow assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack.

Recommendations For TensorFlow versions prior to 2.10.0, update to TensorFlow 2.10.0 or later. For TensorFlow versions 2.9.0, update to TensorFlow 2.9.1 or later. For TensorFlow versions 2.8.0, update to TensorFlow 2.8.1 or later. For TensorFlow versions 2.7.0 through 2.7.1, update to TensorFlow 2.7.2 or later.

Exploit

Fix

Assertion Failure

Weakness Enumeration

CWE-617

Related Identifiers

BIT-TENSORFLOW-2022-35987

CVE-2022-35987

GHSA-W62H-8XJM-FV49

OPENSUSE-SU-2024:12355-1

Affected Products

Tensorflow

References · 9

• 🔥 https://github.com/CVEProject/cvelistV5/tree/main/cves/2022/35xxx/CVE-2022-35987.json · Exploit
• https://github.com/tensorflow/tensorflow/commit/bf4c14353c2328636a18bfad1e151052c81d5f43 · Patch
• https://nvd.nist.gov/vuln/detail/CVE-2022-35987 · Security Note
• https://osv.dev/vulnerability/CVE-2022-35987 · Vendor Advisory
• https://osv.dev/vulnerability/BIT-tensorflow-2022-35987 · Vendor Advisory
• https://osv.dev/vulnerability/GHSA-w62h-8xjm-fv49 · Vendor Advisory
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w62h-8xjm-fv49 · Note
• https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0 · Note
• https://github.com/tensorflow/tensorflow · Note