PT-2022-23069 · Google · Tensorflow

Neophytos Christou

·

Published

2022-09-16

·

Updated

2024-03-06

·

CVE-2022-35970

CVSS v3.1

5.9

Medium

VectorAV: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 and earlier TensorFlow versions 2.8.1 and earlier TensorFlow versions 2.7.2 and earlier
Description The issue arises when QuantizedInstanceNorm is given x min or x max tensors of a nonzero rank, resulting in a segfault that can be used to trigger a denial of service attack. There are no known workarounds for this issue.
Recommendations For TensorFlow versions prior to 2.10.0, update to version 2.10.0 or later. For TensorFlow versions 2.9.1 and earlier, update to version 2.9.1 or later. For TensorFlow versions 2.8.1 and earlier, update to version 2.8.1 or later. For TensorFlow versions 2.7.2 and earlier, update to version 2.7.2 or later. As a temporary workaround, consider avoiding the use of QuantizedInstanceNorm with x min or x max tensors of a nonzero rank until a patch is available.

Exploit

Fix

RCE

Weakness Enumeration

Related Identifiers

BIT-TENSORFLOW-2022-35970
CVE-2022-35970
GHSA-G35R-369W-3FQP
OPENSUSE-SU-2024:12355-1

Affected Products

Tensorflow