CVE-2022-35996 MEDIUM

CVE-2022-35996: Floating point exception in `Conv2D` in TensorFlow

Vendor Tensorflow
Product tensorflow
Weakness CWE-369
Published September 16, 2022
Last update April 23, 2025

CVSS base score

5.9/10
Attack vector Network
Attack complexity High
Privileges required None
User interaction None
Confidentiality None
Integrity None

CVSS vector

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

What the vulnerability does

01Description

TensorFlow is an open source platform for machine learning. If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 611d80db29dd7b0cfb755772c69d60ae5bca05f9. 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.

Key dates

02Disclosure timeline

September 16, 2022 CVE published
April 23, 2025 Record updated