CVE-2022-21737:
Assertion failure based denial of service in Tensorflow
6.5
CVSS Score
3.1
Basic Information
CVE ID
GHSA ID
EPSS Score
0.43492%
CWE
Published
2/9/2022
Updated
11/13/2024
KEV Status
No
Technology
Python
Technical Details
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Package Name | Ecosystem | Vulnerable Versions | First Patched Version |
---|---|---|---|
tensorflow | pip | < 2.5.3 | 2.5.3 |
tensorflow | pip | >= 2.6.0, < 2.6.3 | 2.6.3 |
tensorflow | pip | = 2.7.0 | 2.7.1 |
tensorflow-cpu | pip | < 2.5.3 | 2.5.3 |
tensorflow-cpu | pip | >= 2.6.0, < 2.6.3 | 2.6.3 |
tensorflow-cpu | pip | = 2.7.0 | 2.7.1 |
tensorflow-gpu | pip | < 2.5.3 | 2.5.3 |
tensorflow-gpu | pip | >= 2.6.0, < 2.6.3 | 2.6.3 |
tensorflow-gpu | pip | = 2.7.0 | 2.7.1 |
Vulnerability Intelligence
Miggo AI
Root Cause Analysis
The vulnerable functions are identified by analyzing the changes made to the TensorFlow codebase in the given commit. The patch adds input validation to the Compute methods of DenseBincountOp, SparseBincountOp, and RaggedBincountOp classes, indicating that these functions were previously vulnerable to denial of service attacks due to lack of validation on the 'size' input.