CVE-2022-29211 Explained : Impact and Mitigation

TensorFlow is an open-source platform for machine learning. The vulnerability identified as CVE-2022-29211 affects versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4, specifically in the implementation of

tf.histogram_fixed_width

. This vulnerability can lead to a crash when the values array contains

Not a Number

(

NaN

) elements.

Understanding CVE-2022-20657

This section provides an in-depth look at the details and impacts of CVE-2022-20657.

What is CVE-2022-29211?

The vulnerability occurs due to improper input validation in TensorFlow's

tf.histogram_fixed_width

function. When the 'values' array includes

NaN

elements, the result of the division operation can lead to a crash due to an integer index conversion involving floating-point operations.

The Impact of CVE-2022-29211

The vulnerability has a base score of 5.5, with a medium severity rating. It has a low attack complexity and vector, with high availability impact. While it does not affect confidentiality or integrity, low privileges are required for exploitation.

Technical Details of CVE-2022-29211

This section delves into the specific technical aspects of the CVE.

Vulnerability Description

The vulnerability arises from the handling of

NaN

elements in the 'values' array within the

tf.histogram_fixed_width

function. When 'values' contains

NaN

, the conversion to

int32

leads to a crash, particularly in the CPU implementation.

Affected Systems and Versions

The vulnerability impacts TensorFlow versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4, specifically in the

tf.histogram_fixed_width

function.

Exploitation Mechanism

Exploiting this vulnerability requires low privileges and local attack vector complexity. The attacker can trigger a crash by providing a 'values' array with

NaN

elements.

Mitigation and Prevention

This section outlines steps to mitigate and prevent exploitation of CVE-2022-29211.

Immediate Steps to Take

Users are advised to update TensorFlow to versions 2.9.0, 2.8.1, 2.7.2, or 2.6.4, which contain patches for this vulnerability.

Long-Term Security Practices

Implement proper input validation mechanisms when working with sensitive user input to prevent similar vulnerabilities in the future.

Patching and Updates

Regularly check for TensorFlow updates and apply patches promptly to address known security issues.