CVE-2022-29204 : Exploit Details and Defense Strategies

TensorFlow is an open-source platform for machine learning. This CVE arises from a lack of validation in the implementation of

tf.raw_ops.UnsortedSegmentJoin

, leading to denial-of-service vulnerabilities in versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4.

Understanding CVE-2022-29204

This section delves into the details of the CVE-2022-29204 vulnerability in TensorFlow.

What is CVE-2022-29204?

The vulnerability results from inadequate validation in

tf.raw_ops.UnsortedSegmentJoin

, potentially enabling denial-of-service attacks in certain TensorFlow versions.

The Impact of CVE-2022-29204

With a CVSS base score of 5.5 (medium severity), this vulnerability could allow local attackers to trigger a denial-of-service condition without requiring high privileges.

Technical Details of CVE-2022-29204

Let's explore the technical aspects of CVE-2022-29204 in TensorFlow.

Vulnerability Description

The vulnerability stems from the unchecked assumption of positive scalar input arguments, leading to

num_segments

allocation issues.

Affected Systems and Versions

Versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4 are affected by this vulnerability due to missing input validation.

Exploitation Mechanism

By exploiting the lack of input validation, an attacker can trigger a

CHECK

-failure causing denial-of-service conditions.

Mitigation and Prevention

To secure your systems against CVE-2022-29204, consider the following mitigation strategies.

Immediate Steps to Take

Upgrade TensorFlow to versions 2.9.0, 2.8.1, 2.7.2, or 2.6.4 which contain patches addressing this vulnerability.

Long-Term Security Practices

Regularly update TensorFlow to the latest versions and follow secure coding practices to prevent similar vulnerabilities.

Patching and Updates

Stay informed about security advisories from TensorFlow and apply patches promptly to mitigate potential risks.