CVE-2022-29208 : Security Advisory and Response

A detailed article outlining the CVE-2022-29208 vulnerability in TensorFlow, affecting versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4.

Understanding CVE-2022-29208

This CVE involves a vulnerability in TensorFlow related to incomplete validation that could lead to a segmentation fault-based denial of service.

What is CVE-2022-29208?

TensorFlow, an open-source platform for machine learning, prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, had incomplete validation in the

tf.raw_ops.EditDistance

implementation. This flaw allowed the passing of negative values that could result in a segmentation fault, potentially causing denial of service attacks.

The Impact of CVE-2022-29208

The impact of this vulnerability is rated as HIGH with a base score of 7.1 according to the CVSS v3.1 metrics. The attack complexity is LOW, requiring LOCAL attack vector and LOW privileges.

Technical Details of CVE-2022-29208

This section covers specific technical details of the vulnerability.

Vulnerability Description

The vulnerability in TensorFlow allows for out-of-bounds write due to incomplete validation, where negative values can be leveraged to cause a segmentation fault.

Affected Systems and Versions

Versions affected include:<br>- TensorFlow < 2.6.4<br>- TensorFlow >= 2.7.0rc0, < 2.7.2<br>- TensorFlow >= 2.8.0rc0, < 2.8.1<br>- TensorFlow >= 2.9.0rc0, < 2.9.0

Exploitation Mechanism

The exploitation involves the passing of negative values that were not validated properly in the code, potentially causing a denial of service due to the segmentation fault.

Mitigation and Prevention

Steps to address and prevent the CVE-2022-29208 vulnerability.

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 addressing this issue.

Long-Term Security Practices

Implement secure coding practices, validate user inputs, and conduct regular security audits to prevent similar vulnerabilities.

Patching and Updates

Regularly update TensorFlow to the latest versions to ensure that security patches for known vulnerabilities are applied.