CVE-2022-35959 : Exploit Details and Defense Strategies

TensorFlow, an open-source machine learning platform, is impacted by a vulnerability in the

AvgPool3DGradOp

implementation. This leads to a

CHECK

failure, potentially exploited for a denial of service attack. This article delves into the details of CVE-2022-35959.

Understanding CVE-2022-35959

This section will provide insights into the vulnerability, its impact, technical details, and mitigation strategies.

What is CVE-2022-35959?

CVE-2022-35959 involves a lack of validation in the

orig_input_shape

parameter within TensorFlow's

AvgPool3DGradOp

, allowing for an overflow leading to a

CHECK

failure. This vulnerability could be leveraged by malicious actors to instigate a denial of service attack.

The Impact of CVE-2022-35959

The severity of this vulnerability is classified as MEDIUM with a CVSS base score of 5.9. While it does not impact confidentiality or integrity, its high availability impact can have serious consequences for affected systems.

Technical Details of CVE-2022-35959

In this section, we will explore the vulnerability description, affected systems and versions, as well as the exploitation mechanism.

Vulnerability Description

The vulnerability arises from inadequate input validation in the

AvgPool3DGradOp

implementation, leading to a

CHECK

failure when triggered.

Affected Systems and Versions

The versions impacted by CVE-2022-35959 include TensorFlow versions < 2.7.2, >= 2.8.0, < 2.8.1, and >= 2.9.0, < 2.9.1.

Exploitation Mechanism

Malicious actors can exploit this vulnerability by manipulating the

orig_input_shape

parameter, causing an overflow and subsequent

CHECK

failure.

Mitigation and Prevention

This section will outline immediate steps to take, long-term security practices, and the importance of patching and updates.

Immediate Steps to Take

Users are advised to update TensorFlow to version 2.10.0 or apply the relevant patches available for versions 2.7.2, 2.8.1, and 2.9.1. Additionally, monitor for any suspicious activity on affected systems.

Long-Term Security Practices

To enhance security posture, implement secure coding practices, conduct regular security assessments, and stay informed about emerging threats.

Patching and Updates

Regularly check for security advisories from TensorFlow and apply patches promptly to mitigate the risk of exploitation.