CVE-2022-21731 Explained : Impact and Mitigation

Tensorflow has been identified as an Open Source Machine Learning Framework that is prone to a type confusion vulnerability leading to a denial of service attack. This vulnerability stems from the misuse of the

axis

argument in the

ConcatV2

shape inference implementation. An attacker can exploit this issue to trigger a segfault, potentially causing a denial of service. The vulnerability is assigned a CVSS base score of 6.5, indicating a medium severity threat with high availability impact.

Understanding CVE-2022-21731

This section delves into the details of the type confusion vulnerability in Tensorflow and its potential impact on affected systems.

What is CVE-2022-21731?

The vulnerability in Tensorflow arises from a type confusion issue related to the

axis

argument in the

ConcatV2

shape inference implementation. By manipulating certain parameters, an attacker can induce a denial of service attack, potentially leading to a segfault.

The Impact of CVE-2022-21731

The vulnerability poses a medium-severity threat with a CVSS base score of 6.5. It can result in a denial of service scenario with a high impact on availability but no impact on confidentiality or integrity. Attack complexity is rated as low, with low privileges required and no user interaction necessary.

Technical Details of CVE-2022-21731

This section explores the technical aspects of the vulnerability, including its description, affected systems and versions, and the exploitation mechanism.

Vulnerability Description

The vulnerability is rooted in the mishandling of the

axis

argument in the

ConcatV2

shape inference implementation, leading to a type confusion issue. This can be exploited to trigger a denial of service attack.

Affected Systems and Versions

All versions of Tensorflow up to and including 2.5.3, 2.6.3, and 2.7.1 are affected by this vulnerability. The fix for this issue will be included in Tensorflow version 2.8.0.

Exploitation Mechanism

By leveraging the erroneous handling of the

axis

argument, an attacker can induce a segfault, resulting in a denial of service scenario.

Mitigation and Prevention

This section outlines the steps that users and organizations can take to mitigate the risks posed by CVE-2022-21731.

Immediate Steps to Take

Users are advised to update their Tensorflow installations to version 2.8.0 once the fix is released to eliminate the vulnerability.

Long-Term Security Practices

Employ robust security measures such as network segmentation and access controls to limit the attack surface and prevent potential exploitation.

Patching and Updates

Regularly monitor for security advisories and updates from Tensorflow to ensure timely application of patches and fixes to address known vulnerabilities.