CVE-2022-21734 : Exploit Details and Defense Strategies

Tensorflow is an Open Source Machine Learning Framework that has been found to have

CHECK

-failures in its implementation of

MapStage

. This vulnerability can lead to a

CHECK

-fail if the key tensor is not a scalar. The fix for this issue will be included in TensorFlow 2.8.0, and commits will also be cherrypicked for TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3 versions as they are affected and still within the supported range.

Understanding CVE-2022-21734

This section provides an overview of the vulnerability in Tensorflow regarding

CHECK

-failures in the

MapStage

implementation.

What is CVE-2022-21734?

CVE-2022-21734 highlights the vulnerability in Tensorflow's implementation where a

CHECK

-fail occurs if the key tensor is not a scalar, potentially impacting the integrity and availability of the system.

The Impact of CVE-2022-21734

The impact of this CVE is classified as medium severity with a base score of 6.5. It has low attack complexity but high availability impact, requiring low privileges for exploitation and no user interaction. The vulnerability does not affect confidentiality or integrity.

Technical Details of CVE-2022-21734

In this section, we delve into the technical aspects of the vulnerability in Tensorflow.

Vulnerability Description

The vulnerability arises from the

MapStage

implementation in Tensorflow, where a

CHECK

-fail occurs if the key tensor is not a scalar, leading to potential security risks.

Affected Systems and Versions

TensorFlow versions 2.5.3, 2.6.3, and 2.7.1 are affected by this vulnerability, with a fix included in the upcoming release of version 2.8.0.

Exploitation Mechanism

The exploitation of this vulnerability requires low privileges and can be triggered over a network without requiring user interaction.

Mitigation and Prevention

To secure systems from the CVE-2022-21734 vulnerability, certain mitigation strategies and preventative measures can be implemented.

Immediate Steps to Take

Immediate action includes updating to the latest version of Tensorflow (2.8.0) once the fix is released. Additionally, monitoring security advisories and applying patches promptly is advised.

Long-Term Security Practices

Establishing robust security practices, such as regular vulnerability assessments, code reviews, and security training, can help mitigate risks in the long term.

Patching and Updates

Regularly updating software, including Tensorflow, to the latest patched versions is crucial in preventing vulnerabilities and strengthening the overall security posture.