CVE-2021-37672 : Vulnerability Insights and Analysis

A detailed overview of CVE-2021-37672, a vulnerability in TensorFlow that allows attackers to read outside of the bounds of heap allocated data.

Understanding CVE-2021-37672

In this section, we will delve into what CVE-2021-37672 entails, its impact, technical details, and ways to mitigate the risk.

What is CVE-2021-37672?

CVE-2021-37672 is a vulnerability in TensorFlow that enables attackers to read beyond the boundaries of heap allocated data.

The Impact of CVE-2021-37672

The vulnerability allows threat actors to exploit the

SdcaOptimizerV2

in TensorFlow by providing specially crafted illegal arguments, leading to potential confidentiality issues.

Technical Details of CVE-2021-37672

Let's explore the technical aspects of CVE-2021-37672 in terms of the vulnerability description, affected systems and versions, and exploitation mechanism.

Vulnerability Description

In affected versions of TensorFlow, the issue arises from improper validation of the length of

example_labels

compared to the number of examples, allowing unauthorized data access.

Affected Systems and Versions

The vulnerability impacts TensorFlow versions >= 2.3.4 and < 2.5.1, including versions 2.4.0 to 2.4.3, with potential risks to data confidentiality.

Exploitation Mechanism

Attackers can leverage the vulnerability by sending specially crafted illegal arguments to

tf.raw_ops.SdcaOptimizerV2

, bypassing the intended data bounds.

Mitigation and Prevention

Discover essential steps to address CVE-2021-37672 efficiently and strategies to prevent similar vulnerabilities.

Immediate Steps to Take

Users are advised to apply the provided patches and updates promptly to mitigate the risk of unauthorized data access.

Long-Term Security Practices

Implement secure coding practices, conduct regular security audits, and stay informed about vulnerability disclosures to enhance overall cybersecurity.

Patching and Updates

Ensure to update affected TensorFlow versions to 2.6.0, or relevant patches to versions 2.5.1, 2.4.3, and 2.3.4 to eliminate the vulnerability.