CVE-2021-37637 : Vulnerability Insights and Analysis

TensorFlow, an open source platform for machine learning, is vulnerable to a null pointer dereference in the

CompressElement

function. This CVE allows attackers to trigger a null pointer dereference by providing invalid input to the function, potentially leading to high availability impact and integrity issues. TensorFlow versions 2.5.0 to 2.5.1, 2.4.0 to 2.4.3, and versions below 2.3.4 are affected by this vulnerability.

Understanding CVE-2021-37637

This section delves deeper into the impact and technical details of the vulnerability.

What is CVE-2021-37637?

CVE-2021-37637 is a null pointer dereference vulnerability in TensorFlow's

CompressElement

function. Attackers can exploit this issue by passing malformed input data to the function.

The Impact of CVE-2021-37637

The vulnerability has a High severity rating (CVSS score of 7.7) with Low attack complexity and Local attack vector. While it does not impact confidentiality, it poses a high risk to system availability and integrity.

Technical Details of CVE-2021-37637

Explore the technical aspects and affected systems related to this CVE.

Vulnerability Description

The vulnerability originates from accessing a buffer size without proper validation, which can result in a null pointer dereference.

Affected Systems and Versions

TensorFlow versions 2.5.0 to 2.5.1, 2.4.0 to 2.4.3, and versions below 2.3.4 are vulnerable to this issue.

Exploitation Mechanism

Attackers can exploit this vulnerability by providing invalid input to the

tf.raw_ops.CompressElement

function, leading to a null pointer dereference.

Mitigation and Prevention

Discover the necessary steps to secure your systems against CVE-2021-37637.

Immediate Steps to Take

Update TensorFlow to version 2.6.0, which contains the patch for this vulnerability. For versions 2.5.1, 2.4.3, and 2.3.4, apply the specific commit 5dc7f6981fdaf74c8c5be41f393df705841fb7c5 to address the issue.

Long-Term Security Practices

Regularly monitor for security advisories from TensorFlow and apply updates promptly to prevent exploitation of known vulnerabilities.

Patching and Updates

Ensure timely application of security patches provided by TensorFlow to maintain a secure environment.