CVE-2021-29567 : Vulnerability Insights and Analysis

The vulnerability in TensorFlow with ID CVE-2021-29567 allows an attacker to trigger denial of service attacks or write to memory outside the bounds of heap allocated data. The lack of validation in

tf.raw_ops.SparseDenseCwiseMul

can lead to serious consequences and requires immediate action.

Understanding CVE-2021-29567

This section provides detailed insights into the impact and technical aspects of the vulnerability.

What is CVE-2021-29567?

TensorFlow's vulnerability CVE-2021-29567 arises from a lack of validation in

tf.raw_ops.SparseDenseCwiseMul

. Attackers can exploit this to trigger denial of service attacks or access heap allocated data bounds.

The Impact of CVE-2021-29567

The vulnerability has a LOW base severity score of 2.5 CVSSv3.1. It has a HIGH attack complexity and LOW availability impact. Attack vectors are local, and no user interaction is required.

Technical Details of CVE-2021-29567

Explore the specific technical details related to the vulnerability.

Vulnerability Description

The issue allows attackers to trigger denial of service via

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-fails or access memory outside of heap allocated data bounds within TensorFlow.

Affected Systems and Versions

The affected versions include TensorFlow < 2.1.4, >= 2.2.0 and < 2.2.3, >= 2.3.0 and < 2.3.3, and >= 2.4.0 and < 2.4.2.

Exploitation Mechanism

By exploiting the lack of validation in

tf.raw_ops.SparseDenseCwiseMul

, attackers can abuse input arguments to trigger internal

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assertions or write to memory outside of heap allocated tensor buffers.

Mitigation and Prevention

Discover the necessary steps to mitigate the risks associated with CVE-2021-29567.

Immediate Steps to Take

It is crucial to update TensorFlow to version 2.5.0 or apply the fix cherrypicked for versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4. Ensure prompt action to prevent exploitation.

Long-Term Security Practices

Implement robust security practices, perform regular vulnerability assessments, and stay updated on security advisories to prevent similar vulnerabilities.

Patching and Updates

Regularly check for security patches and updates released by TensorFlow to address vulnerabilities and improve the overall security posture.