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CVE-2021-29524 : Exploit Details and Defense Strategies

Learn about CVE-2021-29524, a TensorFlow vulnerability allowing an attacker to trigger a division by 0. Understand the impact and mitigation steps for enhanced security.

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in

tf.raw_ops.Conv2DBackpropFilter
. The vulnerability allows an attacker to exploit a modulus operation where the divisor is controlled by the caller. The impact is rated as LOW with a CVSS base score of 2.5.

Understanding CVE-2021-29524

This CVE involves a vulnerability in TensorFlow that enables an attacker to provoke a division by 0 in the

Conv2DBackpropFilter
function.

What is CVE-2021-29524?

CVE-2021-29524 highlights a vulnerability in TensorFlow that could be exploited to trigger a division by 0, potentially leading to a denial of service attack.

The Impact of CVE-2021-29524

The impact of this CVE is rated as LOW, with an assigned CVSS base score of 2.5. It poses a risk due to the potential for a denial of service attack through the mentioned vulnerability in

Conv2DBackpropFilter
function.

Technical Details of CVE-2021-29524

The technical details reveal that the vulnerable versions of TensorFlow include ranges below 2.1.4, 2.2.0 to 2.2.3, 2.3.0 to 2.3.3, and 2.4.0 to 2.4.2.

Vulnerability Description

The vulnerability allows an attacker to induce a division by 0 in

Conv2DBackpropFilter
due to a modulus operation vulnerability.

Affected Systems and Versions

Versions of TensorFlow below 2.1.4, 2.2.0 to 2.2.3, 2.3.0 to 2.3.3, and 2.4.0 to 2.4.2 are affected by this vulnerability.

Exploitation Mechanism

An attacker can exploit the vulnerability by manipulating the divisor controlled by the caller in the implementation.

Mitigation and Prevention

It is crucial to take immediate steps to address the CVE in TensorFlow to enhance system security.

Immediate Steps to Take

Ensure to update TensorFlow to version 2.5.0 to fix the vulnerability. Additionally, patch versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4 are also available to address the issue.

Long-Term Security Practices

Regularly update TensorFlow and other software to the latest versions to prevent known vulnerabilities.

Patching and Updates

Stay informed about security advisories and apply patches promptly to mitigate the risk of exploitation.

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