CVE-2021-29571 Explained : Impact and Mitigation

TensorFlow, an open-source platform for machine learning, is impacted by a memory corruption vulnerability in the

DrawBoundingBoxesV2

function. This vulnerability could be exploited by attackers to cause memory corruption.

Understanding CVE-2021-29571

This section will cover the details of the vulnerability, its impact, technical aspects, and mitigation strategies.

What is CVE-2021-29571?

CVE-2021-29571 is a memory corruption vulnerability in TensorFlow's implementation of

DrawBoundingBoxesV2

. Attackers can exploit this vulnerability by providing specially crafted inputs to read/write outside the bounds of allocated memory, potentially leading to memory corruption.

The Impact of CVE-2021-29571

The vulnerability has a CVSS base score of 4.5, indicating a medium severity issue. It has a high attack complexity and can be exploited locally with low privileges required. The integrity, confidentiality, and availability of affected systems are at risk.

Technical Details of CVE-2021-29571

Let's delve into the technical details of the vulnerability to understand the affected systems, exploitation mechanism, and more.

Vulnerability Description

The vulnerability arises from a flaw in how TensorFlow handles inputs in the

DrawBoundingBoxesV2

function. By manipulating certain inputs, attackers can cause reads/writes outside of heap-allocated memory areas, leading to memory corruption.

Affected Systems and Versions

The vulnerability affects TensorFlow versions prior to 2.1.4, between 2.2.0 and 2.2.3, between 2.3.0 and 2.3.3, and between 2.4.0 and 2.4.2. Users of these versions should take immediate action to mitigate the risk.

Exploitation Mechanism

Attackers can exploit this vulnerability by providing specially crafted inputs that do not adhere to the expected format. By supplying values less than 4 in certain input parameters, attackers can write outside of the intended memory bounds, leading to memory corruption.

Mitigation and Prevention

To address this vulnerability and prevent potential exploitation, users and administrators are advised to take immediate action and adopt long-term security practices.

Immediate Steps to Take

Update TensorFlow to version 2.5.0, which includes a fix for this vulnerability.
For users on affected versions (2.1.4 to 2.4.2), apply the fix provided in TensorFlow 2.5.0.

Long-Term Security Practices

Regularly update TensorFlow and other dependencies to the latest versions.
Monitor security advisories and apply patches promptly to mitigate future vulnerabilities.

Patching and Updates

Stay informed about security updates and patches released by TensorFlow. Apply updates as soon as they are available to ensure the security of your machine learning environment.