CVE-2021-41225 : What You Need to Know

TensorFlow has been found to have a vulnerability where the Grappler optimizer uses an uninitialized variable, leading to potential security risks in certain versions. Find out more about the impact and mitigation steps below.

Understanding CVE-2021-41225

TensorFlow vulnerability related to uninitialized value usage.

What is CVE-2021-41225?

TensorFlow's Grappler optimizer in specific versions has an uninitialized variable issue where 'dequeue_node' may remain uninitialized if certain conditions are met. The fix is planned for TensorFlow 2.7.0 and backported to 2.6.1, 2.5.2, and 2.4.4.

The Impact of CVE-2021-41225

The vulnerability has a CVSS base score of 5.5 (Medium severity) with low attack complexity and local attack vector. It has a high availability impact as it could leave 'dequeue_node' uninitialized.

Technical Details of CVE-2021-41225

Details about the vulnerability and affected systems.

Vulnerability Description

Affected versions of TensorFlow may have an uninitialized variable issue in the Grappler optimizer, specifically related to 'dequeue_node'.

Affected Systems and Versions

TensorFlow versions >= 2.6.0 and < 2.6.1
TensorFlow versions >= 2.5.0 and < 2.5.2
TensorFlow versions < 2.4.4

Exploitation Mechanism

By utilizing certain conditions related to the 'train_nodes' vector, the 'dequeue_node' may be left uninitialized due to the issue in the Grappler optimizer.

Mitigation and Prevention

Steps to address and prevent the vulnerability.

Immediate Steps to Take

Update TensorFlow to version 2.7.0 once available.
Apply patches for versions 2.6.1, 2.5.2, and 2.4.4 once released.

Long-Term Security Practices

Regularly check for security advisories from TensorFlow.
Implement secure coding practices to prevent similar vulnerabilities.

Patching and Updates

Monitor TensorFlow's security announcements for patches.
Ensure timely application of updates to mitigate known vulnerabilities.