Cloud Defense Logo

Products

Solutions

Company

Book A Live Demo

CVE-2021-41212 : Vulnerability Insights and Analysis

Learn about the high severity CVE-2021-41212 involving a heap out-of-bounds read vulnerability in TensorFlow versions. Understand the impact, affected systems, and mitigation steps.

TensorFlow is an open source platform for machine learning. In affected versions, the shape inference code for

tf.ragged.cross
can trigger a read outside of bounds of the heap allocated array. The fix is included in TensorFlow 2.7.0, and will be cherrypicked on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4 as they are also affected.

Understanding CVE-2021-41212

In this CVE, a heap out-of-bounds (OOB) read vulnerability in

tf.ragged.cross
within TensorFlow versions can lead to potential security risks.

What is CVE-2021-41212?

This CVE involves a vulnerability in TensorFlow versions where the shape inference code for

tf.ragged.cross
can cause a read operation beyond the bounds of the heap array allocated.

The Impact of CVE-2021-41212

The impact of this CVE is rated as high severity due to its potential to compromise confidentiality with a high availability impact. The attack complexity is low, requiring low privileges and no user interaction, posing a significant risk.

Technical Details of CVE-2021-41212

This section delves into the technical aspects of the vulnerability.

Vulnerability Description

The vulnerability lies in the shape inference code for

tf.ragged.cross
in affected TensorFlow versions.

Affected Systems and Versions

        TensorFlow >= 2.6.0, < 2.6.1
        TensorFlow >= 2.5.0, < 2.5.2
        TensorFlow < 2.4.4

Exploitation Mechanism

The issue arises when the shape inference code for

tf.ragged.cross
attempts to read outside the bounds of the allocated heap array.

Mitigation and Prevention

Taking steps to mitigate and prevent the exploitation of this vulnerability is crucial.

Immediate Steps to Take

        Update TensorFlow to version 2.7.0 to apply the fix.
        If unable to upgrade immediately, consider applying the patches available for TensorFlow 2.6.1, 2.5.2, and 2.4.4.

Long-Term Security Practices

        Regularly update software and dependencies to the latest secure versions.
        Conduct security assessments to identify and address vulnerabilities proactively.

Patching and Updates

Stay informed about security advisories and apply patches promptly to stay protected.

Popular CVEs

CVE Id

Published Date

Is your System Free of Underlying Vulnerabilities?
Find Out Now