CVE-2021-41221 Explained : Impact and Mitigation

TensorFlow vulnerability allows attackers to access invalid memory during shape inference in

Cudnn*

ops.

Understanding CVE-2021-41221

This CVE involves a vulnerability in TensorFlow that can lead to a heap buffer overflow during shape inference, affecting certain versions of the software.

What is CVE-2021-41221?

TensorFlow, an open-source machine learning platform, is susceptible to a heap buffer overflow in the

Cudnn*

operations due to unvalidated input parameters, potentially leading to access of invalid memory.

The Impact of CVE-2021-41221

CVSS Score: 7.8 (High)
Severity: High
Attack Vector: Local
Confidentiality, Integrity, and Availability Impact: High
Privileges Required: Low
The vulnerability's exploit complexity is low, but it can have severe consequences on affected systems, compromising data confidentiality, integrity, and availability.

Technical Details of CVE-2021-41221

This section outlines the technical aspects of the vulnerability.

Vulnerability Description

The vulnerability in TensorFlow allows for a heap buffer overflow during shape inference in

Cudnn*

operations due to unvalidated input parameters.

Affected Systems and Versions

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

Exploitation Mechanism

The ranks of the

input

,

input_h

, and

input_c

parameters are not validated, allowing for potential exploitation via a heap buffer overflow.

Mitigation and Prevention

It is crucial to take immediate steps to mitigate the risks associated with this vulnerability.

Immediate Steps to Take

Update TensorFlow to version 2.7.0 or apply available patches.
Monitor for any unusual activities on TensorFlow instances.
Implement network segmentation to limit potential attacker access.

Long-Term Security Practices

Conduct regular security assessments and code reviews for TensorFlow applications.
Stay informed about security updates and subscribe to relevant security mailing lists.
Train personnel on secure coding practices and threat awareness.

Patching and Updates

Ensure that all TensorFlow installations are promptly updated to version 2.7.0 to address this vulnerability and prevent potential exploitation.