CVE-2021-41211 Explained : Impact and Mitigation

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

QuantizeV2

can trigger a read outside of bounds of the heap-allocated array when certain conditions are met.

Understanding CVE-2021-41211

In this CVE, a vulnerability in TensorFlow allows for a heap out-of-bounds read due to improper handling of negative values for a specific parameter.

What is CVE-2021-41211?

The issue arises when the

axis

parameter is set to a negative value less than

-1

, leading to accessing data before the start of a heap buffer, potentially causing a heap out-of-bounds read.

The Impact of CVE-2021-41211

The vulnerability has a CVSS base score of 7.1 (High), with high confidentiality impact and high availability impact. It requires low privileges and no user interaction for exploitation.

Technical Details of CVE-2021-41211

The following technical details provide insight into the vulnerability.

Vulnerability Description

The shape inference code for

QuantizeV2

triggers a heap out-of-bounds read with negative

axis

values.

Affected Systems and Versions

Product: TensorFlow
Vendor: TensorFlow
Versions Affected: >= 2.6.0, < 2.6.1

Exploitation Mechanism

The vulnerability occurs when the

axis

parameter is set to a negative value less than

-1

, leading to accessing data outside the bounds of the heap-allocated array.

Mitigation and Prevention

To address CVE-2021-41211, consider the following:

Immediate Steps to Take

Update TensorFlow to version 2.7.0 or higher to apply the fix.
For version 2.6.1, a specific commit will address the vulnerability.

Long-Term Security Practices

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

Patching and Updates

Stay updated with the latest TensorFlow releases to patch any security vulnerabilities promptly.