CVE-2021-29583 : Security Advisory and Response

TensorFlow is an end-to-end open source platform for machine learning. The implementation of

tf.raw_ops.FusedBatchNorm

is vulnerable to a heap buffer overflow.

Understanding CVE-2021-29583

This CVE describes a vulnerability in TensorFlow that can lead to a heap buffer overflow and trigger undefined behavior in the

FusedBatchNorm

function.

What is CVE-2021-29583?

The vulnerability in

FusedBatchNorm

allows for heap buffer overflow and potential undefined behavior when empty tensors are encountered, leading to the dereferencing of null pointers.

The Impact of CVE-2021-29583

This vulnerability could be exploited to cause heap out of bounds reads, potentially compromising the integrity and availability of affected systems.

Technical Details of CVE-2021-29583

The vulnerability is assigned a CVSS score of 2.5, indicating a low severity issue. The attack complexity is high, but the privileges required are low with a low availability impact.

Vulnerability Description

The implementation fails to validate certain tensor elements, leading to heap out of bounds reads when buffers are indexed past their boundary.

Affected Systems and Versions

TensorFlow versions below 2.1.4, and between 2.2.0 to 2.4.2 are affected by this vulnerability.

Exploitation Mechanism

An attacker can exploit this vulnerability by crafting specific input to trigger the heap buffer overflow in the

FusedBatchNorm

function.

Mitigation and Prevention

It is crucial to take immediate steps to mitigate the impact of CVE-2021-29583 and prevent potential exploitation.

Immediate Steps to Take

Update TensorFlow to version 2.5.0, which includes the fix for this vulnerability. For versions still within support, patches are available for TensorFlow 2.4.2, 2.3.3, 2.2.3, and 2.1.4.

Long-Term Security Practices

Regularly update TensorFlow to the latest released versions to ensure that known vulnerabilities are patched promptly.

Patching and Updates

Stay informed about security advisories from TensorFlow and apply relevant patches as soon as they are available.