CVE-2021-29614 : Exploit Details and Defense Strategies

TensorFlow is an end-to-end open source platform for machine learning. A vulnerability in TensorFlow versions prior to 2.1.4, 2.2.3, 2.3.3, and 2.4.2 allows for an interpreter crash via

tf.io.decode_raw

. The issue arises due to a bug in the implementation of the

decode_padded_raw_op.cc

file. Specifically, the code moves the

out_data

pointer improperly, leading to an out-of-bounds write (OOB) that can result in a Python interpreter crash or potentially be exploited for severe attacks. The fix for this vulnerability is included in TensorFlow version 2.5.0, and patches have been backported to the affected versions.

Understanding CVE-2021-29614

This section provides an overview of the CVE-2021-29614 vulnerability in TensorFlow.

What is CVE-2021-29614?

CVE-2021-29614 is a vulnerability in TensorFlow that allows for an interpreter crash when using the

tf.io.decode_raw

function due to a bug in pointer arithmetic rules.

The Impact of CVE-2021-29614

The impact of CVE-2021-29614 includes a high availability impact and integrity impact. An attacker with low privileges can cause an interpreter crash or potentially execute more severe attacks exploiting the OOB write.

Technical Details of CVE-2021-29614

In this section, we dive into the technical details of the CVE-2021-29614 vulnerability in TensorFlow.

Vulnerability Description

The vulnerability stems from the improper movement of the

out_data

pointer in the

decode_padded_raw_op.cc

file, leading to an OOB write.

Affected Systems and Versions

TensorFlow versions prior to 2.1.4, 2.2.3, 2.3.3, and 2.4.2 are affected by this vulnerability.

Exploitation Mechanism

The bug allows for an OOB write, which can lead to a Python interpreter crash or be leveraged for more severe attacks due to writing outside the bounds of data.

Mitigation and Prevention

This section outlines the steps to mitigate and prevent the impact of CVE-2021-29614.

Immediate Steps to Take

Users are advised to update their TensorFlow installations to version 2.5.0, which includes the necessary fix. For versions prior to 2.1.4, 2.2.3, 2.3.3, and 2.4.2, patches have been backported to address the vulnerability.

Long-Term Security Practices

In the long term, practitioners should stay informed about security updates and regularly update their software to prevent known vulnerabilities.

Patching and Updates

Regularly check for updates from TensorFlow and apply patches promptly to stay protected against potential vulnerabilities.