CVE-2021-29605 : What You Need to Know

TensorFlow, an open-source platform for machine learning, is vulnerable to an integer overflow issue in the TFLite code that handles memory allocation. This vulnerability allows an attacker to create a malicious model that triggers an overflow in the

int

datatype, leading to memory corruption. The impact of this vulnerability is rated as HIGH.

Understanding CVE-2021-29605

This section delves into the specifics of the CVE-2021-29605 vulnerability in TensorFlow.

What is CVE-2021-29605?

CVE-2021-29605 is an integer overflow vulnerability in TensorFlow's TFLite code, allowing attackers to corrupt memory by crafting malicious models.

The Impact of CVE-2021-29605

The severity of this vulnerability is rated as HIGH, with a CVSS base score of 7.1. It can lead to memory corruption and compromise system integrity.

Technical Details of CVE-2021-29605

Let's explore the technical aspects of the CVE-2021-29605 vulnerability.

Vulnerability Description

The vulnerability arises from an integer overflow issue in the TFLite code used for memory allocation, enabling attackers to manipulate memory.

Affected Systems and Versions

The affected versions of TensorFlow include < 2.1.4, >= 2.2.0 and < 2.2.3, >= 2.3.0 and < 2.3.3, and >= 2.4.0 and < 2.4.2.

Exploitation Mechanism

Attackers can exploit this vulnerability by creating a model that triggers the overflow of the

int

datatype, leading to memory corruption.

Mitigation and Prevention

Discover the steps to mitigate and prevent the CVE-2021-29605 vulnerability in TensorFlow.

Immediate Steps to Take

Users are advised to update TensorFlow to version 2.5.0 or apply the relevant patches backported to versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4.

Long-Term Security Practices

Implement secure coding practices and conduct regular security audits to detect and prevent similar vulnerabilities.

Patching and Updates

Stay informed about security updates and promptly apply patches to secure your TensorFlow installation.