CVE-2021-29547 : Vulnerability Insights and Analysis

TensorFlow is an open-source platform for machine learning. The CVE-2021-29547 describes a vulnerability that allows an attacker to trigger a denial of service by accessing data outside the bounds of

tf.raw_ops.QuantizedBatchNormWithGlobalNormalization

. This occurs due to an assumption in the implementation that the inputs are not empty. The vulnerability affects TensorFlow versions < 2.1.4, >= 2.2.0 and < 2.2.3, >= 2.3.0 and < 2.3.3, >= 2.4.0, and < 2.4.2. A fix will be provided in TensorFlow 2.5.0, with backports to versions still in the supported range.

Understanding CVE-2021-29547

This section delves into the impact, technical details, and mitigation strategies related to the vulnerability in TensorFlow.

What is CVE-2021-29547?

The CVE-2021-29547 vulnerability in TensorFlow allows attackers to cause a denial-of-service condition by accessing data beyond the boundaries of a specific function.

The Impact of CVE-2021-29547

The impact of this vulnerability is assessed as having a low base severity score. It requires a low level of privileges and user interaction, with a high attack complexity but low availability impact.

Technical Details of CVE-2021-29547

The technical aspects of the CVE-2021-29547 vulnerability in TensorFlow are described below.

Vulnerability Description

The vulnerability arises from accessing data outside the expected bounds in

tf.raw_ops.QuantizedBatchNormWithGlobalNormalization

due to improper input validation.

Affected Systems and Versions

TensorFlow versions < 2.1.4, >= 2.2.0 and < 2.2.3, >= 2.3.0 and < 2.3.3, >= 2.4.0, and < 2.4.2 are affected by this vulnerability.

Exploitation Mechanism

Attackers can exploit this vulnerability by manipulating inputs to trigger a denial-of-service condition within TensorFlow.

Mitigation and Prevention

Understanding the necessary steps to mitigate and prevent the CVE-2021-29547 vulnerability is crucial.

Immediate Steps to Take

Users are advised to apply updates promptly when TensorFlow 2.5.0 is released. Until then, exercise caution with untrusted inputs.

Long-Term Security Practices

Developers should validate input data properly to prevent out-of-bound access vulnerabilities in their applications.

Patching and Updates

Stay informed about security advisories from TensorFlow and apply patches as soon as they are available to ensure protection against this and future vulnerabilities.