Learn about CVE-2021-29598 impacting TensorFlow versions < 2.1.4, 2.2.0 to 2.2.3, 2.3.0 to 2.3.3, and 2.4.0 to 2.4.2. Understand the exploit, impact, and mitigation steps for this vulnerability.
TensorFlow, a popular open-source machine learning platform, is susceptible to a division by zero vulnerability in its implementation of the
SVDF
TFLite operator. This vulnerability affects versions prior to 2.1.4, as well as versions between 2.2.0 and 2.2.3, 2.3.0 and 2.3.3, and 2.4.0 and 2.4.2. An attacker can exploit this flaw by crafting a model to make params->rank
equal to 0. The fix will be implemented in TensorFlow 2.5.0, with backports to versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4.
Understanding CVE-2021-29598
This section delves into the specifics of the TensorFlow vulnerability.
What is CVE-2021-29598?
TensorFlow's implementation of the
SVDF
TFLite operator is vulnerable to a division by zero error due to a flaw in handling a specific model parameter.
The Impact of CVE-2021-29598
The vulnerability allows an attacker to trigger a division by zero scenario by manipulating model parameters, potentially leading to denial of service or data integrity issues.
Technical Details of CVE-2021-29598
Explore the technical aspects of the CVE.
Vulnerability Description
The vulnerability arises from a specific parameter (
params->rank
) being set to 0, causing a division by zero when processed by the SVDF
TFLite operator.
Affected Systems and Versions
Versions of TensorFlow prior to 2.1.4, 2.2.0 to 2.2.3, 2.3.0 to 2.3.3, and 2.4.0 to 2.4.2 are susceptible to this vulnerability.
Exploitation Mechanism
An attacker can exploit this vulnerability by crafting a malicious model with the
params->rank
parameter set to 0.
Mitigation and Prevention
Discover the steps to mitigate and prevent exploitation of CVE-2021-29598.
Immediate Steps to Take
Users should update their TensorFlow installations to version 2.5.0 to apply the necessary fix for CVE-2021-29598.
Long-Term Security Practices
Implement secure coding practices and regular security updates to prevent similar vulnerabilities in the future.
Patching and Updates
Stay informed about security patches and updates released by TensorFlow to address known vulnerabilities.