Learn about CVE-2021-29595 involving a division by zero error in TensorFlow's `DepthToSpace` TFLite operator, its impact, affected versions, exploitation mechanism, and mitigation steps.
TensorFlow is an end-to-end open source platform for machine learning. The implementation of the
DepthToSpace
TFLite operator is vulnerable to a division by zero error. An attacker can craft a model such that params->block_size
is 0. The fix will be included in TensorFlow 2.5.0, with cherry-picked commits on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3, and TensorFlow 2.1.4.
Understanding CVE-2021-29595
This section will provide insights into the CVE-2021-29595 vulnerability affecting TensorFlow.
What is CVE-2021-29595?
CVE-2021-29595 involves a division by zero error in the TFLite's implementation of
DepthToSpace
in TensorFlow, which can be exploited by an attacker.
The Impact of CVE-2021-29595
The vulnerability can result in a low severity attack complexity with a local attack vector and low availability impact. No confidentiality or integrity impacts are involved.
Technical Details of CVE-2021-29595
This section will delve into the technical aspects of the CVE-2021-29595 vulnerability.
Vulnerability Description
The vulnerability arises due to a division by zero error in the
DepthToSpace
TFLite operator in TensorFlow.
Affected Systems and Versions
Affected versions include TensorFlow < 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
An attacker can craft a malicious model to make
params->block_size
equal to 0, triggering the division by zero error.
Mitigation and Prevention
This section will outline the steps to mitigate and prevent the exploitation of CVE-2021-29595.
Immediate Steps to Take
Users are advised to update their TensorFlow installations to versions that include the fix for CVE-2021-29595.
Long-Term Security Practices
Maintaining up-to-date software versions and regularly applying security patches are essential for long-term security.
Patching and Updates
Ensure to install the patched versions of TensorFlow (2.5.0 and cherry-picked commits on 2.4.2, 2.3.3, 2.2.3, and 2.1.4) to address the vulnerability.