CVE-2022-21741 Explained : Impact and Mitigation
Learn about CVE-2022-21741, a vulnerability in TFLite allowing attackers to trigger a division by zero in depthwise convolutions. Understand the impact, mitigation, and affected versions.
Tensorflow is an open-source machine learning framework where an attacker can manipulate a TFLite model to trigger a division by zero in the implementation of depthwise convolutions. The divide operation, using user-controlled parameters, doesn't check if the divisor is positive. The vulnerability will be fixed in TensorFlow 2.8.0, and patches will be backported to versions 2.7.1, 2.6.3, and 2.5.3 which are also affected.
Understanding CVE-2022-21741
This section explains the impact, technical details, and mitigation strategies for the Division by zero vulnerability in TFLite.
What is CVE-2022-21741?
The CVE-2022-21741 vulnerability allows an attacker to exploit a division by zero in Tensorflow's TFLite model, potentially leading to security compromises in machine learning applications.
The Impact of CVE-2022-21741
A threat actor can abuse this vulnerability to manipulate the division operation in depthwise convolutions, enabling potential attacks that trigger a division by zero within Tensorflow's implementation.
Technical Details of CVE-2022-21741
Below are the specific technical details regarding the vulnerability in TFLite:
Vulnerability Description
The flaw arises from a lack of validation regarding the divisor's positivity in the division operation, which can be controlled by user parameters.
Affected Systems and Versions
All versions up to TensorFlow 2.8.0 are affected by this vulnerability, with immediate patches available for versions 2.7.1, 2.6.3, and 2.5.3.
Exploitation Mechanism
The attacker crafts a TFLite model to exploit the division operation without the required validation, ultimately triggering a division by zero in depthwise convolutions.
Mitigation and Prevention
To address the Division by zero vulnerability in TFLite, consider these key mitigation strategies:
Immediate Steps to Take
Update Tensorflow to version 2.8.0 or apply the provided patches for versions 2.7.1, 2.6.3, and 2.5.3 to prevent exploitation of the division by zero flaw.
Long-Term Security Practices
Enhance security practices by regularly updating Tensorflow and other open-source dependencies to ensure vulnerabilities are promptly addressed.
Patching and Updates
Stay informed about security advisories and apply relevant patches and updates to mitigate potential risks associated with known vulnerabilities in TFLite.