CVE-2021-37688 : Security Advisory and Response
Learn about CVE-2021-37688, a high-severity vulnerability in TensorFlow Lite that could allow attackers to trigger a null pointer dereference, leading to denial of service. Find out the impacted systems, technical details, and mitigation steps.
A vulnerability has been discovered in TensorFlow Lite that could allow an attacker to trigger a null pointer dereference, leading to a crash and denial of service.
Understanding CVE-2021-37688
This section will cover the details of the CVE-2021-37688 vulnerability in TensorFlow Lite.
What is CVE-2021-37688?
TensorFlow Lite, an open-source machine learning platform, is affected by a vulnerability that enables attackers to exploit a null pointer dereference flaw. The flaw can be triggered by crafting a TFLite model, resulting in a crash and denial of service.
The Impact of CVE-2021-37688
The impact of this vulnerability is rated as high, with a base score of 7.8. The attack complexity is low, but the availability, confidentiality, and integrity impacts are all high. Privileges required for exploitation are low, and the attack vector is local.
Technical Details of CVE-2021-37688
In this section, we will delve into the technical aspects of CVE-2021-37688 in TensorFlow Lite.
Vulnerability Description
The vulnerability arises from the unconditional dereferencing of a pointer in TensorFlow Lite, allowing attackers to crash the software and cause a denial of service.
Affected Systems and Versions
The versions affected by this vulnerability include TensorFlow versions greater than or equal to 2.5.0 and less than 2.5.1, versions greater than or equal to 2.4.0 and less than 2.4.3, and versions less than 2.3.4.
Exploitation Mechanism
An attacker can exploit this vulnerability by crafting a malicious TFLite model that triggers the null pointer dereference flaw, leading to the crash and denial of service.
Mitigation and Prevention
This section will provide guidance on mitigating and preventing the CVE-2021-37688 vulnerability in TensorFlow Lite.
Immediate Steps to Take
Users are advised to update their TensorFlow installations to version 2.6.0, where the issue has been patched. For older versions, patches are available in versions 2.5.1, 2.4.3, and 2.3.4 to address the vulnerability.
Long-Term Security Practices
To enhance security, users should follow best practices such as regularly updating software, using secure code development practices, and staying informed about security advisories.
Patching and Updates
Regularly check for updates from TensorFlow and apply patches as soon as they are released to ensure that the latest security fixes are in place.