CVE-2022-23572 : Vulnerability Insights and Analysis
Learn about CVE-2022-23572 affecting TensorFlow >= 2.5.3, < 2.7.1. Understand the impact, technical details, and mitigation steps for this medium severity vulnerability.
Tensorflow is an Open Source Machine Learning Framework where under certain scenarios, TensorFlow can fail to specialize a type during shape inference, leading to a vulnerability. This vulnerability has been identified as CVE-2022-23572.
Understanding CVE-2022-23572
This section delves into the details of the vulnerability, its impact, technical aspects, and steps to mitigate the risks.
What is CVE-2022-23572?
TensorFlow can encounter a crash when it fails to specialize a type during shape inference. This situation arises due to a function 'DCHECK,' causing an assertion failure in debug builds, and in certain scenarios crashing the system.
The Impact of CVE-2022-23572
The impact of this vulnerability is considered medium with a base score of 6.5. The availability impact is high as it can lead to crashes, though confidentiality and integrity impacts are none. Privileges required are low, and the attack complexity is low.
Technical Details of CVE-2022-23572
Understanding the vulnerability in-depth is crucial to implementing effective mitigation strategies.
Vulnerability Description
The vulnerability arises from TensorFlow's failure to specialize a type during shape inference, leading to assertion failures and system crashes.
Affected Systems and Versions
Versions of TensorFlow affected include >= 2.7.0 and < 2.7.1, >= 2.6.0 and < 2.6.3, and < 2.5.3.
Exploitation Mechanism
The vulnerability can be exploited in network environments with low complexity and low privileges required to carry out the attack.
Mitigation and Prevention
Taking immediate steps to address the vulnerability and adopting long-term security practices is crucial to safeguard systems from potential exploitation.
Immediate Steps to Take
Users are advised to update TensorFlow to version 2.8.0 or apply fixes available in versions 2.7.1 and 2.6.3. Implementing security patches promptly is recommended.
Long-Term Security Practices
Enhancing code review processes, monitoring exceptional conditions, and ensuring robust error handling mechanisms can prevent similar vulnerabilities in the future.
Patching and Updates
Regularly updating TensorFlow to the latest versions and staying informed about security advisories can help mitigate risks associated with CVE-2022-23572.