CVE-2022-35971: TensorFlow - Denial of Service Vulnerability
Summary
CVE-2022-35971: CHECK fail in FakeQuantWithMinMaxVars in TensorFlow. Affects tensorflow across 3 version ranges.
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
>= 2.9.0, < 2.9.1
Fixed in 2.7.2, 2.8.1 or 2.9.1, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow-gpu · PyPI
- tensorflow · PyPI
The same CVE-2022-35971 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
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Background
TensorFlow is an open source platform for machine learning. It provides a comprehensive ecosystem of tools, libraries, and resources for developing and deploying machine learning models. TensorFlow is widely used in various domains, including research, industry, and academia. This vulnerability affects versions 2.7.0 to 2.7.2, 2.8.0 to 2.8.1, 2.9.0 to 2.9.1, and 2.10-rc0.0 to 2.10-rc3.0 of TensorFlow.
Vulnerability Detail
The vulnerability, identified as CVE-2022-35971, resides in the FakeQuantWithMinMaxVars function of TensorFlow. When provided with min or max tensors of a nonzero rank, the function triggers a CHECK fail, leading to a denial of service attack. This vulnerability can be exploited by an attacker to disrupt the availability of TensorFlow applications. The issue has been patched in the GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0 and will be included in TensorFlow 2.10.0. Additionally, the fix will be backported to TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
>= 2.7.0, < 2.7.22.7.2 -
>= 2.8.0, < 2.8.12.8.1 -
>= 2.9.0, < 2.9.12.9.1
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Conclusion
The vulnerability in TensorFlow can lead to a denial of service attack if exploited. It is crucial to update TensorFlow to the latest version or apply the provided patches to mitigate the risk. Regularly updating TensorFlow and staying informed about security patches is essential for maintaining the security and stability of TensorFlow applications. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides tools and resources for developing and deploying machine learning models.
This vulnerability can be exploited by an attacker to trigger a denial of service attack, leading to the disruption of TensorFlow applications.
Versions 2.7.0 to 2.7.2, 2.8.0 to 2.8.1, 2.9.0 to 2.9.1, and 2.10-rc0.0 to 2.10-rc3.0 of TensorFlow are affected.
Yes, the vulnerability has been patched in the GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0 and will be included in TensorFlow 2.10.0. The fix will also be backported to TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2.
Users can update their TensorFlow installation by following the official documentation provided by TensorFlow.
References
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