CVE-2022-35997: Denial of Service Vulnerability in TensorFlow
Summary
CVE-2022-35997: CHECK fail in tf.sparse.cross in TensorFlow. Affects tensorflow across 3 version ranges.
< 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-2022-35997 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 building and deploying machine learning models. TensorFlow is widely used in various industries and research fields for tasks such as image recognition, natural language processing, and recommendation systems. However, a vulnerability has been discovered in TensorFlow that can lead to a denial of service attack.
Vulnerability Detail
The vulnerability in TensorFlow occurs when the tf.sparse.cross function receives a non-scalar input separator. This triggers a CHECK fail, which can be exploited to launch a denial of service attack. The impact of this vulnerability is the potential disruption of TensorFlow-based applications and services. The issue has been patched in the latest versions of TensorFlow, and the fix will be included in TensorFlow 2.10.0. Additionally, the fix has been backported to TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, which are still within the supported range.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 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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Workaround
There are no known workarounds for this vulnerability. It is essential to apply the provided patches or update to the latest version of TensorFlow to mitigate the risk of a denial of service attack.
Conclusion
The vulnerability in TensorFlow can lead to a denial of service attack. It is crucial to update to the latest patched version of TensorFlow or apply the provided patches for affected versions. Failure to do so may result in the disruption of TensorFlow-based applications and services. 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 building and deploying machine learning models.
The vulnerability can be exploited to launch a denial of service attack, potentially disrupting TensorFlow-based applications and services.
To fix the vulnerability, update TensorFlow to the latest patched version or apply the provided patches for affected versions.
No, there are no known workarounds for this vulnerability. It is crucial to apply the provided patches or update to the latest version of TensorFlow.
The patches for affected versions can be obtained from the official TensorFlow GitHub repository.
References
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