CVE-2022-35965: TensorFlow - Denial of Service Vulnerability
Summary
CVE-2022-35965: Segfault in LowerBound and UpperBound 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-2022-35965 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 industries and research domains 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 LowerBound or UpperBound functions are given an empty sorted_inputs input. This results in a nullptr dereference, causing a segmentation fault and leading to a denial of service attack. An attacker can exploit this vulnerability to crash the TensorFlow application, rendering it unavailable for legitimate users. The issue has been patched in the GitHub commit bce3717eaef4f769019fd18e990464ca4a2efeea and will be included in TensorFlow 2.10.0. The fix has also been 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
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Workaround
There are no known workarounds for this vulnerability. It is necessary to update TensorFlow to the patched versions mentioned above.
Conclusion
The vulnerability in TensorFlow can lead to a denial of service attack, impacting the availability of machine learning applications. It is crucial to update TensorFlow to the patched versions or apply the respective patches to ensure the security and stability of the applications. For further support on vulnerability remediation, you can 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.
The vulnerability can be exploited to trigger a denial of service attack, causing the TensorFlow application to crash and become unavailable for legitimate users.
To fix the vulnerability, update TensorFlow to version 2.10.0 or apply the respective patches for TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2.
No, there are no known workarounds for this vulnerability. Updating TensorFlow to the patched versions is necessary.
You can find more information about this vulnerability in the GitHub commit bce3717eaef4f769019fd18e990464ca4a2efeea and the official TensorFlow documentation.
References
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