CVE-2022-41896: TensorFlow - Crash due to input size exceeding allowed max size
Summary
CVE-2022-41896: tf.raw_ops.Mfcc crashes in Tensorflow. Affects tensorflow across 3 version ranges.
< 2.8.4
>= 2.9.0, < 2.9.3
>= 2.10.0, < 2.10.1
Fixed in 2.8.4, 2.9.3 or 2.10.1, 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-2022-41896 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. It offers support for both CPU and GPU computations, making it suitable for a range of hardware configurations. However, a vulnerability has been discovered in TensorFlow that can lead to a crash if the input size exceeds the allowed maximum size.
Vulnerability Detail
The vulnerability in TensorFlow arises when the ThreadUnsafeUnigramCandidateSampler is provided with an input filterbank_channel_count that is greater than the allowed maximum size. This can cause TensorFlow to crash, potentially disrupting any ongoing machine learning processes or applications relying on TensorFlow. The issue has been identified and patched in the GitHub commit 39ec7eaf1428e90c37787e5b3fbd68ebd3c48860. The fix will be included in TensorFlow 2.11 and has also been backported to TensorFlow 2.10.1, 2.9.3, and 2.8.4, 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.
-
< 2.8.42.8.4 -
>= 2.9.0, < 2.9.32.9.3 -
>= 2.10.0, < 2.10.12.10.1
Tip — Not sure which release line you're on? Vulert can find the fix for the version you are using. Scan free →
Conclusion
In conclusion, the vulnerability in TensorFlow can lead to a crash if provided with an input size exceeding the allowed maximum size. It is crucial to update TensorFlow to the latest patched version to mitigate this vulnerability and ensure the security of machine learning processes and applications. For further support on vulnerability remediation, you can reach out to DevNack.com.
See every vulnerability recorded for tensorflow →
FAQ
TensorFlow is an open source platform for machine learning that provides a wide range of tools and resources for developing and deploying machine learning models.
The vulnerability can cause TensorFlow to crash if provided with an input size exceeding the allowed maximum size. This can disrupt ongoing machine learning processes or applications relying on TensorFlow.
To fix the vulnerability, it is recommended to update TensorFlow to the latest patched version available. This ensures that the issue is addressed and the software remains secure.
The vulnerability affects TensorFlow versions 2.8.4, 2.9.3, 2.10.1, and 2.11. Users on these versions are advised to update to the respective patched versions.
You can find more information about this vulnerability, including the GitHub commit and the official fix, in the provided source link: https://github.com/bitnami/vulndb/tree/main/data/tensorflow/BIT-tensorflow-2022-41896.json
References
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