CVE-2022-41890: TensorFlow - BCast::ToShape Crash Vulnerability
Summary
CVE-2022-41890: CHECK fail in BCast overflow 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-2022-41890 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 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 crash when handling large input values in certain scenarios.
Vulnerability Detail
The vulnerability, identified as CVE-2022-41890, originates from a flaw in the BCast::ToShape function of TensorFlow. This function is responsible for converting input data into a shape that can be processed by the system. However, when given input larger than an int32, the function crashes instead of handling it properly as intended. This vulnerability can be triggered, for example, by passing large input to the b parameter in tf.experimental.numpy.outer function. The issue has been patched in the GitHub commit 8310bf8dd188ff780e7fc53245058215a05bdbe5 and will be included in TensorFlow 2.11. Additionally, the fix will be backported to TensorFlow 2.10.1, 2.9.3, and 2.8.4, as these versions are also affected and within the supported range. The severity of this vulnerability is rated as High.
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
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Workaround
There is no specific workaround provided for this vulnerability. Updating to the patched versions is the recommended solution.
Conclusion
In conclusion, TensorFlow is susceptible to a vulnerability that can cause a crash when handling large input values. This issue has been addressed in the latest versions of TensorFlow and the Bitnami TensorFlow package. It is crucial to update to the patched versions to ensure the proper handling of large input values and prevent potential disruptions in machine learning tasks. For further support on vulnerability remediation, please contact DevNack.com.
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FAQ
TensorFlow is an open source platform for machine learning that provides tools and libraries for developing and deploying machine learning models.
The vulnerability can lead to a crash in TensorFlow when handling large input values, potentially disrupting the execution of machine learning tasks.
You can use Vulert's playground at Vulert Scanner to check if your application is affected by this vulnerability. Vulert monitors and alerts in real-time for open-source vulnerabilities without requiring access to the code or installation.
No, only TensorFlow versions 2.8.4, 2.9.0 and above are affected. The vulnerability has been fixed in TensorFlow 2.11 and backported to 2.10.1, 2.9.3, and 2.8.4.
Yes, the vulnerability has been patched in TensorFlow 2.11 and backported to 2.10.1, 2.9.3, and 2.8.4. It is recommended to update to the fixed versions.
References
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