CVE-2022-29212: TensorFlow TFLite Model Converter Crash
Summary
CVE-2022-29212: Core dump when loading TFLite models with quantization in TensorFlow. Affects tensorflow across 3 version ranges.
< 2.6.4
>= 2.7.0, < 2.7.2
>= 2.8.0, < 2.8.1
Fixed in 2.6.4, 2.7.2 or 2.8.1, 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-2022-29212 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 allows users to build and train models using various techniques such as deep learning, reinforcement learning, and more. It is widely used in both research and production environments for a wide range of applications.
Vulnerability Detail
The vulnerability (CVE-2022-29212) affects certain TFLite models that were created using the TFLite model converter in TensorFlow versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4. When these models are loaded in the TFLite interpreter, they would crash. The root cause of the issue is that during quantization, the scale of values could be greater than 1, but the code was assuming sub-unit scaling. As a result, when the code called QuantizeMultiplierSmallerThanOneExp, the TFLITE_CHECK_LT assertion would trigger and abort the process. This vulnerability can lead to denial of service (DoS) as the interpreter crashes when loading the affected models.
How To Fix
Fixed versions by release line
The minimum fixed version depends on the release line you run.
-
< 2.6.42.6.4 -
>= 2.7.0, < 2.7.22.7.2 -
>= 2.8.0, < 2.8.12.8.1
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Workaround
There is no specific workaround mentioned for this vulnerability.
Conclusion
The vulnerability (CVE-2022-29212) in TensorFlow's TFLite model converter can cause crashes in the TFLite interpreter when loading certain models. It is recommended to update TensorFlow to versions 2.9.0, 2.8.1, 2.7.2, or 2.6.4 to mitigate this vulnerability. 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.
TFLite is a TensorFlow library for running machine learning models on mobile and embedded devices.
Versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4 are affected by this vulnerability.
The vulnerability can lead to denial of service (DoS) as the TFLite interpreter crashes when loading the affected models.
To fix this vulnerability, update TensorFlow to versions 2.9.0, 2.8.1, 2.7.2, or 2.6.4, which contain a patch for this issue.
References
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