First published: Fri May 20 2022(Updated: )
TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.
Credit: security-advisories@github.com
Affected Software | Affected Version | How to fix |
---|---|---|
Google TensorFlow | <2.6.4 | |
Google TensorFlow | >=2.7.0<2.7.2 | |
Google TensorFlow | =2.7.0-rc0 | |
Google TensorFlow | =2.7.0-rc1 | |
Google TensorFlow | =2.8.0 | |
Google TensorFlow | =2.8.0-rc0 | |
Google TensorFlow | =2.8.0-rc1 | |
Google TensorFlow | =2.9.0-rc0 | |
Google TensorFlow | =2.9.0-rc1 |
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CVE-2022-29212 has a medium severity level as it can cause certain TFLite models to crash during runtime.
To fix CVE-2022-29212, you should update TensorFlow to version 2.9.0 or later, or any of the specified fixed versions.
CVE-2022-29212 affects TensorFlow versions prior to 2.6.4, 2.7.2, 2.8.1, and 2.9.0.
CVE-2022-29212 impacts certain TFLite models created using the TFLite model converter.
No, CVE-2022-29212 is not a remote code execution vulnerability; it specifically causes a crash in the TFLite interpreter.