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GHSA-5w96-866f-6rm8: TensorFlow has Floating Point Exception in TFLite in conv kernel

Impact

Constructing a tflite model with a paramater filter_input_channel of less than 1 gives a FPE.

Patches

We have patched the issue in GitHub commit 34f8368c535253f5c9cb3a303297743b62442aaa.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.

ghsa
#vulnerability#git

Package

pip tensorflow (pip)

Affected versions

< 2.11.1

Description

Impact

Constructing a tflite model with a paramater filter_input_channel of less than 1 gives a FPE.

Patches

We have patched the issue in GitHub commit 34f8368c535253f5c9cb3a303297743b62442aaa.

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by Wang Xuan of Qihoo 360 AIVul Team.

References

  • GHSA-5w96-866f-6rm8
  • tensorflow/tensorflow@34f8368

Published to the GitHub Advisory Database

Mar 24, 2023

Last updated

Mar 24, 2023

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CVE-2023-27579: Check filter_input_channel > 0 in conv kernel. · tensorflow/tensorflow@34f8368

TensorFlow is an end-to-end open source platform for machine learning. Constructing a tflite model with a paramater `filter_input_channel` of less than 1 gives a FPE. This issue has been patched in version 2.12. TensorFlow will also cherrypick the fix commit on TensorFlow 2.11.1.