CVE-2021-29585: Division by zero in padding computation in TFLite

Published May 14, 2021
·
Updated

Impact The TFLite computation for size of output after padding, ComputeOutSize, does not check that the stride argument is not 0 before doing the division.

cc inline int ComputeOutSize(TfLitePadding padding, int imagesize, int filtersize, int stride, int dilationrate = 1) { int effectivefiltersize = (filtersize - 1) dilationrate + 1; switch (padding) { case kTfLitePaddingSame: return (imagesize + stride - 1) / stride; case kTfLitePaddingValid: return (imagesize + stride - effectivefiltersize) / stride; default: return 0; } } Users can craft special models such that ComputeOutSize is called with stride set to 0.

Patches We have patched the issue in GitHub commit 49847ae69a4e1a97ae7f2db5e217c77721e37948.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

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 has been reported by members of the Aivul Team from Qihoo 360.

Other sources

TensorFlow is an end-to-end open source platform for machine learning. The TFLite computation for size of output after padding, ComputeOutSize(https://github.com/tensorflow/tensorflow/blob/0c9692ae7b1671c983569e5d3de5565843d500cf/tensorflow/lite/kernels/padding.h#L43-L55), does not check that the stride argument is not 0 before doing the division. Users can craft special models such that ComputeOutSize is called with stride set to 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Affected Software

16 affected componentsFixes available
pip/tensorflow-gpu>=2.4.0<2.4.2
2.4.2
pip/tensorflow-gpu>=2.3.0<2.3.3
2.3.3
pip/tensorflow-gpu>=2.2.0<2.2.3
2.2.3
pip/tensorflow-gpu<2.1.4
2.1.4
pip/tensorflow-cpu>=2.4.0<2.4.2
2.4.2
pip/tensorflow-cpu>=2.3.0<2.3.3
2.3.3
pip/tensorflow-cpu>=2.2.0<2.2.3
2.2.3
pip/tensorflow-cpu<2.1.4
2.1.4
pip/tensorflow>=2.4.0<2.4.2
2.4.2
pip/tensorflow>=2.3.0<2.3.3
2.3.3
pip/tensorflow>=2.2.0<2.2.3
2.2.3
pip/tensorflow<2.1.4
2.1.4
Google TensorFlow<2.1.4
Google TensorFlow>=2.2.0<2.2.3
Google TensorFlow>=2.3.0<2.3.3
Google TensorFlow>=2.4.0<2.4.2

Event History

May 14, 2021
CVE Published
via MITRE·07:35 PM
Data Sourced
via MITRE·07:35 PM
DescriptionSeverityWeakness
May 21, 2021
Advisory Published
via GitHub·02:26 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-29585?

CVE-2021-29585 has been classified with a medium severity level due to its potential impact on the output computation in TensorFlow.

2

How do I fix CVE-2021-29585?

To remediate CVE-2021-29585, upgrade TensorFlow to versions 2.4.2, 2.3.3, 2.2.3, or 2.1.4.

3

Which versions of TensorFlow are affected by CVE-2021-29585?

CVE-2021-29585 affects TensorFlow versions below 2.1.4, and between 2.2.0 and 2.2.3, 2.3.0 and 2.3.3, as well as 2.4.0 and 2.4.2.

4

What is the nature of the vulnerability described in CVE-2021-29585?

CVE-2021-29585 is a vulnerability in the TensorFlow Lite padding computation that does not check for a zero stride, potentially leading to incorrect output sizes.

5

Who is the vendor associated with CVE-2021-29585?

CVE-2021-29585 is associated with Google, the vendor that maintains TensorFlow.

Contact

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