CVE-2021-29595: Division by zero in TFLite's implementation of `DepthToSpace`

Published May 14, 2021
·
Updated

Impact The implementation of the DepthToSpace TFLite operator is vulnerable to a division by zero error:

cc const int blocksize = params->blocksize; ... const int inputchannels = input->dims->data[3]; ... int outputchannels = inputchannels / blocksize / blocksize;

An attacker can craft a model such that params->blocksize is 0.

Patches We have patched the issue in GitHub commit 106d8f4fb89335a2c52d7c895b7a7485465ca8d9. 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 implementation of the DepthToSpace TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/depthtospace.cc#L63-L69). An attacker can craft a model such that params->blocksize is 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·07:22 PM
Data Sourced
via MITRE·07:22 PM
DescriptionSeverityWeakness
May 21, 2021
Advisory Published
via GitHub·02:27 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-29595?

CVE-2021-29595 has a severity rating of Medium due to its potential for causing a division by zero error.

2

How do I fix CVE-2021-29595?

You can address CVE-2021-29595 by upgrading TensorFlow to version 2.4.2 or higher.

3

Which versions of TensorFlow are affected by CVE-2021-29595?

CVE-2021-29595 affects TensorFlow versions prior to 2.1.4, and between 2.2.0 and 2.2.3, 2.3.0 and 2.3.3, and 2.4.0 and 2.4.2.

4

Is CVE-2021-29595 present in TensorFlow GPU installations?

Yes, CVE-2021-29595 affects both TensorFlow CPU and GPU installations.

5

What should developers do about CVE-2021-29595?

Developers should review their applications for dependencies on vulnerable TensorFlow versions and consider upgrading.

Contact

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