CVE-2020-15195: Heap buffer overflow in Tensorflow

Published Sep 25, 2020
·
Updated

Impact The implementation of SparseFillEmptyRowsGrad uses a double indexing pattern: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparsefillemptyrowsop.cc#L263-L269

It is possible for reverseindexmap(i) to be an index outside of bounds of gradvalues, thus resulting in a heap buffer overflow.

Patches We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

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

Other sources

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the implementation of SparseFillEmptyRowsGrad uses a double indexing pattern. It is possible for reverseindexmap(i) to be an index outside of bounds of gradvalues, thus resulting in a heap buffer overflow. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Affected Software

21 affected componentsFixes available
pip/tensorflow-gpu=2.3.0
2.3.1
pip/tensorflow-gpu=2.2.0
2.2.1
pip/tensorflow-gpu>=2.1.0<2.1.2
2.1.2
pip/tensorflow-gpu>=2.0.0<2.0.3
2.0.3
pip/tensorflow-gpu<1.15.4
1.15.4
pip/tensorflow-cpu=2.3.0
2.3.1
pip/tensorflow-cpu=2.2.0
2.2.1
pip/tensorflow-cpu>=2.1.0<2.1.2
2.1.2
pip/tensorflow-cpu>=2.0.0<2.0.3
2.0.3
pip/tensorflow-cpu<1.15.4
1.15.4
pip/tensorflow=2.3.0
2.3.1
pip/tensorflow=2.2.0
2.2.1
pip/tensorflow>=2.1.0<2.1.2
2.1.2
pip/tensorflow>=2.0.0<2.0.3
2.0.3
pip/tensorflow<1.15.4
1.15.4
Google TensorFlow<1.15.4
Google TensorFlow>=2.0.0<2.0.3
Google TensorFlow>=2.1.0<2.1.2
Google TensorFlow>=2.2.0<2.2.1
Google TensorFlow>=2.3.0<2.3.1
openSUSE Leap=15.2

Event History

Sep 25, 2020
Advisory Published
via GitHub·06:28 PM
CVE Published
via MITRE·06:40 PM
Data Sourced
via MITRE·06:40 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·07:15 PM
RemedyDescriptionSeverityWeaknessAffected Software

Frequently Asked Questions

1

What is the severity of CVE-2020-15195?

CVE-2020-15195 has been rated as a high severity vulnerability due to its potential impact on the application's performance and security.

2

How do I fix CVE-2020-15195?

To fix CVE-2020-15195, update TensorFlow to version 2.3.1 or later.

3

Which versions of TensorFlow are affected by CVE-2020-15195?

CVE-2020-15195 affects TensorFlow versions 2.3.0, 2.2.0, 2.1.0, 2.0.0, and all versions up to 1.15.4.

4

Is CVE-2020-15195 related to TensorFlow GPU or CPU?

CVE-2020-15195 impacts both TensorFlow GPU and TensorFlow CPU versions.

5

Where can I find more information about CVE-2020-15195?

For more information about CVE-2020-15195, refer to the official TensorFlow GitHub repository and security announcements.

Contact

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