CVE-2020-15207: Segfault and data corruption in tensorflow-lite

Published Sep 25, 2020
·
Updated

Impact To mimic Python's indexing with negative values, TFLite uses ResolveAxis to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/internal/reference/reduce.h#L68-L72

If the DCHECK does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. Patches We have patched the issue in 2d88f470dea2671b430884260f3626b1fe99830a and will release patch releases for all versions between 1.15 and 2.3.

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-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, to mimic Python's indexing with negative values, TFLite uses ResolveAxis to convert negative values to positive indices. However, the only check that the converted index is now valid is only present in debug builds. If the DCHECK does not trigger, then code execution moves ahead with a negative index. This, in turn, results in accessing data out of bounds which results in segfaults and/or data corruption. The issue is patched in commit 2d88f470dea2671b430884260f3626b1fe99830a, 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·06:45 PM
Data Sourced
via MITRE·06:45 PM
DescriptionSeverityWeakness
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Frequently Asked Questions

1

What is the severity of CVE-2020-15207?

CVE-2020-15207 has not been explicitly assigned a CVSS score, but it can lead to potential out-of-bounds read vulnerabilities.

2

How do I fix CVE-2020-15207?

To fix CVE-2020-15207, update TensorFlow to version 2.3.1 or later.

3

Which versions of TensorFlow are affected by CVE-2020-15207?

CVE-2020-15207 affects TensorFlow versions 2.3.0, 2.2.0, 2.1.0, 2.0.0, and 1.15.4.

4

Is CVE-2020-15207 specific to TensorFlow GPU or CPU?

CVE-2020-15207 affects both TensorFlow GPU and TensorFlow CPU installations.

5

Can CVE-2020-15207 affect TensorFlow Lite users?

Yes, CVE-2020-15207 potentially affects users of TensorFlow Lite due to how it handles negative indexing.

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