CVE-2021-29606: Heap OOB read in TFLite

Published May 14, 2021
·
Updated

Impact A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of SplitV:

cc const int inputsize = SizeOfDimension(input, axisvalue);

If axisvalue is not a value between 0 and NumDimensions(input), then the SizeOfDimension function will access data outside the bounds of the tensor shape array:

cc inline int SizeOfDimension(const TfLiteTensor t, int dim) { return t->dims->data[dim]; } Patches We have patched the issue in GitHub commit ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412.

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. A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of SplitV(https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/splitv.cc#L99). If axisvalue is not a value between 0 and NumDimensions(input), then the SizeOfDimension function(https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/kernelutil.h#L148-L150) will access data outside the bounds of the tensor shape array. 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·07:21 PM
Data Sourced
via MITRE·07:21 PM
DescriptionSeverityWeakness
Data Sourced
via NVD·08:15 PM
RemedyDescriptionSeverityWeaknessAffected Software
May 21, 2021
Advisory Published
via GitHub·02:28 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-29606?

CVE-2021-29606 has a high severity due to the potential for an out-of-bounds read on the heap.

2

How do I fix CVE-2021-29606?

To fix CVE-2021-29606, upgrade TensorFlow to version 2.4.2 or later.

3

Which versions of TensorFlow are affected by CVE-2021-29606?

CVE-2021-29606 affects TensorFlow versions earlier than 2.1.4, between 2.2.0 and 2.2.3, between 2.3.0 and 2.3.3, and between 2.4.0 and 2.4.2.

4

What types of TFLite models are impacted by CVE-2021-29606?

CVE-2021-29606 impacts TFLite models that contain specially crafted data, which leads to the vulnerability.

5

Is CVE-2021-29606 related to a specific TensorFlow component?

Yes, CVE-2021-29606 specifically affects the Split_V implementation within TensorFlow Lite.

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