CVE-2021-29605: Integer overflow in TFLite memory allocation

Published May 14, 2021
·
Updated

Impact The TFLite code for allocating TFLiteIntArrays is vulnerable to an integer overflow issue:

cc int TfLiteIntArrayGetSizeInBytes(int size) { static TfLiteIntArray dummy; return sizeof(dummy) + sizeof(dummy.data[0]) size; }

An attacker can craft a model such that the size multiplier is so large that the return value overflows the int datatype and becomes negative. In turn, this results in invalid value being given to malloc:

cc TfLiteIntArray TfLiteIntArrayCreate(int size) { TfLiteIntArray ret = (TfLiteIntArray)malloc(TfLiteIntArrayGetSizeInBytes(size)); ret->size = size; return ret; }

In this case, ret->size would dereference an invalid pointer.

Patches We have patched the issue in GitHub commit 7c8cc4ec69cd348e44ad6a2699057ca88faad3e5.

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 code for allocating TFLiteIntArrays is vulnerable to an integer overflow issue(https://github.com/tensorflow/tensorflow/blob/4ceffae632721e52bf3501b736e4fe9d1221cdfa/tensorflow/lite/c/common.c#L24-L27). An attacker can craft a model such that the size multiplier is so large that the return value overflows the int datatype and becomes negative. In turn, this results in invalid value being given to malloc(https://github.com/tensorflow/tensorflow/blob/4ceffae632721e52bf3501b736e4fe9d1221cdfa/tensorflow/lite/c/common.c#L47-L52). In this case, ret->size would dereference an invalid pointer. 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-2021-29605?

CVE-2021-29605 is rated as a medium severity vulnerability due to the potential for integer overflow issues in TensorFlow.

2

How do I fix CVE-2021-29605?

To fix CVE-2021-29605, upgrade TensorFlow to versions 2.4.2, 2.3.3, 2.2.3, or 2.1.4.

3

What versions of TensorFlow are affected by CVE-2021-29605?

CVE-2021-29605 affects TensorFlow versions prior to 2.1.4 and between 2.2.0 to 2.2.3, 2.3.0 to 2.3.3, and 2.4.0 to 2.4.2.

4

What kind of vulnerability is CVE-2021-29605 classified as?

CVE-2021-29605 is classified as an integer overflow vulnerability related to the allocation of TFLiteIntArray objects.

5

Who is affected by CVE-2021-29605?

Developers using vulnerable versions of TensorFlow for machine learning applications may be affected by CVE-2021-29605.

Contact

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