CVE-2021-29600: Division by zero in TFLite's implementation of `OneHot`

Published May 14, 2021
·
Updated

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

cc int prefixdimsize = 1; for (int i = 0; i < opcontext.axis; ++i) { prefixdimsize = opcontext.indices->dims->data[i]; } const int suffixdimsize = NumElements(opcontext.indices) / prefixdimsize;

An attacker can craft a model such that at least one of the dimensions of indices would be 0. In turn, the prefixdimsize value would become 0.

Patches We have patched the issue in GitHub commit 3ebedd7e345453d68e279cfc3e4072648e5e12e5.

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 OneHot TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/f61c57bd425878be108ec787f4d96390579fb83e/tensorflow/lite/kernels/onehot.cc#L68-L72). An attacker can craft a model such that at least one of the dimensions of indices would be 0. In turn, the prefixdimsize value would become 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·07:21 PM
Data Sourced
via MITRE·07:21 PM
DescriptionSeverityWeakness
May 21, 2021
Advisory Published
via GitHub·02:28 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-29600?

CVE-2021-29600 has a medium severity rating due to the potential for division by zero errors.

2

How do I fix CVE-2021-29600?

To mitigate CVE-2021-29600, update TensorFlow to version 2.4.2 or later.

3

Which versions of TensorFlow are affected by CVE-2021-29600?

CVE-2021-29600 affects TensorFlow versions up to 2.4.1, including versions 2.0.0 to 2.1.4, and 2.2.0 to 2.2.3, as well as 2.3.0 to 2.3.3.

4

What kind of vulnerability is CVE-2021-29600?

CVE-2021-29600 is classified as a division by zero vulnerability in the OneHot operator of TensorFlow.

5

Is CVE-2021-29600 present in TensorFlow lite?

Yes, CVE-2021-29600 specifically impacts the implementation of the OneHot operator within TensorFlow Lite.

Contact

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