medium
5.5
CWE
369
Advisory Published
Advisory Published
Updated

CVE-2021-37680: Division by zero in TFLite in TensorFlow

First published: Thu Aug 12 2021(Updated: )

### Impact The implementation of fully connected layers in TFLite is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/fully_connected.cc#L226): ```cc const int batch_size = input_size / filter->dims->data[1]; ``` An attacker can craft a model such that `filter->dims->data[1]` is 0. ### Patches We have patched the issue in GitHub commit [718721986aa137691ee23f03638867151f74935f](https://github.com/tensorflow/tensorflow/commit/718721986aa137691ee23f03638867151f74935f). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) 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. Concurrently, it has also been reported by Yakun Zhang of Baidu Security.

Credit: security-advisories@github.com security-advisories@github.com

Affected SoftwareAffected VersionHow to fix
pip/tensorflow-gpu=2.5.0
2.5.1
pip/tensorflow-gpu>=2.4.0<2.4.3
2.4.3
pip/tensorflow-gpu<2.3.4
2.3.4
pip/tensorflow-cpu=2.5.0
2.5.1
pip/tensorflow-cpu>=2.4.0<2.4.3
2.4.3
pip/tensorflow-cpu<2.3.4
2.3.4
pip/tensorflow=2.5.0
2.5.1
pip/tensorflow>=2.4.0<2.4.3
2.4.3
pip/tensorflow<2.3.4
2.3.4
TensorFlow Keras>=2.3.0<2.3.4
TensorFlow Keras>=2.4.0<2.4.3
TensorFlow Keras=2.5.0
TensorFlow Keras=2.6.0-rc0
TensorFlow Keras=2.6.0-rc1
TensorFlow Keras=2.6.0-rc2

Remedy

https://github.com/tensorflow/tensorflow/commit/718721986aa137691ee23f03638867151f74935f

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Reference Links

Frequently Asked Questions

  • What is the severity of CVE-2021-37680?

    CVE-2021-37680 has a severity rating of high due to the potential for denial of service through a division by zero error.

  • How do I fix CVE-2021-37680?

    To fix CVE-2021-37680, upgrade to TensorFlow version 2.5.1 or later.

  • Which versions of TensorFlow are affected by CVE-2021-37680?

    TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and 2.5.0, along with pre-releases 2.6.0-rc0, 2.6.0-rc1, and 2.6.0-rc2, are affected by CVE-2021-37680.

  • What is the nature of the vulnerability in CVE-2021-37680?

    CVE-2021-37680 is a division by zero vulnerability that can cause crashes in applications using the affected TensorFlow versions.

  • Is there a workaround for CVE-2021-37680 if I can't update TensorFlow?

    There is no officially recommended workaround for CVE-2021-37680, so updating TensorFlow to a secure version is advised.

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