medium
5.5
CWE
369
Advisory Published
Advisory Published
Updated

CVE-2021-37660: Division by 0 in inplace operations in TensorFlow

First published: Thu Aug 12 2021(Updated: )

### Impact An attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0: ```python import tensorflow as tf tf.raw_ops.InplaceSub(x=[],i=[-99,-1,-1],v=[1,1,1]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/inplace_ops.cc#L283) has a logic error: it should skip processing if `x` and `v` are empty but the code uses `||` instead of `&&`. ### Patches We have patched the issue in GitHub commit [e86605c0a336c088b638da02135ea6f9f6753618](https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618). 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.

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/e86605c0a336c088b638da02135ea6f9f6753618

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Reference Links

Frequently Asked Questions

  • What is the severity of CVE-2021-37660?

    CVE-2021-37660 has a medium severity rating due to the potential for a denial of service via a floating point exception.

  • How do I fix CVE-2021-37660?

    To fix CVE-2021-37660, upgrade to a patched version of TensorFlow, such as 2.5.1 or newer.

  • Which versions of TensorFlow are affected by CVE-2021-37660?

    CVE-2021-37660 affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and specific release candidates of 2.6.0.

  • What type of vulnerability is CVE-2021-37660?

    CVE-2021-37660 is a vulnerability that allows an attacker to trigger a floating point exception through crafted arguments.

  • Is there a workaround for CVE-2021-37660?

    There is no official workaround for CVE-2021-37660; the recommended action is to update to a secure version.

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