medium
5.5
CWE
369
Advisory Published
Advisory Published
Updated

CVE-2021-37636: Floating point exception in `SparseDenseCwiseDiv` in TensorFlow

First published: Thu Aug 12 2021(Updated: )

### Impact The implementation of `tf.raw_ops.SparseDenseCwiseDiv` is vulnerable to a division by 0 error: ```python import tensorflow as tf import numpy as np tf.raw_ops.SparseDenseCwiseDiv( sp_indices=np.array([[4]]), sp_values=np.array([-400]), sp_shape=np.array([647.]), dense=np.array([0])) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L56) uses a common class for all binary operations but fails to treat the division by 0 case separately. ### Patches We have patched the issue in GitHub commit [d9204be9f49520cdaaeb2541d1dc5187b23f31d9](https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9). 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
Google TensorFlow>=2.3.0<2.3.4
Google TensorFlow>=2.4.0<2.4.3
Google TensorFlow=2.5.0
Google TensorFlow=2.6.0-rc0
Google TensorFlow=2.6.0-rc1
Google TensorFlow=2.6.0-rc2
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

Remedy

https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9

Never miss a vulnerability like this again

Sign up to SecAlerts for real-time vulnerability data matched to your software, aggregated from hundreds of sources.

Read MoreStart Free Trial

Reference Links

Frequently Asked Questions

  • What is the severity of CVE-2021-37636?

    CVE-2021-37636 is classified as a high-severity vulnerability due to the potential for division by zero errors in TensorFlow.

  • How do I fix CVE-2021-37636?

    To resolve CVE-2021-37636, upgrade TensorFlow to version 2.5.1 or later.

  • What versions of TensorFlow are affected by CVE-2021-37636?

    CVE-2021-37636 affects TensorFlow versions between 2.3.0 and 2.4.3, as well as 2.5.0 and 2.6.0-rc0, 2.6.0-rc1, and 2.6.0-rc2.

  • What mitigations can be taken for CVE-2021-37636 before upgrading?

    Before upgrading, ensure proper input validation to prevent cases that could lead to a division by zero.

  • Who is affected by CVE-2021-37636?

    Developers and organizations using the specified vulnerable versions of TensorFlow are at risk of encountering this vulnerability.

Company

Resources

Contact

SecAlerts Pty Ltd.
132 Wickham Terrace
Fortitude Valley,
QLD 4006, Australia
info@secalerts.co
By using SecAlerts services, you agree to our services end-user license agreement. This website is safeguarded by reCAPTCHA and governed by the Google Privacy Policy and Terms of Service. All names, logos, and brands of products are owned by their respective owners, and any usage of these names, logos, and brands for identification purposes only does not imply endorsement. If you possess any content that requires removal, please get in touch with us.
© 2025 SecAlerts Pty Ltd.
ABN: 70 645 966 203, ACN: 645 966 203