CVE-2021-37636: Floating point exception in `SparseDenseCwiseDiv` in TensorFlow
Impact The implementation of tf.rawops.SparseDenseCwiseDiv is vulnerable to a division by 0 error:
python import tensorflow as tf import numpy as np
tf.rawops.SparseDenseCwiseDiv( spindices=np.array([[4]]), spvalues=np.array([-400]), spshape=np.array([647.]), dense=np.array([0]))
The implementation 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.
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 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. In affected versions the implementation of tf.rawops.SparseDenseCwiseDiv is vulnerable to a division by 0 error. The implementation uses a common class for all binary operations but fails to treat the division by 0 case separately. We have patched the issue in GitHub 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.
Affected Software
Remediation
Recommended actions to resolve this vulnerability, in priority order.
- Upgrade
Upgrade
pip/tensorflow-gputo a version that resolves this vulnerability.Fixed in 2.5.1 - Upgrade
Upgrade
pip/tensorflow-gputo a version that resolves this vulnerability.Fixed in 2.4.3 - Upgrade
Upgrade
pip/tensorflow-gputo a version that resolves this vulnerability.Fixed in 2.3.4 - Upgrade
Upgrade
pip/tensorflow-cputo a version that resolves this vulnerability.Fixed in 2.5.1 - Upgrade
Upgrade
pip/tensorflow-cputo a version that resolves this vulnerability.Fixed in 2.4.3 - Upgrade
Upgrade
pip/tensorflow-cputo a version that resolves this vulnerability.Fixed in 2.3.4 - Upgrade
Upgrade
pip/tensorflowto a version that resolves this vulnerability.Fixed in 2.5.1 - Upgrade
Upgrade
pip/tensorflowto a version that resolves this vulnerability.Fixed in 2.4.3 - Upgrade
Upgrade
pip/tensorflowto a version that resolves this vulnerability.Fixed in 2.3.4 - Upgrade
Upgrade
tensorflowto a version that resolves this vulnerability.Fixed in 2.6.0 - Upgrade
Upgrade
tensorflowto a version that resolves this vulnerability.Fixed in 2.5.1 - Upgrade
Upgrade
tensorflowto a version that resolves this vulnerability.Fixed in 2.4.3 - Upgrade
Upgrade
tensorflowto a version that resolves this vulnerability.Fixed in 2.3.4 - Upgrade
Upgrade to a fixed release to a version that resolves this vulnerability.
Patch d9204be9f49520cdaaeb2541d1dc5187b23f31d9
Event History
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.