CVE-2021-29580: TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined ...

Description

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. 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.

Metrics

CVSS 3.1

5.5/10

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

EPSS Probability

0.19%

8.7th percentile

Probability of exploitation in the next 30 days. Learn more

Weakness Enumeration

CWE-908

Affected Software

Vendor	Product	Versions
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

References

https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925Patch, Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgpExploit, Patch, Third Party Advisory
https://github.com/tensorflow/tensorflow/commit/32fdcbff9d06d010d908fcc4bd4b36eb3ce15925Patch, Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x8h6-xgqx-jqgpExploit, Patch, Third Party Advisory

Timeline

Published: May 14, 2021
Last Modified: Jun 17, 2026
Status: Modified

Frequently Asked Questions

What is CVE-2021-29580?

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. 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.

How severe is CVE-2021-29580?

CVE-2021-29580 has a CVSS score of 5.5/10 (MEDIUM severity). The EPSS model estimates a 0.19% probability of exploitation in the next 30 days.

How do I fix CVE-2021-29580?

Check the vendor references and advisories linked above for patched versions and mitigation guidance. You can also run a Strix scan to test if your systems are affected.