What’s Vulnerable › Vulnerabilities

CVE-2021-41196: Crash in `max_pool3d` when size argument is 0 or negative

• Severity: medium (CVSS 5.5 v3.1)
• Exploited in the wild: not listed in CISA KEV
• EPSS: 0.2% probability of exploitation in the next 30 days
• Public exploit or detection template: yes
• Published: 2021-11-05 · updated 2026-06-17
• Weakness: CWE-191

Description

TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Affected products

• tensorflow: before 2.4.4; from 2.5.0 before 2.5.2; from 2.6.0 before 2.6.1 — fixed in 2.4.4, 2.5.2, 2.6.1

How to fix

Upgrade to a fixed version: tensorflow 2.4.4, 2.5.2, 2.6.1. Check the vendor advisory for mitigations.

References

• https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b
• https://github.com/tensorflow/tensorflow/issues/51936
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8
• https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b
• https://github.com/tensorflow/tensorflow/issues/51936
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8

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