cve/2021/CVE-2021-41196.md

### [CVE-2021-41196](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-41196)
![](https://img.shields.io/static/v1?label=Product&message=tensorflow&color=blue)
![](https://img.shields.io/static/v1?label=Version&message=n%2Fa&color=blue)
![](https://img.shields.io/static/v1?label=Vulnerability&message=CWE-191%3A%20Integer%20Underflow%20(Wrap%20or%20Wraparound)&color=brighgreen)

### 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.

### POC

#### Reference
No PoCs from references.

#### Github
- https://github.com/ARPSyndicate/cvemon
- https://github.com/adwisatya/SnykVulndb