CVE-2021-41196 – tensorflow

Package

Manager: pip
Name: tensorflow
Vulnerable Version: >=2.6.0 <2.6.1 || >=2.5.0 <2.5.2 || >=0 <2.4.4

Severity

Level: Medium

CVSS v3.1: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

CVSS v4.0: CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

EPSS: 0.00049 pctl0.1474

Details

Crash in `max_pool3d` when size argument is 0 or negative ### Impact The Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative: ```python import tensorflow as tf pool_size = [2, 2, 0] layer = tf.keras.layers.MaxPooling3D(strides=1, pool_size=pool_size) input_tensor = tf.random.uniform([3, 4, 10, 11, 12], dtype=tf.float32) res = layer(input_tensor) ``` 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. ### Patches We have patched the issue in GitHub commit [12b1ff82b3f26ff8de17e58703231d5a02ef1b8b](https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b) (merging [#51975](https://github.com/tensorflow/tensorflow/pull/51975)). 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. ### 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 externally via a [GitHub issue](https://github.com/tensorflow/tensorflow/issues/51936).

Metadata

Created: 2021-11-10T19:36:21Z
Modified: 2024-11-13T21:46:28Z
Source: https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/11/GHSA-m539-j985-hcr8/GHSA-m539-j985-hcr8.json
CWE IDs: ["CWE-191"]
Alternative ID: GHSA-m539-j985-hcr8
Finding: F111
Auto approve: 1