CVE-2021-37675 – tensorflow

Package

Manager: pip
Name: tensorflow
Vulnerable Version: >=0 <2.3.4 || >=2.4.0 <2.4.3 || =2.5.0 || >=2.5.0 <2.5.1

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: 0.00012 pctl0.01115

Details

Division by 0 in most convolution operators ### Impact Most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash: ```python import tensorflow as tf tf.compat.v1.disable_v2_behavior() tf.raw_ops.Conv2D( input = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32), filter = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32), strides = [1, 1, 1, 1], padding = "SAME") ``` The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. ### Patches We have patched the issue in GitHub commit [8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4](https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4). 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](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 by Yakun Zhang of Baidu Security.

Metadata

Created: 2021-08-25T14:41:29Z
Modified: 2024-11-13T21:13:06Z
Source: https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/08/GHSA-9c8h-2mv3-49ww/GHSA-9c8h-2mv3-49ww.json
CWE IDs: ["CWE-369"]
Alternative ID: GHSA-9c8h-2mv3-49ww
Finding: F020
Auto approve: 1