CVE-2022-35973
Assigner: GitHub_M
Published: 2022-09-16T21:00:14
State: PUBLISHED
affected: product: tensorflow
vendor: tensorflow
versions: status: affected
version: < 2.7.2
status: affected
version: >= 2.8.0, < 2.8.1
status: affected
version: >= 2.9.0, < 2.9.1
descriptions: value: TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`, `max_a`, `min_b`, or `max_b` It gives a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48. 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. There are no known workarounds for this issue.
metrics: cvssV3_1: attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 5.9
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
problemTypes: descriptions: cweId: CWE-20
description: CWE-20: Improper Input Validation
type: CWE
source: advisory: GHSA-689c-r7h2-fv9v
discovery: UNKNOWN
title: Segfault in `QuantizedMatMul` in TensorFlow