Upstream information
Description
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.SUSE information
Overall state of this security issue: Does not affect SUSE products
This issue is currently rated as having critical severity.
| National Vulnerability Database | |
|---|---|
| Base Score | 7.5 |
| Vector | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |
| Attack Vector | Network |
| Attack Complexity | Low |
| Privileges Required | None |
| User Interaction | None |
| Scope | Unchanged |
| Confidentiality Impact | None |
| Integrity Impact | None |
| Availability Impact | High |
| CVSSv3 Version | 3.1 |
List of released packages
| Product(s) | Fixed package version(s) | References |
|---|---|---|
| openSUSE Tumbleweed |
| Patchnames: openSUSE-Tumbleweed-2024-12355 |
SUSE Timeline for this CVE
CVE page created: Sat Sep 17 09:33:47 2022CVE page last modified: Tue Sep 3 19:26:12 2024