Upstream information
Description
TensorFlow is an open source platform for machine learning. If `QuantizedBiasAdd` is given `min_input`, `max_input`, `min_bias`, `max_bias` tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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