Vulnerability Information
Although we use advanced large model technology, its output may still contain inaccurate or outdated information.Shenlong tries to ensure data accuracy, but please verify and judge based on the actual situation.
Vulnerability Title
Segfault in `QuantizedMatMul` in TensorFlow
Vulnerability 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.
CVSS Information
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Vulnerability Type
输入验证不恰当
Vulnerability Title
Google TensorFlow 输入验证错误漏洞
Vulnerability Description
Google TensorFlow是美国谷歌（Google）公司的一套用于机器学习的端到端开源平台。 Google TensorFlow 存在输入验证错误漏洞，该漏洞源于如果为 QuantizedMatMul 提供以下非标量输入： min_a 、 max_a 、 min_b 或 max_b ，它会给出一个可用于触发拒绝服务攻击的段错误。该漏洞将在 2.10.0 版本， 2.9.1 版本， 2.8.1 版本， 2.7.2 版本中得到修复。
CVSS Information
N/A
Vulnerability Type
N/A