Speaker
Description
AI-assisted tools are producing an increasing number of Linux kernel bug findings. While these tools can uncover genuine bugs, many findings still require validation before they can be treated as actionable issues. Reports may be false positives, lack a working reproducer, duplicate existing issues, or fail to trigger under the reported conditions.
We would like to share our experience triaging over 1,000 Linux kernel bugs, with a focus on validating findings, understanding the privilege required to trigger them, and assessing their security impact. These steps help distinguish false positives and low-impact corner cases from bugs that deserve higher remediation priority.
To support this process, we are developing a continuous Linux kernel bug collection and verify platform[1] inspired by syzbot. It aggregates findings from multiple sources, like sashiko, and attempts to generate and execute reproducers for them. For bugs with runtime evidence, the platform further analyzes trigger privilege, impact, severity and generating patches.
[1] https://lore.kernel.org/all/20260830115546.3942129-1-yuantan098@gmail.com/