OpenAI披露AI辅助Linux内核漏洞研究
OpenAI称,其研究原型在受控环境中分析了2308个Linux内核候选发现,动态复现了1724个漏洞,并生成948个本地提权漏洞利用。公司利用这些结果确定漏洞报告的优先级,并为维护者审查开发候选补丁。OpenAI还将相关工作扩展为五阶段流程,以一款即将推出的网络安全模型为核心,覆盖漏洞发现、动态验证、可利用性评估和补丁生成;人工研究人员在报告和补丁提交前审核了输出结果。
报告称,AI可以支持面向广泛使用的关键软件的大规模漏洞发现与补丁工作流。报告同时指出,优先级判断和验证仍是实际运营中的瓶颈,而加强Linux等项目的安全可以保护下游系统和用户。
Security research that once required a separate, sustained investigation for each finding can increasingly be run as a systematic process. This document explores one of our efforts in this area.
Vulnerability discovery is becoming easier to scale, but prioritization and validation remain operational bottlenecks. We built a prototype to look for security flaws in the Linux kernel inside a controlled research environment. Our prototype identified and analyzed 2,308 candidate Linux kernel findings, dynamically reproduced 1,724 vulnerabilities, and produced 948 local privilege escalation (LPE) exploits that could allow an unprivileged local user to gain root access.
We used this evidence to prioritize vulnerabilities for reporting and developed candidate patches for maintainer review. Following guidance from the Linux kernel community, we began with critical vulnerabilities and are working with Patch the Planet partners on further reports and patches.
In June, as part of our Patch the Planet initiative, we shared that GPT‑5.5 Cyber had identified Linux kernel vulnerabilities and developed 24 local privilege escalation exploits to validate and report them. We expanded that work into a pipeline, powered by an upcoming cyber model, covering vulnerability discovery, dynamic validation, exploitability assessment, and patch generation. When it finished, human researchers reviewed the outputs and reported found vulnerabilities alongside patches.