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AI 代理让开源漏洞利用提速:仅凭补丁传闻即可触发攻击

Just a rumour of a bug is enough to find a security exploit these days

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Just a rumour of a bug is enough to find a security exploit these days

如今,仅仅是一个关于漏洞的传闻,就足以让人找到安全漏洞。

Anil Madhavapeddy is a professor of computer science at Cambridge and a core maintainer of the OCaml compiler. In this somewhat alarming post he reports that security issues in OCaml projects are seeing evidence of attempted exploits within minutes of patches being shared for discussion:

Anil Madhavapeddy 是剑桥大学的计算机科学教授,也是 OCaml 编译器的核心维护者。在这篇有些令人担忧的帖子中,他报告称,OCaml 项目中的安全问题在补丁被分享讨论后的几分钟内,就出现了被尝试利用的证据:

This normally takes a few days and a release within a week or two is reasonable. Within about ten minutes (!) this website was fielding probes for percent-encoded traversal sequences, indicating that automated watchers are keeping an eye on public repositories.

这通常需要几天时间,在一两周内发布一个版本是合理的。但在大约十分钟内(!),这个网站就收到了针对百分号编码的路径遍历序列的探测,这表明有自动化监视者在关注公共仓库。

Modern coding agents have become so effective at finding flaws that the slightest hint at a new bug can be enough information for them to find it, something Anil has been able to demonstrate using his own agents, switching to DeepSeek V4 Pro⁠ when Claude Fable refused the task.

现代编码代理在发现缺陷方面已经变得非常高效,以至于对某个新漏洞的丝毫提示就足以让它们找到它,Anil 已经能够用自己的代理演示这一点,在 Claude Fable 拒绝任务时,他切换到了 DeepSeek V4 Pro。

Anil points out that this rate of discovery appears incompatible with existing open source embargo practices for new issues. If an issue can become an exploit this fast, we need to figure out new processes for keeping our communities safe.

Anil 指出,这种发现速度似乎与现有的开源问题保密实践不相容。如果一个问题能如此迅速地变成漏洞利用,我们需要制定新的流程来保护我们社区的安全。

rclone maintainer Nick Craig-Wood confirms in the Hacker News comments that his project is seeing this problem:

rclone 的维护者 Nick Craig-Wood 在 Hacker News 的评论中证实,他的项目也遇到了这个问题:

In the first 10 years of the rclone project we received about 20 security disclosures through GitHub. We had to deal with over 40 in the last month! That has taken a huge amount of my time, even using AI tools to triage and come up with fixes for review.

在 rclone 项目的前 10 年里,我们通过 GitHub 收到了大约 20 份安全披露。但在过去一个月里,我们不得不处理超过 40 份!这占用了我的大量时间,即使使用 AI 工具进行分类和提出修复方案供审查。

The hit rate for those security disclosures is pretty good - about 75% of them have a nugget of something which needs looking at. [...]

这些安全披露的命中率相当高——大约 75% 的内容中都有需要关注的有价值信息。[...]

GitHub assigns CVEs for the advisories. Before the AI apocalypse they took 2-3 days for an assignment but now it they are running at 3-4 weeks so I have to send the point releases out with CVE-PENDING in the changelog which isn't ideal.

GitHub 为这些公告分配 CVE 编号。在 AI 灾难之前,分配需要 2-3 天,但现在需要 3-4 周,所以我不得不带着 CVE-PENDING 发布点版本,这并不理想。

Via Hacker News

来源:Hacker News

Tags: open-source, security, ai, generative-ai, llms, coding-agents, ocaml, ai-security-research

标签:开源、安全、AI、生成式AI、大型语言模型、编码代理、OCaml、AI安全研究

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