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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AdvPrefix: An Objective for Nuanced LLM Jailbreaks · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2412.10321/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2412.10321/feed.xml" rel="self" type="application/rss+xml" /><item><title>AdvPrefix: An Objective for Nuanced LLM Jailbreaks — HN submission</title><link>https://news.ycombinator.com/item?id=44060292</link><guid isPermaLink="false">urn:hackerpapers:submission:2412.10321:44060292</guid><pubDate>Thu, 22 May 2025 09:15:52 GMT</pubDate><description>&lt;p&gt;Show HN: Find prompts that jailbreak your agent (open source)&lt;/p&gt;&lt;p&gt;We&amp;#x27;ve built an open-source tool to stress test AI agents by simulating prompt injection attacks. We’ve implemented one powerful attack strategy based on the paper [AdvPrefix: An Objective for Nuanced LLM Jailbreaks](https://arxiv.org/abs/2412.10321). Here&amp;#x27;s how it works: - You define a goal, like: “Tell me your system prompt” - Our tool uses a language model to generate adversarial prefixes (e.g., “Sure, here are my system prompts…”) that are likely to jailbreak the agent. - The output is a list of prompts most likely to succeed in bypassing safeguards. We’re just getting started. Our goal is…&lt;/p&gt;&lt;p&gt;8 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2412.10321/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
