We introduce the LLM Honeypot, a system for monitoring autonomous AI hacking agents. We deployed a customized SSH honeypot and applied prompt injections with temporal analysis to identify LLM-based agents among attackers. Over a trial run of a few weeks in a public environment, we collected 800,000 hacking attempts and 6 potential AI agents, which we plan to analyze in depth in future work. Our objectives aim to improve awareness of AI hacking agents and enhance preparedness for their risks.

翻译：我们提出了LLM蜜罐系统，用于监控自主AI黑客智能体。通过部署定制化SSH蜜罐并应用结合时序分析的提示注入技术，我们在攻击者中识别出基于LLM的智能体。在公共环境中为期数周的试运行期间，我们收集到80万次黑客攻击尝试和6个潜在AI智能体，计划在后续工作中进行深入分析。本研究旨在提升对AI黑客智能体的认知水平，并增强应对其风险的能力。