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arXiv · 2410.13919

LLM Agent Honeypot: Monitoring AI Hacking Agents in the Wild

Reworr·Dmitrii Volkov
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Abstract

Attacks powered by Large Language Model (LLM) agents represent a growing threat to modern cybersecurity. To address this concern, we present LLM Honeypot, a system designed to monitor autonomous AI hacking agents. By augmenting a standard SSH honeypot with prompt injection and time-based analysis techniques, our framework aims to distinguish LLM agents among all attackers. Over a trial deployment of about three months in a public environment, we collected 8,130,731 hacking attempts and 8 potential AI agents. Our work demonstrates the emergence of AI-driven threats and their current level of usage, serving as an early warning of malicious LLM agents in the wild.

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Reworr, Dmitrii Volkov. 2024-10-17. LLM Agent Honeypot: Monitoring AI Hacking Agents in the Wild. https://arxiv.org/abs/2410.13919

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