HydraPoT: A Configurable Multi-Agent Framework for Cost-Aware LLM-Assisted Honeypots

Summary

HydraPoT is a configurable multi-agent honeypot framework that combines traditional emulation, lightweight LLMs, and cloud LLMs, routing each attacker command to an agent by a complexity-based policy while sharing session state. In a three-agent case study, it introduced less than 5% runtime overhead and kept fidelity close to a cloud-LLM-only honeypot. Its policy cut cloud-processed tokens by 72.6% and operational cost by 3.7x.

Topics

• AI agents