2 papers
cs.CR2025
Improving LLM Agents with Reinforcement Learning on Cryptographic CTF Challenges
Lajos Muzsai, David Imolai, András Lukács
We present 'Random-Crypto', a procedurally generated cryptographic Capture The Flag (CTF) dataset designed to unlock the potential of Reinforcement Learning (RL) for LLM-based agen…
cs.CR2024
HackSynth: LLM Agent and Evaluation Framework for Autonomous Penetration Testing
Lajos Muzsai, David Imolai, András Lukács
We introduce HackSynth, a novel Large Language Model (LLM)-based agent capable of autonomous penetration testing. HackSynth's dual-module architecture includes a Planner and a Summ…