ARACNE: An LLM-Based Autonomous Shell Pentesting Agent

2025-02-24 · Tomas Nieponice, Veronica Valeros, Sebastian Garcia

We introduce ARACNE, a fully autonomous LLM-based pentesting agent tailored for SSH services that can execute commands on real Linux shell systems. Introduces a new agent architecture with multi-LLM model support. Experiments show that ARACNE can reach a 60\% success rate against the autonomous defender ShelLM and a 57.58\% success rate against the Over The Wire Bandit CTF challenges, improving over the state-of-the-art. When winning, the average number of actions taken by the agent to accomplish the goals was less than 5. The results show that the use of multi-LLM is a promising approach to increase accuracy in the actions.

📄 PDF Abstract BibTeX arXiv:2502.18528

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RapidPen: Fully Automated IP-to-Shell Penetration Testing with LLM-based Agents

2025-02-23 · Sho Nakatani

We present RapidPen, a fully automated penetration testing (pentesting) framework that addresses the challenge of achieving an initial foothold (IP-to-Shell) without human intervention. Unlike prior approaches that focus…

Task Planning

Mind the Gap: Towards Generalizable Autonomous Penetration Testing via Domain Randomization and Meta-Reinforcement Learning

2024-12-05 · Shicheng Zhou, Jingju Liu, Yuliang Lu, Jiahai Yang 외

With increasing numbers of vulnerabilities exposed on the internet, autonomous penetration testing (pentesting) has emerged as a promising research area. Reinforcement learning (RL) is a natural fit for studying this top…

Large Language Model Meta Reinforcement Learning Reinforcement Learning (RL)

Autonomous Penetration Testing using Reinforcement Learning

2019-05-15 · Jonathon Schwartz, Hanna Kurniawati

Penetration testing (pentesting) involves performing a controlled attack on a computer system in order to assess it's security. Although an effective method for testing security, pentesting requires highly skilled practi…

Q-Learning reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

APIOT: Autonomous Vulnerability Management Across Bare-Metal Industrial OT Networks

2026-05-04 · Adel ElZemity, Budi Arief, Shujun Li, Calvin Brierley 외 arxiv

Bare-metal operational technology (OT) devices -- especially the microcontrollers running Modbus/TCP and CoAP at the base of industrial control systems -- have remained outside the reach of autonomous security attacks. P…

Know Your Agent: Reconnaissance-Driven Pentesting of AI Agents

2026-07-22 · Or Zion Eliav, Eyal Lenga, Shir Bernstien, Yisroel Mirsky arxiv

Traditional pentesting uses reconnaissance at each step to uncover unseen weaknesses, build stronger attacks, and advance the objective; we argue that AI agents require the same treatment. We formalize agent reconnaissan…