Penetration Testing

Penetration testing, the simulated ethical hacking of systems to identify vulnerabilities, is increasingly being automated using artificial intelligence. Current research focuses on developing and benchmarking AI agents, often employing reinforcement learning algorithms like A3C and DQN, or leveraging large language models (LLMs) such as GPT-4, to enhance efficiency and effectiveness across various penetration testing phases, from reconnaissance to post-exploitation. These advancements aim to improve the speed and comprehensiveness of security assessments, ultimately strengthening cybersecurity defenses and reducing reliance on scarce human expertise.