Offensive Security

Offensive security research is increasingly leveraging large language models (LLMs) to automate and enhance various attack vectors, including social engineering, vulnerability exploitation, and penetration testing. Current research focuses on developing and evaluating LLMs' capabilities in these areas using novel benchmark datasets and automated frameworks, while also addressing ethical concerns and limitations in model robustness and control. This work is significant for improving the effectiveness of cybersecurity defenses by providing realistic threat modeling and informing the development of more robust security systems. The development of AI-driven offensive security tools also highlights the need for ongoing research into ethical considerations and responsible AI development in this domain.