This research demonstrates how Large Language Models can autonomously conduct penetration tests in enterprise Active Directory networks, simulating sophisticated attacks without human intervention.

• Successfully compromised accounts within realistic Active Directory testbeds
• Created a novel prototype system driven entirely by LLM capabilities
• Evaluated both strengths and limitations of AI-powered security testing
• Revealed potential for both defensive security improvements and concerning offensive applications

This advancement matters for cybersecurity teams as it provides new automated tools for security assessment while also highlighting the evolving threat landscape where AI could potentially be weaponized by malicious actors.

Original Paper: Can LLMs Hack Enterprise Networks? Autonomous Assumed Breach Penetration-Testing Active Directory Networks