Artificial intelligence (AI) has significantly transformed the cybersecurity landscape by enabling both advanced defensive systems and highly adaptive attack mechanisms. Identity-based cyber threats, such as deepfake impersonation, AI-driven phishing, and autonomous identity exploitation, are emerging as dominant vectors of cyber risk. Existing identity management frameworks were not designed to counter adversaries capable of generating synthetic identities and dynamically adapting attack strategies. This paper presents a theoretical analysis of AI-enabled identity threats and proposes a conceptual framework to classify and understand emerging identity exploitation techniques. The study synthesizes recent cybersecurity research and industry trends to identify structural gaps in current identity security models and outline foundational assumptions for future research.
Saksham Shekher (Wed,) studied this question.