  The advancement of Artificial Intelligence (AI) and Machine Learning (ML) has
profound implications for both the utility and security of our digital
interactions. This paper investigates the transformative role of Generative AI
in Social Engineering (SE) attacks. We conduct a systematic review of social
engineering and AI capabilities and use a theory of social engineering to
identify three pillars where Generative AI amplifies the impact of SE attacks:
Realistic Content Creation, Advanced Targeting and Personalization, and
Automated Attack Infrastructure. We integrate these elements into a conceptual
model designed to investigate the complex nature of AI-driven SE attacks - the
Generative AI Social Engineering Framework. We further explore human
implications and potential countermeasures to mitigate these risks. Our study
aims to foster a deeper understanding of the risks, human implications, and
countermeasures associated with this emerging paradigm, thereby contributing to
a more secure and trustworthy human-computer interaction.
