LLMs can infer sensitive personal attributes from public social media with 97% accuracy, enabling precise targeting for social engineering—defenders need systematic frameworks to measure this exposure before attackers exploit it.
This paper presents a framework for measuring how vulnerable people are to social engineering attacks based on what can be inferred about them from public social media. Using LLMs, researchers extract personal information from posts, infer hidden attributes, and predict which manipulative messages would work on each person.