paperSeptember 2026Unreviewed

Engineered Persuasion: Evaluating Personalized Pretexts in LLM-Generated Spear Phishing

Jerson Francia, Derek Hansen, Benjamin Schooley, Shydra Valynn Murray

Abstract

Large language models can insert workplace details into phishing pretexts at low cost, but those details may either support or undermine a message's credibility. We recruited 180 U.S. working adults to evaluate simulated, AI-generated phishing emails in a disclosed survey. The emails used four cumulative levels of information: workplace (Level 1); recipient name and job title; job responsibilities; and coworker/shared-project context (Level 4). Participants rated each message's convincingness fr

Cite

@misc{francia2026engineered,
  title = {{Engineered Persuasion: Evaluating Personalized Pretexts in LLM-Generated Spear Phishing}},
  author = {Jerson Francia and Derek Hansen and Benjamin Schooley and Shydra Valynn Murray},
  year = {2026},
  month = sep,
  eprint = {2609.04410},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.04410}
}