Prompted Contextual Vectors for Spear-Phishing Detection

Spear-phishing attacks present a significant security challenge, with large language models (LLMs) escalating the threat by generating convincing emails and facilitating target reconnaissance. To address this, we propose a detection approach based on a novel document vectorization method that utilizes an ensemble of LLMs to create representation vectors. By prompting LLMs to reason and respond to human-crafted questions, we quantify the presence of common persuasion principles in the email's content, producing prompted contextual document vectors for a downstream supervised machine …

address attacks challenge cs.cl cs.cr cs.lg detection document emails language language models large llms novel phishing phishing attacks phishing detection reconnaissance representation security spear-phishing attacks target threat