Abstract
Phishing campaigns involve adversaries masquerading as trusted vendors trying to trigger user behavior that enables them to exfiltrate private data. While URLs are an important part of phishing campaigns, communicative elements like text and images are central in triggering the required user behavior. Further, due to advances in phishing detection, attackers react by scaling campaigns to larger numbers and diversifying and personalizing content. In addition to established mechanisms, such as template-based generation, large language models (LLMs) can be used for phishing content generation, enabling attacks to scale in minutes, challenging existing phishing detection paradigms through personalized content, stealthy explicit phishing keywords, and dynamic adaptation to diverse attack scenarios. Countering these dynamically changing attack campaigns requires a comprehensive understanding of the complex LLM-related threat landscape. Existing studies are fragmented and focus on specific ar