This research introduces a debate-driven multi-agent LLM approach to more accurately detect sophisticated phishing emails without requiring extensive labeled datasets.

• Leverages multiple LLM agents in structured debates to analyze emails from different perspectives
• Combines adversarial thinking with collaborative reasoning to reduce false positives/negatives
• Creates a more adaptable system that can identify novel phishing techniques
• Demonstrates how AI debate mechanisms can enhance cybersecurity defenses

This matters because traditional phishing detection methods struggle with evolving attack patterns, while this approach provides a more flexible and resilient detection system that can keep pace with attackers' changing tactics.

Debate-Driven Multi-Agent LLMs for Phishing Email Detection