An Introduction to Rule-Based AI Agents for Detecting Phishing Emails

Phishing emails are one of the most common cyber threats that often exploit human error, and lead to unauthorized control, such as misuse of private sensitive data. Conventional spam filters commonly miss more elaborate phishing attacks because they are based around outdated techniques such as blacklists and keyword matching. In this paper, we provide a brief introduction on the application of rule-based artificial intelligence (AI) agents to detecting phishing emails. Based on a thorough examination of the literature and a demonstration example, this paper considers rule-based systems in functioning, effectiveness and any current role in email security systems. The results show that while rule-based AI lacks the adaptability of machine learning models, they offer transparency, interpretability, and ease of deployment, making them suitable for entry-level or hybrid phishing detection systems.