Phishing email attacks are among the most common and most harmful
cybersecurity attacks. With the emergence of generative AI, phishing attacks
can be based on emails generated automatically, making it more difficult to
detect them. That is, instead of a single email format sent to a large number
of recipients, generative AI can be used to send each potential victim a
different email, making it more difficult for cybersecurity systems to identify
the scam email before it reaches the recipient. Here we describe a corpus of
AI-generated phishing emails. We also use different machine learning tools to
test the ability of automatic text analysis to identify AI-generated phishing
emails. The results are encouraging, and show that machine learning tools can
identify an AI-generated phishing email with high accuracy compared to regular
emails or human-generated scam email. By applying descriptive analytic, the
specific differences between AI-generated emails and manually crafted scam
emails are profiled, and show that AI-generated emails are different in their
style from human-generated phishing email scams. Therefore, automatic
identification tools can be used as a warning for the user. The paper also
describes the corpus of AI-generated phishing emails that is made open to the
public, and can be used for consequent studies. While the ability of machine
learning to detect AI-generated phishing email is encouraging, AI-generated
phishing emails are different from regular phishing emails, and therefore it is
important to train machine learning systems also with AI-generated emails in
order to repel future phishing attacks that are powered by generative AI.

通过描述一个开放给公众使用的 AI 生成钓鱼邮件语料库，论文表明通过使用自动文本分析的机器学习工具，可以高准确率地识别基于 AI 生成的钓鱼邮件，并且 AI 生成的钓鱼邮件与常规钓鱼邮件不同，因此有必要在训练机器学习系统时使用 AI 生成的邮件，以防止由生成型 AI 支持的未来钓鱼攻击。