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This article discusses the ongoing threat of social engineering email attacks and the limitations of current solutions and user training in identifying phishing indicators. It introduces the concept of weak explainable phishing indicators (WEPI) and proposes the use of NLP and machine learning to assist users in detecting these indicators. The article also presents a corpus of 940 emails labeled with 32 WEPI labels and provides insights into WEPI frequencies and areas for improved training.
