In our interconnected world, e-mail communication has become indispensable for individuals and organizations alike. But this ease is accompanied by a growing threat: phishing e-mails. Phishing is a malicious activity whereby criminals assume the identity of reliable organizations to force people to give out private information, like passwords and credit card numbers. Robust, automated e-mail security solutions are necessary because of this wide and constantly changing cyberattack strategy. As a result, we suggested developing a detection system using a combination of deep learning (DL) and natural language processing (NLP) methods. Our approach makes use of a complex algorithm that can recognize phishing e-mails with accuracy. It includes preprocessing the data, multi-component analysis (such as phishing link and hashtag detection), word and hashtag detection, phishing detection using natural language processing, and deep learning model optimization. We assess each part’s performance to make sure our system is successful. The findings demonstrate that. The suggested method correctly identifies phishing attacks, which enhances e-mail security.