International Journal of Scientific Research and Engineering Development

Phishing attack is a prevalent and a growing cyber threat that targets internet users, governments and service pro-viding organizations. In these attacks, attackers are trying to gain access to sensitive user information-including, but not limited to, login credentials, bank or card information, and email addressesusing deceptive email messages or fraudulent websites. Such attacks are frequently based on a social engineering approach, where hackers mimic legitimate web sites and deliver harmful URLs as spam messages, text messages, or in social media. In order to offer a holistic insight into the phishing attacks, this paper offers a literature review of diverse Artificial Intelligence (AI) techniques applied in detecting them such as: Machine Learning, Deep learning, Hybrid learning and Scenario based methods. It also juxtaposes various studies in phishing detection, outlining each of the methods, their advantages, and drawbacks. Also, the paper determines the current limitations of phishing detection and provides the possible future research directions in this field.

Shifa Bilal Tamboli, Simeen Phiroj Mulani, Arman Tajuddin Shiakh,"A Feature-Free Deep Learning Approach for Detecting Phishing Attacks" International Journal of Scientific Research and Engineering Development, V9(2): Page(2505-2513) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.