Behind the Bait: Delving into PhishTank's hidden data

Affan Yasin; Rubia Fatima; Javed Ali Khan; Wasif Afzal

doi:10.1016/j.dib.2023.109959

Behind the Bait: Delving into PhishTank's hidden data

Data Brief. 2023 Dec 15:52:109959. doi: 10.1016/j.dib.2023.109959. eCollection 2024 Feb.

Authors

Affan Yasin¹, Rubia Fatima², Javed Ali Khan³, Wasif Afzal⁴

Affiliations

¹ School of Software, Northwestern Polytechnical University, Xian 710072, Shaanxi, China.
² School of Software, Tsinghua University, Beijing, China.
³ Department of Computer Science, School of Physics, Engineering & Computer Science, University of Hertfordshire, Hatfield, UK.
⁴ School of Innovation, Design and Engineering, Mälardalen University, Västerås, Sweden.

Abstract

Phishing constitutes a form of social engineering that aims to deceive individuals through email communication. Extensive prior research has underscored phishing as one of the most commonly employed attack vectors for infiltrating organizational networks. A prevalent method involves misleading the target by employing phishing URLs concealed through hyperlink strategies. PhishTank, a website employing the concept of crowd-sourcing, aggregates phishing URLs and subsequently verifies their authenticity. In the course of this study, we leveraged a Python script to extract data from the PhishTank website, amassing a comprehensive dataset comprising over 190,0000 phishing URLs. This dataset is a valuable resource that can be harnessed by both researchers and practitioners for enhancing phish- ing filters, fortifying firewalls, security education, and refining training and testing models, among other applications.

Keywords: Artificial intelligence; Computer security; Dataset; Email security; Phished URL; Social engineering; Web security.