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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.