PhishingWebCollector: Async python library for automated phishing feed collection

Abstract

Website phishing represents a significant cyber threat, where attackers create fraudulent websites that imitate legitimate sites to deceive users. Continuous monitoring and detection of malicious websites are crucial for mitigating this threat. This paper introduces PhishingWebCollector, an open-source Python library designed to simplify the collection and integration of phishing feeds. It is an appropriate tool for real-time blacklist updates, creating historical datasets for research, and serving as a foundation for developing AI-based phishing detection systems. Identifying phishing and spoofed websites helps generate high-quality datasets necessary for training models in automated website classification and threat identification. Leveraging Python’s asyncio, it processes multiple feeds concurrently to achieve optimal performance. Available on PyPI with extensive documentation and examples, PhishingWebCollector offers a resource-efficient solution for cybersecurity professionals and researchers.