PhishingWebCollector: Async python library for automated phishing feed collection

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.

Authors

Publication Details

Journal
SoftwareX
Published
2025-12-05
DOI
https://doi.org/10.1016/j.softx.2025.102463
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

PhishingWebCollector: Async python library for automated phishing feed collection

Damian Frąszczak, Edyta Frąszczak
SoftwareX
Spam and Phishing Detection
article

PhishingWebCollector: Async python library for automated phishing feed collection

Damian Frąszczak, Edyta Frąszczak
article en

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.

SoftwareXVol. 33
Openalex Percentile: Top 49%
Spam and Phishing Detection
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