International Journal on Science and Technology

E-ISSN: 2229-7677     Impact Factor: 9.88

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 16 Issue 2 April-June 2025 Submit your research before last 3 days of June to publish your research paper in the issue of April-June.

A Phishing URL Detection Tool PhishGuard Using Python

Author(s) Vasundhara S, Shri Varshini K, Janani P, Dr. S. Mohandoss
Country India
Abstract PhishGuard is an API-based security tool that uses machine learning algorithms to identify and analyze phishing URLs, complemented by the VirusTotal API for full-fledged risk analysis. The tool maximizes its analytical power by integrating machine learning (ML) algorithms for automated URL extraction, analysis, and reporting, giving users useful details regarding the possible danger level of suspicious URLs. Some of the major features are automatic URL scanning by a mere keyboard shortcut (Shift + Click), live analysis of phishing likelihood optimized by ML-based predictions, and PDF report generation with detailed information. PhishGuard also provides visual insights in the form of pie charts, classifying URLs according to their risk levels. All scanned URLs are logged by the system and stored in categorized log files for future use. Developed with Python, PhishGuard combines technologies like Matplotlib for visualization, PyQt6 for the interface, and FPDF for report generation. PhishGuard is made to be easy to use, with simple installation and uninstallation procedures. PhishGuard seeks to improve browsing security by giving users a safe and efficient way of detecting and avoiding malicious URLs using the power of machine learning.
Keywords PhishGuard, Phishing Detection, URL Analysis, VirusTotal API, Machine Learning, Risk Assessment, Python, Cybersecurity, Visualization
Field Computer
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-04-21
Cite This A Phishing URL Detection Tool PhishGuard Using Python - Vasundhara S, Shri Varshini K, Janani P, Dr. S. Mohandoss - IJSAT Volume 16, Issue 2, April-June 2025. DOI 10.71097/IJSAT.v16.i2.3887
DOI https://doi.org/10.71097/IJSAT.v16.i2.3887
Short DOI https://doi.org/g9gds7

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