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@article{203444,
        author = {Tejashree Bhong and Deepa Gandhi and Prerana Pawar and Priyanka More and Prof.Pranali jadhav},
        title = {ML Based Phishing Defence WebApp},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {12401-12404},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203444},
        abstract = {Phishing attacks are a major cybersecurity threat that deceive users into visiting fake websites and stealing sensitive information such as passwords and banking details. This research presents a Python-based ML Based Phishing Defense WebApp developed to detect whether a given URL is safe or phishing-related. The system analyzes various URL features including HTTPS usage, domain structure, suspicious keywords, and redirection patterns to identify malicious links. By offering instantaneous deployment via an intuitive frontend, the developed application empowers non-technical operators to evaluate link integrity dynamically. Index Terms - Phishing, Cyber security, Python, URL Detection, Web Security, Malicious Links.},
        keywords = {},
        month = {May},
        }