Phishing-URL-Detection and Phishing-detector
These are competitors—both tools solve the identical problem of detecting phishing URLs through visual and semantic analysis, so users would choose one or the other rather than use both together.
About Phishing-URL-Detection
vaibhavbichave/Phishing-URL-Detection
Phishers use the websites which are visually and semantically similar to those real websites. So, we develop this website to come to know user whether the URL is phishing or not before using it. URL - http://phishing-url-detector-api.herokuapp.com/
Leverages ensemble machine learning models (Gradient Boosting, CatBoost, XGBoost) trained on URL structural features like HTTPS usage, anchor URLs, and website traffic patterns to achieve 97.4% classification accuracy. Built with Flask for the web interface and scikit-learn for model training, the system extracts feature vectors from submitted URLs and uses a pickled Gradient Boosting classifier for real-time predictions.
About Phishing-detector
asrith-reddy/Phishing-detector
Phishers use the websites which are visually similar to those real websites. So, we developed this website so that user can know whether the URL is phishing or not before using it. URL -
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