phising-detection

AI-powered Cyber Asset Management, Vulnerability Assessment & Attack Surface Management Platform.

A real-time phising detection and URL scanning browser extension just by hovering (Now Available on Edge Addons)

Production-grade MLOps pipeline for phishing URL detection with modular training, MLflow experiment tracking, FastAPI inference, and automated CI/CD to AWS

ML-powered phishing URL detection using Flask, Random Forest, and 30 heuristic security features.

AI-inspired phishing and scam risk detection tool built with Python and Streamlit.

ML phishing URL detector using LightGBM — 93.2% accuracy

AI-powered phishing detection platform for real-time URL analysis and intelligent web threat detection.

Performed email forensic analysis to detect spoofed emails through header analysis, authentication validation (SPF/DKIM/DMARC), and OSINT-based IP attribution

Real-time phishing URL detection using Random Forest ML — 99.90% AUC-ROC

Interpretable phishing email detector built with scikit-learn — TF-IDF + engineered structural features, 5-model comparison, threshold tuning, and feature importance analysis for SOC-ready explainability.

🛡️ PhishGuard – Real-time phishing detection system. Hybrid blacklist/heuristic engine + cross‑browser extension. Built with Django & Python.

Everyone has done this during their university days, and so have we. This is the repository for our SIH and Internal Hackathon Project (2023). There's not much here; the SOURCE CODE, PPT, and ARCHITECTURE are archived and private. Thank you for visiting.

Production-ready phishing email detector with BERT Transformer + Bidirectional LSTM deep learning models. Features live UI with model agreement, confidence comparison, final verdict, risk indicator, and processing time.

end-to-end phishing detection system using ML, FastAPI, Docker, and AWS with CI/CD deployment

Explainable AI scam-message detector built with React, Flask, scikit-learn and SQLite.