SQL Injection Detection Web App

🔗 Live Demo: https://sql-injection-detector.onrender.com

This is a Flask web app that detects and logs SQL injection (SQLi) attempts through a fake login form. It uses both traditional regex pattern matching and an optional machine learning classifier to identify suspicious inputs.

All detected attacks are logged to a SQLite database. An admin dashboard allows reviewing, exporting, and analyzing attack activity.

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🔒 Features

• ✅ Detects SQL injection via regex and optional machine learning (Logistic Regression)
• ✅ Honeypot endpoints to trap bots probing for vulnerable routes
• ✅ Logs all attacks with timestamp, IP address, and credentials
• ✅ Admin dashboard with login protection and session management
• ✅ Downloadable CSV logs for auditing
• ✅ Toggleable dark mode UI
• ✅ Analytics dashboard (Plotly) with interactive charts:
  • Attack volume over time
  • Top payloads
  • Honeypot vs. SQLi attack ratio

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🛠 Technologies Used

• Python, Flask
• Flask-Login, Flask-SQLAlchemy
• Plotly (for dashboard analytics)
• Scikit-learn (for ML-based detection)
• HTML/CSS (Dark Mode UI)
• SQLite

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🧠 Admin Login

• Username: admin
• Password: secure123

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📦 Deployment

This project is deployed using Render. The app can also be Dockerized or hosted on any platform that supports Flask.

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📚 TODO / Future Improvements

• Filter logs by IP or time range
• Display detection source (ML vs Regex)
• Support IP blocking or throttling