ai bug bounty triage

Set up the project with a clean structure: create ai-bug-triage folder, then add backend for APIs and ML, frontend for UI, and scanner for security tools like ZAP, SQLMap, and Nmap.

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To begin building the full-stack AI-powered web application for vulnerability scanning and bug triage, the first phase involves setting up the project structure. This ensures a clean and organized foundation for managing the different components of the application. Start by creating a root directory named ai-bug-triage, which will serve as the main workspace. Inside this directory, create three subfolders: backend, frontend, and scanner. The backend folder will contain all server-side logic including Flask or Node.js code to handle the integration with security tools like ZAP, SQLMap, and Nmap, process ML models (using Scikit-learn or TensorFlow), and manage database operations with MongoDB. The frontend folder will hold the UI code—likely developed with React or another JavaScript framework—to enable real-time bug submissions, vulnerability reports, and triage workflows. The scanner folder will house scripts and configurations specific to security tools, allowing modular execution and easier updates. This folder structure promotes separation of concerns, simplifies deployment via platforms like Vercel (frontend) and Render or Railway (backend and DB), and ensures scalability as new features like automated scoring (CVSS-based) and ML-driven classification are added in future phases. This structured setup sets a strong foundation for building a powerful and intelligent bug triage system.

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