sahilacharya456/neuroshield-ai

# NeuroShield AI NeuroShield AI is a portfolio-level AI-powered SOC/XDR threat monitoring platform built with React, Vite, Tailwind CSS, Framer Motion, Recharts, Lucide Icons, FastAPI, Python, MongoDB, JWT auth, WebSockets, Scikit-learn, and Docker. ## Features - Premium dark cybersecurity SaaS interface with animated navigation, glassmorphism panels, neon cyber accents, live feed animations, and responsive dashboards. - JWT authentication model with Admin, Analyst, and Viewer roles. - Real-time alert streaming over WebSockets. - Alert triage with severity, status, source IP, endpoint, AI risk score, confidence, and explanation. - Scikit-learn AI engine design using Random Forest severity prediction and Isolation Forest anomaly detection. - MITRE ATT&CK mapping for brute force, PowerShell, valid accounts, and malware execution behaviors. - Incident management with assignment, timeline, affected assets, remediation, notes, and generated reports. - Threat intelligence for IPs, domains, hashes, IOC status, history, and incident linking. - Endpoint health monitoring, admin analytics, audit logs, notification placeholders, and report export endpoints. ## Demo Credentials - Admin: admin@neuroshield.ai / NeuroShield@123 - Analyst: analyst@neuroshield.ai / NeuroShield@123 - Viewer: viewer@neuroshield.ai / NeuroShield@123 ## Quick Start ### Frontend cd frontend npm install npm run dev Open http://localhost:5173. ### Backend cd backend python -m venv .venv .venv\Scripts\activate pip install -r requirements.txt uvicorn app.main:app --reload Open http://localhost:8000/docs. ### Docker docker compose up --build Docker files are included; Docker Desktop must be installed separately. ## Project Structure frontend/ React/Vite dashboard UI backend/ FastAPI API, auth, RBAC, WebSockets, services ai-engine/ Scikit-learn model training script sample-data/ Training and seed data docs/ Install, API, deployment, resume docs docker/ Dockerfiles screenshots/ Placeholder for project screenshots

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