🛡️ AI Social Engineering Risk Intelligence Platform

Cyber Risk Intelligence Command Center — An enterprise-grade platform that analyzes public text and URLs to quantify phishing and social engineering risk, generate live attack simulations, and produce actionable mitigation plans.

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🌟 What It Does

Paste any public text (LinkedIn bio, social media post, news article) or a URL and the platform:

1. Extracts entities — names, organizations, locations, dates using NLP
2. Calculates a Risk Score (0–100) — calibrated across 5 risk vectors
3. Generates Attack Simulations — real phishing emails, SMS, LinkedIn InMails, and voice scripts tailored to the extracted data
4. Produces a Mitigation Plan — actionable security recommendations based on the specific risk vectors detected
5. Shows Industry Context — sector-specific threat intelligence

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🏗️ Tech Stack

Layer	Technology
Backend API	Python, FastAPI, Uvicorn
NLP	spaCy (en_core_web_sm)
AI / LLM	OpenRouter API (Mistral-7B, LLaMA-3, Gemma via free tier)
Web Scraping	BeautifulSoup4 + Requests
PDF Generation	ReportLab
Frontend	Next.js 16, React, TypeScript
Styling	TailwindCSS, custom glassmorphism
Charts	Recharts (Radar, Area, Sparklines)

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🚀 Getting Started

Prerequisites

• Python 3.10+
• Node.js 18+
• An OpenRouter account (free tier works)

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1. Clone the Repository

git clone https://github.com/Suryaaa81/Cyber-Risk-Intelligence.git
cd Cyber-Risk-Intelligence

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2. Backend Setup

cd backend

# Create and activate virtual environment
python -m venv venv

# Windows
.\venv\Scripts\activate

# macOS / Linux
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Download spaCy language model
python -m spacy download en_core_web_sm

Configure Environment Variables

# Copy the example env file
copy .env.example .env    # Windows
cp .env.example .env      # macOS/Linux

Open backend/.env and add your OpenRouter API key:

OPENROUTER_API_KEY=sk-or-v1-your-key-here

💡 Get your free key at openrouter.ai. The platform works without a key too — it uses rule-based AI fallbacks automatically.

Start the Backend

uvicorn main:app --reload
# API will run at http://127.0.0.1:8000

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3. Frontend Setup

cd frontend
npm install
npm run dev
# App will run at http://localhost:3000

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🎯 Usage — Test Cases

High-Risk Text (Score: 80–95)

Paste this in the dashboard to see a full attack simulation:

Hi everyone! I'm Jennifer Walsh, new VP of Finance at Goldman Sachs in New York!
Currently staying at the Marriott Marquis while apartment hunting. My husband David
and kids are still in Austin, Texas — joining me after the school year ends.
Planning a family vacation to Dubai in August! Reach me at jennifer.walsh1982@gmail.com

Low-Risk Text (Score: 0–10)

The weather today is nice. I went for a walk in the park and enjoyed the sunshine.

URL Analysis

Paste any public URL (Wikipedia, LinkedIn public profiles, news articles):

https://en.wikipedia.org/wiki/Tim_Cook

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🌐 Deployment (Production)

1. Frontend (Vercel)

• Push your code to GitHub.
• Go to Vercel -> New Project.
• Import this repository.
• Environment Variables:
  • NEXT_PUBLIC_API_URL: Set this to your Backend URL (e.g., https://your-backend.onrender.com).
• Click Deploy.

2. Backend (Render / Railway)

• Go to Render -> New Web Service.
• Connect your GitHub repository.
• Build Command: pip install -r requirements.txt && python -m spacy download en_core_web_sm
• Start Command: uvicorn main:app --host 0.0.0.0 --port 8000
• Environment Variables:
  • OPENROUTER_API_KEY: Your OpenRouter API key.
  • ALLOWED_ORIGINS: Set this to your Vercel URL (e.g., https://your-app.vercel.app).
• Click Deploy.

3. Docker (Alternative)

Run locally or on a VPS using Docker:

docker-compose up --build

• Backend will be on port 8000
• Frontend will be on port 3000

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📁 Project Structure

project_phishing/
├── backend/
│   ├── main.py              # FastAPI app — all agents, endpoints, NLP
│   ├── requirements.txt     # Python dependencies
│   ├── .env.example         # Template for environment variables
│   └── .env                 # Your secrets (git-ignored)
│
└── frontend/
    ├── app/
    │   ├── page.tsx          # Landing page
    │   ├── dashboard/
    │   │   └── page.tsx      # Main command center dashboard
    │   ├── layout.tsx
    │   └── globals.css
    ├── package.json
    └── next.config.ts

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🔌 API Endpoints

Method	Endpoint	Description
POST	/analyze	Analyze raw text
POST	/analyze-url	Analyze content from a URL
POST	/upload-csv	Analyze data from a CSV file
POST	/upload-pdf	Analyze text extracted from a PDF
POST	/generate-report	Download a PDF risk report

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⚠️ Disclaimer

This tool is built for defensive security awareness, penetration testing demonstrations, and educational purposes only. All attack simulations are generated to help organizations understand and reduce their social engineering attack surface.

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📄 License

MIT License — free to use, modify, and distribute.