SecurePolicy‑Maker

📖 What is SecurePolicy‑Maker?

SecurePolicy‑Maker is a mini‑project built using FastAPI (backend) and HTML/CSS (frontend) to help users generate simple cybersecurity policies through an AI‑assisted workflow. It integrates with a local LLM (via Ollama) for basic chatbot support.

This project is built as part of the NPTEL Cybersecurity & Privacy Course, focused on learning how policy generation systems work.

Use Cases

• Generate quick security policy drafts
• Customize and export security rules
• Experiment with Cybersecurity Specific Chatbot

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Screenshots

📁 Repository Structure

/
├── main.py                    # FastAPI backend entry point
├── rules.json                 # Base rules/policy format
├── requirements.txt           # Python dependencies
├── templates/                 # Jinja2 templates for policy rendering
│ └── privacy_policy.j2 
├── static/                    # Frontend assets
│ └── index.html               # HTML file with inline CSS, JS, UI components
└── README.md                  # Project documentation

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🧰 Tech Stack

Layer	Technology / Framework	Purpose
Backend	FastAPI (Python)	Core API, routing, business logic
Frontend	HTML, CSS, Jinja2	UI rendering, templating engine
Chatbot	Llama 3.2:1B (via Ollama)	Chat assistance for explaining security terms; not used for policy generation
Policy Engine	rules.json (custom rule-based system)	Deterministic policy creation
Server	Uvicorn	ASGI server to run FastAPI app
Package Management	pip, venv	Dependency and environment management
PDF Export	Python-based PDF generation	Enables users to download generated policies
Static Assets	CSS, JS (local)	Frontend styling and behavior

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🚀 Setup & Installation

Prerequisites

• Python 3.10+
• Ollama or any local LLM API
• A virtual environment (recommended)

Installation Steps

# 1. Clone the repository
git clone https://github.com/Vedika-Sd/SecurePolicy-Maker.git
cd SecurePolicy-Maker

# 2. Create and activate virtual environment
python -m venv venv
# Windows:
venv\Scripts\activate
# Linux/Mac:
# source venv/bin/activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Run the server
uvicorn main:app --reload

# App runs at:
# http://127.0.0.1:8000

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🧰 How It Works

Once you run the server:

1. Open the UI in your browser.
2. Provide system/context details.
3. System generates a draft policy based on predefined rules.json; the LLM is only used for chatbot responses.
4. Review, refine, export.

Workflow Example

• Select policy category or input details
• LLM processes input and rules.json
• Policy is generated and displayed in UI

⚠ This is an educational project; policies generated must be reviewed manually before real‑world use.

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✨ Features

✔ Current Features

• FastAPI backend with clean routing
• Simple, user‑friendly HTML UI
• JSON‑based rule system (rules.json)
• Chatbot support for more explanation

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🔧 Customization & Extension

You can easily extend functionality:

Modify rules

Edit rules.json to adjust policy templates.

Improve prompts

Customize LLM prompts in main.py to Expand features of Chatbot.

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🤝 Contributing

Contributions are welcome! To contribute:

1. Fork the repo
2. Create a branch (feature/my-update)
3. Commit and push
4. Open a Pull Request

You can help with:

• Better UI/UX
• More policy templates
• Robust backend enhancements
• Documentation improvements

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📝 License

This project is licensed under the MIT License. You are free to use, modify, and distribute it.

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📬 Author & Contact

Created by Vedika (Vedika-Sd). Feel free to raise issues or suggestions directly through GitHub.