A lightweight, interactive cybersecurity education platform optimized for Raspberry Pi and low-resource hardware.
CyberLearn Pi is a project built using the most fundamental and fast technologies to ensure smooth and fluid operation even on low-end, ARM-based systems (e.g., Raspberry Pi 1 Type B - 512 MB RAM). It safely teaches students network security, encryption, and command-line basics in a sandboxed environment. Built with Vanilla JS, compiled TailwindCSS, and a lightweight SQLite-Flask architecture, it runs without the bloat of modern SPA frameworks.
- 📚 Modular Lesson Content: Offline-capable Markdown-based educational documents.
- 💻 Integrated Terminal Simulator: A client-side JavaScript simulator where students can safely practice Linux commands without the risk of damaging a real server.
- 🤔 Interactive Quiz Engine: An AJAX-powered question bank that provides instant feedback at the end of modules without reloading the page.
- 🤖 Cyber-Tutor (AI Assistant): An educational assistant powered by Google Gemini 1.5 Pro AI (Optimized for tokens to keep hardware API costs low).
- ⚡ High Performance: Optimized with Vanilla JS, SQLite, and Flask-Gunicorn (max 2 async workers), eliminating the need for Node.js or massive databases.
- 🔒 Secure Access: A user authentication panel controlled by Flask-Login.
You can use the automated setup script to quickly install it on Linux or macOS distributions:
# Clone the repository to your computer/server
git clone [GITHUB-REPO-LINK]
cd cyberlearn-pi
# Grant permissions and run the setup script
chmod +x scripts/setup.sh
./scripts/setup.shIf you prefer not to use the automated script, follow these standard steps:
1. Prepare the virtual environment:
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt2. Initialize the database and seed initial data:
python3 scripts/seed_db.py3. Set API Keys:
- Rename the
.env.examplefile in the directory to.envand fill in the appropriate fields (Gemini API Secret, etc.).
4. Start the live development server:
bash scripts/dev_server.shThe application will be accessible at http://localhost:5000.
app.py: The main Flask application entry point.blueprints/: Controller structures divided by application domains (Auth, Quiz, Lesson, etc.).models/: Lightweight SQLite3 database tables holding user data (without SQLAlchemy overhead).content/lessons/: A repository of Markdown (.md) files where lesson content is stored.static/js/: Vanilla Javascript files responsible for the education panel, terminal simulator, and quiz interactions.
Pull requests are always welcome for anyone wishing to contribute to the development. However, since we account for hardware RAM limits (max 512 MB) when adding libraries to the project, please avoid including unnecessary npm / pip packages.
This project is distributed under the MIT license. See the LICENSE file for more information.