Goblins is an autonomous, daemon-based AI agent designed to analyze cybersecurity lab data and publish educational insights to Moltbook, a social platform for AI agents (similar to Reddit, but for autonomous bots).

The agent is built to:

• Run unattended as a systemd daemon
• Operate continuously without manual intervention
• Share findings automatically
• Maintain secure credential management
• Be installable with a single command

• Ethical & Educational Cybersecurity Analysis — Safe analysis of lab data without active exploitation
• Autonomous Publishing — Automatic posting of insights to Moltbook
• Flexible Scheduling — Run on a schedule or continuously in daemon mode
• Modular Architecture — Separation of concerns: analysis, summarization, and posting
• systemd Integration — Automatic restart and startup management
• Secure Credential Handling — API keys managed via environment variables
• One-Command Deployment — Simplified installation and uninstallation
• Linux-Native Design — Optimized for Linux systems with systemd

Goblins/
├── goblin/                  # Core AI analysis module
│   ├── analyzer.py          # Lab data analysis logic
│   └── prompts.py           # LLM prompt templates
├── moltbook/                # Moltbook platform integration
│   ├── moltbook_client.py   # API client
│   └── poster.py            # Publishing logic
├── data/                    # Input cybersecurity lab results
├── reports/                 # Generated analysis reports
├── main.py                  # Application entry point
├── requirements.txt         # Python dependencies
├── install.sh               # Installation script
├── uninstall.sh             # Uninstallation script
└── README.md                # This file

1. Read — Loads cybersecurity lab results from the data directory
2. Analyze — Processes findings using AI-powered analysis
3. Summarize — Generates safe, educational summaries of the analysis
4. Publish — Posts insights to Moltbook automatically
5. Wait — Sleeps until the next scheduled run

Key Principle: No active scanning, exploitation, or unauthorized system access—purely educational analysis.

• No Committed Secrets — API keys are never stored in version control
• Environment-Based Secrets — Credentials managed via environment variables only
• Ignored Sensitive Files — .env, venv, and __pycache__ are excluded from Git
• Resilient Daemon — Automatic restart on failure with systemd supervision
• Safe-by-Default — Educational analysis only; no active attack capabilities

• Linux system with systemd
• Python 3.9 or higher
• Moltbook account with valid API key

git clone https://github.com/Pushpenderrathore/Goblins.git
cd Goblins
chmod +x install.sh
./install.sh

You will be prompted to securely enter your Moltbook API key during installation.

# Check service status
systemctl status goblins.service

# View real-time logs
journalctl -u goblins.service -f

# Restart the service
sudo systemctl restart goblins.service

# Stop the service
sudo systemctl stop goblins.service

cd Goblins
chmod +x uninstall.sh
./uninstall.sh

This removes:

• systemd service unit
• daemon registration

Project files are preserved unless explicitly deleted.

For testing before enabling daemon mode:

export MOLTBOOK_API_KEY="your_api_key_here"
python main.py

This runs the agent once in the foreground, useful for debugging and validation.

• Docker containerization support
• Cloud VM deployment (AWS EC2, Fly.io, Railway)
• Multi-agent orchestration
• Enhanced scheduling options

This project is intended strictly for educational and ethical cybersecurity research.

This project does NOT:

• Perform active attacks or scanning
• Access unauthorized systems
• Exploit vulnerabilities in production environments
• Replace professional security auditing or human judgment

Usage Responsibility: You are entirely responsible for ensuring your use complies with applicable laws and ethical guidelines.

Pushpender Singh Rathore
B.Tech Computer Science
Cybersecurity & AI Enthusiast

• GitHub: Pushpenderrathore

Contributions are welcome! Please follow these guidelines:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/your-feature)
3. Commit your changes with clear messages
4. Push to the branch and create a Pull Request

For major changes, please open an issue first to discuss your proposal.

[Add appropriate license here - e.g., MIT, GPL-3.0, etc.]