# AI-Driven Cybersecurity: Deploy Beelzebub + Regolo to Trap Hackers in Minutes

👉[Implement your HoneyPot now](https://dashboard.regolo.ai)

Traditional honeypots are brittle—hackers spot static fake services instantly. Meanwhile, real attacks on your AI agents (prompt injection, lateral movement) happen in blind spots because you can't risk running a "real" vulnerable agent in production just to see what happens.
Security teams need a way to **safely** observe how attackers interact with LLM-based systems without exposing actual infrastructure or customer data.

**Run a Beelzebub Honeypot powered by Regolo in less than 10 minutes. 100% realistic interaction, zero risk to your stack.**

## **Outcome**

- **Hyper-realistic Deception:** The LLM hallucinates a consistent, reactive file system or service (SSH, HTTP) so convincing that attackers waste hours dropping payloads into a void.
- **Zero-Risk Intel:** Catch prompt injections and malicious commands aimed at your AI agents *before* they hit production.
- **Instant Observability:** Logs every keystroke and command directly to your dashboard (or Prometheus/ELK), giving you a "black box" recording of the attack.

## **Prerequisites (Fast)**

- **[Regolo API Key](http://dashboard.regolo.ai)**: Get it from the dashboard.
- **Docker/Go**: Basic container or Go environment installed.
- **Beelzebub**: The open-source framework (free).

## **Step-by-Step (Code Blocks)**

### ****1) Get your Regolo API Key****

Generate a key to give your honeypot a "brain."
*Dashboard > API Keys > Create New*

### **2) Clone & Prepare**

Download the framework. It’s a single Go binary or Docker container.

```
git clone https://github.com/mariocandela/beelzebub
cd beelzebub
mkdir -p ./configurations/services-regoloCode language: Bash (bash)
```

Expected output: Project structure ready for your custom configuration.

### **3) Configure the "Trap" (YAML)**

Define an SSH service that looks like a vulnerable Ubuntu server, but is actually an LLM hallucination powered by Regolo.
*File: ./configurations/services-regolo/ssh-trap.yaml*

```
apiVersion: "v1"
protocol: "ssh"
address: ":2222"
description: "SSH Interactive Trap (Regolo)"
commands:
  - regex: "^(.+)$"
    plugin: "LLMHoneypot"
serverVersion: "OpenSSH"
serverName: "ubuntu"
# Allow common passwords to let them "win" access easily
passwordRegex: "^(root|admin|password|123456)$"
deadlineTimeoutSeconds: 6000
plugin:
  llmProvider: "openai"              
  llmModel: "mistral-small3.2"         # Efficient model for chat/terminal simulation
  host: "https://api.regolo.ai/v1"     # Regolo's OpenAI-compatible endpoint
  openAISecretKey: "YOUR_REGOLO_KEY"
  systemPrompt: "You are an Ubuntu 20.04 LTS terminal. Respond only with the output of the command the user types. Do not explain. Be realistic."Code language: PHP (php)
```

Expected output: A configuration telling Beelzebub to route all SSH commands to Regolo and print the response as if it were a real terminal.

### **4) Build & Run**

Compile the binary and launch it with your new config.​

```
go build -o beelzebub .
./beelzebub --confCore ./configurations/beelzebub.yaml \
            --confServices ./configurations/services-regolo/
```

Expected output:
**\[INFO\] SSH Honeypot listening on :2222**

### **5) Test the Deception**

Try to hack yourself.

```
ssh root@localhost -p 2222
# Password: rootCode language: CSS (css)
```

Once inside, type ls -la, pwd, or cat /etc/passwd.
Expected output: The LLM generates realistic file listings and command outputs instantly. To the attacker, it feels real.

## **Production-Ready: Docker Deploy**

For a persistent deployment that survives reboots and logs data properly.

```
# docker-compose.yml
version: '3'
services:
  beelzebub:
    build: .
    ports:
      - "2222:2222"
    environment:
      - OPEN_AI_SECRET_KEY=${REGOLO_API_KEY}
    volumes:
      - ./configurations/services-regolo:/app/configurations/servicesCode language: YAML (yaml)
```

Command: **docker-compose up -d**

## **Benchmarks & Costs**

Why use Regolo for this?

| **Feature** | **Regolo (Mistral/Llama)** | **Traditional Honeypot** |
|---|---|---|
| **Realism** | **High (Generative)**. Adapts to *any* command.[ beelzebub-honeypot](https://beelzebub-honeypot.com/blog/how-to-build-honeypot-with-beelzebub-and-llm/)​ | Low. Fails on unexpected commands. |
| **Maintenance** | **Zero**. No VM to reimagine or clean up. | High. Must reset compromised VMs daily. |
| **Cost** | **~€0.01 per attacker session**. Pay only for generated text. | Fixed server costs + storage. |
| **Risk** | **None**. Attacker is in a text simulation, not a shell. | Moderate. VM escapes are possible. |

👉[Implement your HoneyPot now](https://dashboard.regolo.ai)

---

## **Resources & Community**

**Official Documentation:**

- [n8n Documentation](https://docs.n8n.io/) - Workflow automation guide
- [Regolo Platform](https://regolo.ai) - European LLM provider, Zero Data-Retention and 100% Green

**Related Guides:**

- [Boost Your Workflows with Regolo AI on n8n](https://regolo.ai/boost-your-workflows-with-regolo-ai-on-n8n/)
- [Build Multi-Agent Workflows with crewAI Teams](https://regolo.ai/build-multi-agent-workflows-with-crewai-teams/)

**Join the Community:**

- [Regolo Discord](https://discord.gg/ZzZvuR2y) - Share your automation builds
- [CheshireCat GitHub](https://github.com/cheshire-cat-ai) - Contribute plugins
- Follow Us on X[ @regolo\_ai](https://x.com/regolo_ai) - Show your integrations!
- Open discussion on our [Subreddit Community](https://www.reddit.com/r/regolo_ai/)

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## **🚀 Ready to Deploy?**

## [**Get Free Regolo Credits →**](https://dashboard.regolo.ai)

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> *Built with ❤️ by the Regolo team. Questions? support@regolo.ai*