Beelzebub
A secure low-code honeypot framework that uses AI to create high-interaction decoy systems for cyber attack detection and analysis.
What is Beelzebub?
Beelzebub is a secure, low-code honeypot framework that uses artificial intelligence to create virtual decoy systems for detecting and analyzing cyber attacks. It simulates high-interaction services like SSH, HTTP, and databases to lure attackers, while maintaining a secure, manageable low-interaction architecture. The framework helps security teams gather threat intelligence, identify malware, and discover vulnerabilities.
Security researchers, DevOps engineers, and cybersecurity professionals who need to deploy honeypots for threat detection, attack analysis, and building distributed threat intelligence networks.
Developers choose Beelzebub for its unique combination of low-code YAML configuration, AI-powered realism, and multi-protocol support, which simplifies deploying convincing honeypots without deep security expertise. Its built-in observability and flexible deployment options make it a practical tool for both research and production security monitoring.
Overview
A secure low code deception runtime framework, leveraging AI for System Virtualization.
Use Cases
Best For
- Deploying decoy SSH servers to capture brute-force attacks and command execution attempts
- Simulating web applications (like WordPress) to detect web-based exploits and unauthorized access
- Setting up MCP (Model Context Protocol) honeypots to detect prompt injection attacks against LLM agents
- Creating TCP service banners (e.g., fake MySQL) to identify network scanning and service enumeration
- Building a distributed honeypot network for global threat intelligence collaboration
- Integrating honeypot data into existing monitoring stacks like Prometheus, ELK, or RabbitMQ
Not Ideal For
- Organizations without budget or access to LLM APIs like OpenAI, as AI features are core to its simulation capabilities
- Teams needing fully emulated, high-interaction honeypots for deep attack analysis, since it prioritizes security with low-interaction architecture
- Projects requiring immediate deployment with zero configuration, as it demands YAML setup for each service
- Environments with strict network isolation that cannot rely on external AI services or cloud integrations
Pros & Cons
Pros
Uses modular YAML files for service definitions, simplifying setup and management without extensive coding, as detailed in the Configuration section with examples for SSH, HTTP, and other protocols.
Integrates LLMs like OpenAI GPT-4o to create convincing high-interaction experiences in SSH and TELNET honeypots, enhancing realism while maintaining secure low-interaction design, shown in the LLM Honeypot Demo.
Supports SSH, HTTP, TCP, TELNET, and MCP (for prompt injection detection), allowing comprehensive threat detection across different attack vectors, with detailed examples provided for each protocol.
Includes Prometheus metrics, event tracing to stdout/RabbitMQ/Beelzebub Cloud, and ELK stack integration, making it easy to monitor and analyze attacks without additional setup.
Cons
AI features rely on external LLM services which require API keys and incur ongoing costs, or local Ollama setup that adds deployment complexity and resource overhead, as noted in the plugin configurations.
Creating highly realistic honeypots necessitates detailed YAML configuration and custom handlers, which can be time-consuming and error-prone, especially for complex service simulations.
While examples are provided, the framework lacks an extensive library of ready-to-use honeypot configurations, pushing users to develop their own from scratch for specific use cases.
Frequently Asked Questions
Related Projects
Auto-GPTAutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
ageA simple, modern and secure encryption tool (and Go library) with small explicit keys, no config options, and UNIX-style composability.
legoLet's Encrypt/ACME client and library written in Go
T-Pot🍯 T-Pot - The All In One Multi Honeypot Platform 🐝
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.