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Build secure low-code deception runtimes with AI-driven system virtualization.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "beelzebub" yet — see the docs or source repo.
Use beelzebub to create an internet-facing SSH decoy environment with low interaction but complete logging. It should capture source connections, command attempts, and session duration, and provide deployment steps and isolation recommendations.
A decoy environment plan with deployment steps, logging design, and isolation guidance.
Use beelzebub to build a system virtualization runtime for a simulated enterprise network, including file services, a login portal, and basic network response behavior for security research and attack path observation.
A runnable virtualized scenario design, component list, and behavior simulation specification.
Design a low-code deception defense prototype with beelzebub that uses AI to generate decoy assets and interaction logic, and explain how to connect it to existing monitoring and alerting systems.
A prototype architecture, decoy generation approach, integration method, and implementation considerations.
Control a BBC Micro emulator with AI for debugging, testing, and exploration.
Use a hosted domain-specialized LLM and MCP tools for coding and security tasks.
Turn app ideas into IA, wireframes, PRDs, and build-ready specs.
Run a self-evolving multi-agent software team for autonomous development tasks.
Validate and audit LLM-generated code securely in Docker sandboxes.
Scan AI coding workflows for code, secrets, dependency, and tool security risks.