🧪 E2B Sandbox Runtime
A secure and flexible runtime sandbox built for AI agent execution, code testing, and workload simulation—developed as part of the E2B Research Program.
👤 GitHub: @Zack4DEV
🔒 CODEOWNERS: @Zack4DEV/e2bSandbox @e2b-dev/e2b
🚀 Project Overview
This project provides an isolated and customizable cloud sandbox designed to execute AI-generated code safely, aligned with agentic use cases in modern AI development. It's part of the E2B initiative to empower developers with full virtual machines accessible through secure APIs.
Key Objectives:
- 🔐 Isolated runtime for secure AI code execution
- ⚙ DevOps-friendly deployment and monitoring
- 🧠 LLM-agnostic compatibility
- ☁ Cloud-native, scalable architecture
🛠 Built With
- E2B Runtime SDK – To manage, test, and monitor sandbox lifecycles.
- E2B CLI – CLI Tool build manager your running E2B sandbox and sandbox templates ,Only NodeJs support.
- Python – Runtime control logic.
- Docker / VMs – For reproducible environments.
- GitHub Actions – CI for test & deployment automation.
🎯 Notable Features
✅ Agent-Ready Execution
Launch and monitor full VMs or containers to safely test AI-generated code in real time.
✅ LLM Framework Agnostic
Compatible with OpenAI, Claude, Hugging Face, and custom LLM setups—no vendor lock-in.
✅ Customizable Sandbox Templates
Define runtime specs and preload packages for your AI workflows.
✅ Terminal & Filesystem Access
Expose command-line tools and secure file I/O to your apps.
🧠 Future Enhancements
- Web UI for sandbox session visualization
- Live logs + terminal stream to frontends
- GPU support for ML workloads
- Billing & usage analytics integration
📜 License
This project is licensed under the MIT License. See the LICENSE file for full terms.
🙌 Acknowledgments
- E2B.dev for enabling secure agentic cloud compute
- Zack4DEV for runtime customization and integration
Built for the future of secure AI runtime execution. Powered by vision, code, and cloud.