Sandboxed.sh — Runs AI agents securely in isolated environments, managing them across local, cloud, and mobile.
Analyzed by Sai Pavan Gopularam · AI · Agents · View on GitHub
- Stars: 513
- Forks: 53
- Commits last 30 days: 100
- Health: Active (100 commits this month)
- Language: Rust
- License: None
What It Is
Imagine a secure playground for your AI agents, like a digital sandbox where they can run code and interact with systems without risking your main computer. Sandboxed.sh provides this isolated environment, ensuring that even if an agent makes a mistake or tries something unexpected, its actions stay contained.
This matters because autonomous AI agents often need to execute code or access tools to complete tasks. Without proper isolation, a buggy or malicious agent could compromise your system. Sandboxed.sh solves this by providing a controlled, observable space, along with client apps for managing agents and their tasks from anywhere.
License Verdict
No License Specified — Commercial Use Prohibited — Proprietary Software • Commercial Use Generally Not Permitted
This repository does not specify an open-source license. By default, this means all rights are reserved by the copyright holder, Th0rgal. You cannot legally use, modify, or distribute this software for commercial purposes without obtaining explicit permission from the owner.
How to Use It
First, run the sandboxed.sh backend on your machine or server using Docker or native Linux. Then, build and open the Orb desktop or iOS client, connect it to your server, and configure your execution environments and model providers. Finally, create a project and launch an AI agent.
Prerequisites:
- Docker
- Rust (for client build)
- Node.js (for client build, implied by Tauri/SolidJS)
Estimated setup time: 30 minutes.
git clone https://github.com/Th0rgal/sandboxed.sh.git
cd sandboxed.sh
# Follow docs/install-docker.md to run the backend, e.g.:
# docker run -d -p 8000:8000 --name sandboxed-backend th0rgal/sandboxed.sh:latest
cd orb
cargo build --releaseWhat I'd Build With This
AI Agent Debugging & Monitoring Dashboard (micro-saas)
Offer a hosted service where developers can connect their sandboxed.sh instances to a centralized dashboard. This dashboard would provide real-time logs, execution traces, and resource usage for agents, helping developers quickly identify and fix issues. Users pay for agent slots and data retention.
Effort: 2 Weeks Build Time · Target: AI Developers, Agent Builders · Pricing: $29/mo for 5 agents, $99/mo for 20 agents
Secure AI Agent Workspace for Teams (saas)
Build a managed SaaS platform based on Sandboxed.sh, offering isolated, collaborative workspaces for teams developing and deploying AI agents. This includes shared projects, credential management, and multi-user access control. Teams can securely run agents against internal systems without exposing sensitive data.
Effort: 3 Months Build Time · Target: Small to Medium AI Development Teams · Pricing: $199/mo per team, plus usage
On-Premises AI Agent Orchestration Platform (enterprise)
Develop an enterprise-grade, self-hosted solution for large organizations to manage and orchestrate hundreds of AI agents across their private cloud or on-premise infrastructure. Focus on robust security, audit trails, custom integrations with existing IT systems, and dedicated support. This leverages sandboxed.sh's remote machine capabilities.
Effort: 6 Months Build Time · Target: Large Enterprises, Government Agencies · Pricing: $50,000+ per year, custom deployments
Sai Pavan Gopularam's Take
This project offers a solid foundation for secure AI agent execution and management, which is a critical need as agents become more capable. The lack of an open-source license is a major hurdle for commercial use, but if the author were to adopt one, a managed service for secure agent deployment could easily fetch $500/month from early adopters.
Watch Out For
- No Commercial License: The repository explicitly states "License: None." This means you cannot legally use, modify, or distribute this software for commercial purposes without explicit permission from the author, which is a significant barrier for any commercial venture.
- Client Build Required: Sandboxed.sh is solely the backend; you need to build and run the Orb desktop (Tauri/SolidJS) or iOS (SwiftUI) client yourself. This adds development complexity and platform-specific overhead.
- Experimental Cloud Connectors: The ChatGPT and Grok Bot connectors are labeled "experimental," implying potential instability or limited functionality. Relying on these for core features in a product could introduce risks.
- Provider Quotas Still Apply: Even with the CLIProxyAPI for model inference, individual provider quotas (e.g., OpenAI, Anthropic) still apply. You will need to manage your own API keys and usage limits, which can be a scaling challenge.
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