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AgentBoundary AI: Secure AI Agent Execution
AgentBoundary AI is a research prototype developed by The Explorers to address a growing security challenge: how can autonomous AI agents perform useful tasks without receiving unrestricted access to computer systems and sensitive information? Modern AI agents can generate code, interact with tools, and execute commands. However, excessive permissions can lead to unauthorized actions, unexpected code execution, and potential exposure of confidential data. Our solution introduces a task-aware security gateway that separates AI-generated actions from permission decisions. Each task receives limited authorization, and the gateway checks whether permission remains valid before allowing another execution step. Users can revoke permission during a multi-step task, preventing subsequent actions from proceeding. The project also includes a design for disposable Docker sandboxes with restricted network access, filesystem permissions, and resource limits. A containment lab provides controlled scenarios intended to evaluate these restrictions. Our current working prototype is deployed on Render using Python, FastAPI, SQLite, HTML, CSS, and JavaScript. It demonstrates predefined two-step task planning, permission revocation, and audit events. The implementation has passed 27 local automated tests. Vultr Serverless Inference integration and live sandbox execution are planned deployment capabilities that still require validation. Our goal is to make AI-agent workflows more controllable, transparent, and accountable while providing a foundation for future research into secure autonomous execution.
8 Nov 2026
