Agent Sandbox provides a secure, and isolated execution layer to safely deploy autonomous AI agents on Kubernetes that generate and run untrusted code at scale.
Use Cases
Short-lived sandbox
Code Execution
Run untrusted code in fully isolated sandboxes. Ideal for code interpreters, analytics tools, and on-demand computation.
Medium-lived sandbox
Coding Agents
Autonomous agents that write, debug, and refactor code inside secure sandboxes with full dev tooling.
Medium-lived sandbox
Computer Use
AI agents that interact with graphical desktops, browsers, and GUI applications inside isolated sandboxes.
Short to medium-lived sandbox
CI/CD
Integrate Agent Sandbox into CI/CD pipelines for isolated testing, validation, and automated workflows.
Always-lived sandbox
Agents in Sandbox — OpenClaw
Run always-on agent environments with OpenClaw inside Agent Sandbox for persistent, long-running workloads.
Isolation runtime
gVisor Isolation
Harden sandbox isolation with gVisor — a userspace kernel that intercepts system calls to protect the host.
Isolation runtime
Kata Containers Isolation
Hardware virtualization with a dedicated kernel per sandbox via Kata Containers and QEMU.
Enable Complex Agentic Workloads
Safely execute arbitrary, untrusted code in a fully isolated environment to enable high-risk applications like stateful code interpretation, agentic web browsing, complex "computer use" tasks, and sophisticated data analysis
Decoupled Isolation. Built for Choice
Interoperability is core to Agent Sandbox with a standardized Kubernetes API that fully decouples the execution layer from the underlying isolation technology. This abstraction supports various backends, including gVisor and Kata Containers, allowing you to select the isolation method that perfectly aligns with your specific security, performance, and workload needs