How do I install Quicksand?

Install with pip install 'quick-sandbox[qemu,alpine]' for a full setup, or pip install quick-sandbox followed by quicksand install qemu alpine to add QEMU and images separately.

What platforms and architectures does Quicksand support?

Quicksand works on x86_64 and ARM64 across macOS, Linux, and Windows with no root privileges required.

Can I save and restore a sandbox environment?

Yes. You can save the VM's disk state to a directory with await sb.save("my-env") and load it later on the same or a different machine, or use checkpoints to capture full VM state and revert if something goes wrong.

Are sandboxes network-isolated by default?

Yes, sandboxes are network-isolated by default. You can opt in to internet access and port forwarding by setting network_mode=NetworkMode.FULL.

Large Language ModelsAI Coding AssistantsOpen-Source AIHacker NewsJul 28, 2026Jul 28, 2026, 22:00 JST

Microsoft releases Quicksand: Python API to sandbox AI agents via QEMU

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3 Key Points

What happened
Microsoft has released Quicksand, an async Python library that launches and controls QEMU virtual machines for sandboxing AI agents. It runs on x86_64 and ARM64 across macOS, Linux, and Windows without requiring Docker, WSL, root privileges, or system dependencies—users can install it with a single pip command.
Why it matters
AI developers need isolated execution environments to safely run agents. Quicksand removes friction by eliminating Docker and system-level setup overhead, making sandboxing accessible to Python developers who want to snapshot, checkpoint, and roll back agent workloads without complex infrastructure.
What to watch
The library ships with five pre-built images (ubuntu, alpine, ubuntu-desktop, alpine-desktop, and quicksand-agent) ranging from ~78 MB to ~445 MB. It supports desktop control via Xfce4, network isolation by default with opt-in full internet access, and persistent state snapshots that can be loaded on different machines.

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Context & Analysis

Quicksand addresses a concrete pain point for AI agent developers: the need to safely execute untrusted or experimental code in isolation. By wrapping QEMU with a Python async API, Microsoft eliminates the typical barriers to VM-based sandboxing—no Docker daemon, no WSL layer, no root privileges. The library's pre-built images (ranging from Alpine at ~78 MB for fast boot to a full agent stack at ~445 MB) and snapshot/checkpoint capabilities make it possible to prototype, test, and roll back agent behavior without managing infrastructure.

The tool's flexibility—supporting both headless and desktop images, file mounts, port forwarding, and cross-machine snapshot restoration—suggests it is designed for both development workflows (where agents may need GUI access or browser control) and production-like scenarios (where state must be preserved and migrated). Network isolation by default aligns with security-first design; opt-in FULL mode lets developers test internet-dependent behaviors when needed.

FAQ

How do I install Quicksand?: Install with pip install 'quick-sandbox[qemu,alpine]' for a full setup, or pip install quick-sandbox followed by quicksand install qemu alpine to add QEMU and images separately.
What platforms and architectures does Quicksand support?: Quicksand works on x86_64 and ARM64 across macOS, Linux, and Windows with no root privileges required.
Can I save and restore a sandbox environment?: Yes. You can save the VM's disk state to a directory with await sb.save("my-env") and load it later on the same or a different machine, or use checkpoints to capture full VM state and revert if something goes wrong.
Are sandboxes network-isolated by default?: Yes, sandboxes are network-isolated by default. You can opt in to internet access and port forwarding by setting network_mode=NetworkMode.FULL.

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