# AWS introduces Strands Box open source AI agent sandbox

> **Key takeaway:** Strands Box provides an Apache 2.0 licensed sandbox that combines OS-level isolation with the Dogwood policy language to govern AI agent actions.

**Published:** 2026-10-07T17:36:46+00:00 
**Source:** AWS Open Source Blog 
**Category:** bigtech-foss 
**Canonical URL:** https://fosswire.org/news/strands-box-ai-agent-sandboxes-powered-by-dogwood.html 

## Summary
AWS has launched the developer preview of Strands Box, an open source sandbox designed to secure autonomous AI agents. Licensed under Apache 2.0, the tool uses OS-level containment and the Dogwood policy language to enforce fine-grained rules based on an agent's action history. It intercepts operations across network egress, Python, Shell, and Model Context Protocol (MCP) servers to prevent unauthorized file access or network requests.

## Technical architecture of Strands Box
- Uses a two-layer approach: **containment** (OS-level isolation like macOS Seatbelt) and **policy** (governance via Dogwood).
- Employs the **Dogwood Local Engine** to evaluate permissions based on current requests and historical event logs.
- Enforcement points include a **network egress proxy**, a **Python interpreter** (using Monty), a **Shell interpreter** (using Strands Shell), and an **MCP broker**.
- Provides contextual security, such as limiting the frequency of specific actions (e.g., Slack posts) or blocking network requests after specific file reads.
- Operates via local sockets, allowing interpreters to run outside the sandbox while enforcing decisions from the host process.

## Why it matters
By providing a standardized, history-aware policy language for AI agents, Strands Box aims to move agent security beyond simple container isolation toward granular, context-dependent governance.