Run Untrusted Agent Code Securely
💡Learn how to run agent-written code with sandboxing, scoped tools, and durable human approval checkpoints.
⚡ 30-Second TL;DR
What Changed
Runs JavaScript and type-stripped TypeScript in a fresh QuickJS context inside a worker thread.
Why It Matters
Run SDK changes agent tool use from a sequence of model-generated calls into an executable, resumable program with explicit authority boundaries. This can reduce context usage and improve safety for agents that coordinate multiple internal services or perform sensitive actions.
What To Do Next
Prototype a sensitive agent workflow with Run SDK by exposing only narrowly scoped host functions such as orders.refund(id), then test pause-and-resume approval flows.
Key Points
- •Runs JavaScript and type-stripped TypeScript in a fresh QuickJS context inside a worker thread.
- •Sandboxed programs have no direct route to Node.js or the network; applications expose selected capabilities through host functions.
- •Signed interruption tokens let applications pause runs for authentication or human approval and resume them later.
- •Completed host-function calls are replayed from recorded results, avoiding duplicate work after resumption.
- •The SDK supports agent code execution, code interpreters, and customer-defined data transformations.
🧠 Deep Insight
Background and context from public sources — not the original article. 12 sources cited.
🔑 Enhanced Key Takeaways
- •Vercel Sandbox leverages Firecracker microVMs to provide hardware-level isolation, moving beyond simple process-level sandboxing.
- •The platform enforces granular network egress policies, allowing developers to explicitly whitelist specific LLM endpoints while defaulting to a 'deny-all' posture.
- •Vercel launched a $1,000,000 bounty program on HackerOne in August 2026 specifically to stress-test the security boundaries of the sandbox environment.
- •The infrastructure supports 'fluid compute' architecture, enabling sub-second cold starts for ephemeral agent execution environments.
- •The system is designed to mitigate AI-specific attack vectors, including resource exhaustion from infinite loops and unauthorized data exfiltration via prompt injection.
📊 Competitor Analysis▸ Show
| Feature | Vercel Sandbox | E2B | Piston (by Pipedream) |
|---|---|---|---|
| Isolation | Firecracker microVM | Firecracker microVM | Docker Containers |
| Primary Focus | Vercel AI Stack Integration | AI Agent Runtime | Code Execution API |
| Pricing | Usage-based (Vercel Billing) | Tiered/Usage-based | Open Source/Self-hosted |
| Benchmarks | Sub-second cold starts | ~1s cold starts | Variable (Host dependent) |
🛠️ Technical Deep Dive
- Uses Firecracker microVMs to provide a dedicated guest kernel for each execution instance.
- Implements ephemeral lifecycle management where environments are destroyed immediately after task completion to prevent state persistence.
- Integrates with the Vercel AI SDK to allow seamless state management and interruption token handling.
- Enforces strict resource constraints (CPU/Memory) at the hypervisor level to prevent denial-of-service attacks from runaway agent code.
- Supports multi-language SDKs including JavaScript, TypeScript, and Python for sandbox orchestration.
🔮 Future ImplicationsAI analysis grounded in cited sources
⏳ Timeline
📎 Sources (12)
Factual claims are grounded in the sources below. Forward-looking analysis is AI-generated interpretation.
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Original source: Vercel News ↗
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