Vercel Sandboxes

Canonical version: Vercel Sandboxes.

Vercel Sandboxes are isolated, ephemeral microVMs that Vercel provides for running untrusted or AI-agent-driven workloads. They give a coding agent a real machine — file system, shell, network — without exposing the host or production infrastructure to the agent.

Why They Exist

AI Agents increasingly need to execute arbitrary commands, install dependencies, and run code. Doing that on your laptop or your production CI runner means the agent inherits whatever credentials and access those environments hold — a serious security and exfiltration risk. Sandboxes solve this by running the agent inside a microVM where:

  • API keys and secrets are injected from outside, not visible to processes inside
  • Network egress is restricted to an allowlist of approved hosts
  • The whole environment is destroyed after the run

This matches the threat model of "treat the agent like a coding agent with full shell access" — because that's exactly what it is.

Use Cases

  • Distributed code analysisVercel DeepSec parallelizes vulnerability scanning across many sandboxes for monorepo-scale codebases
  • Agent execution at scale — running many agent instances in parallel without contention
  • Untrusted code execution — running user-submitted code in SaaS products
  • CI augmentation — replacing or extending traditional CI runners for AI-driven pipelines

How They Fit the Vercel Stack

Sandboxes are part of Vercel's compute family alongside Fluid Compute, serverless functions, and the edge network. They share the platform's deployment, observability, and credential management surfaces, so an agent run inside a sandbox feels native rather than bolted on.

References


About Sébastien

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