Use cases
How teams typically deploy VaultRun. These are reference patterns — not named customer case studies — based on the product’s real capabilities (sandboxes, MCP, CI runner, Enterprise SSO).
01 / platform engineering
Shared sandbox platform for AI agents
Problem. Agents need to run untrusted code and touch files. Letting them loose on shared VMs or developer laptops creates blast-radius and audit gaps.
Pattern. One VaultRun API per environment. Agents create a session, upload tools/scripts via API or MCP, run commands in an isolated container, then tear down. Network stays off unless explicitly allowlisted.
- API keys for agents; Enterprise SSO for humans on the dashboard
- HMAC-signed audit trail for every session/run/file action
- OPA hooks for command and path policy
Outcome. A controlled execution plane that stays on your network — no SaaS telemetry, no third-party code runner.
02 / regulated / security-minded AI
Agent access to data and cloud without ambient credentials
Problem. Giving an LLM toolchain raw AWS/DB credentials is risky; banning tools blocks useful workflows.
Pattern. Use MCP tools with explicit opt-in (e.g. AWS tools only when enabled), scoped filesystem allowlists, and Secrets Manager / Vault injection per run — results redacted in audit where needed.
- 53 MCP tools over stdio (Claude) or HTTP (OpenAI / OpenRouter / custom)
- Postgres / SQLite / Mongo tools without putting the agent on the database host
- Enterprise IdP login so dashboard users never share the master key
Outcome. Capability with a paper trail — suitable as an internal control story for security review.
03 / engineering / CI
PR tests inside an isolated VaultRun sandbox
Problem. CI runners that share state or host Docker sockets leak secrets and flake under load.
Pattern. Point a GitHub webhook at ci-runner. Each PR clones into a VaultRun session, runs your test command list, posts a PR comment + commit status, optionally Slack/Teams.
- HMAC webhook validation
- Token-safe clone via
http.extraheader
- Same security model as interactive agent sandboxes
Outcome. Homogeneous isolation for humans, agents, and bots.