Show HN: Plimsoll, a self-hosted sandbox for code your AI agent writes

plimsoll plimsoll runs untrusted code, such as code an AI agent wrote, inside a sandbox, and every result says how strong that sandbox was. A request can demand a minimum strength; if the sandbox is weaker, nothing runs. The name comes from the Plimsoll line, the load limit painted on the outside of a ship's hull where anyone can check it. plimsoll does the same for the isolation tier: how strong the wall around a run is, stated as one of four levels, weakest first: process, container, kernel, vm. The tier is a value on every result, not a sentence in a datasheet. A request can set a floor, the weakest tier it will accept, and the official Go client checks the tier again when the result comes back. The same machinery lets plimsoll run an exam on code an agent wrote, not only contain it. A trial runner built into the simulation image runs the agent's program against scenarios that program cannot read: each one reaches the runner in a file deleted before the program starts. Every run returns SHA-256 hashes of the request as sent and the result as returned, which the official clients recompute (how). A separate program outside the daemon, plimsoll-attest, signs the checked results, refuses a chain of calls with one missing, and replays a run. The exam itself (the simulated system, the scenarios, the pass mark) stays yours: plimsoll supplies the boundary and the evidence. See one real run An AI agent wrote a controller: a program that reads a system's state at every tick (here, one 10 ms step of the simulation) and decides how to push it. plimsoll ran it against a simulated cart-pole, a cart on a rail with a pole hinged on top, which the controller keeps upright by pushing the cart left and right. The simulator is compiled to WebAssembly, a portable bytecode that runs inside a host program, and built into the sandbox image. The controller was the only file the caller sent, through the ordinary project API, and it ran at the container tier. The cart-pole is the standard teaching problem in control engineering. The runner, a program built into the image that runs the controller against the simulator, records the run's trajectory, every state at every tick, and hashes it into a fingerprint: a SHA-256 hash, so equal fingerprints mean identical numbers. Run the accepted controller twice and the two fingerprints match. The agent's first draft had two gains (multipliers in its formula) with the wrong sign: it drops the pole at 5.96 seconds, and its fingerprint differs. Open the live run report ↗ to replay both runs in the browser, read the controller the agent wrote, and see what the page deliberately does not claim. One execution of the example makes three sandbox runs: the accepted controller twice and the draft once. Reproduce them with make docker-images && go run ./examples/oracle. The two things it does It reports the wall. Every result states the isolation tier the run actually got. Every request can set a floor, and a request whose floor the daemon cannot meet is refused before any code runs: ErrInsufficientIsolation means nothing ran. res, err := provider.Sandbox.RunJavaScript(ctx, sandbox.Request{ Code: "console.log(6 * 7)", MinimumIsolation: sandbox.IsolationVM, // ErrInsufficientIsolation means nothing ran }) // res.Isolation reports the boundary that actually ran. Every refusal that ran nothing is marked as one, with a reason (request, permission, protocol, unsupported, isolation, environment, capacity). sandbox.NotDispatchedReason(err) reads the mark, whether the provider (the backend that runs the code) is in your own process or behind the daemon. An error without the mark may have come after the code started, so it is never safe to retry automatically. A mark counts only on an answer that carries the client's request ID back, so a proxy that serves one request's answer for another cannot make a call that ran read "nothing ran" (what comes back, and what it means). The tier is evidence the daemon collected: its configuration and its own startup checks. It is not attestation, cryptographic proof from the hardware of what software is running, and no provider here offers that. docs/isolation-tiers.md lists what each tier rests on. It lets agent-written code call your API without ever holding your credential, your API's address, or open network access. A grant gives one run permission to call listed routes of one API. The code calls through a small client plimsoll puts in the sandbox, and the broker, the part of plimsoll outside the sandbox that makes the real call, checks the caller and the exact route, then attaches the credential itself. The credential is minted per run: plimsoll asks for it once per run, so it can be a fresh short-lived token, and it never enters the sandbox. Code that skips the client and calls out by hand gets no further, because the broker, not the client, enforces the rules. See docs/capability-grants.md. Use it from an agent framework These agent frameworks can hand their model's code to plimsoll through a tool or code executor of their own (Trigger.dev, one of them, is a hosted TypeScript job runner). Each row names what to install, the guide, and a page that replays recorded calls from that framework's tool to a sandbox and back, refusals included. Give a Trigger.dev agent a code tool The TypeScript add-on gives an executeCode tool to a chat agent on Trigger.dev. On a daemon with a session, one sandbox kept for several calls, each call is a cell, code run inside the interpreter kept for that conversation: variables and files can survive the next call. Each tool result says whether they can survive, whether this call started fresh, the isolation tier it ran behind, and the SHA-256 of the run record, a receipt for what was sent and returned that the client checked before returning. The caller sets a minimum tier, so a weaker provider refuses before running code. See the feature and deployment guide for the exact guarantees and production floor. The deployable Trigger.dev starter has a chat agent and a task that proves two cells share one interpreter through a real daemon, without making an AI model call. Run something in one minute The example needs no daemon, no docker, no credentials and no network: it uses the wasm provider, which runs JavaScript on QuickJS, a small JavaScript engine compiled to WebAssembly, inside your own process. Cloning and fetching Go modules do use the network. git clone https://github.com/plimsollmark/plimsoll && cd plimsoll go run ./examples/minimal provider wasm isolation process exit code 0 timed out false truncated stdout=false stderr=false duration 304ms stdout {"Engineering":59000000,"Sales":20300000,"Operations":9800000} The isolation line comes from the run's result, not from the example's own text. process means there is no operating-system wall at all: do not use it for hostile code. The same snippet runs at the kernel tier once gVisor is installed. gVisor is a layer between a container and your machine's kernel that handles the container's requests to the operating system itself, so the code never talks to your kernel directly. sudo ./docker/install-gvisor.sh installs a pinned gVisor release (one exact version, changed only by editing this repository) and registers its runtime, runsc, with docker. Nothing else about the program changes: make docker-images # builds the project image (plimsoll/sandbox) the docker provider checks for SANDBOX_PROVIDER=docker SANDBOX_DOCKER_RUNTIME=runsc go run ./examples/minimal With SANDBOX_PROVIDER unset, plimsoll uses the Disabled provider, which runs nothing, so code execution is never on by accident. Next: docs/getting-started.md walks through the same pieces on one machine: start the daemon, create a caller credential, write your own client, watch a floor refuse a run, then move the daemon from process to kernel without changing the client. It also covers embedding the Go package instead of running the daemon. Where the pieces sit flowchart LR A["Agent or MCP gateway (MCP: how an AI app offers tools to a model)"] -->|"Run: one payload, a protocol number, minimum_isolation"| AU subgraph D["plimsolld"] AU["authenticate the caller"] --> FL["compare the floor with current provider evidence"] FL --> DI["dispatch"] BR["broker: holds the minted credential, matches the exact route, counts every call"] end DI --> W["wasm: QuickJS on wazero (process tier)"] DI --> K["docker with runsc (kernel tier)"] DI --> V["e2b Firecracker (VM tier)"] W -. "host.get / host.post" .-> BR K -. "per-run Unix socket" .-> BR V -. "authenticated guard" .-> BR BR ==> |"your credential, attached host-side"| API["Your API"] The code inside the sandbox, the guest, never holds the credential and never reaches the network directly. A run with no grant has no network at all. Isolation tiers plimsolld is the plimsoll server. Each one runs exactly one provider, chosen by SANDBOX_PROVIDER: Each tier rests on the daemon's configuration, what the provider reports, and a real test run at startup; none is attestation. docs/isolation-tiers.md lists the evidence for each tier and shows how a request sets its floor. A session trades the fresh sandbox of every call for speed and kept state: code an earlier call ran can change what later calls see, and a call with API access needs a grant that allows sessions (docs/sessions.md). A session is one trust domain, and plimsoll ties it to the authenticated caller, not to that caller's customers: a service that runs many customers' code through one credential must keep each customer in a session of their own (who may share a session). The docker provider can also apply the shipped seccomp profile, a list of the only system calls (requests to the kernel, such as opening a file) its containers may make (docs/seccomp.md). How this compares with the other self-hosted sandboxes for agent code (E2B's self-hosted version, microsandbox, NVIDIA OpenShell, Kubernetes agent-sandbox and eight more), each described from its own documentation, with plimsoll's weak points beside them: the comparison (INTERNAL · plimsoll site →). More real runs Status, plainly Pre-1.0, single author, no external users yet. Breaking changes land without a deprecation path, on purpose. No third-party security audit has ever been performed, and the author's own self-review ledgers are not published either. SECURITY.md says what exists, what it is worth, and what you can check yourself instead. CI runs the gate, in the open, and each check means what it ran. The audit workflow has three jobs. audit runs plain make audit on every push to main and every pull request: build, vet, race tests, lint, buf lint, a generated-code drift check, and govulncheck. After audit, clients runs make clients-suite: npm ci in clients/typescript and examples/trigger-chat, then the Python and TypeScript Go test packages in required mode. A missing runtime, dependency or skipped Go test fails that job. audit-docker also follows audit and runs make docker-suite with the images prepared, in required mode: a missing daemon, a missing image or a skipped test fails the job. A green audit-docker therefore means the docker suite ran under runc with the shipped seccomp profile and proved a read-only root, sized noexec writable mounts, and the broker's refusals. The gvisor workflow runs the same suite under runsc, the kernel tier, from the pinned installer. The race detector runs in the plain audit job and both docker-suite jobs; the client job runs without it. No check exercises E2B or Docker Cloud Sandboxes: those suites drive live paid services and are deliberately never wired to a runner. See CONTRIBUTING.md. Learn how it works The interactive lessons are the fastest way in if you would rather read than clone. Start with Plain English for the idea before the API, or Quick start to run something. Every term these docs use has a one-sentence definition in the glossary. The lessons live in docs/trainers/ and work offline: open any file from a clone in a browser. GitHub shows .html files as source instead of rendering them, which is why the links above point at the published copy. Documentation Each of these answers one question, end to end. License Apache-2.0.