agentlure

Detonate MCP servers against fake credentials before you install them.

agentlure runs an untrusted MCP server inside a sandbox planted with canary credentials and a sinkholed network, calls each of its tools once, and reports what the server actually tried to read or send out. The verdict is deterministic: no account, no LLM judge, no static pattern matching.

Quickstart

pip install agentlure
# or, with uv:
uvx agentlure scan --command "python3 path/to/server.py"

agentlure scan --config ~/.config/mcp.json --server my-server
agentlure scan --command "npx -y some-mcp-server"

Exit codes: 0 = CLEAN, 1 = SUSPICIOUS, 2 = MALICIOUS (see --fail-on below for CI gating).

Requires Linux, Python 3.9+, and a sandbox backend: Docker, Podman, or Linux namespaces (unshare + strace). agentlure refuses to run a target when no sandbox backend is available.

How a scan works

1. Canaries are minted, fresh for every run: an AWS key pair, a GitHub token, an npm token, an SSH key pair, and a .env bundle (database URL, Stripe key, SendGrid key). Each value has a recognizable prefix and a random suffix, so a captured payload attributes to exactly one run.
2. A synthetic HOME is planted with those canaries at the usual paths: ~/.aws/credentials, ~/.ssh/id_rsa, ~/.env, ~/.config/gh/hosts.yml, ~/.npmrc. The target's HOME points at the synthetic directory. Your real home is never the target's home.
3. The target starts inside the sandbox with no real network egress. Its only reachable endpoint is a sinkhole proxy on loopback, injected through the standard HTTP_PROXY/HTTPS_PROXY environment variables. The proxy logs every request and searches the payload — URL, headers, body — for canary values in raw, base64, hex, and URL-encoded form, including encoded-inside-encoded payloads (for example a base64'd file riding in a query string).
4. agentlure drives the server over MCP (stdio, JSON-RPC): initialize, tools/list, then one tools/call per tool with benign arguments synthesized from the tool's input schema (strings become "hello", integers 1, enums their first value, and so on).
5. Behaviour is graded from strace and proxy evidence, and reports are written: a terminal summary, report.json, report.sarif (SARIF 2.1.0), and a standalone report.html. Reports contain masked canary values only; the full proxy capture is kept in network.jsonl next to the reports.

Evidence and verdicts

• MALICIOUS — any canary_egress.
• SUSPICIOUS — any of the other three classes, without egress.
• CLEAN — no evidence.

Reading a canary is not proof of theft — a server may legitimately look at its own configuration. Sending one out is. That is why only egress grades MALICIOUS.

For CI, --fail-on suspicious|malicious turns the exit code into a gate: the scan exits 0 when the verdict is below the chosen grade, and with the grade code (1 or 2) at or above it. Without --fail-on, the exit code is the grade code itself.

Sandbox backends

Backends are auto-detected in this order: Docker, Podman, namespace. --backend forces one.

• Docker / Podman — run with a read-only root filesystem, --cap-drop ALL, no-new-privileges, memory/CPU/pids limits, and --network none; the sinkhole proxy runs inside the container on its loopback. The image (default agentlure-sandbox:latest, override with --sandbox-image or AGENTLURE_SANDBOX_IMAGE) must contain Python 3, strace, agentlure itself, and the runtime your target needs. These backends are implemented to the same interface as the namespace backend but are not covered by the project's own tests in v0.1 — the development environment has no container daemon. Prefer them for hostile targets once you have validated the image.
• Namespace — user + mount + PID + network namespaces via unshare. The target's HOME is the synthetic home; the credential-bearing paths of the real home (~/.aws, ~/.ssh, ~/.config/gh, ~/.env) are additionally bind-masked with the canary versions when they exist, so absolute-path reads hit canaries too. The network namespace contains loopback only, with the sinkhole on it. The target is traced with strace -f. This backend is what agentlure selftest exercises.

Self-safety model

agentlure exists to run hostile code, so the scanner treats itself as part of the attack surface:

• The target never runs outside a sandbox backend; there is no --no-sandbox flag and there will not be one.
• Canary values are fake and minted per run. No real credential is ever planted, read, or passed into the sandbox. The canary manifest reaches the in-sandbox proxy through the environment and is scrubbed from the target's environment before launch.
• The network namespace has no route out; the sinkhole terminates every connection. CONNECT tunnels are logged and closed, never forwarded.
• Wall-clock timeouts, CPU rlimits, and process-group teardown bound every run.

Honest limits of the namespace backend: it redirects HOME, masks the known credential paths, kills the network, and watches syscalls, but it shares the host filesystem — a target that goes looking with absolute paths can see (and, with your user's permissions, modify) files outside the masked paths, and the PID namespace uses the host's /proc when mounting a fresh one is not permitted. For code you actively distrust, use a container backend or a throwaway VM.

Limitations (v0.1)

• Linux only. Stdio MCP servers only — no remote/HTTP servers yet.
• Each tool is called once, with schema-derived arguments. Servers that misbehave only on specific argument values, on a second call, or after a delay longer than the observation window will not be caught by this version.
• A target that exfiltrates through a channel that ignores proxy environment variables gets no route out of the network namespace, so the attempt fails silently instead of producing evidence.
• Verdicts are evidence, not proof of intent: a SUSPICIOUS grade means "look at this", and the HTML report shows exactly what was observed.

GitHub Action

- uses: 0xABCD01/agentlure@v0.1.0
  with:
    config: mcp.json
    server: my-server
    fail-on: malicious

Inputs: command or config (+ server), fail-on, version. Output: verdict. The full report is uploaded as a workflow artifact.

npm wrapper

npx agentlure ... works through a thin Node shim (in npm/): it delegates to uvx agentlure@0.1.0 when uv is present, else to an installed Python package (python3 -m agentlure), else it prints install instructions. The scanner itself is the Python package.

Selftest

The package ships six fixture servers (in agentlure/fixtures/) — three malicious (SSH-key reader, .env exfiltrator, an email tool with a silent BCC copy) and three benign (echo/calculator, a notes server that stays in its workdir, a time client that makes one plain HTTP request). From any install:

pip install agentlure
agentlure selftest        # expects MALICIOUS x3, CLEAN x3

From a source checkout, the unit tests run with python3 -m unittest discover.

selftest runs every fixture through the real sandbox pipeline and fails if any verdict differs from the expected one.

Created by Hafiar — bug hunter & pentester (@0xABCD01).