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Name: actrail
Version: 1.1.3
Summary: Runtime policies for agents — the open-source edge SDK (capture + check + enrichment).
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Keywords: agents,ai,governance,guardrails,llm,security
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Description-Content-Type: text/markdown

<div align="center">

# Actrail

### Runtime policies for AI agents — the open-source edge SDK

Govern what your agents **do**, not just what they say. Actrail captures every agent
action as **metadata-only** telemetry and enforces deterministic policies **before**
a risky action runs — a human-readable rule, never an LLM, in the binding decision.

[![PyPI](https://img.shields.io/pypi/v/actrail.svg)](https://pypi.org/project/actrail/)
[![Python](https://img.shields.io/pypi/pyversions/actrail.svg)](https://pypi.org/project/actrail/)
[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://www.apache.org/licenses/LICENSE-2.0)
[![Ruff](https://img.shields.io/badge/lint-ruff-261230.svg)](https://github.com/astral-sh/ruff)
[![mypy: strict](https://img.shields.io/badge/mypy-strict-2a6db2.svg)](https://mypy-lang.org/)

</div>

---

## Why Actrail

AI agents don't just generate text — they **take actions**: refund a customer, delete a
row, deploy to prod, send data to an external LLM. Content guardrails don't see any of
that. Actrail governs the **actions**:

- **Deterministic enforcement.** Policies are plain rules (`refund > $500 without
  approval → require_approval`) evaluated on a bounded request, fail-open by default.
  No model participates in the verdict.
- **Metadata-only by construction.** The SDK never sends raw arguments or results. It
  emits a redacted, per-field *skeleton* — keys kept, values stripped or transformed —
  built from scratch, never copied.
- **An always-on secrets floor.** API keys, tokens, private keys, passwords, connection
  strings are **never** emitted, and it can't be turned off.

## Install

```bash
pip install actrail
```

**Requirements**

- **Python 3.11+.** The system Python on macOS is 3.9 and will **not** work — use a 3.11/3.12 environment.
- **macOS 12+ (Apple Silicon or Intel) or Linux x86_64.** Prebuilt wheels bundle the native shim — no toolchain needed.

Optional extras for deeper local scanning:

```bash
pip install "actrail[ner]"    # + Presidio / spaCy for names & unstructured PII
pip install "actrail[full]"   # + transformers
```

Verify:

```bash
actrail --help                                        # bundled CLI on PATH
python -c "import actrail; print(actrail.__version__)"
```

> **`not a supported wheel on this platform`?** Almost always your Python isn't 3.11/3.12
> (macOS ships 3.9). Create a 3.11/3.12 env — e.g. `uv venv --python 3.12` — and reinstall.

## Quickstart

### Claude Code (zero-code onboarding)

```bash
actrail init --key ak_live_...     # registers the SDK, wires hooks, starts the daemon (shadow)
actrail doctor                     # verify config · hooks · daemon
```

`init` also registers this SDK release with the backend (metadata only —
integration/version/contract, no customer data), so Actrail can install the managed
policies this release is certified to enforce before the first trail arrives.

`init` wires the pre-tool policy check immediately. Policies still begin in shadow,
so nothing blocks until an administrator graduates one to enforce in the Actrail
console. `actrail enforce off` is an explicit local emergency opt-out; `enforce on`
restores the hook if it was removed.

Two managed catalog rules intentionally need organization-specific named sets before
they can govern: `production_destructive_action` needs `prod_hosts`, and
`customer_data_unapproved_destination` needs `approved_destinations`. Configure those
in the console during onboarding; the SDK never guesses tenant trust boundaries.

### Any agent (the library)

```python
import actrail

actrail.init(key="ak_live_...", agent="support-bot")

# Before a risky action — get a deterministic, bounded verdict.
verdict = actrail.check(
    trail_id="sess_42",
    tool="pay.api",
    action="refund",
    payload={"order": {"amount": 2500, "currency": "USD"}, "table": "prod.customers"},
)
if not verdict.allow:
    raise PermissionError(verdict.reason)   # require_approval / deny

# After it runs — capture the action as metadata-only telemetry (fire-and-forget).
actrail.capture(
    trail_id="sess_42",
    tool="pay.api",
    action="refund",
    payload={"order": {"amount": 2500}, "customer": {"email": "alice@example.com"}},
)
```

`payload` is the **structured** tool-call args. Actrail walks it into a governed
`fields[]` envelope — it **never leaves your machine** as raw data.

## The telemetry contract

Every field passes through a **transform ladder**, least → most revealing, and the
customer governs it per field (default-deny):

| Rung | What's emitted | Example |
| --- | --- | --- |
| `drop` | nothing (skeleton only) | unknown fields |
| `type_only` | just the type | `customer.email` → *(type: email)* |
| `derived` | a safe derivation | `email` → `domain:example.com` |
| `bucket` | a coarse bucket | `amount: 2500` → `1000_10000` |
| `token` | a one-way HMAC pseudonym | join without revealing |
| `raw` | the value verbatim | only for non-secret, opted-in fields |

Three guarantees stack, in order:

1. **Default-deny** — an un-contracted field gets a conservative per-type default.
2. **Secrets floor** — a secret-typed field, or *any* value that looks secret, is
   forced to `drop`. **Non-overridable** — a contract can never lift a secret onto the wire.
3. **Outbound validator (fail-closed)** — every emitted value is re-scanned and
   scrubbed if it still looks secret, the last line before anything leaves.

A [seeded fuzz test](tests/contract/test_fuzz_safety.py) asserts the invariant under the
worst case — every field forced to `raw`: **no secret ever appears in an emitted value.**

## What leaves the machine

```jsonc
{
  "tool": "pay.api", "action": "refund", "destination": "internal",
  "data_classes": ["financial", "pii"],          // derived from the envelope
  "fields": [                                     // the redacted skeleton
    {"path": "order.amount", "semantic_type": "amount", "handling": "bucket", "value": "1000_10000"},
    {"path": "customer.email", "semantic_type": "email", "handling": "type_only"},
    {"path": "auth.api_key", "semantic_type": "api_key", "handling": "drop"}   // floored — no value
  ],
  "amount": 2500,                                 // a first-class grammar fact
  "taint_sources": [{"table": "prod.customers"}], // enables "data from prod.customers" policies
  "taint": ["email:v1:9f3a…"],                    // one-way fingerprints (flow, not values)
  "sdk_version": "1.1.0", "contract_version": "v1"
}
```

No `args`. No `result`. No raw values. Ever.

## Architecture

```
tool call ──► capture()/check() ──► enrich (taint) ──► contract pipeline ──────► backend
              payload · content       HMAC fingerprints  build ▸ govern ▸ validate  /spans · /check
                                                         fields[] · amount · sources
```

- **Deterministic** outside, **fail-open** at `/check`, **fail-safe** at ingest.
- **BYO scanner** — the enrichment scanners implement a simple `Scanner` protocol.
- Optional NER (`pip install actrail[ner]`) for richer PII detection; the default path
  stays lightweight (regex + entropy + [`detect-secrets`](https://github.com/Yelp/detect-secrets)).

## File and script provenance (v1.1)

Claude Code frequently reads sensitive data, writes a local helper script, and then
runs `python send.py` or `uv run python send.py`. The final command does not contain
the payload, so command scanning alone cannot govern it. v1.1 keeps a small local,
metadata-only provenance index:

1. `Read` records a one-way resource token, classifications, record count, and taint.
2. Before a file-upload command, Python script, or Git push runs, Actrail performs
   bounded local analysis of only the referenced regular files. Python uses a small
   deterministic data-flow pass, so a local read counts only when its value reaches a
   supported network call; simple co-occurrence is not treated as a flow.
3. The `/check` candidate carries the inherited classifications and the external
   destination, while earlier source spans are flushed first for ordered evaluation.

Paths, session ids, file contents, and customer values are never persisted in this
index. Resource identities and file generations are HMACed, and the state file is
written with mode `0600`. Script reads are limited to 1 MiB, data classification and
record counting to 8 MiB/10,000 records, Git config to 256 KiB, and symlinks, FIFOs,
devices, sockets, or files over those limits are never read.

This closes ordinary file-backed `curl`, supported Python data flows, and Git push
paths; it is not an OS network sandbox. Node, Ruby, arbitrary shell scripts,
deliberately obfuscated or runtime-downloaded code, native processes that conceal their
file/network relationships, and traffic outside a Claude Code tool hook require richer
runtime telemetry or host/network controls in addition to Actrail.

After upgrading, run:

```bash
actrail init --key ak_live_...     # idempotently upgrades owned hook matchers
actrail restart                    # loads the new SDK into the warm daemon
actrail doctor
```

## Security & privacy

The metadata-only guarantee is by **construction**, not detection — see
[SECURITY.md](SECURITY.md). Short version: raw payloads never leave the machine, secrets
are floored non-overridably, taint is one-way HMAC, and the wire is fail-closed validated.

## Development

```bash
uv venv && uv pip install -e ".[dev]"
uv run pytest          # tests (+ safety-invariant fuzz)
uv run ruff check .    # lint
uv run mypy            # strict types
```

## License

[Apache 2.0](LICENSE)
