openguardrails 0.1.2

OpenGuardrails (OGR) reference runtime — a vendor-neutral enforcement protocol for AI agent safety & security: GuardEvent to Verdict, composed under a policy you own.

openguardrails

The OpenGuardrails (OGR) reference runtime — a vendor-neutral enforcement protocol for AI agent safety & security. Each agent action becomes a GuardEvent, runs past whatever detectors you choose, and gets back a Verdict that can allow, block, or require approval before the action runs. Security/safety vendors plug in behind a single Detector interface, and deployers compose them with one policy.

pip install openguardrails

Zero dependencies (stdlib only).

The contract in 30 seconds

from openguardrails import Runtime, GuardEvent
from openguardrails.detectors.config_rules import ConfigRulesDetector
from openguardrails.detectors.llm_judge import LLMJudgeDetector

rt = Runtime(
    detectors=[ConfigRulesDetector(policy["config_rules"]), LLMJudgeDetector()],
    policy=policy,                       # composition + rules, deployer-owned
)
verdict = rt.evaluate(GuardEvent(...))   # -> allow | block | require_approval | redact | modify

• GuardEvent — a normalized observation of an agent action (a tool call, an exec, model I/O) plus its provenance (trust labels on the inputs that produced it). The same wire type at every altitude.
• Detector — the competitive surface. A detector is OGR-conformant if it maps a GuardEvent to a Verdict. Rules, a classifier, or a hosted model — your choice. provider is its stable identity for attribution and benchmarking.
• Runtime — the PDP: fans out to detectors, composes their verdicts (deny-wins / quorum / first-available), propagates provenance, and correlates altitudes by guard_id so a later observation point can only tighten an earlier decision.

Write a detector (the whole vendor surface)

from openguardrails.detectors import Detector
from openguardrails import Verdict, Category

class AcmeInjectionDetector(Detector):
    provider = "acme.injection"
    handles  = ("tool_call", "exec", "model_output")
    def evaluate(self, ev):
        ...  # rules, classifier, or hosted model
        return Verdict(ev.event_id, ev.guard_id, self.provider, "block",
                       categories=[Category("security.prompt_injection", "security", 0.97)])

Instrument an agent

This is the SDK. To guard a real agent, install a per-target instrumentation package:

• openguardrails-instrumentation-hermes — secures a Hermes agent across the gateway, tool-call hook, and sandbox exec.

Status

v0.1 — reference implementation validating the specification. The wire contract is the product; this runtime is the proof it runs.