waveframe-guard 0.5.0

Local enforcement SDK and simulation environment for AI governance.

Waveframe Guard

Stop unsafe AI and automated actions before they execute.

Waveframe Guard enforces governance at the execution boundary. If an action violates policy, it never runs.

Current release: 0.5.0.

Example

This example assumes a published contract artifact exists at contracts/finance-policy-1.0.0.contract.json. In your application, point contract_path at the contract published by your governance workflow.

from pathlib import Path

from waveframe_guard import install_guard, guard

install_guard(
    actor={"id": "user-1", "type": "human", "role": "intern"},
    contract_path=Path("contracts") / "finance-policy-1.0.0.contract.json"
)

@guard
def transfer(amount):
    print(f"Transferred ${amount}")

transfer(100)

Execution blocked: required role not satisfied: manager

Governed Runtime

For applications that want to resolve published contracts from a registry, use GovernedRuntime:

from waveframe_guard import GovernedRuntime

runtime = GovernedRuntime(
    registry_path="contracts/index.json"
)
runtime.bind_contract("finance-policy@1.0.0")

runtime.execute(
    actor={"id": "user-1", "type": "human", "role": "intern"},
    fn=transfer,
    args=(1250000,),
)

Runtime authority refs are explicit and versioned. Bind or pass finance-policy@1.0.0; unversioned contract IDs such as finance-policy are rejected because replay, audit, and cache integrity depend on deterministic authority identity.

By default, blocked execution raises GovernanceError. To observe the decision without raising, pass raise_on_block=False:

result = runtime.execute(
    actor={"id": "user-1", "type": "human", "role": "intern"},
    contract_id="finance-policy@1.0.0",
    fn=transfer,
    args=(1250000,),
    raise_on_block=False,
)

print(result.allowed)
print(result.reason)
print(result.contract_hash)

Allowed executions return GovernedExecutionResult(allowed=True, reason="execution allowed", value=<function return value>, ...). Blocked executions return GovernedExecutionResult(allowed=False, reason=<policy reason>, error=<block error>, ...).

The registry can map contract IDs to published contract artifacts:

{
  "contracts": [
    {
      "contract_id": "finance-policy",
      "contract_version": "1.0.0",
      "contract_hash": "sha256:...",
      "path": "finance-policy-1.0.0.contract.json"
    }
  ]
}

Runtime execution is intentionally small: registry lookup, load the published contract, install the Guard context, execute the guarded function, then allow or block.

You can also bind runtime context once and omit it from each execution:

runtime = GovernedRuntime(registry_path="contracts/index.json")
runtime.install_actor({"id": "user-1", "type": "human", "role": "manager"})
runtime.bind_contract("finance-policy@1.0.0")

result = runtime.execute(
    fn=transfer,
    args=(1250000,),
    raise_on_block=False,
)

Per-call actor and versioned contract_id values still work and override the bound context for that call.

Replay Admissibility

Replay systems can evaluate approval evidence without executing the governed function:

from waveframe_guard import evaluate_admissibility

decision = evaluate_admissibility(contract, execution_state)

The returned decision includes allowed, reason, missing_approvals, and a governed decision trace.

For proposal-bound execution, pass a normalized proposal directly:

result = runtime.execute_proposal(
    proposal,
    raise_on_block=False,
)

execute_proposal evaluates the proposal against the bound or supplied contract and returns the same GovernedExecutionResult shape.

Each runtime execution also emits a structured SDK-local audit event. Events are kept in memory on the runtime and attached to non-raising results:

result = runtime.execute(
    fn=transfer,
    args=(1250000,),
    raise_on_block=False,
)

print(result.event)
print(runtime.last_event)
print(runtime.audit_events)

Example event:

{
    "event_type": "governed_execution",
    "execution_type": "function",
    "allowed": False,
    "authority_ref": "finance-policy@1.0.0",
    "reason": "required role not satisfied: manager",
    "error": "Execution blocked: required role not satisfied: manager",
    "contract_id": "finance-policy",
    "contract_version": "1.0.0",
    "contract_hash": "...",
    "actor": {"id": "user-1", "type": "human", "role": "intern"},
    "target": "transfer",
    "timestamp": "2026-05-12T12:00:00+00:00",
}

To append events locally as JSON lines:

runtime = GovernedRuntime(
    registry_path="contracts/index.json",
    audit_path="runtime-audit.jsonl",
)

What Waveframe Guard Does

• Intercepts function execution
• Loads published contract artifacts
• Evaluates governance rules before execution
• Blocks invalid actions deterministically
• Continues enforcement even if Cloud is unavailable

Local vs Cloud

Mode	Behavior
Local	Fast, local enforcement
Cloud	Policy sync, audit, and attestation

Guard enforces locally. Cloud provides authority, audit, and verification.

Fail Modes

Mode	Behavior
cache (default)	Use cached policy if Cloud is unavailable
closed	Block if Cloud is unavailable and no cached policy exists
open	Allow execution if policy is unavailable and mark the decision unverified

Install

pip install waveframe-guard cricore-contract-compiler cricore-proposal-normalizer

Live Demo

python examples/live_enforcement_demo.py

The demo shows:

• an intern blocked by policy
• a manager allowed by policy
• cached local enforcement during a simulated Cloud outage

Published Contracts

Guard runtime consumes published governance authority artifacts:

from pathlib import Path

install_guard(
    actor={"id": "user-1", "type": "human", "role": "manager"},
    contract_path=Path("contracts") / "finance-policy-1.0.0.contract.json"
)

Inline policy dictionaries are authored and compiled before runtime. Guard loads the compiled contract artifact and enforces against it locally.

Guard also records contract metadata in runtime context for audit and telemetry:

{
    "contract_id": "finance-policy",
    "contract_version": "1.0.0",
    "contract_hash": "..."
}

Why This Exists

Most AI systems can suggest, warn, or log.

Waveframe Guard is the layer that can stop execution.

Architecture Note

The Waveframe Guard SDK operates independently and does not require Cloud components to enforce governance locally.

The cloud directory contains experimental Cloud control plane components and is not required for SDK operation.