Governance-first security research runtime with policy-gated execution and public-safe proof artifacts
Project description
RAVENCLAW
RAVENCLAW is a governance-first security research runtime for bounded, auditable security operations.
It is built around a simple idea: advanced autonomy is only useful when it remains bounded, observable, and accountable.
What Ravenclaw does
Ravenclaw is a multi-layer runtime for running security workflows under explicit governance. It combines:
- deterministic planning and runtime contracts
- policy and approval gates before execution
- constrained execution through a dedicated execution engine
- artifact analysis and evidence-oriented qualification
- operator-facing visibility through Logdash
The goal is not maximum automation. The goal is reliable autonomy under governance.
The public repository should be read as a public core of that system: a publishable runtime/control-plane artifact with explicit governance and validation surfaces, not a claim that every private operator integration is bundled here.
What makes it different
Ravenclaw is not an unconstrained offensive automation system. Its core design claim is narrower:
- planning, authorization, execution, and interpretation are separated
- policy is enforced in runtime paths, not only described in prompts or docs
- operator approval remains explicit for sensitive actions
- evidence quality and replayability matter as much as action generation
In short, Ravenclaw optimizes for useful actions that stay within policy, scope, and review boundaries.
Ravenclaw now consumes GovEngine for reusable governed-runtime kernel mechanics and SCLite for contract lifecycle artifacts.
The current public dependency baseline is govengine>=0.12.2a0,<0.13 and sclite-core>=1.0.1,<1.1; it consumes the published GovEngine 0.12.2a0 line and SCLite 1.0.1 line.
The current reusable direction is a small Security Contract Layer backed by Ravenclaw Runtime artifacts: intent and scope binding, policy decisions, execution contracts, scoped execution tickets, execution receipts, evidence contracts, review bundles, and runtime truth. Ravenclaw owns the host-side lifecycle projection; SCLite owns lifecycle/review integrity and GovEngine owns neutral governed-runtime contracts. OpenClaw, MCP, and A2A are potential later carriers for these contracts, not new protocols Ravenclaw is trying to own.
The current published public helper package is ravenclaw-security==0.18.3. It exposes the public
Ravenclaw security-profile and OpenClaw readiness contract helpers. The full
runtime, demo, Logdash, and validation surfaces remain source/reference
repository workflows in this package line.
The package/runtime boundary is mechanically checked by
scripts/validate_package_runtime_boundary.py. The OpenClaw fixture-presenter
review harness is checked by scripts/validate_openclaw_fixture_presenter.py
against committed public-safe fixture data; it is not an OpenClaw adapter.
Safe quickstart
The current official public-safe path is local and dry-run oriented.
Shortest reviewer path:
INSTALL.mdDEMO.mdREVIEWER_VALIDATION_GUIDE.mdQUALITY_SIGNALS.mdPUBLIC_STATUS.md
Broader navigation lives in DOCS_MAP.md; architecture depth starts with ARCHITECTURE_OVERVIEW.md.
This path is intentionally narrow and honest.
It shows the governed flow with a small one-command demo entrypoint (bin/demo), a shared bootstrap path (scripts/bootstrap_public_demo.sh), and an explicit RAVENCLAW_MODE=demo delivery profile, without pretending the repo already has a polished one-command public deployment story.
Architecture at a glance
High-level governed flow:
scope/input -> planner -> policy gate / auditor -> approved execution spec -> execution engine -> analysis -> operator visibility
Main runtime layers:
- Planner: turns scope and operator input into structured campaign/runtime intent
- Policy gate / Auditor: enforces scope, tool, auth, and aggression rules before execution
- Execution engine: the only layer allowed to build and run final commands
- Analysis / qualification: turns raw artifacts into bounded findings and summaries
- Logdash: operator-facing control plane for visibility, control, and state truth
See ARCHITECTURE_OVERVIEW.md for the short version and ARCHITECTURE.md for the deeper map.
Public maturity and status
Ravenclaw is not a flat-maturity repository. Some parts are stable enough to be treated as strong public reference surfaces, while others remain experimental or local/internal.
Use PUBLIC_STATUS.md as the canonical public maturity guide.
For public proof and trust surfaces, use VALIDATION.md, QUALITY_SIGNALS.md, and references/public-safe-proof-walkthrough.md.
For the public-core/private-overlay split, read references/public-core-private-overlay-boundary.md.
For trusted-core authority boundaries, failure modes, and non-guarantees, read THREAT_MODEL.md.
For the emerging contract layer, read SECURITY_CONTRACT_LAYER.md and references/approved-execution-spec-v0.1.md.
For Logdash operator-facing control/recovery semantics, see references/logdash-operator-truth-contracts.md.
Install and run posture
Fastest public-safe start:
./scripts/bootstrap_public_demo.sh demo
Reusable public demo bundle:
./scripts/bootstrap_public_demo.sh bundle
Reviewer-facing package-chain scenario:
./scripts/bootstrap_public_demo.sh scenario
That scenario generates a local dry-run summary tying Ravenclaw demo artifacts to the GovEngine boundary report, Ravenclaw security-profile status, and SCLite lifecycle-chain verification. In demo mode, Ravenclaw also records a deterministic GovEngine signing/trust-port example on the execution ticket, binding the ticket evidence to the execution-contract digest without claiming PKI, CA, KMS, key-store, or production identity ownership.
For containerized public-demo bring-up, see .devcontainer/ and compose.demo.yaml.
Today, the repo is strongest as:
- a governance-first runtime architecture
- a research platform with real control and policy surfaces
- a codebase that can be inspected seriously
It now has an official public-safe local dry-run path, but it is not yet in its final lowest-friction form. That remaining gap is real and still an active priority.
Who this is for
Ravenclaw is best suited to technically serious readers who care about:
- governance-first security automation
- policy-gated execution
- operator-visible control and recovery
- contract-oriented runtime design
- evidence and replayability
If you want a clearer fit/non-fit guide, read AUDIENCE.md.
Limits and non-goals
Ravenclaw is not:
- an unconstrained offensive automation platform
- an opaque autonomous attacker
- a replacement for operator judgment
- a guarantee of security outcomes
- a polished consumer product or hosted service
- a beginner-first security starter kit
It is intended for authorized security research and controlled environments. Its value depends on bounded behavior, explicit governance, and operator visibility.
Why this project exists
Many autonomous security systems have a hard tradeoff:
- rigid systems can be safe but not useful enough;
- unconstrained systems can act quickly but are hard to trust.
Ravenclaw separates proposal, approval, execution, and review so adaptive parts can help without owning final authority.
For the short public thesis, read WHY_RAVENCLAW.md.
Repository guide
Main areas:
engine/- planning, runtime orchestration, policy, execution, qualification, evaluationlogdash/- operator-facing dashboard and control planetests/andengine/tests/- regression and contract coveragereferences/- short reference docs for important contracts and boundariesimplementation-plans/- bounded plans for meaningful repo/runtime improvement waves
Release and public-release framing
Version milestones are tracked in VERSION_ROADMAP.md.
High-level open-source/public-release direction is tracked in OPEN_SOURCE_1_0_PLAN.md.
Current public truth:
- the technical core has real governance, contract, and validation surfaces
- the public repo is best understood as a governance-first public core, not a full private operator environment
- the public repo shape is improving, but is still being refined
- public clarity, demo usability, and proof surfaces are better than before, but remain active work
Documentation map
For intent-based navigation, use DOCS_MAP.md.
For final publication workflow, use PUBLISHING.md.
Deeper reading
If you want more depth, read in this order:
PUBLIC_STATUS.mdAUDIENCE.mdQUALITY_SIGNALS.mdVALIDATION.mdDOCS_MAP.mdARCHITECTURE_OVERVIEW.mdWHY_RAVENCLAW.mdARCHITECTURE.mdSTATE_FILES.mdOPEN_SOURCE_1_0_PLAN.md
Ravenclaw should be understood as intelligence under governance: adaptive enough to be useful, bounded enough to remain inspectable and trustworthy.
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