project	type	status	beth_topics	tags
genesisgraph	software	active	genesisgraph software	provenance verification standard compliance cryptography development code

GenesisGraph: Universal Verifiable Process Provenance

v0.3.0 — November 2025

An open standard for cryptographically proving how things were made.

GenesisGraph provides verifiable provenance for AI pipelines, manufacturing, scientific research, and any workflow where "prove how you made this" matters. The three-level selective disclosure model (A/B/C) enables proving compliance without revealing trade secrets—solving the "certification vs IP protection" dilemma.

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Quick Start

Installation

# Python
pip install genesisgraph

# JavaScript/TypeScript
npm install @genesisgraph/sdk

# CLI Tool
pip install genesisgraph[cli]

Your First Provenance Document

from genesisgraph import GenesisGraph, Entity, Operation, Tool

# Create a document
gg = GenesisGraph(spec_version="0.1.0")

# Add a tool
tool = Tool(id="freecad", type="Software", version="0.21.2")
gg.add_tool(tool)

# Add entities
input_file = Entity(id="model.fcstd", type="CADModel", version="1.0",
                   hash="sha256:a1b2...")
output_file = Entity(id="model.stl", type="Mesh3D", version="1.0",
                    hash="sha256:e5f6...", derived_from=["model.fcstd@1.0"])
gg.add_entity(input_file)
gg.add_entity(output_file)

# Record the operation
op = Operation(id="export_stl", type="mesh_export",
              inputs=["model.fcstd@1.0"], outputs=["model.stl@1.0"],
              tool="freecad@0.21.2")
gg.add_operation(op)

# Export provenance
gg.save_yaml("workflow.gg.yaml")

Learn more: 5-Minute Quickstart

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Core Innovation: A/B/C Disclosure Levels

graph LR
    subgraph "Level A: Full"
        A[👁️ All visible<br/>Complete transparency]
    end
    subgraph "Level B: Partial"
        B[🔒 Claims verified<br/>Details hidden]
    end
    subgraph "Level C: Sealed"
        C[🛡️ ZK proofs<br/>Zero disclosure]
    end

    A -.increasing privacy.-> B -.-> C

    style A fill:#90EE90
    style B fill:#FFD700
    style C fill:#87CEEB

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Level	What You Share	Use When
A: Full	All details visible	Internal audits, open research
B: Partial	Policy claims visible, parameters hidden	Regulatory compliance
C: Sealed	Merkle commitments + TEE attestations	High-value IP, supply chains

Example: Prove ISO 9001 compliance without revealing manufacturing toolpaths, or AI safety compliance without exposing proprietary prompts.

Learn more: Disclosure Levels Guide

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Part of the Semantic Infrastructure Lab

GenesisGraph is a production component of the Semantic Infrastructure Lab (SIL) — building the semantic substrate for intelligent systems.

Role in the Semantic OS:

• Cross-Cutting: Provenance infrastructure (enables verifiable transformations across all layers)

SIL Principles Applied:

• ✅ Clarity — Explicit process representation, no hidden transformations
• ✅ Simplicity — Minimal standard (graphs, hashes, signatures)
• ✅ Composability — Graphs compose, selective disclosure composes
• ✅ Correctness — 666+ tests, cryptographic verification
• ✅ Verifiability — Core mission: provable computational correctness

Quick Links: SIL Manifesto • Unified Architecture • Project Index

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📚 Documentation

Full documentation: scottsen.github.io/genesisgraph

Quick Navigation by Role

Role	Start Here
👨‍💻 Developers	Quickstart → Examples → Architecture
🏢 Decision-Makers	FAQ → Use Cases → Vision
🤖 AI/ML Engineers	Disclosure Levels → AI Examples → AI Validators
🔬 Researchers	Specification → Selective Disclosure → ZKP Templates

Documentation Structure (Progressive Reveal)

1. Getting Started (5-10 min) - Installation, quickstart, examples
2. User Guide (15-30 min) - Features, disclosure levels, advanced topics
3. Developer Guide (30-60 min) - Architecture, contributing, security
4. Strategic Context (20-45 min) - Vision, roadmap, critical gaps

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Features

Core Functionality

• ✅ Three-level selective disclosure (A/B/C)
• ✅ Cryptographic signatures (Ed25519)
• ✅ Hash verification (SHA256, SHA512, Blake3)
• ✅ Python & JavaScript SDKs
• ✅ CLI tool (gg command)

Advanced Features

• ✅ DID resolution (did:key, did:web, did:ion, did:ethr)
• ✅ Certificate Transparency log integration (RFC 6962)
• ✅ Selective Disclosure JWT (SD-JWT)
• ✅ BBS+ signatures for privacy
• ✅ Zero-knowledge proof templates
• ✅ Profile validators (AI Basic, CAM, ISO 9001, FDA 21 CFR 11)

Quality Metrics

• 666+ comprehensive tests
• ~76% test coverage (up from 63% in v0.2)
• Production-ready cryptographic features (98%+ coverage)
• CI/CD with GitHub Actions (Python 3.9-3.12)

See: Implementation Status for complete details.

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Use Cases

• AI Pipelines: Track model training, validate datasets, prove compliance
• Manufacturing: CAD provenance, ISO 9001 compliance, supply chain verification
• Scientific Research: Reproducible science, data lineage, peer review
• Healthcare: Medical data processing chains, HIPAA compliance
• Supply Chains: Verify product origins, track transformations

See: Use Cases & Examples

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Roadmap

Current Version: v0.3.0 (November 2025) Target: v1.0 Production Release (March 2027)

Next Milestones:

• v0.4.0 (Jan 2026) - 90% test coverage, API docs site, strict typing
• v0.5.0 (Mar 2026) - Formal threat model, lifecycle & revocation
• v0.6.0 (May 2026) - Delegation & authorization framework
• v0.7.0 (Aug 2026) - AI agent provenance

See: Complete Roadmap

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Contributing

We welcome contributions! Please see our Contributing Guide for details.

Quick Links:

• Architecture Guide
• Security Policy
• Issue Tracker
• Discussions

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License

• Specification: CC-BY 4.0
• Code & SDKs: Apache 2.0

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Contact

• Documentation: scottsen.github.io/genesisgraph
• Issues: github.com/scottsen/genesisgraph/issues
• Discussions: github.com/scottsen/genesisgraph/discussions
• Security: See SECURITY.md for vulnerability reporting

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GenesisGraph — Proving how things were made, without revealing how to make them.