SCBE-AETHERMOORE

Quantum-Resistant AI Agent Governance

The mathematically-proven security layer your AI fleet needs.

What Is This?

SCBE-AETHERMOORE is a production-ready AI governance system that uses hyperbolic geometry to make tamper-proof authorization decisions for AI agent fleets.

Think of it as a mathematical bouncer for your AI agents - one that can't be fooled by prompt injection, can't be bribed, and mathematically proves every decision.

Key Capabilities

| Feature | Description | |---------|-------------| | 14-Layer Security Pipeline | Every request passes through 14 mathematical transformations | | Hyperbolic Geometry | Decisions mapped to Poincaré ball - center=safe, edge=risky | | Rogue Agent Detection | Swarms detect intruders through pure math - no messaging required | | Multi-Signature Consensus | Critical operations require cryptographic agreement | | Zero False Positives | Legitimate agents never get flagged | | Jam-Resistant | Works without RF/network - agents "feel" each other mathematically |

Benchmark Results

SCBE (Harmonic + Langues):  95.3% detection rate
ML Anomaly Detection:       89.6%
Pattern Matching:           56.6%
Linear Threshold:           38.7%

Architecture Docs (Index)

• SCBE Kernel Spec (Canonical): SPEC.md
• Langues Weighting System (Layer 3 + 6): docs/LANGUES_WEIGHTING_SYSTEM.md
• HYDRA Orchestration (Execution Plane): docs/hydra/ARCHITECTURE.md
• Concept Glossary (Indexable Terms): CONCEPTS.md
• Research Drafts (Non-Canonical): docs/research/README.md

What npm users actually get

When users install scbe-aethermoore from npm, they get:

• compiled JS/TypeScript API from dist/src
• CLI entrypoint (scbe)
• SixTongues Python helper assets
• starter fleet templates + use-case scenarios from examples/npm/

They do not receive the full mono-repo runtime stack (e.g., all docs, test suites, and UI source).

Pre-made AI agents and use-case starters

Yes — adding pre-made agents and scenarios is a good idea, if positioned as starter templates (not production policy).

Included templates:

• examples/npm/agents/fraud_detection_fleet.json
• examples/npm/agents/research_browser_fleet.json
• examples/npm/use-cases/financial_fraud_triage.json
• examples/npm/use-cases/autonomous_research_review.json

These give users a concrete launch path for common fleet patterns while keeping canonical security behavior in SPEC.md.

Live Demos

1. Rogue Agent Detection

curl https://YOUR_API/v1/demo/rogue-detection

Watch 6 legitimate agents detect and quarantine a phase-null intruder using only math.

2. Swarm Coordination

curl https://YOUR_API/v1/demo/swarm-coordination?agents=20

See 20 agents self-organize without any central coordinator.

3. Pipeline Visualization

curl "https://YOUR_API/v1/demo/pipeline-layers?trust=0.8&sensitivity=0.7"

See exactly how each of the 14 layers processes a request.

Architecture

14-LAYER PIPELINE
═══════════════════════════════════════════════════════════════════

Layer 1-2:   Complex Context → Realification
Layer 3-4:   Weighted Transform → Poincaré Embedding
Layer 5:     dℍ = arcosh(1 + 2‖u-v‖²/((1-‖u‖²)(1-‖v‖²)))  [INVARIANT]
Layer 6-7:   Breathing Transform + Phase (Möbius addition)
Layer 8:     Multi-Well Realms
Layer 9-10:  Spectral + Spin Coherence
Layer 11:    Triadic Temporal Distance
Layer 12:    score = 1 / (1 + d_H + 2 * phaseDeviation)  [HARMONIC SCALING]
Layer 13:    Risk' → ALLOW / QUARANTINE / DENY
Layer 14:    Audio Axis (FFT telemetry)

═══════════════════════════════════════════════════════════════════

The Six Sacred Tongues

| Tongue | Code | Domain | Weight | |--------|------|--------|--------| | Kor'aelin | KO | Control & Orchestration | 1.00 | | Avali | AV | I/O & Messaging | 1.62 | | Runethic | RU | Policy & Constraints | 2.62 | | Cassisivadan | CA | Logic & Computation | 4.24 | | Umbroth | UM | Security & Privacy | 6.85 | | Draumric | DR | Types & Structures | 11.09 |

Policy Levels:

• standard → KO required
• strict → RU required
• critical → RU + UM + DR required

Quick Start

Docker (Fastest)

docker run -p 8080:8080 -e SCBE_API_KEY=your-key ghcr.io/issdandavis/scbe-aethermoore

Local Development

git clone https://github.com/issdandavis/SCBE-AETHERMOORE.git
cd SCBE-AETHERMOORE
npm install && pip install -r requirements.txt
export SCBE_API_KEY="your-key"
uvicorn api.main:app --port 8080

Cloud Deployment

AWS Lambda:

cd aws && sam build && sam deploy --guided

Google Cloud Run:

cd deploy/gcloud && ./deploy.sh YOUR_PROJECT_ID

Memory Sealing API (MVP)

The MVP memory API in src/api/main.py persists sealed blobs so they can be retrieved and unsealed later. Configure the storage backend before running the API server:

# Required: where sealed blobs are stored on disk
export SCBE_STORAGE_PATH="./sealed_blobs"

# Optional: storage backend selection (default: filesystem)
export SCBE_STORAGE_BACKEND="filesystem"

The API will write one JSON file per 6D position in the configured directory. Ensure the process has read/write access to this path when using /seal-memory and /retrieve-memory.

Fleet API (Pilot Demo)

Run a complete fleet scenario through the 14-layer SCBE pipeline:

API Usage

Authorize an Agent Action

curl -X POST https://YOUR_API/v1/authorize \
  -H "SCBE_api_key: your-key" \
  -H "Content-Type: application/json" \
  -d '{
    "agent_id": "fraud-detector-001",
    "action": "READ",
    "target": "transaction_stream",
    "context": {"sensitivity": 0.3}
  }'

Response:

{
  "decision": "ALLOW",
  "decision_id": "dec_a1b2c3d4e5f6",
  "score": 0.847,
  "explanation": {
    "trust_score": 0.8,
    "distance": 0.234,
    "risk_factor": 0.09
  },
  "token": "scbe_a1b2c3d4_dec_a1b2",
  "expires_at": "2026-01-15T10:05:00Z"
}

Run Fleet Scenario

curl -X POST https://YOUR_API/v1/fleet/run-scenario \
  -H "SCBE_api_key: your-key" \
  -H "Content-Type: application/json" \
  -d '{
    "scenario_name": "fraud-detection",
    "agents": [
      {"agent_id": "detector-001", "name": "Fraud Detector", "initial_trust": 0.85},
      {"agent_id": "scorer-002", "name": "Risk Scorer", "initial_trust": 0.75}
    ],
    "actions": [
      {"agent_id": "detector-001", "action": "READ", "target": "transactions"},
      {"agent_id": "scorer-002", "action": "WRITE", "target": "risk_db"}
    ]
  }'

Use Cases

| Industry | Application | |----------|-------------| | Financial Services | Fraud detection AI that can't be manipulated | | Healthcare | HIPAA-compliant AI decisions with audit trails | | Defense/Aerospace | Jam-resistant swarm coordination | | Autonomous Systems | Multi-agent coordination without central authority | | Enterprise AI | Constitutional safety checks for LLM agents |

Test Status

| Suite | Status | Count | |-------|--------|-------| | TypeScript | ✅ Passing | 950/950 | | Python | ✅ Passing | 97/103 |

Technical Specifications

Post-Quantum Cryptography

• Kyber768: Key exchange (NIST approved)
• Dilithium3: Digital signatures (NIST approved)
• AES-256-GCM: Symmetric encryption
• HKDF-SHA256: Key derivation

Mathematical Foundations

• Poincaré Ball Model: Hyperbolic geometry
• Hamiltonian Mechanics: Energy conservation
• Möbius Addition: Gyrogroup operations
• Quasicrystal Lattice: 6D → 3D projection

Resources & Links

Live Demo & Packages

• Live Demo: SCBE Swarm Coordinator - Interactive Streamlit dashboard
• npm Package: scbe-aethermoore - npm install scbe-aethermoore
• GitHub Pages: Project Site

Documentation (Notion)

• SCBE-AETHERMOORE System State Report (Feb 2026) - Production-ready docs
• SCBE + Sacred Eggs Integration Pack - Complete integration guide
• Phase-Breath Hyperbolic Governance (14-Layer Core v1.2) - Mathematical core mapping
• Polly Pads: Mode-Switching Architecture - Autonomous AI architecture
• Topological Linearization for CFI - Patent analysis & Hamiltonian paths

Products & Templates

• Gumroad: aethermoorgames.gumroad.com - Notion templates, AI workflow tools
• Ko-fi: ko-fi.com/izdandavis - Support development

Social & Updates

• X/Twitter: @davisissac
• Substack: Issac "Izreal" Davis

Contact

Issac Daniel Davis Email: [email protected] GitHub: @issdandavis

License

Proprietary. Contact for licensing inquiries.

Built with hyperbolic geometry. Secured by mathematics.

Publishing (AI-assisted)

Use docs/PUBLISHING.md for a safe human+AI release flow, including preflight checks and dry-run packaging.