Add trust & security visualization dashboard with metrics API

[Copilot]

Implements visualization layer for trust, security, ethics, and operational metrics. Users can now visually verify system behavior, compliance status, and component health at a glance.

Architecture

Browser (127.0.0.1) → HTTP Server → Metrics API → System Components
                                                 ↓
                                            REGISTRY.json

Backend (trust_metrics_api.py, 482 LOC)

• 6 data models: TrustRating, SecurityProtocol, EthicalPriority, RuntimeErrorMetric, ReliabilityMetric, BenchmarkVerification
• 8 RESTful endpoints: /api/metrics/{all,trust,security,ethics,errors,reliability,benchmarks,signals}
• Automatic REGISTRY.json discovery with path traversal protection

Server (dashboard_server.py, 118 LOC)

• Tunnel-only enforcement (hard fails on non-127.0.0.1 binding)
• Request logging for audit trail
• Static file serving with API routing

UI (dashboard_simple.html, 752 LOC)

• Pure CSS/JS (no external CDN dependencies for PPA-003 compliance)
• 8 visualization components: bar charts, progress rings, status indicators, priority badges

Key Metrics Visualized

• Trust Ratings: Component verification scores (97.90% avg)
• Security Protocols: Active protocols with PPA compliance levels
• Ethical Priorities: Enforcement status across 5 priority tiers
• Runtime Errors: Distribution by module and severity
• Reliability: Uptime and success rates (99.94% avg)
• Benchmarks: Certification scores with attestation hashes
• Symbolic Signals: Governance lock, audit trail, tunnel-only mode, etc.

Usage

cd HeadySystems_v13/apps/heady_admin_ui
python3 dashboard_server.py
# Dashboard: http://127.0.0.1:8080/
# API: curl http://127.0.0.1:8080/api/metrics/all

Security & Compliance

• CodeQL: 0 vulnerabilities
• PPA-001 through PPA-004 verified
• Tunnel-only gateway enforced at runtime
• No external dependencies (CDN-free)
• Data isolation boundaries respected
• SHA-256 attestation (display truncation documented)

Screenshots

Full Dashboard View

Production Integration

Currently uses sample data. Production integration points marked with TODO comments:

def get_trust_ratings(self) -> List[Dict[str, Any]]:
    """Retrieve trust ratings for all system components.
    
    TODO: In production, integrate with actual system monitoring to retrieve
    real-time trust metrics from component health checks and attestation services.
    """

See IMPLEMENTATION_GUIDE.md for integration patterns.

Files Added

• trust_metrics_api.py - Metrics API with data models
• dashboard_server.py - HTTP server with RESTful endpoints
• dashboard_simple.html - Dashboard UI (pure CSS/JS)
• test_api.py - Test suite (7/7 passing)
• IMPLEMENTATION_GUIDE.md - Production integration guide
• SUMMARY.md - Implementation overview
• Updated README.md with usage instructions

Original prompt

The goal is to enhance the software's presentation layer to simplify understanding its underlying trust, security, ethics, physics, philosophy, and foundational processes. These enhancements should employ visual explanations to ensure users easily grasp and verify the software's workings and intentions.

Proposed Steps:

1. Visualization Layer: Create widgets or dashboards representing trust ratings, ethical priorities, security protocols, and execution philosophies.
   • Example: Use charts for runtime error distribution to show physics-handling modules' reliability metrics.
2. Trust Metrics Display: Implement the API/models to retrieve and display symbolic signals for checking correctness, then showcase these (as seen in modular audits).
3. Provide benchmark verifications/certifications easily understood via visuals analyses when attempting similar.

This pull request was created from Copilot chat.

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