🛡 Aspidos

Hope Shield for Anomaly Systems

When systems fail silently, Aspidos becomes the shield.

⚡ TL;DR

Aspidos is a dynamic anomaly stabilization engine.

Not detection. Stabilization.

🚀 Quick Start

const { PandoraDefense } = require('aspidos');

const pd = new PandoraDefense();

// normal event const result = pd.analyze(0.3); console.log(result.level);

// anomaly event const alert = pd.analyze(0.9, { penetration: 0.2 });

if (alert.alert) { console.log('⚠️ System instability detected'); }

🎯 Convergence Demo

const { PandoraDefense } = require('aspidos');
const pd = new PandoraDefense();

// Phase A — Harmonic baseline
const stable = pd.analyze(0.25);
console.log(stable.level);        // 'NORMAL'
console.log(stable.omega.phase);  // 'STABLE_PHASE'

// External noise
pd.analyze(0.85, { penetration: 0.1 });

// Internal rule deviation → RECOVERY_NEEDED
const slapped = pd.analyze(0.4, { theory: 0.95, penetration: 0.05 });
console.log(slapped.core.status);    // 'RECOVERY_NEEDED'
console.log(slapped.core.category);  // 'HIGH_DEVIATION'
console.log(slapped.core.action);    // 'RECOVERING'

// Autonomous re-stabilization
const recovery = pd.analyze(0.3);
console.log(recovery.level);  // 'NORMAL'

// Buffer saturation stress
const cliff = pd.analyze(0.5, { penetration: 0.9 });
console.log(cliff.pgu.level);  // 'OVERLOAD'

❓ Why Aspidos?

Most systems:

• Use fixed thresholds
• React after failure
• Treat anomalies as errors

Aspidos:

• No fixed thresholds
• Models anomalies as distortions in a dynamic field
• Includes built-in stabilization (Ω loop)

👉 This is not monitoring. 👉 This is state control.

🧠 Core Concept

Aspidos models a system as a dynamic field:

• ΔΨ (DeltaPsi) → distortion
• PGU → accumulated risk
• Ω (Omega) → system stability

Flow:

ΔΨ (distortion) → PGU (accumulation) → Ω (stability)

     ┌────────────┐
     │   ΔΨ Engine │
     └─────┬──────┘
           ↓
     ┌────────────┐
     │    PGU     │
     └─────┬──────┘
           ↓
     ┌────────────┐
     │   Ω Loop    │
     └────────────┘

⚙️ Features

ΔΨ Engine — Distortion Detection

Detect anomalies as distortions in a dynamic field rather than fixed thresholds.

PGU Model — Accumulated Risk Field

Continuously integrates risk and detects saturation leading to critical transitions.

Ω Loop — Self-Stability System

Maintains system stability through self-referential feedback dynamics.

Adaptive Behavior

Learns baseline behavior dynamically and adapts to changing environments.

Designed for Critical Systems

Built for environments where silent failure is unacceptable.

🛡 Use Cases

• Security monitoring systems
• AI anomaly detection
• Real-time system health tracking
• Critical infrastructure monitoring

📦 Installation

npm install aspidos

📁 Project Structure

/src Core engine /examples Node.js examples /demo Browser demo /assets Logos and visuals

🧲 Keywords

anomaly-detection, cybersecurity, ai, complex-systems, control-theory

🧠 Philosophy

Aspidos is built on a simple idea:

Anomalies are not errors. They are distortions in a system trying to remain stable.

We do not just detect them.

«We hold the system together.»

📄 License

MIT License

🌌 Final Note

Aspidos is not just a library.

It is a way to think about systems.

«Not detection. Stabilization.»