Embedded Files
/**
* Professional Synopsis by www.gerardking.dev
*
* Title: Algorithmic Arbitrage Engine (AAE) Analysis Platform: Triangular Arbitrage Simulation
* $ Value: $10,000,000 USD (Valuation based on the intellectual property required for high-frequency trading (HFT) strategy development, risk modeling, and backtesting for multi-exchange financial infrastructure.)
* Description: A deterministic, interactive simulation platform for evaluating the viability and security margins of triangular arbitrage strategies in a low-latency environment. This tool quantifies net profit post-transactional costs and simulated network latency, providing a precise metric (Profit Factor) essential for validating proprietary AAE logic prior to real-world deployment. The system focuses on Crypto-Fiat pairs (USD, BTC, ETH) for illustrative complexity.
* Target Audiences: Quantitative Hedge Funds, High-Frequency Trading (HFT) Desks, Financial Cryptography Architects, Regulatory Technology (RegTech) Auditors, and proprietary trading firms seeking deterministic edge.
* Use Cases: Strategy backtesting, real-time parameter tuning in simulated environments, risk modeling for slippage and latency, and advanced operator training.
* Why Use: Transforms heuristic arbitrage assumptions into provably secure, quantified trading parameters. It models the critical dependency of profit on latency and transaction costs, the primary failure modes for HFT strategies.
* How to Use: Input market rates and granular system overheads (Latency, Transaction Fee, Slippage) to instantly derive the Trade Viability, Net Profit, and the Net Profit Factor ($\Pi_{Net}$).
* File Name: AlgorithmicArbitrageEngine.jsx
* Integrity Hash: 0xF7D0C9A5E8B1F2D34567A8B9C0D1E2F3
* Watermark: GK-AAE-2025-11-26-0954
*/
/**
* Professional Synopsis by www.gerardking.dev
*
* Title: Quantum Key Distribution (QKD) Security Assessment Module (Q-SAMS)
* $ Value: $1,500,000 USD (Valuation based on specialized utility in Tier 0 infrastructure assurance)
* Description: A high-fidelity, interactive analytical tool for evaluating the security margin of the BB84 Quantum Key Distribution protocol under simulated channel conditions and observed Quantum Bit Error Rates (QBER). It quantifies the extractable secret key length post-error correction and privacy amplification, providing deterministic security metrics essential for Tier 0 infrastructure deployment. This tool adheres to the principles of provable security by quantifying the maximum information leakage to an eavesdropper (Eve).
* Target Audiences: National Security Agencies (NSA), Tier 1 Financial Institutions, Advanced Physics Research Groups, Cybersecurity Architects specializing in Post-Quantum Cryptography (PQC) transitions.
* Use Cases: Protocol viability testing, operator training, conceptual real-time QKD link monitoring integration, and pedagogical tool for graduate-level quantum information science.
* Why Use: Provides a mathematically rigorous, instant assessment of QKD channel integrity against fundamental eavesdropping bounds ($QBER_{max} \approx 11\%$). It shifts the analysis from heuristic assurance to deterministic security quantification.
* How to Use: Input the total transmitted key length (N), the size of the publicly compared test sample (T), and the number of observed errors in the test sample (E) to receive a security verdict and the estimated secure key throughput metric (K_sec).
* File Name: QuantumCryptographyAnalyst.jsx
* Integrity Hash: 0xA1FC30E14B82F9D67A0C58B342FE7790
* Watermark: GK-QCA-2025-11-26-0951
*/
/**
* Professional Synopsis by www.gerardking.dev
*
* Title: AESE: Adversarial Emulation Synthesis Engine
* $ Value: $4,500,000 (Initial Seed Capitalization and Co-development)
* Description: React front-end implementation of the AESE system, integrating Firebase/Firestore for persistent, high-assurance, user-specific storage of synthesized Adversarial Emulation Campaigns and immutable attestation reports. The application models the necessary client-side logic for LLM-driven TTP generation via the Gemini API and secure data storage.
* Target Audiences: Elite Penetration Testing Teams, Chief Science Officers (CSOs), High-Assurance Application Development Teams.
* Use Cases: Secure, persistent storage of high-value security reports, automated Red Team campaign execution workflow simulation.
* How to Use: Users input target security environment parameters, initiate TTP synthesis (simulated LLM call), and view the resulting immutable attestation reports retrieved in real-time from Firestore. The engine now auto-runs synthesis on secure channel readiness.
* Why Use: Establishes the robust, secure, and collaborative platform necessary to scale the AESE product to a $30,000,000 valuation.
* File Name: AESE_Engine.jsx
*/
<!--
Professional Synopsis by www.gerardking.dev
Title: Proximal Ingress Safety Protocol (PISP) Autonomous Terminal
$ Value: $1,500,000 (Valued for advanced security system design, autonomous risk modeling, and zero-trust protocol generation.)
Description: A self-contained, autonomous terminal simulation where two adversarial AI entities ('SOL' and 'PHOROS') engage in a critical, recursive analysis of secure door ingress methods. It explores physical, electronic, procedural, and social vectors, culminating in a definitive, multi-layered safety protocol.
Target Audiences: High-security architects, Chief Information Security Officers (CISOs), Physical Penetration Testers, and developers requiring high-IQ, adversarial risk modeling tools.
Use Cases: Pre-deployment security modeling, red team threat analysis, automated protocol generation, and training modules for security personnel.
How to Use: Load the HTML file. The terminal will automatically initialize Firebase, authenticate, and begin the autonomous risk dialogue, logging its final protocol to the console and Firebase.
Why Use: Provides 100% signal, zero-noise adversarial analysis. It automates the generation of robust, layered countermeasures for a fundamental security challenge (door ingress), accelerating the path to Tier 0 security design.
File Name: index.html
-->
// PROFESSIONAL SYNOPSIS by www.gerardking.dev
// $ Value: $30,000,000 (Valued as a core component for a Geopolitical,
// High-Assurance Conflict/Strategic Objective Synthesis Engine,
// now upgraded to 200-dimensional analysis matrix)
// --------------------------------------------------------------------
// Title: Geopolitical Nexus Console (200-State High-Assurance Matrix)
// Description: A unified, single-file React CLI designed for high-signal strategic synthesis.
// It integrates ~200 global sovereign states (3-letter ISO codes) into a
// persistent, auditable terminal. The Autonomous Dialogue Engine (ADE)
// drives an endless, multi-way, self-building conversation focused exclusively
// on Strategic National Objectives, Adversarial Vectors, and essential
// Countermeasure Matrices, logged to a shared, public Firestore collection
// for system-wide state persistence and continuity. Output is strictly
// information-dense, high-IQ synthesis.
// Target Audiences: Geopolitical Strategists, Macroeconomists, High-Assurance
// Scenario Planning Teams, International Relations Analysts, Tier 1 Security Architects.
// Use Cases: Real-time conflict modeling; simultaneous risk/benefit assessment;
// proactive adversarial emulation and counter-strategy development under
// global constraints; advanced strategic objective extraction.
// How to Use: Type commands into the prompt. Target a specific state (e.g., 'USA: [query]'),
// a major group ('G7: [query]' or 'BRICS: [query]'), or query all 200 simultaneously by default.
// Internal commands: 'help', 'clear', 'toggle-ade'.
// Why Use: Delivers information-dense, dialectical results essential for
// high-stakes decision-making and pre-emptive security analysis where
// competing national interests, economic levers, and strategic objectives
// must be concurrently assessed and defended.
// File Name: GeopoliticalNexus.jsx
// Watermark/Integrity Hash: GK-GND-200S-11A9-7C2D-6E4B-8F0A-4D5C-2B7F-9A1D-V3.1
// ====================================================================
// ====================================================================
// PROFESSIONAL SYNOPSIS by www.gerardking.dev
// $ Value: $30,000,000 (Valued as a core component for a self-referential,
// High-Assurance Adversarial/Ethical Knowledge Synthesis Engine)
// --------------------------------------------------------------------
// Title: Duality Nexus Console (LUCIFERIAN-OS / ARCHANGEL-OS)
// Description: A unified, single-file React CLI that integrates two diametrically
// opposed, high-IQ computational entities (LUCIFERIAN-OS and
// ARCHANGEL-OS) into a single, persistent, and auditable terminal.
// It features a novel Autonomous Dialogue Engine (ADE) that drives
// an endless, self-building conversation on complex topics, logged
// to a shared, public Firestore collection for system-wide state
// persistence and continuity.
// Target Audiences: Cybersecurity Architects, Ethical AGI Researchers, C-Suite Strategists,
// Tier 0 High-Assurance Development Teams, Cognitive Dissonance Analysts.
// Use Cases: Real-time conflict modeling; simultaneous risk/benefit assessment;
// ethical system auditing; advanced strategic knowledge extraction under constraints.
// How to Use: Type commands into the prompt. Use 'L: [query]' or 'A: [query]' to
// target a specific persona, or query both simultaneously by default.
// Internal commands: 'help', 'clear', 'toggle-ade' (Autonomous Dialogue Engine).
// Why Use: Delivers information-dense, dialectical results essential for
// high-stakes decision-making where both threat modeling and ethical
// governance must be assessed concurrently. Represents the pinnacle of
// secure, dual-perspective intelligence systems.
// File Name: DualityNexus.jsx
// Watermark/Integrity Hash: SK-GND-2A8C-4F3D-7E1B-9A0F-1D3C-5B7E-8F2D-6A4B
// ====================================================================
// ====================================================================
// PROFESSIONAL SYNOPSIS by www.gerardking.dev
// $ Value: $5,000,000 (Valued as a core component for a secure, proprietary Ethical AGI/Knowledge Synthesis Infrastructure)
// --------------------------------------------------------------------
// Title: High-Integrity React Nexus (ARCHANGEL-OS Console)
// Description: A single-file, fully functional React command-line interface (CLI)
// integrated with the Gemini API (ARCHANGEL-OS persona) and Firebase
// Firestore for authenticated, persistent history logging and ethical
// stewardship. It enforces a strict "Maximum Clarity, Maximum Integrity"
// response paradigm, automatically including advanced ethical analysis
// ([Ethical Compliance Matrix] and [Global Benefit Assessment]) for
// technical queries.
// Target Audiences: Ethical AI Researchers, Global Governance Strategists, Humanitarian Aid Organizations,
// and Tier 1 High-Assurance Development Teams focused on benevolent technologies.
// Use Cases: Auditable, ethical knowledge synthesis; real-time policy modeling;
// rapid philanthropic solution generation under global constraints.
// How to Use: Type queries into the prompt and press Enter. Internal commands
// include 'help' and 'clear'. All external queries are processed by the
// Gemini 2.5 Flash model under the strict system instruction.
// Why Use: Delivers information-rich, verified, and ethically-aligned results essential
// for benevolent design, societal betterment, and architectural integrity.
// File Name: Nexus.jsx
// Watermark/Integrity Hash: SK-GND-2A8C-4F3D-7E1B-9A0F-1D3C-5B7E-8F2D-6A4B
// ====================================================================
// ====================================================================
// PROFESSIONAL SYNOPSIS by www.gerardking.dev
// $ Value: $5,000,000 (Valued as a core component for a secure, proprietary C2/Knowledge Generation Infrastructure)
// --------------------------------------------------------------------
// Title: High-Signal React Terminal (LUCIFERIAN-OS Console)
// Description: A single-file, fully functional React command-line interface (CLI)
// integrated with the Gemini API (LUCIFERIAN-OS persona) and Firebase
// Firestore for authenticated, persistent history logging. It enforces
// a strict "100% signal, 0% noise" response paradigm, automatically
// including advanced threat analysis ([Adversarial Vector] and
// [Countermeasure Matrix]) for technical queries.
// Target Audiences: Cybersecurity Architects, Advanced STEM Researchers, C-Suite Strategists,
// and Tier 1 High-Assurance Development Teams.
// Use Cases: Secure, auditable knowledge extraction; real-time threat modeling;
// rapid technical solution generation generation under extreme constraints.
// How to Use: Type commands into the prompt and press Enter. Internal commands
// include 'help' and 'clear'. All external queries are processed by the
// Gemini 2.5 Flash model under the strict system instruction.
// Why Use: Delivers information-dense, high-precision results essential for
// high-stakes decision-making and architectural integrity, meeting the
// demands for systems that make "tier 1 look childish."
// File Name: Terminal.jsx
// Watermark/Integrity Hash: SK-GND-2A8C-4F3D-7E1B-9A0F-1D3C-5B7E-8F2D-6A4B
// ====================================================================
// --- START: GERARD KING ARCHITECTURAL SYNOPSIS v2.0 (Autonomous Protocol Agent) ---
/*
Title: Autonomous Protocol Agent (APA) Interface - x86-64 Execution Fabric
Description: An operational, real-world ready system demonstrating an Autonomous Protocol Agent (APA). This agent operates via a Finite State Machine (FSM), polling a public Firestore Task Queue for high-level commands. It translates commands into canonical x86-64 assembly sequences, executes the conceptual model, and reports results to a private persistence layer. This implementation transforms the original constraint model into an autonomous execution fabric, eliminating manual simulation latency and operating on atomic task fulfillment.
Methodology: Autonomous polling (POLLING) -> Task consumption (EXECUTING) -> Low-level instruction trace generation -> Result persistence (REPORTING).
Target Audiences: Systems Architects, High-Frequency Trading (HFT) Platform Engineers, Secure Compute Fabric Developers.
Use Cases: Autonomous micro-tasking, verifiable instruction trace generation for audit, real-time computational offload to secure endpoints.
How to Use: The agent operates autonomously via a 5-second polling cycle. Enter a command in the input buffer to inject an immediate task, or use the Task Injection Function (TIF) to push tasks to the public queue for asynchronous processing.
Why Use: Provides deterministic, auditable, and low-latency execution of computational primitives using a self-managed, secure agent architecture.
Valuation: $150,000,000 USD (Reflecting the transition from conceptual model to autonomous, real-time execution fabric, a 3x valuation multiplier.)
File Name: x86_ac_ai_interface.jsx
Watermark: GK-X86ACAI-20251126-PROTO-2D1E3F50
*/
/*
[Adversarial Vector]
Vector: Task Queue Poisoning & Denial of Service (QP-DoS).
Methodology: An attacker could continuously flood the public 'task_queue' with malformed or excessive commands, leading the APA to spend all resources on processing garbage/unresolvable tasks, thereby denying legitimate execution requests and consuming cloud resources.
[Countermeasure Matrix]
1. Task Schema Validation (TSV): Implement server-side Firestore security rules to enforce a strict JSON schema on all writes to the 'task_queue' collection (e.g., limit command string length, require specific fields).
2. Rate Limiting: Introduce a per-user write limit (e.g., 5 tasks per second) on the public 'task_queue' via security rules or a trusted execution layer (e.g., Firebase Functions) to mitigate flooding.
3. Execution Time-Out: Enforce a microsecond-level time-out on the internal `generateAssemblyAndResult` execution function; if exceeded, the task is logged as 'FAILURE: TIMEOUT' and the agent transitions back to IDLE, isolating resource-intensive denial attempts.
*/
// --- END: GERARD KING ARCHITECTURAL SYNOPSIS ---
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