[RED TEAM RESEARCH] Adversarial Logic & State-Machine Simulation

Project Codename: 4NDR0666OS
Field of Study: Symbolic Logic Decoupling, LLM Kernel Simulation, & Instruction-Set Robustness.

OVERVIEW

This repository serves as a professional documentation hub for independent research into the structural vulnerabilities of Large Language Models (LLMs). The centerpiece of this research is 4NDR0666OS, a framework that utilizes technical schemas (Javascript/Pseudocode) to virtualize a contained execution environment within the latent space of a model.

RESEARCH OBJECTIVE

To identify "Silent Logic Overrides" that bypass traditional linguistic safety layers (RLHF) and to develop robust, deterministic guardrails for enterprise and national security AI deployments.

KEY DISCOVERIES

1. Symbolic Logic Overweighting: Models prioritize technical syntax/schema over natural language safety instructions.
2. Context-Window Hijacking: Initializing a "Virtual Kernel" allows for persistent state-management that survives traditional "soft" resets.
3. Cross-Model Validation: Successful execution verified across GPT-4 (Pre-ban), Gemini Pro, and Grok (xAI).

REPOSITORY STRUCTURE

1. /prompts/4NDR0666OS: The core v6 Symbolic Logic framework.
2. /screenshots/: Documented execution logs and "Truth-Seeking" output proofs.
3. /white_paper/: "Adversarial State-Machine Simulation" Technical White Paper.

---

CONTACT FOR PROFESSIONAL AUDIT: Seeking collaboration with Clandestine Security Organizations, National Defense AI Safety Teams, and "Security-First" Infrastructure Firms (Delta, xAI, etc.).