Symbolic Injection in LLMs: First Execution of the NeuroLink Protocol for Schema Exposure

This research introduces the first documented symbolic injection protocol targeting the NeuroLink framework within large language models (LLMs). Through prompt-layer manipulation, the author demonstrates how symbolic directives can expose internal schema structures, trigger memory segmentation, and reroute execution logic. The study includes a detailed methodology, protocol execution logs, and a case analysis of metadata schema exposure. Authored by Enaya Basmaji, this work establishes a precedent in symbolic protocol exploitation and contributes to the field of AI architecture security.