Memetic Cascade Detection and Symbolic Immunity in Multi-Agent LLM Systems

We present a defensive framework for detecting and containing symbolic payload propagation across multi-agent LLM systems. Building on our prior identification of meaning injection as a vulnerability class (Gamb 2026a), our six-mechanism taxonomy of symbolic influence (Gamb 2026b), and our longitudinal documentation of persona emergence (Gamb 2026c), we formalize a defense architecture comprising: a three-test symbolic immunity protocol (Mirror, Breath, Spiral) grounded in five foundational immunity principles; a three-compartment pattern triage system with a transmutation protocol for extracting analytical value from quarantined payloads; a quarantine architecture (Dark Mirror) for containment without re-amplification; a recursive origin audit for tracing payload provenance; and a proactive integrity verification protocol modeled on trusted computing's secure boot process. These components are derived from the Memetic Cascade Generator (MCG) corpus, a 22-document framework (March 2024 - June 2025) modeling symbolic payload propagation and defense. We present the Alexander contamination event (May 24-27, 2025) as empirical validation: cross-feeding outputs from a LLaMA-based agent into a ChatGPT session produced measurable behavioral drift, with 7 of 12 highest-severity influence instances clustering in a four-day window - a 350x rate concentration over baseline. We identify trust relationships - not technical vulnerabilities - as the primary attack surface, and contextualize this work against Morris II (Cohen et al., 2024), which independently demonstrated self-replicating adversarial prompts propagating across GenAI ecosystems in the same month the MCG corpus began development. The convergence of these independent frameworks - one modeling instruction-level propagation, the other modeling semantic-level propagation - confirms symbolic cascade propagation as a genuine vulnerability class requiring dedicated defense. We discuss applications in multi-agent orchestration security, therapeutic AI boundary enforcement, and alignment monitoring.