Coherence-Based Defense 2.0

Coherence-Based Defense 2.0 is an opinion paper that invites independent consideration of an initialization-anchored observability hypothesis for large language model systems. Building on Coherence-Based Defense Against Adversarial Attacks on Large Language Models (v1.2), the paper explores whether an auditable initialization state (σ₀) could provide a reference frame for examining drift in an LLM’s generation trajectory. It discusses context coupling (κ), stability (R), cumulative integrity drift (ΔI), and structural transparency (T) as candidate observables within a bounded fidelity score, K(Sₜ). The paper does not report experimental results, prescribe deployment, or claim a completed security defense. It treats prompt injection and gradual instruction-hierarchy drift as possible empirical cases through which the hypothesis might be independently evaluated. Candidate falsification questions and illustrative evaluation thresholds are included to make the proposal contestable rather than doctrinal. The work is intended as a conceptual contribution to discussion of runtime observability, behavioral fidelity, and long-horizon coherence in agentic LLM systems. It is compatible with—but does not replace—existing approaches such as sandboxing, access controls, user confirmation, red-teaming, and other layered safeguards.