Cytokine storm syndromes arise from a systemic collapse of immune homeostasis due to dynamic imbalance between danger load (L) and immune buffer capacity (B). Existing linear “danger signal → inflammation” models cannot explain why high antigen loads sometimes produce only mild inflammation, why hyperinflammation and immunosuppression often co‑exist, or why similar danger signals lead to divergent clinical outcomes. Here we propose a systems immunology framework: L represents the total pro‑inflammatory pressure, while B is a network of promoting and suppressive forces analogous to acid–base or coagulation buffers. We introduce a dynamic S‑index (S_actual ≈ Treg/Teff functional ratio) as an “immunological pH” for the adaptive arm. Four equilibrium states are defined – high‑buffer, low‑buffer, promoting‑dominant, and suppressive‑dominant – each with distinct storm pathways (direct vs. indirect). Three dominant dynamic states are described: innate‑driven collapse (immune‑deficiency‑associated and massive necrosis types), adaptive dynamic mismatch (a four‑stage progression), and mixed oscillatory states. Differences between PAMP and DAMP are clarified, and diverse storm phenotypes are mapped onto a unified state space. The framework explains inter‑individual heterogeneity and temporal evolution, and it provides a rationale for individualized therapy. Several experimentally testable predictions are proposed. All quantitative descriptions are purely theoretical and await experimental validation.