Track papers across labs, topics, and trends.
Search papers, labs, and topics across Lattice.
This paper analyzes the design space of emergency override mechanisms in decentralized protocols, which are crucial for mitigating exploits but introduce centralization risks. They develop a Scope x Authority taxonomy to map emergency architectures and formalize the trade-offs between centralization costs and containment effectiveness as a stochastic cost-minimization problem. Empirical analysis of 705 exploit incidents validates their model, revealing the impact of authority type on containment time, the heavy-tailed distribution of losses, and the influence of community sentiment on intervention costs.
Emergency intervention in decentralized protocols is not just an ideological debate, but a quantitatively analyzable engineering problem with design principles that can minimize costs and maximize effectiveness.
Decentralized protocols claim immutable, rule-based execution, yet many embed emergency mechanisms such as chain-level freezes, protocol pauses, and account quarantines. These overrides are crucial for responding to exploits and systemic failures, but they expose a core tension: when does intervention preserve trust and when is it perceived as illegitimate discretion? With approximately $10$ billion in technical exploit losses potentially addressable by onchain intervention (2016--2026), the design of these mechanisms has high practical stakes, but current approaches remain ad hoc and ideologically charged. We address this gap by developing a Scope $\times$ Authority taxonomy that maps the design space of emergency architectures along two dimensions: the precision of the intervention and the concentration of trigger authority. We formalize the resulting tradeoffs of a standing centralization cost versus containment speed and collateral disruption as a stochastic cost-minimization problem; and derive three testable predictions. Assessing these predictions against 705 documented exploit incidents, we find that containment time varies systematically by authority type; that losses follow a heavy-tailed distribution ($\alpha \approx 1.33$) concentrating risk in rare catastrophic events; and that community sentiment measurably modulates the effective cost of maintaining intervention capability. The analysis yields concrete design principles that move emergency governance from ideological debate towards quantitative engineering.