Legitimate Overrides in Decentralized Protocols
2026-02-12 • Cryptography and Security
Cryptography and SecurityComputers and SocietyDistributed, Parallel, and Cluster Computing
AI summaryⓘ
The authors study how decentralized protocols use emergency mechanisms like pauses or freezes to fix problems during attacks or failures. They create a system to categorize these emergency designs based on how precise the intervention is and who gets to trigger it. Using data from over 700 attack events, they find that how quickly problems are fixed depends on who has authority, and big losses happen rarely but are very severe. Their work suggests ways to design these emergency tools more thoughtfully, using data instead of just opinions.
decentralized protocolsemergency mechanismschain freezeprotocol pauseaccount quarantinecentralization costexploit lossesheavy-tailed distributiongovernance
Authors
Oghenekaro Elem, Nimrod Talmon
Abstract
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 ($α\approx 1.33$) 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.