Ethical Risk Analysis of L2 Rollups

Layer 2 rollups improve throughput and fees, but can reintroduce risk through operator discretion and information asymmetry. We ask which operator and governance designs produce ethically problematic user risk. We adapt Ethical Risk Analysis to rollup architectures, build a role-based taxonomy of decision authority and exposure, and pair the framework with two empirical signals, a cross sectional snapshot of 129 projects from L2BEAT and a hand curated incident set covering 2022 to 2025. We analyze mechanisms that affect risks to users’ funds, including upgrade timing and exit windows, proposer liveness and whitelisting, forced inclusion usability, and data availability choices. We find that ethical hazards rooted in L2 components control arrangements are widespread: instant upgrades without exit windows appear in about 86 percent of projects, and proposer controls that can freeze withdrawals in about 50 percent. Reported incidents concentrate in sequencer liveness and inclusion, consistent with these dependencies. We translate these findings into ethically grounded suggestions on mitigation strategies including technical components and governance mechanisms.

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Publication Details

Journal
ACM Transactions on the Web
Published
2025-12-25
DOI
https://doi.org/10.1145/3786147
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

Ethical Risk Analysis of L2 Rollups

Georgy Ishmaev, François Taı̈ani, Davide Frey, Emmanuele Anceaume
ACM Transactions on the Web
Ethics and Social Impacts of AI
article

Ethical Risk Analysis of L2 Rollups

Georgy Ishmaev, François Taı̈ani, Davide Frey, Emmanuele Anceaume
article en

Abstract

Layer 2 rollups improve throughput and fees, but can reintroduce risk through operator discretion and information asymmetry. We ask which operator and governance designs produce ethically problematic user risk. We adapt Ethical Risk Analysis to rollup architectures, build a role-based taxonomy of decision authority and exposure, and pair the framework with two empirical signals, a cross sectional snapshot of 129 projects from L2BEAT and a hand curated incident set covering 2022 to 2025. We analyze mechanisms that affect risks to users’ funds, including upgrade timing and exit windows, proposer liveness and whitelisting, forced inclusion usability, and data availability choices. We find that ethical hazards rooted in L2 components control arrangements are widespread: instant upgrades without exit windows appear in about 86 percent of projects, and proposer controls that can freeze withdrawals in about 50 percent. Reported incidents concentrate in sequencer liveness and inclusion, consistent with these dependencies. We translate these findings into ethically grounded suggestions on mitigation strategies including technical components and governance mechanisms.

ACM Transactions on the Web
Institut de Recherche en Informatique et Systèmes Aléatoires (FR), Centre Inria de l'Université de Rennes (FR), Université de Rennes (FR)
Reduced inequalities
Openalex Percentile: Top 28%
Ethics and Social Impacts of AI
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