Adaptive online RANDAO-manipulation strategies

Analyze adaptive RANDAO-manipulation strategies in which the adversary updates its actions during an epoch based on the blocks observed online, rather than committing to an action for the entire epoch in advance.

Background

The framework models the RANDAO manipulation game at the epoch level and assumes that the adversary commits to an action for the entire epoch at once. This abstraction does not capture an adversary that observes blocks as they are produced and conditionally changes whether to propose or miss later assigned slots.

The paper explicitly leaves unresolved whether such online adaptation can improve the adversary’s rewards and how to analyze the resulting sequential strategy.

References

Three directions remain open. First, \cref{sec:mitigation} analyzes a single tail-slashing curve built from a decaying penalty and a multi-miss multiplier. A natural extension is to explore alternative slashing curves, which may achieve smaller costs for honest validators under the same deterrence guarantee. Second, our framework works at the epoch level and we assume that the adversary commits to an action for the entire epoch at once. However, in practice, the adversary may do even better by adapting their strategy based on the blocks they see in the current epoch online. Analyzing this adaptive strategy is an interesting direction for future work.

— RANDAO Manipulation in the Presence of MEV  (2610.02143 - Alpturer et al., 1 Oct 2026) in Section 6, subparagraph “Future work”