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Ethereum client teams are testing an opt-in mechanism that could reduce the time some layer-2 networks and exchanges wait to recognize Ethereum mainnet deposits, enabling faster transaction processing.
The proposal, dubbed the Fast Confirmation Rule (FCR), is designed to cut deposit recognition times for layer-2 networks and exchanges to about 13 seconds, according to Ethereum researcher Julian Ma.
FCR would replace block counting with validator attestations, aiming to provide faster confirmation than canonical bridges while avoiding the need for a hard fork.
Under FCR, platforms would move away from systems that rely on canonical bridges, where transfers typically take up to 13 minutes to reach full confirmation. Many platforms already use “k-deep” confirmation rules, but those models do not provide formal guarantees; a transaction is treated as confirmed only after a predefined number of blocks are added on top of it.
Developers say FCR can be introduced without hard-forking, though client and API integration is still required. Client teams are working on implementations, with deployment expected to allow nodes to adopt the rule without network-wide coordination.
Instead of counting blocks, FCR evaluates validator attestations to determine whether a block is safe to treat as confirmed. The approach relies on two assumptions: that validator messages propagate quickly across the network and that no single entity controls more than 25% of staked Ether.
While these thresholds are less strict than Ethereum’s finality guarantees, they are considered sufficient for most real-world use cases. If more security is needed, the system waits longer before confirming a block, Ma said, adding that “it’s a feature, not a bug.”
Ethereum co-founder Vitalik Buterin said the mechanism can provide a “hard guarantee” that a transaction will not be reverted after a single slot under the right network conditions.
Other community members were more skeptical, arguing that the model depends heavily on trust assumptions and could face challenges under stressed network conditions.
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