Ethereum client teams are testing an optional fast confirmation mechanism that could reduce the time layer-2 networks and exchanges take to recognize mainnet deposits to roughly 13 seconds.
Known as the Fast Confirmation Rule (FCR), the proposal aims to cut deposit times from Ethereum’s base layer to L2s or exchanges by 80–98%, according to Ethereum researcher Julian Ma.
Currently, most users rely on canonical bridges, where transfers wait for multiple block confirmations or full finality — a process that can take around 13 minutes. Some platforms instead use “k-deep” confirmation rules, treating transactions as final after a set number of blocks, though this approach lacks formal guarantees.
Developers say FCR can be introduced without a hard fork, though client updates and API integrations are still in progress. Once implemented, nodes can adopt the rule independently, with exchanges, L2s, and infrastructure providers expected to integrate it with minimal adjustments.
How the Fast Confirmation Rule works
Instead of relying on block counts, FCR uses validator attestations to assess whether a block is safe to treat as confirmed, addressing delays in bridging.
The system is based on two key assumptions: that validator messages propagate across the network within seconds, and that no single entity controls more than 25% of staked Ether. While these conditions are less strict than Ethereum’s full finality requirements, they are considered sufficient for most practical use cases.
Ma noted that the mechanism can adapt to changing conditions — if additional security is needed, nodes can simply wait longer before confirming a block.
Ethereum co-founder Vitalik Buterin has also expressed support for the approach, stating that under certain network conditions it can offer a strong guarantee that a transaction will not be reversed after a single slot, or roughly 12 seconds.
Community concerns persist
Not everyone is convinced that the Fast Confirmation Rule will perform reliably under real-world conditions. Some critics argue that the model depends heavily on trust assumptions, with one user noting that the requirement for a supermajority of honest validators “is doing a lot of heavy lifting.”
Others see clear potential benefits, particularly in improving user experience through near-instant confirmations. However, they caution that these advantages depend on whether the underlying assumptions can consistently hold up under network stress.
