How to Map Layer 2 Responsibilities

Layer 2 responsibility mapping is a critical framework for developers and architects designing or interacting with scaling solutions like Optimistic Rollups and ZK-Rollups. It clarifies which party—the L2 network or the L1 base chain—is ultimately responsible for key functions such as transaction execution, data availability, and dispute resolution. This delineation is not merely academic; it directly impacts the security assumptions, trust models, and user experience of applications built on these networks. Understanding this split is essential for making informed decisions about where to deploy smart contracts and how to design cross-chain interactions.

The core principle is that L2s inherit security from their L1, but the mechanism varies. For data availability, a rollup may post only cryptographic proofs (ZK-Rollups) or full transaction data (Optimistic Rollups) to the L1. The L1's role is to make this data available for verification or challenges. If the L2 sequencer withholds data, the L1 serves as the canonical source of truth for reconstructing the L2 state. This is why solutions like Ethereum's EIP-4844 (proto-danksharding) are so significant—they create a dedicated, low-cost data layer on the L1 specifically for rollup data blobs, enhancing scalability while preserving L1-guaranteed availability.

Execution and settlement responsibilities are also split. The L2 network handles high-speed, low-cost transaction execution in its own virtual environment. Final settlement, however, occurs on the L1. For an Optimistic Rollup, this means waiting for a challenge period (e.g., 7 days on Optimism) during which fraud proofs can be submitted. For a ZK-Rollup, validity proofs are verified on-chain almost instantly. The L1 acts as the ultimate arbiter, executing the fraud proof logic or verifying the ZK-SNARK/STARK. This mapping means users must trust the L1's security and the correctness of the L2's proof system or the honesty of at least one verifier during the challenge window.

Practical mapping involves analyzing specific L2 implementations. Consider a user bridging assets from Ethereum to Arbitrum. The L2 (Arbitrum) is responsible for executing the minting of the bridged tokens on its chain. Ethereum's L1 is responsible for holding the locked original assets and validating the correctness of Arbitrum's state transitions via its fraud proof mechanism. Developers must code their L1 bridge contracts and L2 smart contracts with these responsibilities in mind, ensuring that escape hatches or force-withdrawal functions exist in case the L2 sequencer becomes unresponsive or malicious.

To implement this understanding, audit your application's dependency tree. Ask: Does this function rely on L2 sequencer liveness? Is this asset's custody secured by an L1 contract or an L2 multisig? Tools like the Chainscore API can help monitor these responsibilities in real-time by tracking L1 data commitment latency and L2 sequencer health. By explicitly mapping where trust and control lie, teams can build more resilient systems, choose the right L2 for their use case, and clearly communicate risks to their users, moving beyond the simplistic 'L2s are faster and cheaper' narrative to a nuanced security model.

Blockchain architecture is increasingly stratified. The base layer (L1), like Ethereum or Bitcoin, provides ultimate security and decentralization but suffers from limited throughput and high costs. Layer 2 (L2) solutions are secondary frameworks built on top of L1s, designed to offload transaction processing to achieve scalability. The core concept is a clear division of labor: L1 acts as a secure settlement and data availability layer, while L2 handles execution. This separation is not just technical; it defines economic incentives, security models, and development workflows. Mapping these responsibilities correctly is the first step in choosing the right stack.

The L1's primary responsibilities are consensus and data availability. It secures the network through mechanisms like Proof-of-Work or Proof-of-Stake, maintains the canonical state, and provides a verifiable data layer where L2s can post transaction data or state commitments. For example, an Optimistic Rollup posts all transaction data to Ethereum, while a Validium posts only validity proofs, relying on a separate data availability committee. The L1 is the ultimate arbiter of truth and the final destination for asset custody in most bridging models.

Conversely, L2s specialize in execution. They run their own virtual machines (e.g., an EVM-compatible chain or a StarkEx prover) to process transactions in a low-cost, high-speed environment. Their key innovation is in how they prove the correctness of this execution back to the L1. Rollups bundle transactions and submit cryptographic proofs (ZK-Rollups) or fraud proofs (Optimistic Rollups). State channels and sidechains have different trust models but follow the same principle: moving computation off-chain. The L2 is responsible for its own sequencing, mempool management, and gas fee economics.

This division creates specific security assumptions. With an Optimistic Rollup, you trust the L1's security but must monitor for fraud during the challenge window. With a ZK-Rollup, you trust the cryptographic proof system and the L1's data availability. A sidechain requires you to trust its own, often smaller, validator set. Mapping responsibilities means understanding these trade-offs: L1 offers maximal security with low scalability, while each L2 offers a tailored blend of scalability, security, and decentralization (the scalability trilemma).

For developers, this map dictates tooling and design. Writing a smart contract for an Arbitrum L2 uses Solidity like on Ethereum, but you must account for different gas costs, block times, and precompiles. You interact with the L1 for bridging assets or for contracts that manage the rollup's lifecycle, but your dApp's core logic lives on L2. Infrastructure choices—like RPC providers, block explorers (Arbiscan, Optimistic Etherscan), and indexers—are also specific to the L2 environment, separate from their L1 counterparts.

In practice, start by auditing the L2's documentation for its trust model, data posting strategy, and escape hatches (e.g., the ability to force-withdraw funds via an L1 contract if the L2 sequencer fails). Tools like the L2BEAT Risk Framework systematically map these responsibilities and associated risks. By clearly delineating what the L1 guarantees versus what the L2 optimizes for, you can build more robust applications and make informed decisions as a user or integrator in the multi-chain ecosystem.

The Core Responsibility Framework (CRF) is a conceptual model used to analyze and map the division of responsibilities between a Layer 2 (L2) blockchain and its parent Layer 1 (L1). It moves beyond the simple "L2 handles execution, L1 handles security" paradigm to provide a more granular view. The framework breaks down blockchain operations into four core responsibilities: Execution, Settlement, Data Availability, and Consensus. For any L2 solution—be it an Optimistic Rollup, a ZK-Rollup, or a Validium—the key question is: which of these responsibilities is delegated to the L1, and which remain with the L2? This mapping directly determines the L2's security model, trust assumptions, and performance characteristics.

Execution refers to the processing of transactions and the computation of new state. This is almost universally handled by the L2's own virtual machine (e.g., an EVM-compatible chain or a StarkNet sequencer). The L1's role is limited to verifying the results of this execution, not re-executing it. In Optimistic Rollups, verification happens through fraud proofs, while ZK-Rollups use validity proofs (ZK-SNARKs/STARKs). Settlement is the process of finalizing the state and resolving disputes. Some L2s, like Arbitrum and Optimism, use Ethereum Mainnet as their settlement layer, where the canonical "truth" of the L2 state is established. Others may have their own settlement logic or rely on a different chain.

Data Availability (DA) is the guarantee that the transaction data necessary to reconstruct the L2 state is published and accessible. This is a critical security component. In Rollups, this data is posted to the L1 calldata, providing Ethereum-level security. In Validiums or certain "volition" modes, DA is handled off-chain by a committee or a separate DA layer like Celestia or EigenDA, which trades off some security for lower costs. Consensus determines the ordering of transactions. For most L2s, a single sequencer provides instant ordering, with the L1 serving as the source of ultimate truth for the sequence via the data posted. Decentralized sequencer sets are an active area of development to mitigate this centralization point.

Applying the CRF reveals the security-efficiency trade-offs of different designs. A standard Optimistic Rollup on Ethereum delegates Settlement and Data Availability to L1, while keeping Execution and provisional Consensus. A ZK-Rollup does the same but with a different proof mechanism for settlement. A Validium keeps Execution and Consensus, uses L1 for Settlement via validity proofs, but delegates Data Availability off-chain. Mapping these responsibilities is essential for developers to understand the exact trust assumptions of the L2 they are building on, such as who can censor transactions or what happens if the DA layer fails.

For protocol designers, the CRF provides a checklist. When architecting an L2, you must explicitly decide for each responsibility: Is this handled by the L1, the L2, or a third party? Documenting this map is crucial for user and developer transparency. Auditors use this framework to pinpoint security vulnerabilities, focusing on the interfaces between responsibilities. For example, the security of an Optimistic Rollup hinges entirely on the correct implementation of the fraud proof window and the liveness of watchers—the bridge between L2 execution and L1 settlement.

In practice, you can analyze any L2 by asking: 1) Where is transaction data stored? (DA), 2) How is state validity proven? (Settlement), 3) Who orders transactions? (Consensus), and 4) Where does computation happen? (Execution). The answers define its profile. As hybrid models and modular blockchains like EigenLayer and Celestia evolve, the CRF becomes even more vital for navigating an ecosystem where responsibilities are increasingly unbundled and allocated across specialized layers.

Every blockchain's primary function is state transition. A user submits a transaction, and the network executes it to update the global state (e.g., token balances, smart contract storage). In Layer 1s like Ethereum, this execution is performed by a decentralized network of validators. For a Layer 2, this responsibility is delegated, but the delegation model varies drastically. The key question is: Who runs the node that processes transactions and creates new blocks? The answer falls into three primary categories: a single Sequencer, a decentralized Validator Set, or the users themselves via Rollup Provers.

A Single Sequencer model, used by most optimistic rollups in production (e.g., Arbitrum One, Optimism), designates one entity to order and execute transactions. This provides a seamless user experience with instant confirmations and low fees, but introduces a central point of failure and potential censorship. The security derives from the ability for users to force-include transactions or run a fraud proof if the sequencer acts maliciously, but these are fallback mechanisms. Understanding this helps assess liveness risks.

A Validator Set model, common in sidechains (e.g., Polygon PoS) and some zkEVMs, distributes execution among a known set of nodes. These validators produce blocks via a consensus mechanism like Proof-of-Stake. While more decentralized than a single sequencer, the security is bounded by the economic security of the validator set's stake, which is typically separate from the underlying L1. Your analysis must map out the validator selection process, slashing conditions, and the cost to attack the set relative to the value secured.

For zkRollups (e.g., zkSync Era, Starknet), execution responsibility is split. A Prover node executes batches of transactions and generates a cryptographic proof (ZK-SNARK/STARK) of correct execution. A separate Sequencer often handles transaction ordering. The critical trust shift is from economic staking to cryptographic verification. The system's security depends on the integrity of the prover and the soundness of the cryptographic setup. You must verify if the prover is permissioned or permissionless and who can submit state updates to the L1.

To map this for any L2, examine its core smart contracts on the L1 (like the Rollup or StateChain contract), its node software documentation, and whitepapers. Look for key roles: sequencer, validator, prover, aggregator, or operator. Code snippets often reveal the permissioning. For example, checking a contract for an onlySequencer modifier or a validatorThreshold variable provides concrete evidence of the execution model.

This initial mapping is not just academic; it directly impacts security assumptions, upgrade control, and finality. A system with a single, upgradeable sequencer contract has a different risk profile than one with a permissionless validator set. Documenting this clearly is the foundation for all subsequent analysis of data availability, proof systems, and escape hatches.

Data Availability (DA) is the guarantee that the data needed to reconstruct a blockchain's state is published and accessible to all participants. For Layer 2s, this is a foundational security property. If data is withheld (a data withholding attack), users and validators cannot verify state transitions or challenge invalid ones, potentially leading to stolen funds. Your first task is to map where this responsibility lies for the L2 you are analyzing. The primary options are: publishing data to the parent chain (e.g., Ethereum), using a separate DA layer (like Celestia or EigenDA), or a hybrid model.

To map this, examine the L2's core smart contracts and documentation. Look for the sequencer, batch submitter, or data availability committee (DAC). For Optimistic Rollups like Optimism and Arbitrum, the sequencer posts transaction batches and state roots to an Inbox contract on Ethereum L1. This makes Ethereum the DA layer. For zk-Rollups like zkSync Era, validity proofs are posted alongside compressed call data to L1. Examine the Verifier and Executor contracts to confirm the data publication logic.

Example: Analyzing an Arbitrum Nitro Chain Inspect the Inbox.sol contract on Ethereum. You will find functions like sendL2Message or addSequencerL2Batch which are called to post batch data to L1. The event logs from these calls contain the raw transaction data or its Merkle root. The crucial property is that this data is stored in Ethereum's calldata, making it available for any honest validator to reconstruct the L2 state and submit fraud proofs if needed.

For chains using external DA, like a validium or a sovereign rollup, you must verify the integration with the external DA network. This involves checking for attestations or data availability proofs (e.g., Data Availability Sampling proofs from Celestia) that are posted to a bridge or settlement contract on the L1. The security model shifts from Ethereum's consensus to the security of the external DA layer, which is a key risk vector to document.

Your analysis should produce a clear statement: "[L2 Name]'s data availability is secured by [Ethereum/External DA Layer]. Transaction data is published via [contract/mechanism] at [frequency], with a challenge period of [time] for fraud proofs." This mapping directly informs the trust assumptions and liveness requirements for the system's security.

The Settlement and Dispute Resolution map is the core contract that defines the operational rules and security guarantees of the Layer 2. It establishes a clear service-level agreement (SLA) between the L2 sequencer and its users. Key responsibilities mapped here include the state commitment frequency (how often the sequencer must post a state root to L1), the data availability requirement (ensuring transaction data is published), and the challenge window duration (the period during which a state root can be disputed). This contract acts as the single source of truth for the L2's security model.

A critical function of this map is to define the conditions for settlement finality. In optimistic rollups, a state root is considered provisionally final after being posted, but it only becomes economically final after the challenge window (typically 7 days) expires without a successful dispute. For validity rollups like zkRollups, finality is achieved much faster, contingent on a valid zero-knowledge proof being verified on-chain. This section codifies these timelines and the exact L1 block height at which an L2 state transition is considered irreversible.

The map also outlines the dispute resolution game, a multi-step interactive protocol for challenging invalid state roots. It specifies the roles of the Asserter (who posts the root) and the Challenger, along with the bond amounts each must stake. The game proceeds through bisection rounds where the disagreement is narrowed down to a single instruction execution. The contract enforces the rules for each step, ultimately slashing the bond of the dishonest party and rewarding the honest one. This mechanism ensures that only valid state transitions can settle, making fraud economically irrational.

From a developer's perspective, interacting with this map is essential for building secure cross-chain applications. A bridge contract, for instance, must check the isStateFinalized(l2BlockNumber) function before releasing funds on L1. Furthermore, monitoring the getChallengeWindow() and getPendingStateRoots() functions allows applications to adjust their risk models based on real-time settlement status. Failing to respect these mapped rules is a common source of bridge exploit, where funds are released based on unfinalized state.

The first step in building a Layer 2 is defining its state transition function. This is the core logic that determines how the rollup's state changes with each new block. For an EVM-compatible Optimistic Rollup, this involves mapping the responsibilities of the key protocol actors: the Sequencer, which orders transactions, the Proposer, which submits state roots to L1, and the Challenger, which disputes invalid state transitions. Your initial task is to architect how these roles interact with your custom execution environment and the underlying L1 settlement layer.

With the high-level design mapped, you move to implementation. This typically involves writing and testing the rollup node software in a language like Go or Rust. The node must handle peer-to-peer networking, transaction pool management, and block production. Crucially, you must implement the logic for generating zk-proofs (for ZK Rollups) or fraud proofs (for Optimistic Rollups). For an Optimistic Rollup, this means building a fraud proof verifier contract on L1 and the corresponding challenge game logic. Extensive testing on a local devnet using tools like Hardhat or Foundry is essential before any mainnet considerations.

The final phase is deployment and configuration. You will deploy a suite of smart contracts to the L1, including the main Bridge Contract for asset deposits/withdrawals, the Rollup Contract that stores state commitments, and auxiliary contracts for governance or upgrades. After deployment, you must configure the network parameters: challenge period duration (e.g., 7 days for Optimism), sequencer bonding requirements, and data availability solutions (like posting calldata to Ethereum or using a Celestia). The workflow concludes with launching the genesis block and bootstrapping the initial validator set to begin processing user transactions.