Detailed Instructions

First, you must identify the data availability layer the protocol relies on. This is foundational, as the verification method differs per solution. For an L2 like Arbitrum Nova, check that it uses the Ethereum calldata model. For an Optimism chain, verify it posts data to an EigenDA or Celestia sequencer. Examine the protocol's official documentation or the chain's genesis configuration. For a rollup, inspect the bridge contract (e.g., 0x8315177aB297bA92A06054cE80a67Ed4DBd7ed3a for Arbitrum One) to see where it posts state roots. Use a block explorer to view recent transactions from the sequencer address to confirm the target DA layer.

• Sub-step 1: Query the chain's RPC endpoint for eth_chainId and cross-reference with public lists of L2s and their DA solutions.
• Sub-step 2: Examine the BatchInbox address or Sequencer contract for transaction patterns pointing to Ethereum, Celestia, or a DA committee.
• Sub-step 3: Review the protocol's or chain's whitepaper for explicit mentions of data availability sampling (DAS) or a specific DA bridge.

Tip: For modular stacks like Polygon CDK or Arbitrum Orbit, the DA layer is a configurable choice set by the deployer; verify this in the chain's deployment parameters.

Detailed Instructions

Continuously monitor the flow of data from the execution layer to the DA layer. For an Ethereum-based rollup, this means watching the calldata posted in L1 transactions. Use a service like Dune Analytics to create a dashboard tracking the batch submission interval and calldata size. For a Celestia-based chain, you would monitor the Celestia network for blob submissions containing the rollup's block data. Check for finality by verifying the DA layer's consensus. On Ethereum, confirm the transaction has sufficient block confirmations (e.g., >15 blocks). On Celestia, ensure the data root has been included in a finalized block via light client verification.

• Sub-step 1: Set up an alert for failed transactions from the sequencer's batch submitter address.
• Sub-step 2: Query the DA layer's block explorer for the specific namespace or address used by the rollup to post data.
• Sub-step 3: Calculate the data withholding time window (e.g., fraud proof window) and ensure new data is posted well within this period.

bashCopy
# Example: Query recent batches from an Arbitrum sequencer via Etherscan API
curl "https://api.etherscan.io/api?module=account&action=txlist&address=0x1c479675ad559dc151f6ec7ed3fbf8cee79582b6&startblock=latest"

Tip: A sudden drop in calldata volume or increased submission latency is a critical red flag for potential DA issues.

Detailed Instructions

Data being posted is not sufficient; it must be retrievable by any honest node. This step tests the data availability guarantee. For rollups using Ethereum blob transactions (EIP-4844), verify the blob sidecar is available via the network's blob propagation protocol. Use tools like the eth_getBlobSidecars RPC call. For validity proofs, you must be able to fetch all input data required for the ZK proof verification. Attempt to sync a full node or a light client for the L2 from the data published on the DA layer. The process should succeed without relying on a centralized sequencer API. Check that data availability sampling light clients, if applicable, can successfully sample the data.

• Sub-step 1: Run a light client for the DA layer (e.g., a Celestia light node) and attempt to fetch the rollup's block data by its namespace ID.
• Sub-step 2: Use a public RPC endpoint for the L2 to fetch a recent block, then trace its data back to the corresponding transaction on the DA layer.
• Sub-step 3: Validate that the Merkle root or KZG commitment published on-chain corresponds to the data you retrieved.

Tip: If the only way to obtain historical data is via a centralized gateway, the system has a critical weakness in its DA assumption.

Detailed Instructions

Analyze the cryptoeconomic security model that disincentivizes data withholding. For a rollup with fraud proofs, examine the bond or stake required from the sequencer that can be slashed. For a system like EigenDA, review the staking and slashing parameters of the operators in the DA committee. Calculate the cost of withholding data versus the potential profit from a malicious action—this is the cost of corruption. Verify that the slashing penalty is significantly higher than the maximum extractable value (MEV) from a successful attack. Inspect the smart contracts governing these bonds on the DA layer. For example, in an Optimistic Rollup, the challenge period is a key parameter; ensure it is long enough (e.g., 7 days) for watchers to detect and challenge missing data.

• Sub-step 1: Locate the staking contract address for DA operators and query the total bonded value.
• Sub-step 2: Review the protocol's documentation for the exact slashing conditions triggered by proven data unavailability.
• Sub-step 3: Model a scenario where the sequencer withholds a block and calculate the profit from a double-spend versus the slashed bond.

solidityCopy
// Example: Simplified view of a slashing condition in a contract
function slash(bytes32 batchHash, Proof calldata proof) external {
    require(!dataAvailable(batchHash, proof), "Data is available");
    uint256 bond = sequencerBond[msg.sender];
    sequencerBond[msg.sender] = 0;
    payable(msg.sender).transfer(bond); // Slash and reward challenger
}

Tip: A system with a low total bonded value relative to the TVL it secures presents a higher systemic risk.

Detailed Instructions

Manual verification is insufficient for operational security. Implement automated monitoring to detect data availability liveness failures. Create a service that periodically checks the timestamp and hash of the latest data batch posted to the DA layer. If the elapsed time exceeds a predefined threshold (e.g., 2x the average batch interval), trigger an alert. Monitor the gas prices on the DA layer; sustained high fees can cause the sequencer to skip submissions. Set up a watchdog that attempts to reconstruct the latest L2 state from the published DA data; a failure to reconstruct is a critical alert. Integrate these checks with incident management platforms like PagerDuty. Use multi-source data feeds to avoid false positives from a single RPC endpoint failure.

• Sub-step 1: Write a script that queries the L1 bridge contract for the lastBatchTimestamp() and alerts if it's stale.
• Sub-step 2: Deploy a light client for the DA layer in a cloud function to perform continuous data availability sampling.
• Sub-step 3: Set up a dashboard (Grafana) visualizing key metrics: batch submission latency, data size, and DA layer gas costs.

Tip: Your monitoring should be independent of the protocol's own sequencer or node services to avoid blind spots during their failures.