Why Modular Staking Stacks Increase Attack Surfaces

Rollups must trust an external DA layer (e.g., Celestia, EigenDA, Avail) for data. A malicious or faulty DA provider can censor or withhold data, preventing fraud proofs and halting chain progress.

• Trust Assumption: Shifts from a single L1 validator set to a smaller, specialized committee.
• Liveness Risk: If DA fails, the rollup stops finalizing, freezing $10B+ in bridged assets.
• Verification Gap: Light clients struggle to verify data availability without complex fraud proofs.

Sovereign rollups (e.g., Celestia rollups) settle to a DA layer, not Ethereum L1. This removes Ethereum's consensus and social consensus as a backstop, creating a weaker security floor.

• No Inherited Security: Disputes are resolved by the sovereign chain's own validator set, not Ethereum's ~$50B+ staked.
• Fork Coordination Chaos: In a catastrophic bug, there's no canonical L1 to coordinate a social fork.
• Bridge Vulnerability: All bridges to/from the sovereign rollup become high-value attack targets.

Most rollups use a single, centralized sequencer (e.g., Optimism, Arbitrum, Base) for transaction ordering. This creates a central point of failure and value extraction.

• Censorship Vector: A malicious sequencer can front-run, censor, or reorder user transactions.
• Profit Motive: Sequencers capture >90% of rollup MEV, creating misaligned incentives versus users.
• Liveness Dependency: If the sole sequencer goes offline, the network stalls until a manual intervention or slow-mode fraud proof is triggered.

Modular chains rely on cross-chain messaging (e.g., LayerZero, Axelar, Wormhole) and bridges to move assets and state. Each bridge is a separate, complex smart contract vulnerable to logic hacks.

• Trust Minimization Failure: Most 'light client' bridges rely on external oracle/relayer networks, not the underlying chain's consensus.
• Concentrated Loss: A bridge hack can drain assets from the entire modular ecosystem, as seen with the $600M+ Wormhole and $325M Ronin exploits.
• Systemic Contagion: A failure in a widely used messaging layer can cascade across dozens of connected chains.

Projects like EigenLayer and Espresso Systems enable shared sequencers and proof aggregation. This creates new cryptoeconomic and technical dependencies between unrelated rollups.

• Correlated Failure: A bug in the shared prover (e.g., RISC Zero, SP1) invalidates proofs for all dependent chains simultaneously.
• Restaking Slashing Risk: Validators restaking via EigenLayer face slashing across multiple AVSs, potentially losing their entire stake from a fault in one module.
• Complexity Blowup: The security model becomes a function of the weakest link in the shared service provider's stack.

Modular chains often have complex, multi-sig controlled upgrade mechanisms for their core contracts (bridge, sequencer, prover). This creates a persistent admin key risk.

• Multisig as Root of Trust: Many chains rely on a 5-of-9 multisig held by foundation members, a far weaker trust model than Ethereum's decentralized client diversity.
• Governance Capture: Token-holder governance can be manipulated to pass malicious upgrades, especially on chains with low voter turnout.
• Timelock Bypass: Critical emergency upgrades often have short or zero timelocks, enabling rapid, unilateral changes.

Relying on a third-party sequencer (e.g., Espresso, Astria) for transaction ordering creates a single point of failure and censorship. This reintroduces the very centralization risks modularity aims to solve.

• Liveness Risk: Sequencer downtime halts all dependent rollups.
• Censorship Vector: A malicious or compliant sequencer can reorder or exclude transactions.
• MEV Extraction: Centralized sequencing centralizes MEV, undermining credibly neutral block building.

Staking derivatives (e.g., EigenLayer, Babylon) and liquid staking tokens (LSTs) must bridge trust and liquidity between modular components. Each bridge is a new smart contract vulnerability.

• TVL Concentration: A single bridge hack can drain $10B+ in restaked or liquid assets.
• Validation Complexity: Proving state correctness across heterogeneous DA layers (Celestia, EigenDA) is untested at scale.
• Oracle Reliance: Price feeds for LSTs become critical, creating Chainlink-dependent failure modes.

Modular stacks often settle to a base layer (e.g., Ethereum L1, Bitcoin) for finality. A deep re-org on the settlement layer invalidates the entire history of the modular chain, breaking all derived state.

• Finality Assumption Violation: Assumed finality from the settlement layer is probabilistic, not absolute.
• Cross-Chain Domino Effect: A single settlement layer re-org can cascade across dozens of rollups and AVSs.
• Data Availability Gaps: If the DA layer (e.g., a Celestia light client) and settlement layer disagree, the system forks.

Actively Validated Services (AVSs) in stacks like EigenLayer force node operators to run multiple, complex software clients simultaneously. This increases operational risk and the chance of correlated slashing.

• Correlated Failure: A bug in one AVS client can cause mass slashing across unrelated services.
• Operator Centralization: High complexity pushes out smaller operators, consolidating stake with a few large entities.
• Economic Attack: An attacker can force slashing on a cheaper AVS to trigger liquidations on a more valuable one.