Why AVS Interdependence Creates a House of Cards

Every AVS inherits the liveness and censorship-resistance of its chosen DA layer. A failure here halts state progression for all dependent AVS.

• EigenDA and Celestia concentrate risk for dozens of AVSs.
• ~12s finality on Ethereum means all AVS finality is bounded by this floor.
• A DA outage creates a cascade of stalled chains, not a single failure.

Delegating transaction ordering to a shared sequencer like Espresso or Astria trades decentralization for efficiency, creating a new centralization vector.

• A malicious or faulty sequencer can censor, reorder, or front-run transactions across all connected rollups.
• This creates meta-MEV opportunities at the sequencing layer, extracting value from multiple chains simultaneously.
• The system is only as live as its sequencer.

EigenLayer-style re-staking creates hidden leverage. The same ETH is securing the consensus layer, multiple AVSs, and potentially liquid staking tokens (LSTs) like stETH.

• A correlated slash event could trigger mass unbonding, draining liquidity from the base layer and all AVSs simultaneously.
• This is a systemic liquidity risk akin to rehypothecation in traditional finance.
• Security is diluted as stake is multiplied across an unbounded number of AVSs.

AVSs are designed to be composed, like a Hyperlane interchain security module depending on an EigenDA-based oracle. Failure propagates through the dependency graph.

• Creates unmodeled risk feedback loops where the failure probability of the whole system is greater than the sum of its parts.
• Oracle downtime can freeze DeFi protocols across multiple chains that share the same AVS.
• There is no circuit breaker for cross-AVS failure modes.

AVS upgrades often require coordinated action from their underlying layers (e.g., a new EigenLayer slashing condition). This creates governance paralysis.

• A hard fork on the DA or consensus layer can strand AVSs that fail to upgrade in time.
• Creates versioning hell and fragmentation, as seen in early Cosmos and Polkadot ecosystem upgrades.
• Security patches cannot be deployed unilaterally by the AVS operator.

Advertised $10B+ in re-staked secure value is misleading. It's not capital dedicated to a single AVS; it's shared, diluted, and subject to whale withdrawal risk.

• The marginal cost to attack a specific AVS is far lower than the total staked value.
• Slashing is a weak deterrent when the same stake is securing 50 other services—the penalty is amortized.
• Real security is determined by the least committed validator subset, not the total TVL.

Banks bundled risky mortgages into complex, interdependent derivatives (CDOs) that were rated AAA. When the underlying mortgages failed, the entire synthetic structure collapsed because risk was correlated, not diversified. This is the canonical example of hidden systemic risk in a networked system.

• Key Flaw: Misunderstood correlation between underlying assets.
• AVS Parallel: Interdependent slashing conditions and shared operators create similar hidden, correlated failure modes.

UST's stability depended entirely on LUNA's market cap via a mint/burn arbitrage loop. This created a reflexive, circular dependency. When confidence broke, the negative feedback loop destroyed both assets, wiping out ~$40B in value in days.

• Key Flaw: No exogenous collateral or circuit breakers.
• AVS Parallel: AVS revenue tokens securing other AVS services create similar reflexive dependencies, where a failure in one crashes the economic security of another.

Ethereian validators outsourced block building to a handful of dominant MEV-Boost relays (e.g., BloXroute, Flashbots). This created a single point of failure where relay censorship or downtime could halt a significant portion of chain activity. The ecosystem's efficiency became its fragility.

• Key Flaw: Concentrated critical infrastructure with minimal redundancy.
• AVS Parallel: A few top-tier operators (e.g., Figment, Chorus One) securing dozens of AVSs replicate this centralization risk, where their failure slashes multiple services simultaneously.

Bridges like Wormhole ($325M hack) and Ronin Bridge ($625M hack) became fat targets because they aggregated massive liquidity into a single, complex smart contract system. Their security was only as strong as their weakest component (often a multi-sig).

• Key Flaw: High-value, centralized choke points in a decentralized narrative.
• AVS Parallel: AVS networks that act as "meta-bridges" or shared sequencing layers concentrate even more value and functionality, creating a higher-value target with more potential attack vectors.