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the-modular-blockchain-thesis-explained
Blog

Why Restaking Models Are a Double-Edged Sword for Security

Restaking, popularized by EigenLayer, offers a quick path to bootstrap security for new chains and services. This analysis argues it creates a fragile, correlated risk layer that threatens the entire modular ecosystem during a slashing event.

introduction
THE SECURITY TRADE-OFF

Introduction

Restaking amplifies capital efficiency but creates systemic risk by concentrating security assumptions across multiple protocols.

Capital efficiency is a trap. Restaking protocols like EigenLayer allow ETH stakers to rehypothecate their stake to secure other networks, creating a shared security marketplace. This recycles capital but makes the security of disparate systems interdependent.

Security is not additive. The combined security of a restaked validator is not the sum of its parts. A single slashing event on an actively validated service (AVS) like a data availability layer or oracle network can cascade to the underlying Ethereum stake, creating a systemic contagion vector.

The yield incentive misaligns risk. Validators are economically motivated to opt into high-yield AVSs, creating a race to the bottom on security diligence. This mirrors the flawed incentive structures seen in pre-collapse Terra/Luna and cross-chain bridge hacks like Nomad.

Evidence: The $15B+ TVL rapidly deposited into EigenLayer demonstrates market demand but also quantifies the potential single point of failure. This concentration rivals the total value secured by many Layer 1s, creating a too-big-to-fail dynamic within DeFi.

thesis-statement
THE DOUBLE-EDGED SWORD

The Core Contradiction

Restaking concentrates security but creates systemic risk by linking the failure of one protocol to the solvency of many.

Security is a Monoculture. Restaking recycles a single capital base, like Ethereum's ETH, to secure dozens of new protocols. This creates a shared security layer but also a single point of failure. A catastrophic bug in a major AVS like EigenLayer or a liquid restaking token (LRT) like Ether.fi's eETH can cascade through the entire ecosystem.

Slashing is a Blunt Instrument. The economic penalty for validator misbehavior is a non-targeted financial nuke. A slashing event triggered by a buggy oracle AVS like Chainlink or a faulty data availability layer doesn't just punish that service—it directly reduces the capital securing every other AVS using that staked ETH, creating cross-protocol contagion.

The Yield Trap. The economic pressure to maximize yield drives restakers to delegate to the highest-paying AVSs, regardless of risk. This creates a race to the bottom on security diligence, mirroring the pre-2008 financial system's hunt for yield on complex, opaque products. Protocols compete on subsidy, not safety.

Evidence: The Total Value Locked (TVL) in restaking protocols like EigenLayer exceeds $15B. This capital is now a systemic liability; a 10% slashing event would vaporize over $1.5B in cross-protocol security simultaneously, a risk not present in isolated proof-of-stake chains.

RESTAKING MODELS

The Concentration Risk Matrix

Comparing the security and systemic risk profiles of major restaking protocols, highlighting the trade-offs between capital efficiency and centralization.

Risk Vector / MetricEigenLayer (Native)EigenLayer (LST)Babylon (Bitcoin)Karak (Multi-Asset)

Primary Staked Asset

Native ETH

Liquid Staking Tokens (e.g., stETH)

Native Bitcoin

ETH, stETH, USDC, WBTC

TVL Concentration in Top 3 AVSs

65%

65%

N/A (Early)

70%

Slashing Risk Correlation

High (Shared Security Pool)

High (Shared Security Pool)

Isolated per AVS

High (Shared Security Pool)

LST Depeg Contagion Pathway

Indirect

Direct

None

Direct (for LSTs)

Validator Client Diversity

~85% Geth

~85% Geth

Native Bitcoin Miners/Nodes

Relies on Underlying Chain

Time to Withdraw / Unbond

7+ days

7+ days + LST Unstaking

~21 days (Bitcoin Timelock)

Varies by asset (7+ days for ETH)

Proven Slashing Events

0

0

0

0

Active AVSs / Modules

100

100

<10

<20

deep-dive
THE CASCADE

The Mechanics of a Systemic Slashing Cascade

Restaking's security is a recursive promise that fails simultaneously across multiple protocols.

Slashing is non-linear and contagious. A single validator fault in EigenLayer triggers a penalty. That same stake is simultaneously securing dozens of Actively Validated Services (AVSs) like AltLayer and EigenDA. The slashing event propagates instantly, draining collateral from every AVS secured by that node.

The cascade amplifies through shared infrastructure. AVSs compete for security by attracting restakers, creating dense, overlapping dependencies. A failure in a widely used oracle or bridge AVS like Hyperlane doesn't just fail one service—it correlates slashing risk across the entire restaking ecosystem, creating systemic, not isolated, risk.

Liquid restaking tokens (LRTs) are transmission vectors. Protocols like Kelp DAO and Renzo mint derivative tokens representing restaked positions. These LRTs are then deposited into DeFi pools on Aave or Curve. A slashing event depegs the LRT, triggering liquidation cascades in lending markets, exporting systemic risk from consensus layers into DeFi.

Evidence: The 2022 stETH depeg demonstrated how derivative token devaluation can freeze a DeFi ecosystem. In a slashing cascade, the underlying asset (ETH) is forcibly removed, making the crisis more severe and irreversible.

risk-analysis
SYSTEMIC RISKS

The Bear Case: What Could Go Wrong?

Restaking concentrates systemic risk by recycling the same capital to secure multiple layers, creating fragile interdependencies.

01

The Cascading Slash

A single fault in a major AVS like EigenLayer or EigenDA can trigger slashing that propagates across the entire restaking ecosystem. This creates a contagion risk where a failure in one service jeopardizes the security of dozens of others.

  • Correlated Failure: A bug in a widely used AVS slashes the same stake securing other networks.
  • Liquidation Spiral: Slashed LRTs (e.g., ether.fi, Renzo) could trigger mass liquidations in DeFi, collapsing collateral loops.
$10B+
TVL at Risk
>100
AVS Interdependencies
02

The Yield Cartel

Restaking creates a powerful, centralized cartel of node operators (like Figment, Chorus One) who control the validation of hundreds of AVSs. This centralizes veto power and creates a single point of governance capture.

  • Oligopoly Control: A handful of operators can dictate terms or censor transactions across the AVS stack.
  • Yield Extraction: Operators can demand higher fees from AVSs, stifling innovation and passing costs to end-users.
~60%
Top 10 Operator Share
0
AVS Opt-Out
03

The Liquidity Illusion

Liquid Restaking Tokens (LRTs) like eETH and ezETH create a dangerous perception of liquidity. In a crisis, the underlying staked ETH is illiquid and subject to unbonding delays, while the LRT's peg could collapse.

  • Peg Fragility: A major AVS slash could break the LRT/ETH peg, similar to the UST depeg.
  • DeFi Contagion: Billions in LRTs used as collateral (on Aave, Compound) could be instantly devalued, causing systemic liquidations.
$5B+
LRT DeFi Collateral
7+ Days
ETH Unbonding Delay
04

The Complexity Attack

The security model of an AVS is only as strong as its weakest dependency. Operators must now manage dozens of complex, untested codebases, exponentially increasing the attack surface for exploits.

  • Operator Overload: Human operators cannot adequately audit or monitor the security of 50+ AVS clients.
  • Weakest Link: A minor, obscure AVS with a bug can become the entry point for draining the shared security pool.
50+
AVS Codebases
1
Required Exploit
05

The Regulatory Kill-Switch

By concentrating validation power, restaking creates a clear target for regulators. A single legal action against a dominant operator or the EigenLayer foundation could freeze or dismantle the security for the entire ecosystem.

  • Jurisdictional Risk: Operators in compliant jurisdictions could be forced to censor transactions.
  • Foundation Risk: EigenDAO governance could be coerced, turning the protocol into a regulatory tool.
1
Legal Action
Global
Impact Radius
06

The Economic Abstraction Trap

Restaking abstracts security into a commodity, divorcing it from the underlying chain's social consensus. This creates a market where security is bought by the highest bidder, not aligned with Ethereum's long-term health.

  • Security Mercenaries: Validators prioritize AVS yield over Ethereum's liveness, creating misaligned incentives.
  • Race to the Bottom: AVSs compete on cost, pressuring operators to cut corners on infrastructure and monitoring.
>5%
Yield Premium
0
Chain Loyalty
counter-argument
THE GOVERNANCE FALLACY

The Rebuttal: "But the Security Council and Slashing Conditions..."

Proposed governance and slashing mechanisms fail to mitigate the systemic risk of restaking.

Security Councils are centralized bottlenecks. They create a single point of failure for the entire restaking ecosystem. This contradicts the decentralized security premise of EigenLayer and similar protocols.

Slashing conditions are unenforceable across chains. A validator slashed on a consumer chain like EigenDA cannot be penalized on Ethereum without a complex, centralized oracle. This breaks the security model.

The risk is recursive and systemic. A major slashing event on a high-value AVS could cascade, triggering liquidations across DeFi protocols like Aave or Compound that accept restaked assets as collateral.

Evidence: The Ethereum community rejected in-protocol slashing for L2 bridges. This precedent highlights the immense complexity and risk of cross-domain enforcement that restaking reintroduces.

takeaways
RESTAKING RISKS

TL;DR for Protocol Architects

Restaking models like EigenLayer promise pooled security but introduce systemic fragility that architects must design around.

01

The Slashing Avalanche Problem

Correlated slashing events can cascade across the EigenLayer ecosystem, liquidating the same capital backing multiple AVSs (Actively Validated Services). This creates a systemic risk multiplier, not a diversification benefit.\n- Key Risk: A single bug in a major AVS could trigger mass, correlated slashing.\n- Architect's Task: Design slashing conditions that are non-correlated and asynchronous to other services.

>60%
TVL at Risk
Cascading
Failure Mode
02

The Yield-Optimizer Attack Surface

Restaked ETH is not held by sophisticated node operators but by liquid restaking tokens (LRTs) like ether.fi and Renzo. These LRTs become massive, centralized points of failure. Their governance and withdrawal logic is now a critical security dependency for every AVS.\n- Key Risk: LRT governance exploit or bug compromises security of all integrated AVSs.\n- Architect's Task: Audit and diversify LRT dependencies; demand non-custodial or trust-minimized staking pools.

$20B+
LRT TVL
~5 Major
LRT Providers
03

Security is a Commodity, Not a Feature

Restaking turns cryptoeconomic security into a cheap, rentable resource. This leads to a race-to-the-bottom on slashing costs as AVSs compete for the same capital. The result is marginally secured networks where the cost to attack is a fraction of the value secured.\n- Key Risk: Security budget becomes detached from the economic value of the service being secured.\n- Architect's Task: Build native economic security or hybrid models; treat restaked security as a temporary bootstrap, not a foundation.

<1%
Slashing Yield
Commoditized
Security
04

The Liquidity vs. Finality Trade-off

To attract capital, LRTs promise liquidity via their own tokens. This creates a withdrawal queue risk similar to traditional finance bank runs. During stress, AVS operators may be unable to exit positions to meet slashing obligations, breaking the security model.\n- Key Risk: Liquidity illusion undermines the credible threat of slashing.\n- Architect's Task: Model security under withdrawal queue congestion; prefer AVS designs with slow-slashing mechanisms that are resilient to liquidity crunches.

7-30 Days
Queue Risk
Illiquid
Collateral
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Restaking Security: The Fragile Foundation of Modular Blockchains | ChainScore Blog