Security Economics: The Real Cost of Shared Security

Security Economics is the hidden layer beneath every shared security narrative in crypto. While the idea of “borrowing security” promises cheaper, safer, and faster scaling, it quietly reshapes how costs, risks, and incentives are distributed across networks. Shared security doesn’t eliminate the price of safety. It reallocates it, often in ways that are easy to overlook. To understand whether shared security strengthens the ecosystem or simply concentrates new systemic risks, we need to look beyond architecture and into the economic mechanisms that govern who pays, who benefits, and who ultimately bears the downside when things break.

What is shared security (economically)?

Shared security represents a fundamental shift in how blockchain networks allocate cryptoeconomic protection. Economically, it refers to security that a protocol derives from an external source, where resources pooled by participants in one protocol, such as capital or computational power, are used to create economic security for another protocol. Rather than each network independently bootstrapping validator sets and token value, shared security enables protocols to leverage existing economic stakes from established chains like Ethereum.

This creates a marketplace where restakers provide capital in search of yield, while protocols and services purchase security backed by staked capital. The economic model transforms security from a fixed cost into a tradeable commodity, allowing smaller blockchains to borrow security resources from larger, more established ones, fundamentally changing the capital efficiency calculus of network launch and maintenance.

Why isn’t shared security automatically cheaper or safer?

Shared security models can suffer from stake fragmentation, greater operator workload, lower attack costs, and larger attack surfaces. While pooling security appears economical, restaking introduces compounded slashing risk, where an error or attack related to one secured service can lead to slashing of capital securing multiple services. Each restaking layer also introduces new smart contracts, increasing the attack surface for exploits.

Higher concentrations of users’ funds locked in individual staking protocols create vulnerable single points of failure and centralization issues that could threaten the broader crypto ecosystem if hacked or corrupted. Moreover, users face challenges assessing risks across different protocols, services, and operators, while operators shoulder the burden of managing diverse software stacks and heterogeneous slashing rules. The complexity of coordinating incentives across multiple chains creates hidden operational costs that can exceed traditional security bootstrapping expenses.

How are costs, rewards, and risks distributed across chains?

Asymmetric distribution model

In shared security systems, cost and risk distribution often follows asymmetric patterns that favor base layer participants over dependent chains. Restakers receive base ETH staking rewards plus additional AVS fees, minus operator and protocol fees, along with time limited incentives, while bearing compounded slashing risks and withdrawal queue costs. AVSs can distribute rewards to specific operator sets based on task complexity, while operators can set custom fees at the operator level, creating a multi-tiered payment structure.

Pooled security with disproportionate exposure

Redistributable operator sets may offer higher rewards, but stakers must weigh these against increased slashing risks, where malicious AVSs or compromised operators could potentially drain delegated funds. This creates pooled security where the same restaked ETH can secure multiple AVSs simultaneously, but operators differ in which AVSs they validate and how risky each service is. The economic burden falls disproportionately on capital providers who bear slashing exposure, while consumer chains benefit from security without proportional risk assumption.

Why is incentive misalignment the main failure mode?

Incentive misalignment emerges as the primary failure mode because incentives determine behavior at scale. Well crafted incentives foster decentralization by spreading network participation, but when incentives are misaligned, they create systemic vulnerabilities. In decentralized systems, misaligned incentives often lead to cost cutting behaviors that compromise integrity. The free rider problem becomes acute in shared security environments where participants can benefit from security provided by others without proportionally contributing, producing rational but collectively harmful outcomes.

In shared data availability layers, an attacker can target the most vulnerable rollup, knowing that the resulting congestion impacts others as collateral damage, exploiting weak fee defenses as a Trojan horse to spam cheaply. When rewards do not align with risks across multiple chains, validators optimize for short term gains over network health, while consumer chains extract security value without bearing proportional costs. This coordination failure can undermine the entire shared security model.

How does slashing spread (or shift) risk between networks?

Slashing creates systemic contagion channels across interconnected networks through what researchers call cascading slashing effects. One misstep on Network A might trigger slashing penalties or losses on all networks where that same stake is active, creating a chain reaction of penalties spreading across platforms. If the same stake is restaked across several AVSs by the same validator, the cumulative gain from malicious behavior may exceed the loss from slashing, creating network level vulnerabilities.

A mistake in one AVS environment could ripple across others, increasing risk exposure, while critics warn that if restaked assets are repeatedly routed through lending loops or derivative stacks, any breach can cascade across protocols, causing rapid and correlated losses. This consolidated security model means a validator can lose rewards from Ethereum consensus and potentially all of their staked ETH if they breach any rules of any supported AVS, effectively externalizing risks from individual protocols to the shared security ecosystem and its capital providers.

What changes when security becomes a market with pricing?

When security becomes a market with dynamic pricing, protocols like EigenLayer enable a marketplace where restakers provide capital in search of yield, while AVSs purchase security, with operators selecting which services to validate based on yield relative to underlying risk. This results in an open and competitive marketplace for pooled security, easing bootstrapping because new protocols can purchase security on the open market rather than building and maintaining their own validator sets.

Security abstraction emerges where economic trust becomes a composable asset. By 2025, the restaking market surpassed $25 billion in TVL, and a single validator can contribute to multiple networks simultaneously, creating a more efficient allocation of security resources. This shift moves from isolated security models to a networked approach where economic security becomes more fluid and adaptable across ecosystems. However, pricing can also introduce concentration risks, where dominant protocols become single points of failure if their governance or security models are compromised.

Conclusion

Shared security isn’t “cheaper security,” it’s redistributed security. It can improve capital efficiency, but it also introduces new risks through slashing contagion, complexity, and incentive misalignment. In the end, resilience depends less on architecture and more on whether rewards, accountability, and downside are aligned across every network sharing the same stake.