Restaking boom: EigenLayer & Jito
Restaking via EigenLayer (Ethereum) and Jito (Solana) is accelerating as a multi‑layer yield strategy, letting staked ETH and SOL be used to secure middleware, DA services, and off‑chain infrastructure. Traders can boost nominal yields but face slashing and technical risk — the trend is increasing demand for real‑time, ML‑powered slashing/risk monitors. (chainup.com)
EigenLayer’s on‑chain footprint tops major trackers — DeFiLlama reports EigenLayer at $18.57 billion TVL while Jito’s Solana stake pool shows roughly $2.9 billion locked, underscoring cross‑chain scale for restaking markets. (defillama.com) EigenLayer’s protocol‑level slashing went live on April 17, 2025, turning theoretical penalties into enforceable economic risk for AVSs and operators. (blog.eigenlayer.xyz) Small but material slashing events have already hit operators: analysis and on‑chain trackers flagged a February 2026 oracle feed failure that resulted in ~127 ETH being slashed across three operators, illustrating correlated exposure in multi‑AVS stacks. (dev.to) Open monitoring projects and grant‑backed dashboards are proliferating — Restake Watch publishes rolling operator risk metrics and lists Ethereum Foundation ESP support for its monitoring work. (restake.watch) Infrastructure and risk vendors are productizing protection: Blockdaemon announced an industry‑first staking/slashing insurance offering and is pitching institutional node services to cover restaking counterparty risk. (blockdaemon.com) Market‑facing risk firms and strategic backers are active — Gauntlet (risk models/optimization) is expanding institutional deployments and was central to a recent $380M exit narrative, while Jito secured a $50M strategic investment from a16z in October 2025 to accelerate MEV‑powered staking and its (re)staking product rollout. (gauntlet.xyz) Real‑time data providers and observability stacks are being cited as core inputs for automated slashing detection: Amberdata advertises enterprise-grade state changes and chain analytics for risk teams, and mempool/mempool‑level tooling vendors like Blocknative are positioned to feed low‑latency signals into ML‑based slashing monitors. (blog.amberdata.io)
