Defimon: Real-Time DeFi Security with Streams

Defimon 如何將區塊偵測延遲縮短至原來的四分之一、將鏈數從 3 條擴展至 8 條，並將基礎設施管理從團隊協作轉變為僅需一名工程師即可完成。

4x fasterBlock-to-detection latency, from 2s to under 0.5s
8 chainsMonitored in real-time, up from 3
$48K/year savedInfrastructure costs eliminated entirely

In DeFi, the window between an exploit landing onchain and a protocol team being alerted can be critical. Defimon exists to close that window with instant security alerts and automated incident response. Built by the security team at Decurity which is trusted by 1inch, Gearbox, and the Arbitrum Foundation, it monitors EVM chains 24/7 and fires Telegram alerts to the protocol teams, security companies and risk curators before hacks make the news. That speed is the product. So when the infrastructure keeping it alive started getting in the way, something had to change.

挑戰

Legacy streaming data pipelines are hard to adapt to the onchain monitoring

Defimon tracks millions of wallet addresses and contract interactions in real-time. Their original setup, Apache Flink SQL pipelines running on AWS, held this watchlist in memory. As coverage expanded, out-of-memory errors became a trigger to look for the alternatives. The system couldn't scale with the scope of what needed monitoring.

$4,000 a month for 3 chains, with a team of 4 to keep it running

Infrastructure cost approximately $4,000 per month on AWS to cover just three networks and required three to four engineers: pulling RPC data manually, managing SQL schemas, debugging pipeline failures. The team's expertise was in detection logic. They were spending it on infrastructure plumbing.

Block latency that degraded alert quality

Manual RPC polling produced around two seconds of latency per block. For a product where detection timing determines whether a protocol team gets warned in time, that was a structural problem.

解決方案

Defimon replaced their self-managed pipeline with Quicknode Streams. The migration was near-instant. Existing detection logic carried over, and the team was up and running without having to rebuild from scratch.

The memory problem, solved at the source

Streams' upstream filtering and native integrations with Key-Value Store lists lets Defimon define exactly which data reaches their system, by address, contract, or event type, before it ever touches their pipeline. The watchlist no longer lives in RAM as a growing, crashing list. Adding or removing monitored addresses became a configuration change, not an engineering task.

One pipeline. Eight chains.

Ethereum, BNB Smart Chain, Arbitrum, Base, Polygon, Avalanche, Optimism, and HyperEVM all run through a single Streams integration. Adding a new chain no longer means new infrastructure. It means updating a config. The team went from three chains managed across a fragmented AWS setup to eight chains managed by one person.

「Quicknode Streams 區塊鏈節點層級運行的靈活 JS 篩選器Streams 讓我們能夠在不造成系統停機的情況下強化並部署業務邏輯，並能即時偵測到漏洞攻擊。」
— Arseniy Reutov, CTO & Co-founderDecurity

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結果

4x faster detection

Block latency dropped from around two seconds to under 0.5 seconds per block. Telegram alerts fire in under one second from detection.

Every protocol. Every chain. Every block.

Defimon doesn't monitor a subset of protocols. Every protocol is monitored, every exploit detected across the chains that matter most to DeFi. No gaps, no exceptions.

One engineer. Eight chains. Zero ops burden.

Infrastructure that required three to four people to maintain now runs with one, focused entirely on detection logic rather than pipeline management.

The engineering time that used to go toward keeping infrastructure alive now goes where it always should have: improving detection and staying ahead of what's coming next.

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Defimon: Real-Time DeFi Security with Streams

挑戰

解決方案

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結果