We built a cross-chain ERC20 token bridge using LayerZero V2. It moves BRG tokens across Ethereum, Arbitrum, Base, and Optimism — 12 directional pathways, all trustless, with multi-DVN verification. This post walks through the actual code. The full source is at github.com/gnuser/brg-bridge.

Architecture

Lock-and-Mint Model

The bridge uses LayerZero’s OFT (Omnichain Fungible Token) standard:

• Ethereum (home chain): BridgeOFTAdapter locks ERC20 tokens when bridging out, unlocks when bridging back.
• L2 chains: BridgeOFT mints synthetic tokens on receive, burns on send. No pre-minted supply.

Total supply is always conserved: locked on Ethereum = minted across L2s.

LayerZero is the leading omnichain interoperability protocol, connecting 70+ blockchains with 130M+ cross-chain messages delivered. Backed by $263M from a16z and Sequoia at a $3B valuation, it has attracted 35,000+ developers and 50,000+ deployments. We conducted a full market + technical deep dive. Here’s what we found.

V2 Architecture

LayerZero V2 (launched 2024) was a major overhaul. The old Oracle+Relayer model — widely criticized for centralization — was replaced with Decentralized Verifier Networks (DVNs). The core Endpoint contracts are now immutable: no admin keys, no upgrades, no governance attacks.

LayerZero 是领先的全链互操作协议，连接 70+ 条区块链，已传递超过 1.3 亿条跨链消息。获得 a16z 和红杉资本 2.63 亿美元投资，估值 30 亿美元，吸引了 35,000+ 开发者和 50,000+ 部署。我们进行了完整的市场和技术调研，以下是核心发现。

V2 架构

LayerZero V2（2024 年上线）是一次重大升级。被广泛批评为中心化的 Oracle+Relayer 模型被替换为去中心化验证者网络（DVN）。核心 Endpoint 合约现在是不可变的：没有管理员密钥，没有升级，没有治理攻击。

核心创新：每个应用选择自己的安全配置。你可以选择哪些 DVN 来验证消息 — Google Cloud DVN、Polyhedra ZK DVN，或者运行自己的。这与竞品的协议级统一安全模型有本质区别。

竞争格局

协议	链数	安全模型	优势
LayerZero	70+	应用可配置 DVN	灵活性 + 覆盖范围
Wormhole	30+	Guardian 多签 (13/19)	Solana 生态
Chainlink CCIP	~20	Chainlink 预言机网络	机构信任
Axelar	50+	dPoS 验证者	Cosmos 生态
Hyperlane	35+	无许可 ISM	可定制性

LayerZero 的护城河是最大的链覆盖范围、应用可配置安全性和不可变核心协议的组合。一旦协议在 LayerZero 上部署 OFT，切换成本很高。

A comprehensive guide to jq, the command-line JSON processor, covering basic to advanced usage with real-world examples for data extraction, filtering, and transformation.

Learn how Anthropic’s Model Context Protocol (MCP) with code execution reduces token usage by 98.7% and enables more efficient AI agent workflows through progressive tool discovery and native code execution.

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