Flash Boys 2.0: Frontrunning, Transaction Reordering, and Consensus Instability in Decentralized Exchanges
Philip Daian, Steven Goldfeder, Tyler Kell, Yunqi Li, Xueyuan Zhao,, Iddo Bentov, Lorenz Breidenbach, Ari Juels

TL;DR
This paper investigates how arbitrage bots exploit decentralized exchanges through frontrunning and transaction reordering, revealing systemic security risks and proposing a game-theoretic model of priority bidding.
Contribution
It provides the first comprehensive analysis of frontrunning and transaction reordering in DEXes, formalizes a game-theoretic model of priority gas auctions, and empirically demonstrates security risks posed by MEV.
Findings
Arbitrage bots significantly profit from frontrunning in DEXes.
High transaction fees for priority ordering threaten blockchain security.
MEV poses a systemic risk to Ethereum's consensus integrity.
Abstract
Blockchains, and specifically smart contracts, have promised to create fair and transparent trading ecosystems. Unfortunately, we show that this promise has not been met. We document and quantify the widespread and rising deployment of arbitrage bots in blockchain systems, specifically in decentralized exchanges (or "DEXes"). Like high-frequency traders on Wall Street, these bots exploit inefficiencies in DEXes, paying high transaction fees and optimizing network latency to frontrun, i.e., anticipate and exploit, ordinary users' DEX trades. We study the breadth of DEX arbitrage bots in a subset of transactions that yield quantifiable revenue to these bots. We also study bots' profit-making strategies, with a focus on blockchain-specific elements. We observe bots engage in what we call priority gas auctions (PGAs), competitively bidding up transaction fees in order to obtain priority…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Auction Theory and Applications · Complex Systems and Time Series Analysis
