Quantifying Blockchain Extractable Value: How dark is the forest?
Authors: Kaihua Qin, Liyi Zhou, Arthur Gervais
Permissionless blockchains such as Bitcoin have excelled at financial services. Yet, adversaries extract monetary value from the mesh of decentralized finance (DeFi) smart contracts. Some have characterized the Ethereum peer-to-peer network as a dark forest, wherein broadcast transactions represent prey, which are devoured by generalized trading bots. While transaction (re)ordering and front-running are known to cause losses to users, we quantify how much value was sourced from blockchain extractable value (BEV). We systematize a transaction ordering taxonomy to quantify the USD extracted from sandwich attacks, liquidations, and decentralized exchange arbitrage. We estimate that over 2 years, those trading activities yielded 28.80M USD in profit, divided among 5, 084 unique addresses. While arbitrage and liquidations might appear benign, traders can front-run others, causing financial losses to competitors. To provide an example of a generalized trading bot, we show a simple yet effective automated transaction replay algorithm capable of replacing unconfirmed transactions without understanding the victim transactions’ underlying logic. We estimate that our transaction replay algorithm could have yielded a profit of 51, 688.33 ETH (17.60M USD) over 2 years on past blockchain data. We also find that miners do not broadcast 1.64% of their mined transactions and instead choose to mine them privately. Privately mined transactions cannot be front-run by other traders or miners. We show that the largest Ethereum mining pool performs arbitrage and seemingly tries to cloak its private transaction mining activities. We therefore provide evidence that miners already extract Miner Extractable Value (MEV), which could destabilize the blockchain consensus security, as related work has shown.