Feng Luo (The Hong Kong Polytechnic University), Zihao Li (The Hong Kong Polytechnic University), Wenxuan Luo (University of Electronic Science and Technology of China), Zheyuan He (University of Electronic Science and Technology of China), Xiapu Luo (The Hong Kong Polytechnic University), Zuchao Ma (The Hong Kong Polytechnic University), Shuwei Song (University of Electronic Science and Technology of China), Ting Chen (University of Electronic Science and Technology of China)
Due to the transparency of permissionless blockchain, opportunistic traders can extract Maximal Extractable Value by competing for profit opportunities and making the process never stop by creating MEV bots. However, this behavior undermines the consensus security and efficiency of the blockchain system. Therefore, understanding the behavior strategies of MEV bots is crucial to protect against their harm. Unfortunately, existing work focuses on macro-measurements of the MEV market, and the specific types and distributions of MEV bot strategies remain unknown. In this paper, we conduct the first systematic study of MEV bot profitability strategies by developing APOLLO, a tool to analyze fine-grained strategies throughout the entire lifecycle of bots. Our large-scale analysis of 2,052 MEV bots yields many new insights. In particular, we first introduce 20 code-level strategies employed by bots in the wild, take the first step towards smart contract de-obfuscation to discover strategies hidden in obfuscated bot code, and discover five specific types of transactions that bring profit opportunities to MEV bots.