NDSS2026
Light into Darkness: Demystifying Profit Strategies Throughout the MEV Bot Lifecycle
Feng Luo, Zihao Li, Wenxuan Luo, Zheyuan He, Xiapu Luo, Zuchao Ma, Shuwei Song, Ting Chen
1 citation
Abstract
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.