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More to Extract: Discovering MEV by Token Contract Analysis

Jiaqi Chen, Yuzhe Tang, Yue Duan

TL;DR

A pipeline of techniques for tMEV discovery is presented, including tSCAN, a static analysis tool for identifying non-standard supply-control functions in token contracts, and tSEARCH, a searcher that uncovers profitable tMEV opportunities by generating, refining, and solving token-specific constraints.

Abstract

This paper tackles the discovery of tMEV, that is, the Maximal Extractable Value on blockchains that arises from Token smart contracts. This scope differs from the existing MEV-discovery research, which analyzes application-layer contracts or attacker contracts, but ignores the wide and diverse range of token contracts. This paper presents a pipeline of techniques for tMEV discovery, including tSCAN, a static analysis tool for identifying non-standard supply-control functions in token contracts, and tSEARCH, a searcher that uncovers profitable tMEV opportunities by generating, refining, and solving token-specific constraints. By replaying real-world transactions, this paper demonstrates both the profitability of tMEV strategies and existing searchers' unawareness of them: the proposed tSEARCH extracts $10\times$ more profit than observed MEV activity on Ethereum. The practicality of tMEV searching is demonstrated through a prototype built on Slither, showing high effectiveness with low performance overhead.

More to Extract: Discovering MEV by Token Contract Analysis

TL;DR

A pipeline of techniques for tMEV discovery is presented, including tSCAN, a static analysis tool for identifying non-standard supply-control functions in token contracts, and tSEARCH, a searcher that uncovers profitable tMEV opportunities by generating, refining, and solving token-specific constraints.

Abstract

This paper tackles the discovery of tMEV, that is, the Maximal Extractable Value on blockchains that arises from Token smart contracts. This scope differs from the existing MEV-discovery research, which analyzes application-layer contracts or attacker contracts, but ignores the wide and diverse range of token contracts. This paper presents a pipeline of techniques for tMEV discovery, including tSCAN, a static analysis tool for identifying non-standard supply-control functions in token contracts, and tSEARCH, a searcher that uncovers profitable tMEV opportunities by generating, refining, and solving token-specific constraints. By replaying real-world transactions, this paper demonstrates both the profitability of tMEV strategies and existing searchers' unawareness of them: the proposed tSEARCH extracts more profit than observed MEV activity on Ethereum. The practicality of tMEV searching is demonstrated through a prototype built on Slither, showing high effectiveness with low performance overhead.
Paper Structure (16 sections, 5 equations, 4 figures, 3 tables, 2 algorithms)

This paper contains 16 sections, 5 equations, 4 figures, 3 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Background
  3. Threat Model
  4. Motivating Observations
  5. Code Example
  6. tMEV from Code Example
  7. (In)feasibility of Existing Approaches
  8. Definitions
  9. Token Supply Control (TSC) Functions
  10. Price-Insensitive Exchanges (PITEX)
  11. Defining tMEV Templates
  12. The MEV-Search System
  13. Detecting TSC with tSCAN
  14. Identifying PITEX
  15. Constraint-centric MEV Search ( tSEARCH)
  16. ...and 1 more sections

Figures (4)

  • Figure 1: Defining price-insensitive exchange (PITEX).
  • Figure 2: tMEV templates and baselines
  • Figure 3: System workflow in offline and online phases.
  • Figure 4: Static token-contract analysis.