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Ordering Power is Sanctioning Power: Sanction Evasion-MEV and the Limits of On-Chain Enforcement

Di Wu, Yuman Bai, Shoupeng Ren, Xinyu Zhang, Yiyue Cao, Xuechao Wang, Wu Wen, Jian Liu

Abstract

Centralized stablecoins such as USDT and USDC enforce financial sanctions through contract-layer blacklist functions, yet on public blockchains a freeze is merely an ordinary transaction that must compete for execution priority. We identify a fundamental gap between contract-layer authority and consensus-layer enforcement: when a sanctioned entity's transfer and the issuer's freeze race for inclusion in the same block, the outcome is determined not by regulatory mandate but by the economically motivated ordering decisions of block producers. We term the resulting value extraction Sanction-Evasion MEV (SE-MEV). To quantify this vulnerability, we construct the first comprehensive dataset of on-chain sanctions enforcement and evasion for Ethereum-based USDC and USDT (Nov 2017-Aug 2025), covering over $1.5 billion in frozen assets. We find that 7.3% of sanctioned USDT addresses and 18.7% of sanctioned USDC addresses were drained to zero balances before enforcement took effect, and document a clear escalation trajectory-from issuer-side out-of-gas failures, to public gas auctions, to private order flow, to direct proposer bribery. We further develop a game-theoretic model that yields three results: (i) compliant issuers cannot rationally stay outside the MEV market; (ii) fixed participation costs concentrate evasion among specialized, MEV-aware actors; and (iii) the implicit MEV tax extracted by block proposers grows without bound as regulatory penalties intensify, creating structural incentives for issuers to vertically integrate into block-building infrastructure. Our findings demonstrate that on any blockchain where ordering power is allocated by economic incentives, ordering power is sanctioning power-and contract-level authority alone cannot guarantee enforcement.

Ordering Power is Sanctioning Power: Sanction Evasion-MEV and the Limits of On-Chain Enforcement

Abstract

Centralized stablecoins such as USDT and USDC enforce financial sanctions through contract-layer blacklist functions, yet on public blockchains a freeze is merely an ordinary transaction that must compete for execution priority. We identify a fundamental gap between contract-layer authority and consensus-layer enforcement: when a sanctioned entity's transfer and the issuer's freeze race for inclusion in the same block, the outcome is determined not by regulatory mandate but by the economically motivated ordering decisions of block producers. We term the resulting value extraction Sanction-Evasion MEV (SE-MEV). To quantify this vulnerability, we construct the first comprehensive dataset of on-chain sanctions enforcement and evasion for Ethereum-based USDC and USDT (Nov 2017-Aug 2025), covering over $1.5 billion in frozen assets. We find that 7.3% of sanctioned USDT addresses and 18.7% of sanctioned USDC addresses were drained to zero balances before enforcement took effect, and document a clear escalation trajectory-from issuer-side out-of-gas failures, to public gas auctions, to private order flow, to direct proposer bribery. We further develop a game-theoretic model that yields three results: (i) compliant issuers cannot rationally stay outside the MEV market; (ii) fixed participation costs concentrate evasion among specialized, MEV-aware actors; and (iii) the implicit MEV tax extracted by block proposers grows without bound as regulatory penalties intensify, creating structural incentives for issuers to vertically integrate into block-building infrastructure. Our findings demonstrate that on any blockchain where ordering power is allocated by economic incentives, ordering power is sanctioning power-and contract-level authority alone cannot guarantee enforcement.

Paper Structure

This paper contains 39 sections, 6 theorems, 53 equations, 5 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Preliminaries
  3. Blockchain and Smart Contracts
  4. Digital Assets and Tokens
  5. Regulation and Sanctions
  6. The MEV Supply Chain
  7. Threat Model
  8. Scope of Study
  9. System Roles
  10. Observability Boundary
  11. Methodology: Dataset Construction
  12. Phase 0: Raw On-Chain Data Collection
  13. Phase I: Sanction Semantic Filtering
  14. Phase II: Adversarial Actor Filtering
  15. Phase III: Evasion Episode Identification
  16. ...and 24 more sections

Key Result

Proposition 1

Consider a single sanction contest in which both $I$ and $B$ participate and play pure strategies. There exists a unique interior Nash equilibrium with bids success probabilities and intensity ratio $s^*=\frac{b_I^*}{b_B^*}$ given by the unique positive solution to The expected total contest expenditure (MEV revenue) is

Figures (5)

  • Figure 1: Reactive sanction races escalate into ordering competition across public and private regimes.
  • Figure 2: Overview of the dataset-construction pipeline
  • Figure 3: Statistics for Frozen Values
  • Figure 4: Provenance of Sanctioned Addresses
  • Figure 5: Trend of Gas Price Ratio of Sanction and Evasion

Theorems & Definitions (12)

  • Proposition 1: Equilibrium bids in the SE-MEV contest
  • Corollary 1: The MEV tax
  • Corollary 2: Value of ordering control
  • proof : Proof of \ref{['prop:1']}
  • proof : Proof of \ref{['cor:1']}
  • proof : Proof of \ref{['cor:2']}
  • Lemma A.1
  • proof
  • Lemma A.2
  • proof
  • ...and 2 more