A formal framework for the economic security of DeFi compositions

· Source: cs.SE updates on arXiv.org · Field: Technology & Digital — Blockchain & Distributed Ledger Technology, Cybersecurity & Data Privacy · Depth: Expert, quick

Summary

Massimo Bartoletti, Riccado Marchesin, and Roberto Zunino introduce a formal framework for the economic security of Decentralized Finance (DeFi) compositions, addressing risks arising from smart contract interactions. This framework defines "MEV non-interference," a security notion ensuring that the maximal extractable value from new contracts is not increased by existing blockchain state interactions. It also introduces "local MEV," a measure focusing on economic losses for specific victim contracts. The research investigates adversarial models with both bounded and unbounded wealth, establishing sufficient conditions and locality principles for modular reasoning about secure composability. The framework is applied to various DeFi compositions, including exchanges, AMMs, options, lending pools, routers, and arbitrage contracts, demonstrating its ability to differentiate between secure and vulnerable setups. This work, published as arXiv:2606.05418 on June 3, 2026, provides foundational tools for analyzing DeFi economic security.

Key takeaway

For DeFi Security Engineers evaluating new smart contract deployments, this framework offers a robust method to assess economic security risks. You should apply MEV non-interference and local MEV measures to predict potential losses from contract interactions. This helps you identify vulnerable compositions before deployment, ensuring your systems maintain economic integrity against various adversarial models. Consider integrating these formal methods into your pre-deployment security audits.

Key insights

A formal framework, MEV non-interference, and local MEV measure economic security risks in DeFi smart contract compositions.

Principles

Method

The framework defines MEV non-interference and local MEV, studies bounded and unbounded adversarial models, and establishes sufficient conditions for secure composability, applied to various DeFi compositions.

In practice

Topics

Best for: AI Security Engineer, Software Engineer, Research Scientist

Related on AIssential

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by cs.SE updates on arXiv.org.