Why Is My Transaction Risky? Understanding Smart Contract Semantics and Interactions in the NFT Ecosystem

TL;DR

This study analyzes nearly 100 million Ethereum transactions to understand smart contract semantics and interactions in the NFT ecosystem, revealing patterns linked to transaction risks and scam tokens.

Contribution

It provides the first large-scale empirical analysis of smart contract semantics and interactions in NFTs, highlighting risk factors and common patterns associated with scams.

Findings

Limited semantic diversity among contracts, dominated by proxy, token, and DeFi types.

Scam tokens show bytecode convergence, unlike legitimate tokens.

Certain interaction patterns are linked to risky transactions.

Abstract

The NFT ecosystem represents an interconnected, decentralized environment that encompasses the creation, distribution, and trading of Non-Fungible Tokens (NFTs), where key actors, such as marketplaces, sellers, and buyers, utilize smart contracts to facilitate secure, transparent, and trustless transactions. Scam tokens are deliberately created to mislead users and facilitate financial exploitation, posing significant risks in the NFT ecosystem. Prior work has explored the NFT ecosystem from various perspectives, including security challenges, actor behaviors, and risks from scams and wash trading, leaving a gap in understanding the semantics and interactions of smart contracts during transactions, and how the risks associated with scam tokens manifest in relation to the semantics and interactions of contracts. To bridge this gap, we conducted a large-scale empirical study on smart contract semantics and interactions in the NFT ecosystem, using a curated dataset of nearly 100 million transactions across 20 million blocks on Ethereum. We observe a limited semantic diversity among smart contracts in the NFT ecosystem, dominated by proxy, token, and DeFi contracts. Marketplace and proxy registry contracts are the most frequently involved in smart contract interactions during transactions, engaging with a broad spectrum of contracts in the ecosystem. Token contracts exhibit bytecode-level diversity, whereas scam tokens exhibit bytecode convergence. Certain interaction patterns between smart contracts are common to both risky and non-risky transactions, while others are predominantly associated with risky transactions. Based on our findings, we provide recommendations to mitigate risks in the blockchain ecosystem, and outline future research directions.