Understanding NFTs from EIP Standards

2025-08-10

AI Summary

Existing research lacks a systematic understanding of NFT technology foundations—particularly regarding standard evolution, cross-standard compatibility, and security implications. Method: This paper presents the first comprehensive, EIP-centric analysis of Ethereum NFT architecture, grounded in 191 NFT-related EIPs and over 10,000 community discussions. It integrates automated Solidity interface parsing, graph-based inheritance modeling, contributor profiling, and community semantic mining for multi-dimensional empirical analysis. Contribution/Results: We uncover weak interoperability across mainstream standard versions and demonstrate that functional layering significantly exacerbates smart contract security risks. We propose a standardized inheritance taxonomy and evolutionary pathway, identifying critical emerging standards beyond ERC-721/1155 and their governance bottlenecks. Our work establishes the first empirically grounded, EIP-ecosystem-based framework for NFT protocol design, standardization advancement, and security governance.

Technology Category

• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Machine Learning: Deep Neural Architectures and Foundation Models
• Game Theory and Economic Paradigms: Mechanism Design

Application Category

• Security and Privacy: Data transparency and provenance
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Audits of web technologies, standards, platforms, and applications

Abstract

We argue that the technical foundations of non-fungible tokens (NFTs) remain inadequately understood. Prior research has focused on market dynamics, user behavior, and isolated security incidents, yet systematic analysis of the standards underpinning NFT functionality is largely absent. We present the first study of NFTs through the lens of Ethereum Improvement Proposals (EIPs). We conduct a large-scale empirical analysis of 191 NFT-related EIPs and 10K+ Ethereum Magicians discussions (as of July, 2025). We integrate multi-dimensional analyses including the automated parsing of Solidity interfaces, graph-based modeling of inheritance structures, contributor profiling, and mining of community discussion data. We distinguish foundational from emerging standards, expose poor cross-version interoperability, and show that growing functional complexity heightens security risks.

Problem

• Analyzing NFT technical foundations via EIP standards
• Investigating cross-version interoperability issues in NFTs
• Assessing security risks from NFT functional complexity

Innovation

• Analyzing NFTs via Ethereum Improvement Proposals
• Large-scale empirical study of 191 NFT-related EIPs
• Multi-dimensional analysis including Solidity parsing