A Threat Taxonomy for Smart Contracts in Institutional Real-World Asset Blockchain Systems

Abstract

Smart contract security research has historically emphasized exploit-driven threat models developed for open, permissionless blockchain environments. While effective for identifying adversarial attacks and loss-of-funds scenarios, these models are insufficient for institutional blockchain systems supporting Real-World Assets (RWAs). In regulated and asset-backed deployments, threats frequently arise from non-adversarial actors, design assumptions, operational dependencies, and compliance enforcement failures rather than from direct malicious exploitation.This paper presents a structured threat taxonomy tailored to institutional RWA smart contract systems. The taxonomy classifies threats according to origin, intent, capability, and impact, explicitly incorporating adversarial, non-adversarial, and systemic threat sources. By decoupling threat analysis from exploit-centric assumptions, the taxonomy enables correctness-oriented risk assessment, formal specification of threat boundaries, and alignment with institutional audit and compliance requirements. The proposed framework provides a foundation for secure system design, verification, and operational governance in regulated blockchain environments.