Säkerhetsanalys av konkurrensstyrning inom decentraliserad finans : En hotmodelleringsstudie av Foresight-protokollet

Abstract

Decentralized Finance (DeFi) protocols face significant security challenges, with over $500 million lost to exploits in 2024. While technical vulnerabilities are well-studied, the security implications of novel governance mechanisms remain underexplored, particularly for protocols using competitive dynamics rather than traditional voting. This thesis presents the first comprehensive security analysis of the Foresight Protocol, a DeFi system that optimizes reserve composition through competitive game-theoretic mechanisms. The research adapts traditional threat modeling for blockchain by extending STRIDE with three DeFispecific categories: Governance Vulnerabilities (G), Parameter Interaction Vulnerabilities (P), and Systemic Risks (SR). The analysis reveals that Foresight’s economic design effectively eliminates traditional attack vectors including flash loans, MEV exploitation, and bank runs through stake requirements and extended evaluation periods. However, critical vulnerabilities emerge from the protocol’s governance complexity. The reliance on decentralized decision-making introduces social and educational requirements that actors could exploit through identity spoofing, economic bribery, or information asymmetries. Additionally, the mathematical sophistication of competition parameters creates opportunities for manipulation disguised as optimization, while distinguishing genuine value from market manipulation remains an inherent challenge. Key findings indicate that while economic incentives can provide robust security, governance mechanisms introduce attack surfaces just as significant as technical vulnerabilities. The extended threat modeling framework offers a reusable methodology for analyzing innovative DeFi protocols. The research demonstrates that next-generation DeFi protocols can achieve security through economic design, but success requires sophisticated community capabilities and ongoing empirical validation. This work emphasizes the importance of threat modeling starting from the design phase to ensure comprehensive security in novel DeFi systems.