Exploring Vulnerabilities and Anomalies in NFT Marketplaces

Abstract

Since the invention of the blockchain, an increasing number of people have been working on creating various decentralized financial (DeFi) products. NFTs, or non-fungible tokens, are among the most widely used DeFi products. The NFT market is developing and expanding quickly and drawing more players. However, the NFT market is experiencing several technological and financial security challenges. Our goal in this thesis is to present a systematic and thorough assessment of NFT security challenges, including technical flaws, fraud, market manipulation, and money laundering, as well as to suggest cutting-edge detection methods for the rug-and-pull and wash trade utilizing the machine learning model and graph-based model, respectively. The validation findings from random sampling indicate that our detection techniques successfully identify targeted dishonesty.