This catalog entry describes a scholarly work examining whether cryptocurrency scams can be detected early. Published in the SSRN Electronic Journal, the piece surveys theoretical concepts and practical considerations in fraud detection within crypto markets, with attention to the unique characteristics of digital assets, decentralized platforms, and information asymmetries. The work adopts a neutral, integrative stance and situates the topic within broader discussions of market integrity, consumer protection, and risk management. The entry notes that the focus is on detection prospects during early stages of scam development rather than post hoc analysis. Content overview: The document discusses scam typologies observed in cryptocurrency ecosystems, including misrepresentation, rug pulls, and pump-and-dump schemes, and contrasts conventional financial fraud with crypto-specific challenges. It considers detection approaches such as pattern recognition, anomaly detection, network analysis of on-chain activity, due diligence frameworks, and monitoring of information channels. Data sources are described in general terms, including on-chain data, exchange and wallet activity, and publicly available reports, without presenting specific datasets or results. The discussion emphasizes methodological trade-offs, measurement issues, and the need for reproducibility and transparency. Audience and implications: Aimed at researchers, practitioners, and policymakers, the work highlights implications for platform governance, investor education, and regulatory design. It presents a balanced view of early-detection prospects, noting potential benefits as well as limitations and ethical considerations. Overall, the entry serves as a reference point for understanding how early indicators might inform preventive strategies in cryptocurrency markets.