#稳定币 The verdict in the Do Kwon case has been handed down, with a 15-year prison sentence—this data is worth a close look.

From an on-chain perspective, the UST collapse essentially exposed the systemic risks of algorithmic stablecoins. At the time, abnormal signals within the ecosystem had already appeared: Anchor's high-yield subsidies were unsustainable, Luna's price support weakened, and the reserve structure of the stablecoin was opaque. These are early warning signs that can be captured from on-chain data.

Behind the $40 billion evaporation lies a fundamental flaw in stablecoin mechanism design—over-reliance on a single asset collateral and a lack of sufficient risk buffers. Kwon's team concealed control of Mirror Protocol, fabricated Chai settlement data, and exaggerated the stability of the algorithm, with these fraudulent behaviors directly impacting investors' decision-making chain.

The lesson for today: When evaluating stablecoins, you can't just look at nominal value; you need to track actual fund inflows and outflows, reserve authenticity, and mechanism transparency. On-chain data analysis can help you identify similar risks in advance—monitor large fund movements, compare on-chain and off-chain data discrepancies, and trace interaction patterns of core contracts.

This case illustrates a reality: no matter how sophisticated the mechanism design, it cannot escape fundamental principles. When making strategic judgments, data speaks louder and is more trustworthy than narratives.