Google Engineer Charged Over $1.2M Polymarket Insider Trades
DOJ and CFTC allege Michele Spagnuolo used non-public data to profit on the decentralized prediction market.

The U.S. Department of Justice and the CFTC charged Google software engineer Michele Spagnuolo on May 2025 with insider trading after he allegedly used non-public company information to place bets on Polymarket, netting approximately $1.2 million in profit, according to CoinTelegraph.
Why It Matters
This case marks one of the first high-profile instances of insider trading enforcement applied directly to a decentralized prediction market, signaling that U.S. regulators treat Polymarket positions as financial instruments subject to securities and commodities law. For the prediction market sector, the charges confirm that the CFTC views material non-public information as equally illegal to exploit on-chain as in traditional markets. Participants who assume pseudonymous blockchain activity shields them from prosecution face a clear counter-example here — blockchain transaction data proved traceable enough to support federal charges. The case raises the compliance burden for any professional handling sensitive corporate information who also trades on prediction platforms.
Context
Polymarket is a decentralized prediction market built on Polygon, where users trade on the outcomes of real-world events using USDC. As of May 2025, it remains one of the largest prediction markets by volume, having processed billions in notional bets during the 2024 U.S. election cycle, per Dune Analytics data. Spagnuolo allegedly accessed confidential information through his role as a Google software engineer and timed Polymarket positions to exploit that information before it became public.
What's Next
The DOJ and CFTC will pursue prosecution through federal court, with the outcome likely to set a precedent for how insider trading law applies to decentralized prediction markets going forward. Any conviction or settlement could accelerate calls for formal KYC and market surveillance requirements across Web3 prediction platforms.
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