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Introduction
Insider trading traditionally refers to trading public securities based on material non-public information (“MNPI”) in breach of a duty of trust, confidence, or loyalty. Liability can arise under multiple overlapping theories, including the classical theory (corporate insiders trading in their company’s securities), the misappropriation theory (outsiders obtaining and misusing a corporation’s confidential information), and tipping liability (individuals improperly sharing MNPI that others use to trade). Where traditional securities statutes do not apply, prosecutors may rely on wire fraud, securities fraud, and commodities fraud to charge deceptive trading activity.
Today, scrutiny is no longer confined to public equities markets. In a pair of recent prosecutions, including last week’s indictment of a Google employee, the Department of Justice has made clear that it will pursue insider trading type cases wherever (i) confidential data moves prices, and (ii) a duty-bound actor exploits that data for trading advantage, even outside the securities laws. Prediction markets and crypto platforms appear to be the primary testing ground for this expanded enforcement theory.
Classic Insider Trading
Prediction markets and digital asset trading platforms create opportunities for users and insiders to trade on non-public information, misuse platform data, or exploit information asymmetries, drawing scrutiny from regulators. Regulators are increasingly focused on the extent to which trading outcomes depend on MNPI. As a result, regulators are increasingly treating these platforms not as novel betting or technology environments, but as information-sensitive trading markets subject to anti-fraud enforcement.
For example, in March 2026, the CFTC issued an Advance Notice of Proposed Rulemaking soliciting public comment about event contract derivatives traded on prediction market platforms. David Miller, Director of the CFTC’s Division of Enforcement, subsequently said in his first official speech that “[i]nsider trading in the prediction markets, where there is misappropriated information, is precisely the kind of serious violation that we are going after vigorously.”
In crypto markets, allegations of exploitation of confidential or proprietary information continue to draw enforcement scrutiny, and regulators remain willing to test alternative theories. Recent allegations involving crypto platform Axiom, where a senior employee was accused of using internal tools to trade on user transaction data, underscore that pressure is on regulators to address alleged data misuse and access controls, even when the precise legal theory is still evolving. Prediction markets are trading platforms that allow users to buy and sell contracts tied to the outcome of future real-world events like elections, geopolitical developments, or economic indicators. Platforms like Polymarket (a crypto-based event market) and Kalshi (a CFTC regulated exchange) enable users to take positions based on their expectations, with contract prices fluctuating as new information emerges and reshapes the market’s forecast. Unlike traditional sports betting, where odds are set by the “house,” prediction markets function more like exchanges. Sports betting is typically governed by state gaming laws, whereas prediction markets (particularly those involving financial-like instruments) fall under federal commodities or derivatives regulation.
Digital Asset Trading Platforms
Crypto exchanges like Binance and Coinbase are online platforms that allow users to buy, sell, and trade digital assets, while also providing market infrastructure such as custody, liquidity, and pricing for cryptocurrencies. NFT exchanges like OpenSea are platforms that enable users to buy, sell, and trade non-fungible tokens (“NFTs”), which are unique digital assets representing ownership of items such as art or collectibles.
(A) United States v. Chastain
The prosecution of Nathaniel Chastain, an executive of NFT exchange OpenSea, was DOJ’s first major test case for insider trading-type claims in crypto markets. The U.S. Attorney’s Office for the Southern District of New York charged Chastain with wire fraud and money laundering for orchestrating an alleged scheme to buy NFTs that he knew would be featured on OpenSea’s homepage, which typically led to increased trading activity and value. Although Chastain was convicted, the Second Circuit vacated the conviction, holding that the government failed to show that the information was commercially valuable, and, as a result, failed to show it was OpenSea’s “property” under the wire fraud statute. United States v. Chastain, 145 F.4th 282, 293-94 (2d Cir. 2025). While Chastain narrowed one legal pathway under the wire fraud statute, subsequent prosecutions in prediction markets demonstrate the continued enforcement risk.
(B) The Van Dyke Case – Government Information
In April 2026, the U.S. Attorney’s Office for the Southern District of New York brought the first criminal insider trading-type case arising from prediction market activity. Gannon Ken Van Dyke, a U.S. Army soldier, was charged with misappropriating classified information to trade on Polymarket. Specifically, in December 2025, Van Dyke was involved in planning Operation Absolute Resolve, a military operation to capture Venezuelan president Nicolás Maduro. Van Dyke allegedly used that information to trade contracts regarding whether U.S. military forces would invade Venezuela and whether Maduro would be removed from power by January 31, 2026.
Prosecutors alleged that Van Dyke used non-public and classified government intelligence to place these profitable trades. They charged him with wire fraud, commodities fraud, unlawful use of confidential government information for personal gain, and related offenses under a misappropriation theory.
In parallel, the CFTC filed a civil enforcement action against Van Dyke based on the same conduct, alleging commodities fraud and manipulative trading practices. The CFTC’s complaint reflects its growing view that event based contracts resemble derivatives markets subject to its anti-fraud authority, particularly where trading is influenced by non-public information or deceptive conduct.
By pursuing civil remedies alongside criminal charges, regulators signaled a coordinated enforcement strategy aimed at bringing prediction markets within existing regulatory frameworks.
(C) The Spagnuolo Case – Corporate Information
In May 2026, SDNY unsealed a second criminal case targeting prediction market trading, charging Google software engineer Michele Spagnuolo with wire fraud and related offenses for trading on Polymarket using confidential information held by his employer, Google. The indictment alleges that Spagnuolo used non-public internal search data to trade contracts regarding who would be Google’s most searched person of 2025. According to the indictment, Spagnuolo used Google’s non-public search analytics to predict that the singer known as D4vd would become the most searched person of 2025, and entered a trade on Polymarket in anticipation of this outcome. At the time, Polymarket assigned a near-zero probability to this result. When Google announced its “Year in Search 2025” results, Spagnuolo’s trading resulted in approximately $1.2 million in profit.
Following the Second Circuit’s decision in Chastain, the Spagnuolo indictment expressly alleges that Google’s internal search data was commercially valuable, closely guarded, and integral to Google’s business model. These charges underscore that Chastain narrowed, but did not foreclose, fraud-based insider trading prosecutions in non securities markets.
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