In late February 2026, four anonymous wallets appeared on the Polymarket platform. These wallets were created just days before and seemed very confident. Over the next few weeks, they placed over 80 bets on specific mechanisms of a war between the U.S. and Iran, the timing of the first strike, the removal of Iran’s Supreme Leader, and the announcement of a ceasefire.

When Bubblemaps finally mapped this cluster of bets and linked the initial four wallets to five others, it was discovered that these nine related accounts had won over $2.40M in prizes with a win rate as high as 98%, even though many of the bets were placed with low odds. Now, this phenomenon has a name, or at least a category: information laundering. To understand why it is so destructive, one must first understand the nature of prediction market prices, because the very mechanisms that make these markets work are also the mechanisms that make them vulnerable to exploitation.

Leaving aside the crypto wrapper, PM contracts are actually very simple. Each share earns $1.00 if the prediction is correct and nothing if the prediction is wrong. Because each binary question has only two outcomes, one “yes” share plus one “no” share always equals $1.00, so a “yes” share priced at $0.36 means the market believes there is a 36% probability that the prediction is correct. Crucially, Polymarket does not set these prices. They come from a trader order book (CLOB). The relationship between supply and demand among traders determines the price, and the displayed price is at the midpoint of the bid-ask spread. This is perhaps where its ingenuity lies.

In this model, the price is not the opinion of a bookmaker, but the collective expectation of all traders in the order book. When new information emerges, such as a strong jobs report or lower-than-expected CPI data, traders reprice and the price adjusts accordingly. In effect, the market becomes a constantly updated probability estimate, and financial institutions are willing to pay for it. Institutions such as Bloomberg, Reuters, and hedge funds now purchase real-time access to Polymarket data interfaces, viewing them as a faster indicator of market sentiment than traditional polls.

However, the trap is that a system designed to turn information into prices cannot distinguish between public and stolen information. The order book doesn’t ask where your edge comes from, it just records that you bought in. This is where the term “laundering” comes in. In traditional money laundering, dirty cash flows in from one end of the system and clean, untraceable cash flows out the other. In information laundering, confidential information flows in from one end and market prices flow out the other, without any trace.

For example, suppose someone knows that a strike will occur in 48 hours, and the market is currently pricing it at 15%. Their buying pressure would eat up all the sell orders in the order book and push the midpoint up, say the contract price rises to 35%. To others, this would look like just a normal repricing, as if a trader had a precise grasp of geopolitics. The secret is cleverly packaged as a clear signal. When the strike occurs, the price of the YES contract will rise to $1.00. A position bought near $0.15 would return approximately 6.7x. The Maduro case a few months ago clearly demonstrated this scale. Prosecutors accused the army sergeant of turning a bet of approximately $34,000.00 into approximately $400,000.00.

The laundering metaphor also applies to covering up the truth. Bubblemaps found that the Iranian criminal group’s losses were minimal, only a few hundred dollars, which the company believes were deliberately incurred to mislead investigators. A 98% win rate looks extraordinary, while a 98% win rate plus some negligible, deliberately incurred losses looks almost like a very good trader. However, the most ironic thing is that these markets are more transparent than traditional exchanges. Even if account holders remain anonymous, every transaction is at least recorded in a public system. It is this openness that allows analysts to use tools such as Bubblemaps to reconstruct a conspiracy involving nine wallets based on time correlations and trading volume, such as the trades recorded in the days before the market movements on February 28.

But the same transparency also brings a secondary risk that regulators are deeply concerned about. If external analysts can decipher that a coordinated group is heavily betting on an attack, so can hostile forces. Hostile observers can spot unusual trades and use them to develop war plans and predict markets. The unusual spikes in certain war markets are a low-cost, deniable source of intelligence for anyone watching the chain. Launderers launder their information, and as a byproduct, they spread the original secret to the world in abstract form.

Why can’t current laws simply cover this situation? Because traditional insider trading rules are built around stocks, material non-public information related to companies, earnings, mergers and acquisitions, executive disclosures, etc., rather than the timing of military operations. War has no “issuer” and no corporate insiders in the legal sense. The geographical factor of jurisdiction exacerbates this problem. U.S. federal law prohibits prediction markets from offering bets on war or assassination, but Maduro’s bets were placed on Polymarket’s offshore website, which is not subject to these restrictions. And the barrier to entry is ridiculously low, easily circumventing the U.S. ban with a VPN that costs about $2.00 per month. A KYC-verified account can also simply be purchased.

Nevertheless, Washington has finally taken notice. On May 22, the House Oversight Committee launched a formal investigation into prediction markets, demanding records of how they verify identities, enforce geographic restrictions, and handle suspicious transactions related to Venezuela and Iran. Proposed bills, the Death Bet Act and the Public Integrity of Financial Prediction Markets Act, aim to ban war bets and prohibit officials from trading on non-public information. The harsh reality is that information laundering is not a man-made vulnerability in prediction markets, but a side effect of their core operating mechanism. A market that perfectly translates knowledge into price is inherently determined to reward those who have the best information, including those who shouldn’t have it. You can’t completely close this loophole without weakening the mechanisms that make these markets more accurate than polls.

As the industry looks to the future, even if only 1-2% of derivatives traders adopt these tools, it could push annual trading volume to $50.00B, the question is no longer whether prediction markets work, but that they work too well. The question is whether a society can tolerate a machine that turns its most closely guarded secrets into publicly quoted, tradable numbers and pays holders handsomely for it.

[ChainCatcher]