Sandwich bots extracted about $29.7 million before costs from Solana trades over an 11-month period, according to blockchain data provider Bitquery. It found 96% of detected attacks on memecoin platform Pump.fun's launch curve and its PumpSwap exchange.
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The investigation, covering successful swaps, counted 6,850,144 attacks by 2,545 bot wallets affecting 2,154,994 distinct wallets between October 30, 2025, and October 7, 2026. Those addresses do not represent a count of individual people: other bots' trades accounted for 39% of the estimated gross take.
A sandwich places a bot's purchase and sale around another trader's swap. The first purchase raises the pool price; the intervening buyer receives fewer tokens, and the bot sells into the higher price. The cost reaches the trader through execution, even when the swap completes successfully.
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Wide slippage marked greater exposure
Among trades sent by swap router Jupiter through Pump.fun's launch curve or PumpSwap, trades allowing 20%–50% slippage were sandwiched 14 times as often as those allowing under 3%, Bitquery found.
Slippage tolerance sets how far execution can depart from a quote. Jupiter's documentation describes a minimum acceptable output after applying that tolerance. A price move beyond the limit can cause a swap to fail; a wider limit permits a worse fill. That creates a tradeoff between completing a volatile trade and limiting the price concession accepted along the way.
The observed attack rates did not rise uniformly with every wider setting. Trades below 0.5% tolerance were hit more often than those at 1%–3%, while the 50%-or-more band was hit less often than the 20%–50% band.
The slippage comparison is observational and covers Jupiter routes through Pump.fun's launch curve or PumpSwap. Jupiter carried only a small share of all victim trades in the investigation.
The $29.7 million estimate values SOL at the minute of each attack and does not measure net profit. In Bitquery's separate 63-attack fee sample, bots retained 68% of aggregate gross proceeds, and 18 attacks lost money after costs. That sample does not establish net earnings for the full period. The report also identifies inconsistent Pump.fun sale-fee recording that affects its gross estimate by about 3%.
Bitquery used repeated trading patterns to identify bots, excluded round trips beginning in a token's first 10 slots, and reports gaps in exchange and block coverage. Chain records cannot prove a bot saw an order beforehand, and some qualifying wallets may be fast traders.
Slippage limits address the price a trader will accept. A separate research preprint submitted September 23, 2026 examined protected order flow, meaning transactions intended to be shielded from front-running, across six blockchains. Its authors found sandwich patterns extending across trades and blocks and concluded these protections can offer weaker guarantees than users expect.