Front-running attacks exploit transaction ordering to extract value from users. Learn about MEV, sandwich attacks, and how to protect your DeFi protocol from these threats.
Front-running occurs when attackers observe pending transactions in the mempool and submit competing transactions with higher gas fees to execute before the original transaction. This allows them to profit from advance knowledge of upcoming price movements or trades.
Front-run user's trade to increase slippage, then back-run to capture profit.
Race to liquidate undercollateralized positions for liquidation rewards.
Detect arbitrage opportunities and execute them before the original finder.
Front-run large trades on decentralized exchanges to profit from price movements.
Front-running is when an attacker (or MEV bot) sees a pending transaction in the mempool and submits a competing transaction with higher gas fees to be executed first. On DEXes, this lets attackers buy tokens before a large trade, then sell immediately after — profiting at the trader's expense.
MEV bots monitor the Ethereum mempool for large swap transactions. When they spot one, they calculate the expected price impact, submit an identical buy transaction with higher gas (so miners process it first), then a sell transaction after the victim's swap — a sandwich attack. Flashbots and private mempools emerged specifically to fight this.
Common mitigations: (1) Use commit-reveal schemes — users submit a hash of their action, then reveal it later. (2) Set slippage limits — reject trades where the executed price deviates too far from expected. (3) Use Flashbots Protect or a private RPC to bypass the public mempool. (4) Add a time delay to sensitive operations.
MEV extraction (which includes front-running, sandwich attacks, and arbitrage) has extracted billions from DeFi users. Flashbots research estimated over $1.3B in extracted MEV on Ethereum in 2021 alone. Individual victims rarely see large losses but millions of small losses aggregate into massive transfer of value from traders to bots.
Audits can identify patterns that create front-running risk — unprotected price-sensitive operations, missing slippage checks, and NFT minting that reveals information before finalization. SmartContractAuditor.ai flags these patterns and recommends commit-reveal schemes or slippage protections where applicable.