Sandwich Attack Checker: Was My Swap Front-Run?
Paste a swap transaction to see whether a bot wrapped it in a front-run and a back-run, and what that sandwich cost the trader.
EthereumBNB ChainBase+1Report · FolioPlanned
MEV Sandwich Attacks by Chain: Monthly Losses
How many sandwich attacks happened this month on each chain, and how much value did they take from traders?
A dated monthly count of sandwich attacks on Ethereum, Solana, BNB Chain, Base and Arbitrum: victims, value taken, bots and the pools hit.
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Blueprint
What the report will cover.
The report as it will open in Folio. Each figure is named here and arrives with its receipt; until its data is published, its place stays empty.
A monthly edition, dated and cited
MEV Sandwich Attacks by Chain: Monthly Losses
The month in one paragraph
How many sandwiches were found, the value taken from traders and how the month compared with the last, chain by chain.
- Sandwich attacks this month
- Value taken from traders
- Change from last month
Sandwiches by chain
Attacks, victims and value taken on each covered chain, with the share of each chain's DEX volume that was sandwiched.
- Attacks per chain
- Value taken per chain
- Share of DEX volume sandwiched
The pools and tokens hit hardest
The pools with the most attacks and the largest losses, and how much of the month's loss came from new or thinly traded tokens.
- Most sandwiched pools
- Losses on new tokens
Who ran the sandwiches
The bot contracts behind the month's attacks, their profit after costs and what they paid builders or validators to be ordered.
- Profit of the largest bots
- Paid to block producers
What victims had in common
Trade sizes, slippage limits and routes of sandwiched swaps, and how many of them went through private transaction routes.
- Median loss per victim
- Victims with a wide slippage limit
Method and corrections
The detection rules this edition used, attacks reclassified since the last edition and the known gaps on each chain.
About
What it answers, and for whom.
A sandwich attack wraps a victim's swap between two trades by the same bot: a buy just before it that pushes the price up, and a sell just after it that takes the difference. This report counts those attacks each month on each covered chain, from the order of swaps inside each block, and states how much value moved from traders to bots.
Sandwiching depends on who can see a swap before it lands. Public mempools, private order flow, sequencer design and validator behaviour differ from chain to chain, so the same detection method gives very different results. Each edition compares the chains on one definition and shows which pools, tokens and bots drove the month.
For a single swap, the sandwich attack checker answers whether it was hit. This report is the monthly record across chains, dated so that reclassified attacks appear as corrections in the next edition.
Method
How it will be measured.
Every figure will be read at a block, kept with its source and its exact read, and open a receipt anyone can re-check.
How receipts work →- A sandwich is a front-run and a back-run by the same bot, in opposite directions in the same pool, around a victim's swap in that pool inside one block; on Solana the search also spans consecutive slots of one leader.
- The victim's loss is what the swap would have received at the pool state before the front-run minus what it did receive, valued at oracle prices at that block.
- Bot profit is the back-run's output minus the front-run's input, net of gas, priority fees and any tips paid to builders or validators.
- Counts and amounts cover the calendar month in UTC and each attack links to its transactions; chains are compared only on this shared definition.
The data it needs
Read from chain state and history
- mev_dailyTo buildMEV, builders and sandwichesBlocks by builder, MEV-Boost relay share, and detected sandwich attacks with the value taken from users, per day.
- dex_swaps_dailyTo buildDEX volumeSwap counts and volume per DEX, pool and chain per day, decoded from Swap events, valued with stablecoin legs and oracle prices.
- address_labelsTo buildAddress labelsLabels for known addresses: exchanges, bridges, protocols, funds, treasuries, sanctioned addresses and known attackers.
- native_prices_dailyTo buildOracle prices by dayReference prices of major assets read from on-chain oracle feeds (Chainlink latestRoundData) at each day's last block, with each round's update time.
- DEX Swap logs in each block, ordered by transaction index and log index
- Solana DEX program swap instructions, ordered by slot and position
- Pool reserves or tick state before each front-run, to replay the victim's swap
- Gas, priority fees and builder or validator tips paid by the bot transactions
Questions
Questions people ask.
What is a sandwich attack?
A bot sees a pending swap, buys the same token just before it so the victim pays a worse price, then sells right after the victim's trade. The victim's loss is capped by the slippage limit it set, and the bot keeps the difference minus its costs.
Which chain has the most sandwich attacks?
It depends on how transactions reach block producers. Chains with a public mempool, or with validators willing to reorder trades, see more, while sequencers that keep pending transactions private see fewer. The report ranks the chains each month on one detection method rather than assuming.
How can traders reduce the risk of being sandwiched?
A tight slippage limit caps what a sandwich can take, and private transaction routes keep a swap out of public view until it is included. Splitting a large swap and avoiding thin pools also shrink the gain an attacker can make.
Why do sandwich estimates differ between sources?
Methods differ. Some count only attacks inside one block while others include attacks spread over several slots, and losses can be measured against the pre-attack price or the victim's limit. This report states its method and links every counted attack to its transactions.
Is every front-run a sandwich?
No. Arbitrage that follows a trade, or a liquidation that races others, is MEV but takes nothing extra from one victim's swap. The report counts only the pattern of a front-run and a back-run by the same bot around a victim in one pool.
- MEV
- Maximal extractable value: the profit a block producer, or bots that pay it, can make by including, excluding or ordering transactions.
- Slippage limit
- The worst price a trader accepts for a swap. A sandwich can move the price no further than this limit without making the swap fail.
- Private order flow
- Transactions sent straight to builders or validators instead of a public mempool, so other bots cannot see them first.
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