Solana sandwich bots target some token-launch swaps because a new or thinly traded pool can move sharply when a buyer enters, while the buyer’s slippage setting may permit a worse fill. The bot buys immediately before the victim, lets the victim’s swap execute at the shifted price, then sells afterward. That sequence can be arranged through Jito or other ordering paths, but a launch-time buy is not automatically an attack, and no cited measurement establishes how often launch swaps are sandwiched.
What a Solana sandwich attack does
A sandwich attack is an ordered set of trades around another trader’s swap. The attacker, often called a searcher, tries to profit from the price movement caused by the victim’s transaction rather than from a long-term view of the token.
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The buy-side sequence
- Front-run: The searcher buys the same token first. In an automated market maker (AMM) pool, that purchase moves the pool price upward.
- Victim swap: The user’s pending buy executes after the searcher’s trade. Because the pool has already moved, the user receives fewer tokens or pays a higher effective price than before the front-run. The transaction still succeeds if the result remains inside the slippage limit the user accepted.
- Back-run: The searcher sells after the victim’s purchase, seeking to capture the price difference created by the two trades.
Solana’s official MEV protection documentation describes this front-run, victim, and back-run pattern and explains that the back-run attempts to pocket the difference. The attacker’s profit is not guaranteed: fees, competition, adverse price movement and insufficient price impact can erase the opportunity.
The sell-side inverse
A sell order can be sandwiched in the opposite direction. The searcher sells first, pushing the pool price down; the victim then sells at a worse rate within the victim’s tolerance; the searcher buys back afterward. The same principle applies: an initial trade moves the pool, the victim receives the unfavorable intermediate price, and the final trade attempts to unwind the searcher’s position.
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Why slippage matters
Slippage is the maximum execution difference a user permits between the quoted price and the final result. It is not a fee paid to a bot, but a bound that determines whether a transaction can still settle after the market moves. A broad bound gives a searcher more room to move the pool and still have the victim’s swap execute. A tight bound reduces that room, although normal volatility can then cause the swap to fail instead.
Why a token launch can be an attractive setting
The relevant mechanism is price sensitivity, not the word “launch” by itself. A newly created or lightly traded pool may have relatively little liquidity. A buy that would barely move a deep pool can move a thin pool materially. If a launch buyer also allows a wide slippage range, a searcher may be able to trade before and after the buyer while keeping all three transactions executable.
Thin liquidity magnifies price impact
AMM pricing changes as assets are removed from one side of a pool and added to the other. In a shallow pool, the same order size represents a larger share of available liquidity, so the curve produces a larger price change. That creates a possible, not certain, sandwich opportunity. The searcher still needs enough expected movement to cover network fees, priority costs, bundle tips and the risk that another searcher gets the ordering position first.
Launch slippage can create execution room
People buying a volatile new token may choose a generous tolerance because they fear a failed transaction or a rapidly rising quote. Solana documentation identifies tight slippage as a transaction-level defense, and the Jito Foundation describes sandwiching as “explicitly predatory” and says it “largely relies on users or DEX interfaces having set overly-broad slippage settings in order to work.” A generous setting is therefore an exposure, not proof that an attack occurred.
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What is not established
Published measurements do not establish that token launches are the most common sandwich target, that every launch pool is shallow, or how frequently launch swaps are sandwiched. It supports an incentive-based explanation: when a pool is price-sensitive and the victim’s tolerance is wide enough, positioning around the swap may be economically attractive. Launch timing alone cannot establish an attack.
How transaction visibility and ordering work on Solana
Solana’s transaction path differs from chains that expose a shared public mempool. Solana’s official guide says transactions are forwarded to the upcoming block leader rather than held in one public waiting room. That can narrow the observation window, but it does not make sandwiching impossible.
Specialized access still creates opportunities
Searchers with optimized infrastructure and direct connections to validators can observe transaction flow and compete to have their transactions processed in a favorable order. The practical question is not whether every observer can see every pending transaction; it is whether a searcher can obtain enough visibility and ordering influence for a particular swap. Some opportunities may occur within one slot, while others involve activity spread across several slots.
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Where Jito bundles fit
Jito documents bundles as groups of up to five transactions that execute sequentially and atomically: either the entire bundle lands or none of it does. Searchers submit bundles to a block engine connected to Jito-Solana validators, and bundles compete using tips. When the execution path and ordering rules permit it, a bundle can place the searcher’s buy before a victim transaction and the sell after it.
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That does not mean every Solana sandwich uses a Jito bundle. Solscan notes that bots can use a bundle or another execution method and that suspicious patterns can span slots. A bundle is one way to coordinate an ordered sequence, not the definition of a sandwich.
How to tell a sandwich from ordinary launch volatility
A fast buy followed by a fast sale may look suspicious, but three nearby trades are not conclusive evidence. Launches naturally produce rapid price changes, arbitrage, liquidity rebalancing and competing users. Investigation has to connect the transactions and their economic effects.
Single-slot pattern
Solscan describes a single-slot sandwich as a front-run, victim transaction and back-run that all occur in one slot. This is the easiest pattern to notice, but adjacency alone is insufficient. Review whether the first and third trades belong to related accounts, interact with the same pool and asset, move in opposite directions, and leave a balance change consistent with a profit.
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A wide sandwich can span multiple slots. The searcher’s first trade, the victim swap and the unwinding trade may not appear next to one another in an explorer view. Reconstruct the activity across blocks, following account ownership, token balances, pool interactions and trade direction.
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An investigation checklist
- Identify the victim transaction and its exact pool, input amount, output amount and slippage limit.
- Find trades immediately before and after it, then expand the time window to multiple slots.
- Check whether the same or linked accounts controlled the suspected front-run and back-run.
- Verify that the trades use the same asset pair or a route whose price movement explains the victim’s worse execution.
- Compare balances before and after the sequence, including fees and tips, rather than treating gross price movement as profit.
- Record whether the sequence was submitted through a known bundle path, while recognizing that the absence of a bundle label does not disprove a sandwich.
Explorer leaderboards and labels are useful entry points, not final verdicts. Transaction-level reconstruction is required before calling a sequence an attack.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Defenses and their trade-offs
Set the narrowest practical slippage
Choose a tolerance that reflects the token’s normal volatility and the size of the order instead of using an unnecessarily broad default. A tighter bound leaves less room for an attacker to worsen the fill. The cost is a higher chance of an ordinary failure when prices move quickly or liquidity is insufficient. There is no universal percentage that is safe for every pool.
Choose the transaction path deliberately
Solana’s guide documents Jito DontFront, which uses a valid public key beginning with jitodontfront in an instruction. Jito’s block engine requires that transaction to appear first in a bundle. Jito says the account should be read-only to improve landing speed. This control applies through Jito block-engine endpoints; it does not protect a transaction sent by a path that bypasses that block engine.
Understand DontFront’s limit
Jito’s documentation states: “This feature may help reduce sandwich attacks but is not guaranteed to do so and is not a solution for all variations in transaction ordering, including any ordering conducted by third parties.” Treat it as a bounded ordering preference, not an all-purpose shield. Third-party ordering and execution outside the Jito block engine remain outside its stated protection.
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Do not confuse tips with protection
Jito documents tips as bids associated with bundles and discusses tip and priority-fee configuration. Paying more can affect competition and landing speed, but faster landing is not the same as guaranteed safe ordering. A tip by itself is not an anti-sandwich guarantee.
Separate custody from execution risk
A hardware wallet can protect private-key custody, but it does not determine the order in which a swap reaches a validator or change the slippage encoded in that swap. Key security and transaction-ordering protection are different controls.
What measured research says about frequency
A 2025 ACM Internet Measurement Conference paper by Nicole Gerzon, Ben Weintraub, Junbeom In, Alan Mislove and Cristina Nita-Rotaru analyzed more than four months of Jito data from early 2025. The authors reported that sandwiching was relatively rare overall in that measured Jito dataset, despite widespread anticipation of adversarial activity.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsThat result should be read narrowly. It is a study of Jito data during the period examined, not a current census of every Solana execution path, and it does not report a token-launch-specific rate. It cannot show that sandwiches are absent or that the same prevalence applies to every launch venue, wallet, router or private transaction route.
| Figure | What it describes | Qualification |
|---|---|---|
| More than four months | Jito data analyzed by the 2025 study | Early-2025 measurement window; not a 2026 all-Solana census |
| $0.00064 median transaction fee | Context reported by the study authors | Figure cited by the paper; not a current fee quote or a launch-specific cost |
| Approximately $720 million in MEV | Ethereum validator MEV between 2020 and 2024 | Figure date specified as September 12, 2025; Ethereum context, not a Solana sandwich-loss estimate |
A practical decision process before a launch swap
- Inspect the pool: Determine whether liquidity appears deep enough for your order size. Thin liquidity means your own trade may create substantial price impact even without an attacker.
- Reduce unnecessary tolerance: Set slippage only wide enough to accommodate expected movement, and accept that an overly tight value can cause a failed transaction.
- Review the route: Know whether your transaction is submitted directly or through a Jito block-engine path. The path determines which ordering controls can apply.
- Consider DontFront where supported: Use the documented
jitodontfrontread-only account mechanism only through a compatible Jito endpoint, and keep its non-guaranteed nature in mind. - Evaluate the result: After execution, compare the quoted output, actual output, pool movement and fee totals. A worse-than-expected fill can result from ordinary volatility, not necessarily a sandwich.
- Investigate before accusing: If the trade looks abnormal, trace accounts, pools, slots and balances using the single-slot and cross-slot methods above.
The bottom line for launch buyers
Solana sandwiching is an economic sequence: front-run, victim swap at a worse price within the victim’s tolerance, then back-run. Token launches can expose that sequence when liquidity is thin and slippage is broad, but neither launch timing nor a rapid buy-and-sell pair proves an attack. Solana’s non-public-mempool transaction path narrows visibility without eliminating specialized observation and ordering. Tighter slippage and, where appropriate, a Jito block-engine path with DontFront can reduce exposure, yet both have operational limits and neither guarantees protection.
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