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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11To detect a possible Solana sandwich, start with a victim swap and look for trading that worsened its execution price, followed by activity that reverses the suspected attacker’s exposure and leaves that trader with a net gain. A three-transaction pattern is a useful lead, not proof: the final ledger does not show whether transactions belonged to the same Jito bundle, how they were submitted, or what their submitter intended.
What counts as a sandwich pattern?
A sandwich attack is an ordering pattern: a trader’s transaction moves the price against a target swap, then a later trade takes the other side of that position so the trader can realize a gain. The target is often called the victim. In a simple example, an attacker buys a token before the victim’s buy, pushing its price up; the victim then receives a worse exchange rate, and the attacker sells afterward.
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That shape alone is not enough to call an event an attack. Trades around a swap may be arbitrage or ordinary market activity. A persuasive detection should show both that the earlier trade adversely affected the target’s execution and that later attacker activity reversed exposure and produced a net gain. Transaction order or proximity alone does not establish either point.
What can public Solana data prove?
Final-ledger evidence
On-chain transaction details can support analysis of instruction order, signers, token balance changes, transfers, and pool activity. These can help identify which assets were traded, estimate realized amounts, link accounts, and test whether a sequence had the necessary price impact and reversal. A block explorer such as Solscan may help inspect transactions, but seeing neighboring transactions in a block does not show they were submitted together.
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The final Solana ledger does not record original Jito bundle membership. It also cannot, by itself, establish what a trader saw before a transaction was included, the submitter’s intent, or whether a transaction arrived at a producer through a particular private route. Report a pattern as a detected candidate under explicit criteria—not as proof of intent or submission path.
Bundle evidence
Bundle membership requires a separate data source. In their 2025 Jito-focused study, Nicole Gerzon, Ben Weintraub, Junbeom In, Alan Mislove, and Cristina Nita-Rotaru obtained bundle IDs and included transaction IDs from Jito Explorer’s public-facing, undocumented API, then requested details for selected bundles. That is an additional metadata layer, not a fact recoverable from the ledger alone. Because the interface is undocumented, access, historical coverage, and reproducibility can be limited.
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How to investigate a candidate swap
- Select a victim candidate. Start with the transaction you suspect may have received a worse price. Record its slot and position, signer or signers, program instructions, route or pool, and transaction status.
- Decode what it traded. Examine the instructions and token balance changes to identify the traded mints, trade direction, and realized amounts. Account for the route when a swap passes through multiple pools; the apparent first and last assets may not reveal every market where the price could have moved.
- Inspect the local trading sequence. Check transactions immediately before and after the candidate in the relevant pool or route. Compare signers and token movements, but treat adjacency only as a way to find leads. A transaction in the same block can be unrelated.
- Expand the search window when needed. Look beyond an adjacent, same-block triplet. The 2026 preprint by Lioba Heimbach, Ozan Solmaz, Burak Öz, and Christof Ferreira Torres describes broader attack patterns that can span wider positions and blocks. Split trades, intervening activity, and linked accounts can also obscure a simple sequence.
- Test adverse price impact. Compare the price effect of the suspected attacker’s earlier trade with the victim’s execution in the same assets and relevant pool or route. The question is whether that earlier activity worsened the victim’s exchange rate, not merely whether the victim traded at a different price from a transaction nearby.
- Test for reversal and gain. Follow the suspected attacker’s later trades, transfers, and balance changes. Determine whether they reversed the earlier exposure and whether the overall activity produced a net gain. Consider the full sequence rather than counting a profitable-looking exit in isolation.
- Record the evidence source and scope. State whether findings came from ledger data, an RPC transaction-history service, or additional Jito bundle metadata. Note the history available, collection gaps, and the rule used to classify candidates. If bundle metadata came from Jito Explorer’s API, identify that source rather than implying bundle membership was visible on chain.
A published Jito-bundle heuristic—and what it misses
Gerzon and coauthors’ 2025 study used five core checks for a canonical sandwich in a Jito bundle:
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- The first and third transactions shared attacker account A, while the middle transaction belonged to a different account, B.
- All three transactions traded the same minted coins.
- A’s first trade worsened the exchange rate for B’s trade.
- A gained currency without payment or ended with a net gain in the sold coin.
- A bundle whose final transaction only tipped a Jito validator was excluded.
This is a reproducible starting rule, not a universal definition. The authors note that extra unrelated instructions or trades, multiple sandwiches in one bundle, and other forms of disguise can evade it. It is also deliberately bundle-dependent: without bundle metadata, a ledger-only analyst cannot apply the same membership test just by finding three nearby transactions.
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Choose a method that matches the evidence you need
| Method | What it can support | Key limitation |
|---|---|---|
| Final ledger or block-explorer inspection | Transaction order, instructions, signers, balance changes, transfers, and pool-related evidence visible in recorded transactions. | Does not identify original Jito bundle membership or submission route. An adjacent triplet alone does not prove adverse impact, reversal, or intent. |
| RPC transaction history | Searching and retrieving transactions over the history available from the RPC service, for wider-window and account-link analysis. | Coverage depends on archive depth and service limits. History availability does not establish bundle membership; document gaps and collection conditions. |
| Ledger or RPC data plus Jito bundle metadata | Can add bundle IDs and included transaction IDs when the metadata source provides them, enabling bundle-specific checks such as the 2025 study’s heuristic. | The 2025 study used a public-facing undocumented Jito Explorer API. Availability and historical completeness should not be assumed, and bundle data still does not prove intent. |
For broader scans, state the detection policy as well as the data source: whether the rule requires one signer or allows linked accounts, whether it searches adjacent transactions or wider windows, and whether it requires demonstrated price harm and net gain. These choices change what gets counted. Wider windows and account-link rules can find cases a triplet rule misses, but they also make it more important to show the evidence behind each label.
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Gerzon and coauthors reported 521,903 candidate Jito-bundle sandwich attacks for their collection from February 9 to June 9, 2025. Collection was interrupted, and the count reflects their criteria and measured period—not a current daily rate or an ecosystem-wide total. They reported that 95% of successive pairs of their bundle-data requests overlapped as a collection-completeness check; that overlap does not mean the dataset was complete. They characterize measured prevalence and harm as lower bounds because their data access and criteria could miss cases.
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A September 23, 2026 preprint by Heimbach, Solmaz, Öz, and Ferreira Torres reports an estimate of 28.0 million protected-order-flow sandwich attacks on Solana across its three-year study. The authors use broader heuristics and a different population and methodology from the Jito-specific 2025 study. Treat the figure as that preprint’s estimate, not as a directly comparable update to the 521,903 count.
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Solana’s official guide, MEV Protection with Jito DontFront, describes a sandwich as occurring when a searcher detects a pending swap and exploits transaction ordering. The same guide says transactions are forwarded to upcoming leaders rather than held in a shared public mempool, and that unprocessed transactions expire after roughly 150 blocks—about one minute. It also notes that MEV extraction still occurs; those design details should not be read as proof that Solana is immune to sandwiching.
Jito’s Low Latency Transaction Send documentation says accepted bundles contain up to five transactions and execute sequentially and atomically. DontFront uses a valid public key prefixed with jitodontfront to impose an ordering constraint through the Jito block engine: a bundle containing the marked transaction must place it first. Solana’s guide quotes Jito’s qualification that the feature may help reduce sandwich attacks, but is not guaranteed to do so and does not address every variation in transaction ordering, including ordering by third parties. A DontFront constraint is therefore not evidence that a transaction could not have been exposed to other ordering paths.
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