What is a sandwich attack in DeFi?

A sandwich attack in DeFi involves front-running and back-running a target trade to profit from price slippage on decentralized exchanges like Uniswap.

Jul 06, 2025 at 08:42 am

Understanding the Concept of a Sandwich Attack

In the decentralized finance (DeFi) ecosystem, a sandwich attack is a type of front-running and back-running strategy employed by malicious actors to exploit predictable changes in token prices during trades. This manipulation typically occurs on decentralized exchanges (DEXs) that rely on automated market makers (AMMs) like Uniswap or SushiSwap. The attacker positions themselves before and after a target transaction, effectively "sandwiching" it to extract value from price slippage.

At its core, a sandwich attack involves three main steps:

• Monitoring pending transactions for large trades.
• Front-running the trade by placing a buy order just before the target transaction executes.
• Back-running by selling the acquired tokens immediately after the target trade impacts the price.

This sequence allows the attacker to profit from the temporary price volatility caused by the large trade.

How DeFi's Structure Enables Sandwich Attacks

The foundation of DeFi lies in transparency and openness, which paradoxically makes it vulnerable to attacks like these. Since blockchain transactions are visible in the mempool before they're confirmed, attackers can analyze and act upon them. AMMs use constant product formulas (like x*y=k), where a large trade significantly alters the price ratio between two assets.

When a user places a large buy order, the price of the asset increases due to the shift in liquidity pool balances. A sandwich attacker detects this change early and acts swiftly. They first buy the same token before the large trade, pushing the price slightly higher. Then, after the original trade further inflates the price, the attacker sells their holdings at a profit.

This manipulation is possible because transaction priority can be influenced by gas fees. By paying higher gas fees, attackers ensure their transactions are mined ahead of others, allowing them to execute both front-run and back-run orders efficiently.

Step-by-Step Execution of a Sandwich Attack

To better understand how a sandwich attack unfolds, let’s walk through a practical example:

• An unsuspecting trader wants to buy 100 ETH worth of Token X on Uniswap.
• The attacker monitors the mempool and identifies this transaction.
• The attacker submits a buy order with a high gas fee, ensuring it gets executed right before the target trade.
• The target transaction follows, causing significant price slippage due to the size of the trade.
• Immediately after, the attacker submits a sell order at the inflated price, realizing a profit.

Each step requires precise timing and often the use of bots or scripts to scan and react to mempool activity in real time. These tools allow attackers to automate detection and execution, making sandwich attacks scalable and profitable across multiple transactions.

Crucially, the attacker must calculate the exact amount to buy to maximize profit without over-investing. Too little, and the profit margin shrinks; too much, and the attacker risks losses if the price doesn't rebound sufficiently after the target trade.

The Role of Gas Fees and Transaction Priority

Gas fees play a pivotal role in enabling sandwich attacks. On Ethereum and other EVM-compatible chains, users pay gas fees to have their transactions included in a block. Miners (or validators in proof-of-stake systems) prioritize transactions with higher gas fees.

Attackers exploit this mechanism by submitting their transactions with extremely high gas fees, ensuring they get processed immediately before and after the target trade. This prioritization allows them to sandwich the victim's trade tightly, maximizing profit from the price movement.

Tools like Flashbots have been developed to prevent such exploitation by offering private transaction channels that bypass public mempools. However, not all users utilize Flashbots, leaving many transactions exposed to potential sandwich attacks.

Moreover, gas optimization techniques used by bots help attackers reduce costs while maintaining high-priority status. This balance between cost and speed is crucial for sustaining profitability in repeated sandwich attacks.

Protecting Against Sandwich Attacks in DeFi

Mitigating the risk of sandwich attacks requires a combination of technical strategies and platform-level solutions. Users can take several precautions to reduce exposure:

• Use platforms that offer private transaction relays, such as Flashbots, to avoid exposing trades in the public mempool.
• Break large trades into smaller chunks to minimize price impact and reduce the incentive for attackers.
• Set tight slippage tolerances when trading to reject trades that result in excessive price movement.
• Utilize DEX aggregators that split trades across multiple pools or exchanges, thereby reducing predictability and impact on any single liquidity pool.

Additionally, developers building DeFi protocols can implement anti-sandwich mechanisms, such as dynamic fee models or privacy-preserving transaction bundling. Some newer DEXs are experimenting with order flow auctions and batched transaction processing to obscure individual trades and make sandwich attacks less effective.

Despite these defenses, no solution is entirely foolproof. As long as DeFi remains transparent and permissionless, there will always be opportunities for exploitation.

Real-World Examples and Observations

Sandwich attacks are not theoretical—they occur frequently in live DeFi environments. Researchers and blockchain analysts have observed numerous instances of these attacks using on-chain analytics tools like Etherscan, Dune Analytics, and Bloxy.

For instance, one widely cited case involved an automated bot systematically executing sandwich attacks on Uniswap v2, generating thousands of dollars in profit daily. The bot monitored large swaps and inserted its own trades strategically, leveraging high gas fees to maintain execution priority.

These examples highlight the profitability and scalability of sandwich attacks when deployed via smart contracts and bots. They also underscore the need for ongoing improvements in transaction privacy and execution security within DeFi protocols.

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Frequently Asked Questions

Q: Can sandwich attacks happen on centralized exchanges?

A: No, sandwich attacks primarily occur on decentralized exchanges due to their open and transparent nature. Centralized exchanges operate with internal order books and do not expose pending transactions publicly, making such attacks impractical.

Q: Are sandwich attacks illegal or unethical?

A: While not explicitly illegal, sandwich attacks are considered unethical by many in the DeFi community. They exploit system mechanics rather than committing fraud, but they harm regular users and undermine trust in decentralized markets.

Q: How can I detect if I’ve been a victim of a sandwich attack?

A: You can check your transaction details on block explorers and look for unusual slippage or sudden price movements around your trade. Tools like MEV-explore and Dune dashboards may also help identify patterns indicative of sandwich attacks.

Q: Do all DEXs suffer from sandwich attacks equally?

A: No, some DEXs are more susceptible due to their fee structures, pool sizes, and transaction visibility. Larger pools with deeper liquidity are generally harder to manipulate, while smaller or newly launched tokens face higher risks.