MEV and Sandwich Attacks: Systemic Challenges in the DeFi Ecosystem

As blockchain technology continues to mature and the ecosystem becomes increasingly complex, Maximum Extractable Value (MEV) has evolved from being initially viewed as an incidental flaw caused by transaction ordering defects into a highly complex, systematic profit extraction mechanism. Among them, sandwich attacks have garnered significant attention due to their unique operational method, becoming one of the most controversial and destructive attack techniques in the DeFi ecosystem.

1. Basic Concepts of MEV and Sandwich Attacks

The Source and Technological Evolution of MEV

MEV originally refers to the additional economic gains that miners or validators can obtain during the block construction process by manipulating the order of transactions, as well as their rights to include or exclude transactions. The theoretical basis lies in the openness of blockchain transactions and the uncertainty of transaction ordering in the memory pool. With the development of tools like flash loans and transaction bundling, the originally sporadic arbitrage opportunities have been gradually amplified, forming a complete profit harvesting chain. MEV has evolved from an initial sporadic event into a systematic and industrialized arbitrage model, which is not only present on Ethereum but also exhibits different characteristics on other public chains.

The principle of sandwich attacks

Sandwich attacks are a typical operation method in MEV extraction. Attackers monitor pending transactions in the memory pool in real-time, submitting their own transactions before and after the target transaction, forming the sequence "Front --- Target Transaction --- Back" to achieve arbitrage through price manipulation. The core steps include:

1. Front-running: An attacker detects large or high slippage trades and immediately submits buy orders to drive up or down the market price.
2. Target Trade Ambush: The target trade is executed after the price is manipulated, resulting in a deviation between the actual transaction price and the expected one, causing the trader to incur additional costs.
3. Post-Trade: The attacker submits a reverse trade immediately after the target transaction to sell previously acquired assets at a high price or buy at a low price, locking in the price difference profit.

2. The Evolution and Current Status of MEV Sandwich Attacks

From sporadic vulnerabilities to systematic mechanisms

MEV attacks initially occurred only occasionally and on a small scale. With the explosive growth of trading volume in the DeFi ecosystem and the development of tools such as high-frequency trading bots and flash loans, attackers have begun to build highly automated arbitrage systems, transforming this attack method into a systematic and industrialized arbitrage model. Through high-speed networks and precise algorithms, attackers can deploy front-running and back-running trades in a very short time, using flash loans to obtain large amounts of capital, and completing arbitrage operations within the same trade.

Attack modes of different platform characteristics

Different blockchain networks exhibit distinct implementation characteristics of sandwich attacks due to differences in design philosophies, transaction processing mechanisms, and validator structures:

• Ethereum: The public and transparent memory pool allows all pending transaction information to be monitored, and attackers often pay higher Gas fees to take precedence in transaction packing order.
• Solana: Despite the absence of a traditional memory pool, some nodes may collude with attackers due to the relatively centralized nature of the validator nodes, leaking transaction data in advance, allowing attackers to quickly capture and exploit target transactions.
• Binance Smart Chain: Lower transaction costs and a simplified structure provide space for arbitrage activities, allowing various bots to employ similar strategies to achieve profit extraction.

Latest Case

On March 13, 2025, a trader on a certain trading platform suffered a loss of up to $732,000 while executing a trade worth approximately 5 SOL, due to a sandwich attack. This incident demonstrates how attackers exploit front-running to seize block packaging rights, inserting trades before and after the target transaction, causing the victim's actual execution price to deviate significantly from expectations.

In the Solana ecosystem, sandwich attacks are not only frequent but also new attack patterns have emerged. Some validators are suspected of colluding with attackers, leaking transaction data to gain advance knowledge of user trading intentions, and thus implementing precise strikes. This has resulted in some attackers on the Solana chain increasing their profits from tens of millions of dollars to over a hundred million dollars in just a few months.

3. The Operating Mechanism and Technical Challenges of Sandwich Attacks

To implement a sandwich attack, the following conditions must be met:

1. Transaction monitoring and capture: Real-time monitoring of unconfirmed transactions in the mempool, identifying transactions with significant price impact.
2. Competition for priority packaging rights: Using higher gas fees or priority fees to take the lead in getting one's transactions packaged into blocks.
3. Precise Calculation and Slippage Control: Accurately calculate the trading volume and expected slippage, while driving price fluctuations and ensuring that the target transaction does not fail due to exceeding the set slippage.

This type of attack not only requires high-performance trading bots and fast network responses but also requires paying high miner bribe fees. In intense competition, multiple bots may simultaneously attempt to seize the same target transaction, further squeezing the profit margins.

4. Industry Response and Prevention Strategies

Strategies for ordinary users to prevent risks

1. Set a reasonable slippage protection: Set a reasonable slippage tolerance based on current market volatility and expected liquidity conditions.
2. Use privacy trading tools: Leverage technologies such as private RPC and order bundling auctions to hide transaction data outside the public memory pool.

Technical Improvement Suggestions at the Ecosystem Level

1. Transaction Ordering and Proposal-Builder Separation (PBS): By separating the responsibilities of block construction and block proposal, it limits the control of a single node over transaction ordering.
2. MEV-Boost and Transparency Mechanisms: Introducing third-party relay services and solutions like MEV-Boost to enhance the transparency of the block construction process.
3. Off-chain order flow auction and outsourcing mechanism: By utilizing the outsourcing of orders and order flow auction mechanism, batch matching of orders is achieved.
4. Smart Contracts and Algorithm Upgrades: By leveraging artificial intelligence and machine learning technologies, enhance real-time monitoring and predictive capabilities for abnormal fluctuations in on-chain data.

V. Conclusion

MEV sandwich attacks have evolved from occasional vulnerabilities into a systemic profit harvesting mechanism, posing a severe challenge to the DeFi ecosystem and the security of user assets. Whether on mainstream trading platforms or emerging public blockchains, the risks of sandwich attacks still exist and are continuously escalating. To protect user assets and market fairness, the blockchain ecosystem needs to work together on technological innovation, trading mechanism optimization, and regulatory collaboration. Only in this way can the DeFi ecosystem find a balance between innovation and risk, achieving sustainable development.