MEV Sandwich Attack: From Occasional Vulnerabilities to Systemic Threats

With the continuous development of blockchain technology and the increasing complexity of the ecosystem, MEV (Maximum Extractable Value) has evolved from being initially regarded as an incidental issue caused by transaction ordering flaws into a highly complex systematic profit extraction mechanism. Among them, sandwich attacks have garnered significant attention due to their unique operational methods, becoming one of the most controversial and destructive attack techniques in the DeFi ecosystem.

1. Basic Concepts of MEV and Sandwich Attacks

The Origin and Technological Evolution of MEV

MEV originally refers to the additional economic benefits obtained by miners or validators through manipulating the transaction order, inclusion or exclusion rights during the block construction process. This concept is based on the transparency of blockchain transactions and the uncertainty of transaction ordering in the memory pool. With the emergence of tools such as flash loans and transaction bundling, previously sporadic arbitrage opportunities have been amplified, forming a complete profit extraction chain. MEV has evolved from an occasional event into a systematic and industrialized arbitrage model, which exists not only on Ethereum but also presents different characteristics on other public chains.

Sandwich attack principle

The sandwich attack is a typical method in MEV extraction. Attackers monitor the mempool transactions in real-time, submitting their own transactions before and after the target transaction, forming a "front-running - target transaction - back-running" sequence to achieve arbitrage through price manipulation. The core steps include:

1. Front-running: Submit buy orders immediately to influence market prices after detecting large or high slippage trades.
2. Target trade execution: Executed after the price is manipulated, resulting in additional costs for traders.
3. Post-Trade: Submit a reverse trade immediately after the target trade to lock in the price difference profit.

This method of operation is akin to "sandwiching" the target transaction between two transactions, hence the name "sandwich attack".

2. The Evolution and Current Status of MEV Sandwich Attacks

From sporadic vulnerabilities to systemic mechanisms

MEV attacks were initially sporadic, small-scale events within blockchain networks. However, with the surge in trading volume in the DeFi ecosystem and the development of tools like high-frequency trading bots and flash loans, attackers have begun to construct highly automated arbitrage systems. This has transformed the attack methods from sporadic events to systematic, industrialized arbitrage models. Currently, the profit from a single transaction can reach hundreds of thousands or even millions of dollars, marking the MEV mechanism as a mature profit harvesting system.

Characteristics of attacks on different platforms

Due to differences in design concepts, transaction processing mechanisms, and validator structures in blockchain networks, sandwich attacks exhibit different characteristics across different platforms:

• Ethereum: Attackers typically pay higher gas fees to prioritize their transactions in the packing order. To address this issue, the Ethereum ecosystem has introduced mechanisms such as MEV-Boost and proposer-builder separation (PBS).

• Solana: Although there is no traditional memory pool, due to the relatively centralized nature of validator nodes, some nodes may collude with attackers to leak transaction data in advance, resulting in frequent attacks and substantial profits.

• Binance Smart Chain (BSC): The lower transaction costs and simplified structure provide space for arbitrage activities, with various bots employing similar strategies to realize profit extraction.

Latest Case

On March 13, 2025, during a transaction on a certain DEX, a trader suffered a loss of up to $732,000 when conducting a transaction worth approximately 5 SOL due to a sandwich attack. The attacker exploited front-running to seize block packaging rights, inserting trades before and after the target transaction, causing the victim's actual execution price to significantly deviate 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 by leaking transaction data to gain prior knowledge of users' trading intentions, allowing them to implement precise strikes. As a result, some attackers on the Solana chain have seen their profits grow from tens of millions of dollars to over a hundred million dollars in a short period.

These data and cases indicate that MEV sandwich attacks have become a systemic issue arising alongside the growth in transaction volumes and increasing complexity of blockchain networks.

3. The Mechanism of Sandwich Attacks and Technical Challenges

As the market trading volume continues to expand, the frequency of MEV attacks and the profit per transaction are on the rise. The following conditions must be met to implement a sandwich attack:

1. Transaction Monitoring and Capture: Real-time monitoring of unconfirmed transactions in the memory pool to identify transactions with significant price impact.
2. Priority gas fee competition: Use higher gas fees or priority fees to ensure your transaction is executed before or after the target transaction.
3. Accurate Calculation and Slippage Control: Accurately calculate trading volume and expected slippage, driving price fluctuations while ensuring that the target trade 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 necessitates paying high miner fees to ensure transaction priority. In intense competition, multiple bots may simultaneously target the same transaction, further compressing profit margins. These technical and economic barriers constantly prompt attackers to update their algorithms and strategies, while also providing a theoretical basis for the design of preventive mechanisms.

IV. Industry Response and Prevention Strategies

Prevention strategies for ordinary users

1. Set a reasonable slippage protection: Based on market volatility and expected liquidity conditions, set a reasonable slippage tolerance to avoid losses due to improper settings.
2. Use privacy trading tools: By utilizing private RPC, order bundling auctions, and other technologies, transaction data is hidden outside of the public memory pool, reducing the risk of being attacked.

Suggestions for technological improvements at the ecosystem level

1. Transaction Ordering and Proposer-Builder Separation (PBS): Limiting the control of a single node over transaction ordering to reduce the possibility of validators extracting MEV by exploiting ordering advantages.
2. MEV-Boost and Transparency Mechanisms: Introduce third-party relay services and solutions like MEV-Boost to enhance the transparency and competitiveness of the block construction process.
3. Off-chain Order Flow Auction and Outsourcing Mechanism: By outsourcing orders and order flow auctions, batch matching is achieved, enhancing price efficiency and reducing the likelihood of individual operations.
4. Smart Contracts and Algorithm Upgrades: Utilize artificial intelligence and machine learning technologies to enhance real-time monitoring and predictive capabilities for abnormal fluctuations in on-chain data, helping users avoid risks.

As the DeFi ecosystem expands, MEV and related attack methods will face more technical countermeasures and economic games. In the future, in addition to technical improvements, how to reasonably allocate economic incentives while ensuring decentralization and network security will become an important topic of concern in the industry.

V. Conclusion

MEV sandwich attacks have evolved from sporadic vulnerabilities into a systematic profit extraction mechanism, posing a serious challenge to the DeFi ecosystem and the security of user assets. Recent cases indicate that the risk of sandwich attacks on mainstream platforms continues to escalate. To protect user assets and market fairness, the blockchain ecosystem must work together in technological innovation, optimization of trading mechanisms, and regulatory collaboration. Only in this way can the DeFi ecosystem achieve a balance between innovation and risk, ensuring sustainable development.