MEV Sandwich Attack: From Occasional Vulnerabilities to Systematic Profit Harvesting Mechanism

In today's rapidly evolving blockchain technology and increasingly complex ecosystem, MEV (Maximum Extractable Value) has gradually evolved from an initially perceived incidental vulnerability caused by transaction ordering flaws into a highly complex and systematic profit extraction mechanism. Among them, sandwich attacks have gained significant attention for utilizing transaction ordering rights to insert their own transactions before and after target transactions, manipulating asset prices to achieve low buy and high sell arbitrage, making it one of the most controversial and destructive attack methods in the DeFi ecosystem.

1. Basic Concepts of MEV and Sandwich Attacks

The Origin and Technological Evolution of MEV

MEV (Maximum Extractable Value) originally referred to the additional economic benefits that miners or validators could obtain during the block construction process by manipulating the order of transactions and the rights to include or exclude them. Its theoretical foundation lies in the transparency of blockchain transactions and the uncertainty of transaction ordering in the memory pool. With the development of tools such as flash loans and transaction packaging, the originally sporadic arbitrage opportunities have gradually been amplified, forming a complete profit extraction chain. MEV has evolved from an initial sporadic event into a systematic and industrialized arbitrage model, existing not only on Ethereum but also exhibiting different characteristics across multiple public chains.

The principle of sandwich attacks

Sandwich attacks are a typical operational means in MEV extraction. Attackers leverage their real-time monitoring capabilities of the memory pool transactions to submit trades before and after the target transaction, forming a "front-run --- target transaction --- back-run" sequence of trades, achieving arbitrage through price manipulation. Its core principles include:

• Front-running: When an attacker detects a large or high-slippage trade, they immediately submit a buy order to push up or down the market price.

• Target Trading Trap: The target trade is executed after the price has been manipulated, resulting in a significant deviation between the actual execution price and the expected price, causing traders to incur additional costs.

• Post-trade: Following the target trade, the attacker submits a reverse trade, selling previously acquired assets at a high price or buying at a low price, locking in the profit from the price difference.

2. The Evolution and Current Status of MEV Sandwich Attacks and Case Studies

From sporadic vulnerabilities to systematic mechanisms

MEV attacks initially occurred occasionally due to inherent shortcomings in the transaction ordering mechanism, and were of small scale. With the surge in trading volume of the DeFi ecosystem and the development of tools like high-frequency trading bots and flash loans, attackers began to build highly automated arbitrage systems, transforming this attack method into a systematic and industrialized arbitrage model. Through high-speed networks and sophisticated 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 transaction. Currently, there have been cases on multiple platforms where a single transaction has yielded profits of hundreds of thousands or even millions of dollars, marking the evolution of the MEV mechanism from an occasional vulnerability to a mature profit harvesting system.

attack patterns of different platform characteristics

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

• Ethereum: The public and transparent memory pool allows all pending transaction information to be monitored. Attackers often pay higher Gas fees to seize the transaction packing order. The Ethereum ecosystem has introduced mechanisms such as MEV-Boost and proposer-builder separation (PBS) to reduce the risk of a single node manipulating transaction ordering.

• Solana: Although it does not have a traditional memory pool, the validator nodes are relatively concentrated, and some nodes may collude with attackers to leak transaction data in advance, allowing attackers to quickly capture and exploit target transactions, resulting in frequent sandwich attacks with substantial profits.

• Binance Smart Chain (BSC): Although there are differences in ecological maturity compared to Ethereum, the lower transaction costs and simplified structure provide space for arbitrage activities, and various bots can similarly adopt strategies to achieve profit extraction.

The differences in this cross-chain environment lead to unique attack methods and profit distribution on different platforms, while also raising higher requirements for prevention strategies.

Latest data and case studies

A case from a trading platform: On March 13, 2025, during a transaction on a certain DEX, a trader executed a trade worth approximately 5 SOL, but suffered asset losses of up to $732,000 due to a sandwich attack. This incident shows that attackers exploit front-running to seize block packing rights, inserting transactions before and after the target transaction, causing the victim's actual transaction price to deviate significantly from expectations.

The Continuous Evolution on the Solana Chain: 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 advance knowledge of user transaction intentions, thereby implementing precise strikes. As a result, the profits of some attackers on the Solana chain have increased from tens of millions of dollars to over a hundred million dollars in just a few months.

These data and cases indicate that MEV sandwich attacks are no longer isolated incidents, but are showing systematic and industrial characteristics along with the increasing transaction volume and complexity of blockchain networks.

3. The Operating Mechanism and Technical Challenges of Sandwich Attacks

As the overall market trading volume continues to expand, the frequency of MEV attacks and the profits from individual transactions are on the rise, with some platforms seeing the cost-to-revenue ratio of sandwich attack transactions reaching high levels. Implementing a sandwich attack requires meeting the following conditions:

• Transaction Monitoring and Capture: Attackers must monitor the mempool for unconfirmed transactions in real-time, identifying those transactions that have a significant price impact.

• Competition for priority packaging rights: Attackers use higher gas fees or priority fees to rush their transactions into blocks, ensuring execution before and after the target transaction.

• Precise calculation and slippage control: When executing pre-position and post-position trades, it is essential to accurately calculate the trading volume and expected slippage, ensuring that price fluctuations are driven while also ensuring that the target trade does not fail due to exceeding the set slippage.

Implementing such an attack not only requires high-performance trading bots and fast network responses but also involves paying high miner bribes to ensure transaction priority. These costs constitute the main expenditure for attackers, and in a highly competitive environment, multiple bots may simultaneously attempt to seize the same target transaction, further compressing profit margins. These technical and economic barriers continuously drive attackers to update their algorithms and strategies in a fiercely competitive landscape, while also providing a theoretical basis for the design of prevention mechanisms.

4. Industry Response and Prevention Strategies

Prevention strategies for ordinary users

• Set reasonable slippage protection: When submitting a trade, you should reasonably set the slippage tolerance based on current market volatility and expected liquidity conditions, to avoid trade failures due to overly low settings, and also to prevent being maliciously squeezed due to overly high settings.

• Use privacy trading tools: With the help of private RPC, order bundling auctions, and other technical means, hide trading data outside of the public memory pool to reduce the risk of being attacked.

suggestions for technical improvements at the ecosystem level

• Transaction Ordering and Proposer-Builder Separation (PBS): By separating the responsibilities of block construction and block proposal, it limits a single node's control over transaction ordering, reducing the likelihood of validators exploiting ordering advantages for MEV extraction.

• MEV-Boost and Transparency Mechanisms: Introducing third-party relay services and schemes such as MEV-Boost to make the block construction process open and transparent, reducing reliance on a single node and enhancing overall competitiveness.

• Off-chain order flow auction and outsourcing mechanism: By leveraging the outsourcing of orders and order flow auction mechanisms, bulk matching of orders is achieved, which not only enhances the likelihood of users obtaining the best prices but also makes it difficult for attackers to operate individually.

• Smart Contract and Algorithm Upgrade: Utilizing artificial intelligence and machine learning technologies to enhance real-time monitoring and predictive capabilities for abnormal fluctuations in on-chain data, helping users to avoid risks in advance.

As the DeFi ecosystem continues to expand, trading volume and complexity of transactions are on the rise, which will lead to more technical confrontations and economic games regarding MEV and its related attack methods. In the future, in addition to improvements in technical means, how to reasonably allocate economic incentives while ensuring decentralization and network security will become an important issue of common concern in the industry.

V. Conclusion

MEV sandwich attacks have evolved from an initial sporadic vulnerability into a systematic profit harvesting mechanism, posing a severe challenge to the DeFi ecosystem and the security of user assets. The latest cases and data from 2025 indicate that the risks of sandwich attacks still exist and are continuously escalating, whether on mainstream DEXs or public chains like Solana. To protect user assets and market fairness, the blockchain ecosystem needs to work together in terms of 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.