MEV and Sandwich Attacks: Emerging Threats in the Blockchain Ecosystem

As blockchain technology continues to mature and the ecosystem becomes increasingly complex, MEV (Maximum Extractable Value) has evolved from being initially viewed as an occasional vulnerability caused by transaction ordering flaws into a highly complex and systemic 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 Evolution of MEV

MEV, originally known as miner-extractable value, refers to the additional economic benefits that miners or validators in a Blockchain network can obtain by manipulating the order of transactions, including or excluding certain transactions, during the block construction process. The theoretical foundation of this concept is based on the transparency of Blockchain transactions and the uncertainty of transaction ordering in the mempool.

With the development of tools such as flash loans and transaction bundling, the originally sporadic arbitrage opportunities have gradually been amplified, forming a complete profit harvesting chain. MEV has evolved from an initial sporadic event into a systematic and industrialized arbitrage model, which not only exists on Ethereum but also presents different characteristics on other public chains.

Sandwich Attack Principle

Sandwich attacks are a typical method of MEV extraction. Attackers monitor transactions in the memory pool in real-time and submit their own transactions before and after the target transaction, forming the sequence of "front-running transaction - target transaction - back-running transaction," achieving arbitrage through price manipulation. The core steps include:

1. Front-running: The attacker detects large or high-slippage trades and immediately submits buy orders to influence market prices.

2. Target transaction squeeze: The target transaction is executed after the price is manipulated, resulting in a deviation between the actual transaction price and the expected price.

3. Post-trade: The attacker submits a reverse trade immediately after the target trade to lock in the price difference profit.

This operation method is like "sandwiching" the target transaction between two other transactions, hence it is called a "sandwich attack".

2. The Evolution and Current Status of MEV Sandwich Attacks

From sporadic vulnerabilities to systemic mechanisms

MEV attacks were initially a sporadic phenomenon in blockchain networks, relatively small in scale. However, with the surge in trading volume in the DeFi ecosystem and the development of tools such as high-frequency trading bots and flash loans, attackers began to build highly automated arbitrage systems. This transformed MEV from isolated incidents into a systematic and industrialized arbitrage model.

By leveraging high-speed networks and sophisticated algorithms, attackers can deploy front-running and back-running transactions in a very short time, using flash loans to acquire large amounts of capital, and completing arbitrage operations within the same transaction. Currently, there have been cases on certain platforms where a single transaction has yielded profits of hundreds of thousands or even millions of dollars, marking the MEV mechanism's evolution into a mature profit harvesting system.

Characteristics of attacks on different platforms

Due to the differences in design concepts, transaction processing mechanisms, and validator structures among various Blockchain networks, sandwich attacks exhibit unique implementation characteristics on different platforms:

• A well-known public Blockchain: The publicly transparent memory pool allows all pending transaction information to be monitored. Attackers usually pay higher Gas fees to gain priority in transaction packaging order. To address this issue, multiple new mechanisms have been introduced within the ecosystem to reduce the risk of a single node manipulating transaction ordering.

• A certain high-performance public blockchain: Although this chain does not have a traditional memory pool, due to the relatively centralized validator nodes, some nodes may collude with attackers to leak transaction data in advance. This allows attackers to quickly capture and exploit target transactions, leading to frequent sandwich attacks in this ecosystem with substantial profits.

• A certain smart contract platform: Although its ecological maturity differs from that of some mainstream public chains, the lower transaction costs and simplified structure provide space for arbitrage activities, and various bots can similarly adopt similar strategies to extract profits in this environment.

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

Latest Cases and Data

On March 13, 2025, a notable incident occurred on a certain DEX platform. A trader incurred a loss of up to $732,000 during a transaction worth approximately 5 SOL due to a sandwich attack. This case illustrates how attackers exploit front-running to seize block packaging rights, inserting transactions before and after the target transaction, causing the victim's actual execution price to deviate significantly from expectations.

In a certain high-performance public blockchain ecosystem, sandwich attacks not only occur frequently but also new attack patterns have emerged. There are signs that some validators may collude with attackers by leaking transaction data to gain early knowledge of user trading intentions, thereby implementing precise strikes. This has caused the profits of some attackers on the chain to grow 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 incidental events, but rather exhibit systematic and industrial characteristics with the increasing transaction volume and complexity of blockchain networks.

3. The Operating Mechanism and Technical Challenges of Sandwich Attacks

With the continuous expansion of overall market trading volume, the frequency of MEV attacks and the profit per transaction are on the rise. On certain platforms, the cost-to-revenue ratio of sandwich attacks has even reached a high level. To implement a sandwich attack, the following conditions must be met:

1. Transaction monitoring and capturing: Attackers must monitor the transactions pending confirmation in the memory pool in real-time and identify those transactions that have a significant price impact.

2. Competition for priority packing rights: By utilizing higher gas fees or priority fees, attackers can prioritize their transactions to be included in the Block, ensuring execution before and after the target transaction.

3. Accurate Calculation and Slippage Control: When executing front and back trades, it is essential to accurately calculate the trading volume and expected slippage, ensuring price fluctuations 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 necessitates paying high miner bribe fees (e.g., increasing gas fees) to ensure transaction priority. These costs constitute the main expenses of the attacker, and in intense competition, multiple bots may attempt to seize the same target transaction simultaneously, further squeezing profit margins.

These technologies and economic barriers continuously compel attackers to update their algorithms and strategies in a fiercely competitive environment, while also providing a theoretical basis for the design of preventive mechanisms.

4. Industry Response and Prevention Strategies

Suggestions for ordinary users' precautions

1. Set a reasonable slippage protection: When trading, you should set a reasonable slippage tolerance based on current market volatility and expected liquidity conditions to avoid transaction failure due to setting it too low or being maliciously squeezed due to setting it too high.

2. Use privacy trading tools: By leveraging private RPC, order packing auctions, and other technical means, hide transaction data outside of the public memory pool to reduce the risk of being attacked.

Technical improvement suggestions at the ecosystem level

1. Separation of transaction ordering and proposer-builder: By separating the responsibilities of block construction from block proposal, the control of a single node over transaction ordering is limited, reducing the likelihood of validators exploiting the ordering advantage for MEV extraction.

2. Transparency mechanism: Introduce third-party relay services and related solutions to make the Block construction process open and transparent, reduce dependence on a single node, and enhance overall competitiveness.

3. Off-chain order flow auction and outsourcing mechanism: By utilizing the outsourcing orders and order flow auction mechanism, batch matching of orders is achieved, which not only enhances the possibility for users to obtain the best price but also makes it difficult for attackers to operate individually.

4. Smart Contracts and Algorithm Upgrades: Utilizing artificial intelligence and machine learning technologies to enhance real-time monitoring and predictive capabilities of abnormal fluctuations in on-chain data, helping users to avoid risks in advance.

As the DeFi ecosystem continues to expand, trading volume and trading complexity are on the rise, and MEV and its related attack methods will face more technical confrontations and economic games. 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 extraction 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 risk of sandwich attacks still exists and continues to escalate on platforms such as mainstream DEXs and high-performance public chains. To protect user assets and market fairness, the blockchain ecosystem needs to work together on technological innovation, transaction mechanism optimization, and regulatory collaboration. Only in this way can the DeFi ecosystem find a balance between innovation and risk, achieving sustainable development.