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MEV Attacks: Understanding and Protection

Updated: Jun 9

In the fast-paced world of DeFi, transactions are in a race to be included in the next block.


This competitive environment has led to the rise of Maximal Extractable Value (MEV) bots, which exploit opportunities in the mempool—the waiting area for unconfirmed transactions.




MEV bots use various strategies to exploit pending transactions:

  • Front-Running: If a bot sees a large buy order in the mempool, it can place a similar order with a higher gas fee to ensure its transaction gets processed first. The bot buys the token at a lower price and sells it at a higher price after the original transaction.

  • Back-Running: Bots place an order right after a large transaction to benefit from the price change caused by the initial trade.

  • Sandwich Attacks: This strategy involves placing one order before and one after a detected profitable trade, effectively "sandwiching" the transaction to maximize profit.

These strategies can lead to increased costs and reduced profits for regular users, making MEV attacks a significant concern in DeFi.



Good MEV vs. Bad MEV:

It’s important to differentiate between good MEV (arbitraging) and bad MEV (sandwich attacks). 

Good MEV can provide liquidity and improve market efficiency, while bad MEV exploits users and distorts the market. 


Detecting Good MEV

Good MEV typically involves arbitrage opportunities, where traders exploit price differences between various decentralized exchanges (DEXs) to make a profit.


Detecting good MEV involves:

Scanning Swap Events: By analyzing past blocks for token swap events on DEXs like Uniswap and Balancer, arbitrage opportunities can be identified. These events show tokens being exchanged, which can be linked to an arbitrage cycle.

Linking Swaps: Swaps are connected when one swap's output token is the next's input token. Arbitrage is confirmed when a sequence of swaps forms a cycle, bringing the final output token back to the initial input token.


Detecting Bad MEV

Bad MEV, such as sandwich attacks, exploits users by manipulating the order of transactions.


Detecting bad MEV involves:

Analyzing Token Transfer Events: By examining past blocks for token transfers, it's possible to identify patterns typical of sandwich attacks.

Identifying Attack Sequences: In sandwich attacks, attackers execute a transaction before and after a victim's transaction. Detecting these involves finding pairs of transactions where the same amount of tokens is transferred in and out around a victim's trade.



How to Protect Against MEV Attacks:

Platforms like JupiterExchange and MultiDex AI have developed protective tools to combat MEV attacks. JupiterExchange's Tipping via Jito Bundles helps Solana users hide transactions from MEV bots. MultiDex AI adds MEV protection by creating private pools, refining order algorithms, and implementing slippage controls to ensure fair trade.

(always verify the authenticity of the tools and resources you use.)


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