MEV (Maximal Extractable Value) Strategies & Mitigation

Maximal Extractable Value (MEV) is a complex and often debated topic in the blockchain space, particularly in Ethereum and other highly active DeFi chains. It represents the profit that block producers (validators/miners) and sophisticated traders (“searchers”) can extract by manipulating the order, inclusion, or exclusion of transactions within a block.

While some MEV, like certain forms of arbitrage, can be seen as beneficial for market efficiency, other forms, especially those that directly exploit users, are considered predatory.

Common MEV Strategies

Here are some of the most prevalent MEV strategies:

1. Arbitrage:
   • Description: This is the most common and often considered the “healthy” form of MEV. Searchers identify price discrepancies for the same asset across different decentralized exchanges (DEXs). They then execute a series of atomic (single-transaction) trades to buy low on one DEX and sell high on another, profiting from the difference.
   • Impact: While profitable for searchers, it helps to keep asset prices consistent across the ecosystem. However, it can still contribute to higher gas fees as arbitrageurs compete to get their transactions included.
2. Liquidations:
   • Description: In DeFi lending protocols (e.g., Aave, Compound), users collateralize loans. If the value of their collateral falls below a certain threshold, their position becomes “undercollateralized” and eligible for liquidation. Liquidators (bots) monitor these positions and, once eligible, repay a portion of the loan on behalf of the borrower, taking a discounted portion of the collateral as a reward.
   • Impact: Essential for the solvency of lending protocols, as it ensures loans are repaid. However, it’s a competitive MEV game, and liquidators often pay high gas fees to be the first to liquidate.
3. Sandwich Attacks:
   • Description: A malicious and user-harming strategy. A searcher observes a large pending swap transaction in the public mempool. They then execute two of their own transactions:
     • A “front-run” buy order before the victim’s swap, driving the price up.
     • A “back-run” sell order after the victim’s swap, profiting from the price increase caused by the victim’s trade.
   • Impact: The victim’s transaction executes at a worse price (higher slippage), and the attacker profits directly at the user’s expense. This is a significant source of user loss and discourages large trades.
4. Front-running (General):
   • Description: A broader category where an attacker sees a pending transaction in the mempool and submits their own transaction with a higher gas fee to ensure it’s processed before the victim’s.
   • Examples: Buying an NFT before a large public sale is announced (if the transaction ordering can be influenced), or purchasing tokens ahead of a significant market-moving event.
   • Impact: Can lead to unfair outcomes and erode trust in the transparency of the blockchain.
5. Back-running (General):
   • Description: Placing a transaction immediately after a target transaction to profit from its immediate price impact or state change.
   • Examples: Selling tokens that just increased in value due to a large buy order, or claiming rewards from a newly available pool.
   • Impact: Can contribute to price volatility and may reduce the profitability of the original transaction’s initiator.
6. Long-Tail MEV / JIT (Just-In-Time) Liquidity:
   • Description: More complex strategies often involving concentrated liquidity pools (e.g., Uniswap V3). Searchers can add liquidity to a narrow price range just before a large trade, capture the trading fees, and then remove their liquidity immediately after.
   • Impact: While contributing to liquidity, it can also lead to LPs (Liquidity Providers) being “jited” and effectively losing out on fees to sophisticated bots.
7. Time-Bandit Attacks / Reorgs:
   • Description: While rare and costly, this is a theoretical (and sometimes observed) attack where a block producer attempts to re-org (reorganize) past blocks to capture a significant MEV opportunity that was missed or to reverse a transaction. This requires a substantial amount of hashing power (in PoW) or stake (in PoS).
   • Impact: Extremely detrimental to network security and finality, as it undermines the immutability of the blockchain.

MEV Mitigation Techniques

Mitigating MEV is a multi-faceted challenge involving protocol-level changes, application-level design, and user-side practices.

1. Protocol-Level (In-Protocol) Mitigation:

• Proposer-Builder Separation (PBS) / Enshrined PBS (ePBS):
  • Concept: As discussed previously, ePBS aims to separate the role of block proposer from block builder. The builder optimizes for MEV, while the proposer simply picks the highest-bidding block from a competitive market.
  • Impact on Strategies:
    • Democratizes MEV rewards: By creating an open market for block building, solo stakers and smaller validators can earn MEV previously only accessible to large entities. This reduces the centralization pressure from MEV.
    • Reduces “Dark Forest” effect: By moving the transaction ordering competition off-chain (into the builder market), it aims to reduce the public mempool as a source of front-running.
    • Censorship Resistance: A well-designed ePBS with many competing builders makes it harder for any single entity to censor transactions, as other builders can include them and outbid the censoring builder.
    • Still allows extraction: PBS doesn’t eliminate MEV; it aims to redistribute its profits more fairly and make its extraction less harmful to users by making the competition for block space more efficient and transparent.
• Fair Sequencing Services (FSS) / Encrypted Mempools:
  • Concept: These experimental approaches aim to provide a more “fair” ordering of transactions before they enter the public mempool or are processed by builders.
  • How it works: Transactions are submitted in an encrypted state and only decrypted and ordered after a consensus has been reached on their sequence, or they are processed in batches at a uniform clearing price.
  • Impact on Strategies: Directly combats front-running, sandwich attacks, and other reordering MEV by making it impossible for searchers to see and react to pending transactions. Projects like Shutter Network are working on this.
• Batch Auctions:
  • Concept: Instead of processing transactions individually, a batch of transactions is collected over a period of time and executed at a single, uniform clearing price.
  • Impact on Strategies: Eliminates sandwich attacks and front-running by removing the ability to manipulate prices within a single block. All trades in the batch settle at the same price.
  • Trade-offs: Can introduce latency and potentially alter the user experience for fast-paced trading.

2. Application-Level Mitigation:

• Tight Slippage & Deadline Checks:
  • For Users: When performing swaps on DEXs, users should set a low “slippage tolerance” (the maximum acceptable price deviation) and a “transaction deadline.”
  • Impact on Strategies: While it doesn’t prevent MEV, it limits the damage from sandwich attacks. If the price moves beyond the set slippage, the transaction reverts, protecting the user from significant loss. The deadline prevents transactions from being executed much later at an unfavorable price.
  • For Developers: Smart contracts should always enforce amountOutMin (or amountInMax) for swaps and a deadline parameter to protect users.
• Commit-Reveal Schemes:
  • Concept: For sensitive actions (e.g., bidding in an auction, revealing a secret), users first commit a “hash” of their action (the “commit” phase), which is public but doesn’t reveal the details. Later, in a separate transaction, they “reveal” the actual action, which is then verified against the committed hash.
  • Impact on Strategies: Prevents front-running because the actual action is hidden until the reveal phase, making it impossible for bots to react in advance.
  • Trade-offs: Adds an extra transaction and increases complexity for users. Best for high-value or privacy-critical operations.
• Specialized DEX Designs (e.g., CoW Protocol / Intent-Based Systems):
  • Concept: Protocols like CoW Protocol use a “solver” network to find the best possible trade execution for users, often by matching orders directly without routing through AMM pools (Coincidence of Wants – CoWs). If no CoW is found, it routes to AMMs with MEV protection.
  • Impact on Strategies: Can significantly reduce MEV extraction by optimizing order flow and minimizing reliance on public mempools. It effectively abstracts away the complexities of MEV for the end-user.

3. User-Level Mitigation:

• Private Transaction Relays (e.g., Flashbots Protect RPC, mevblocker.io):
  • Concept: Instead of broadcasting transactions directly to the public mempool (where MEV bots constantly monitor), users can send their transactions to a private relay. These relays then bundle the transactions and directly submit them to block builders/validators for inclusion.
  • Impact on Strategies:
    • Prevents front-running/sandwich attacks: The transaction is not exposed to the public mempool, so bots cannot see it in advance.
    • Potentially better execution: By going through a private channel, users might get better execution prices as their transactions are included directly in a block without being subjected to mempool competition.
    • MEV Rebates: Some private RPCs (like Flashbots Protect via MEV-Share) allow users to share some of the extracted MEV with the searchers who execute their transactions, effectively turning predatory MEV into a rebate.
• Avoid Illiquid Pairs:
  • Concept: Trading on very illiquid pairs makes trades more susceptible to price manipulation and larger slippage, making them prime targets for sandwich attacks.
  • Impact on Strategies: By sticking to liquid pairs, users naturally reduce the potential MEV profit for attackers, making them less attractive targets.
• Stay Informed:
  • Concept: The MEV landscape is constantly evolving. Users should keep up with new mitigation tools, wallet features, and best practices.

The Role of MEV-Boost in Mitigation:

MEV-Boost is the current implementation of out-of-protocol PBS. While it doesn’t eliminate MEV, it significantly mitigates its centralizing effects and democratizes its distribution:

• Democratizes MEV access for validators: It allows even small, solo stakers to earn a share of MEV revenue by connecting to a competitive marketplace of builders. This makes staking more profitable and helps prevent large staking pools from monopolizing MEV.
• Shifts bidding off-chain: It moves the “priority gas auction” (PGA) from the public mempool (where users bid against bots) to an off-chain auction between builders and proposers. This can reduce overall network congestion caused by failed MEV transactions and frantic bidding.
• Enables privacy for users (via relays): Users can send transactions to relays (like Flashbots Protect) which then go to builders connected to MEV-Boost. This bypasses the public mempool, offering front-running protection.

However, as discussed, MEV-Boost’s reliance on centralized relays is a current vulnerability that enshrined PBS (ePBS) aims to address.

In conclusion, MEV is an inherent aspect of transparent, open blockchains. While some forms are beneficial, the predatory aspects necessitate robust mitigation strategies. The Ethereum ecosystem is actively working on multiple fronts—from foundational protocol changes like ePBS and FSS to application-level design and user tools—to minimize its negative impacts and ensure a fairer, more decentralized, and efficient network for all participants.