Detailed Instructions

Maximum Extractable Value (MEV) is the profit that can be extracted by reordering, inserting, or censoring transactions within a block, beyond the standard block reward and gas fees. It arises from the inherent latency and transparency of public blockchains. For users, MEV primarily manifests as increased costs and execution uncertainty. When bots compete to capture arbitrage or liquidation opportunities, they drive up gas prices for everyone. This creates a priority gas auction (PGA), where the highest bidder gets their transaction ordered favorably. Users may also suffer from sandwich attacks, where their trades are front-run and back-run, resulting in worse execution prices. The net effect is a less predictable and often more expensive experience, where sophisticated actors profit at the expense of regular users.

• Impact on Cost: Monitor gas price spikes on platforms like Etherscan during high network activity; these are often MEV-related.
• Impact on Fairness: Recognize that your transaction's placement is not guaranteed, potentially leading to failed trades or missed opportunities.
• Systemic Risk: Large-scale MEV can destabilize protocols, as seen in flash loan-enabled exploits.

Tip: Use a wallet with built-in MEV protection (like some RPC endpoints) to help mitigate these risks.

Detailed Instructions

Front-running involves a searcher or bot detecting a profitable pending transaction in the mempool and submitting their own transaction with a higher gas fee to ensure it is executed first. This strategy directly impacts users by causing their transactions to fail or execute at a worse price. The searcher uses mempool surveillance tools to identify transactions like large DEX swaps or NFT purchases. Upon finding a target, they copy the transaction logic but with a higher maxPriorityFeePerGas to jump the queue. The profit comes from, for example, buying an asset before the user's large buy order, which drives the price up, and then selling it immediately after.

• Step 1: Surveillance: Run a node or use a service like Alchemy or Infura to stream pending transactions. Filter for specific method signatures like swapExactTokensForETH.
• Step 2: Simulation: Use a tool like eth_call or Tenderly to simulate the target transaction's impact on pool reserves and calculate potential profit.
• Step 3: Execution: If profitable, craft a similar transaction with a 10-20% higher gas price. For a swap, the searcher's transaction might look like:

solidityCopy
// Simplified front-run transaction
IUniswapV2Router(0x7a250d5630B4cF539739dF2C5dAcb4c659F2488D).swapExactTokensForETH(
    amountIn, 
    amountOutMin, 
    path, 
    address(this), 
    deadline
);

• Step 4: Submission: Broadcast the transaction via a private transaction pool or a high-gas RPC to increase chances of inclusion before the victim's.

Tip: Users can use Flashbots RPC (https://rpc.flashbots.net) to submit transactions privately, bypassing the public mempool and avoiding front-runners.

Detailed Instructions

A sandwich attack is a specific, harmful form of MEV where a searcher places one transaction before and one after a victim's trade to profit from the price impact. It directly reduces the user's received output tokens. The attacker first front-runs the victim's buy order with their own buy, increasing the asset's price in the liquidity pool due to the constant product formula (x * y = k). The victim's trade then executes at this inflated price. Immediately after, the attacker back-runs the victim by selling the asset they just bought, profiting from the price difference.

• Step 1: Identify Target: Find a pending DEX swap transaction (e.g., on Uniswap V2) for a significant amount (e.g., >10 ETH worth) in the mempool.
• Step 2: Calculate Parameters: Determine the optimal amount to trade. Use a formula or bot to solve for the input amount that maximizes profit given the victim's trade size and pool reserves. The profit is often a percentage of the victim's trade value.
• Step 3: Execute Front-run Transaction: Send a buy transaction for the same asset as the victim, with a higher gas fee. For example, if the victim is swapping 100 ETH for DAI, the attacker might first swap 50 ETH for DAI.
• Step 4: Victim's Transaction Executes: The victim's swap occurs, further moving the price.
• Step 5: Execute Back-run Transaction: The attacker immediately sells the DAI they acquired in step 3 back into ETH, capturing the price difference. The entire sequence must be bundled into a single block.

Tip: Users can set lower slippage tolerances (e.g., 0.5%) and use DEX aggregators that split trades across multiple pools to make sandwich attacks less profitable.

Detailed Instructions

Arbitrage is a less directly harmful but very common MEV strategy that involves buying an asset on one DEX where it's cheaper and simultaneously selling it on another where it's more expensive, profiting from the price difference. While this helps align prices across markets (a positive externality), the competition to perform it drives up gas costs. Searchers use sophisticated bots that monitor price feeds across multiple DEXs like Uniswap, SushiSwap, and Curve. When a discrepancy exceeding the cost of gas and fees is detected, the bot executes a flash loan to fund the trade, performing the entire arbitrage loop in a single transaction.

• Step 1: Price Monitoring: Continuously poll the getReserves() function of multiple liquidity pools for the same token pair (e.g., WETH/USDC on Uniswap V2 and SushiSwap). Calculate the implied price from the reserve ratios.
• Step 2: Opportunity Identification: Identify a price difference greater than the estimated transaction cost. For example, if 1 WETH = 3000 USDC on DEX A but 3010 USDC on DEX B, a 10 USDC gross profit exists per ETH.
• Step 3: Flash Loan Execution: Use a protocol like Aave or dYdX to borrow the required capital with no upfront collateral, as the loan will be repaid within the same transaction. A typical flow involves:

solidityCopy
// Pseudocode for a simple arbitrage
function executeArbitrage(address tokenA, address tokenB, uint amount) external {
    // 1. Take flash loan of `amount` of tokenA
    // 2. Swap tokenA for tokenB on DEX A (cheaper)
    // 3. Swap tokenB back to tokenA on DEX B (more expensive)
    // 4. Repay flash loan + fee
    // 5. Keep profit in tokenA
}

• Step 4: Transaction Bundling: The searcher often bundles this transaction with a high gas bid to a block builder or validator to ensure inclusion.

Tip: While arbitrage is economically beneficial, users trading during volatile periods may experience rapid price changes and higher slippage due to this intense bot activity.

Detailed Instructions

Liquidation MEV involves searchers repaying under-collateralized loans on lending protocols like Aave or Compound to claim a liquidation bonus (or penalty paid by the borrower). When a borrower's health factor falls below 1 (e.g., due to collateral value dropping), their position becomes eligible for liquidation. Searchers run bots that monitor these health factors across thousands of positions. The first searcher to successfully liquidate a position earns a bonus, typically 5-15% of the repaid amount. This creates a competitive race that can burden the borrower with additional fees but is crucial for protocol solvency.

• Step 1: Monitoring Positions: Track the getAccountLiquidity() function for user addresses on Compound, or the getUserAccountData() function on Aave V2, to check health factors in real-time.
• Step 2: Identifying Targets: Flag any address where the health factor drops below the threshold (e.g., 1.0). For example, a position with 100 ETH collateral and 200,000 DAI debt might become liquidatable if ETH price drops sharply.
• Step 3: Executing the Liquidation: Upon detection, the searcher sends a transaction calling the protocol's liquidation function. On Compound V2, this involves:

solidityCopy
// Example call to liquidate a COMP borrow
Comptroller(0x3d9819210A31b4961b30EF54bE2aeD79B9c9Cd3B).liquidateBorrow(
    address(borrower), 
    repayAmount, 
    address(cTokenCollateral)
);

The searcher repays part of the debt (e.g., in DAI) and receives a proportional amount of the borrower's collateral (e.g., ETH), plus the bonus.

• Step 4: Profit Realization: The searcher immediately sells the seized collateral on a DEX to realize profit, often using a flash loan to fund the initial repayment.

Tip: Borrowers should monitor their health factors closely and maintain a safe collateral buffer to avoid liquidation, especially during market volatility.

Detailed Instructions

Maximum Extractable Value (MEV) is the total value that can be extracted by reordering, including, or censoring transactions within blocks, beyond standard block rewards and gas fees. It arises from the transparent and deterministic nature of blockchain mempools. To quantify MEV, you must analyze public data.

• Sub-step 1: Use MEV tracking dashboards. Visit sites like EigenPhi or Flashbots' mev-explore to see real-time data on arbitrage, liquidations, and sandwich attacks.
• Sub-step 2: Query historical data. Use a service like Dune Analytics. For example, a query might show that total extracted MEV on Ethereum exceeded $1.2 billion in 2023.
• Sub-step 3: Identify common MEV strategies. These include DEX arbitrage (profiting from price differences), liquidations (triggering and claiming collateral), and sandwich attacks (frontrunning and backrunning a user's trade).

Tip: The scale of MEV is a direct indicator of network congestion and economic activity. High MEV often correlates with high gas fees and poor user experience.

Detailed Instructions

MEV directly harms users by increasing costs and causing transaction failures. Gas price auctions between searchers drive up network fees for everyone. The most direct impact is through sandwich attacks, where a user's swap is exploited.

• Sub-step 1: Simulate a sandwich attack. A user submits a swap of 10 ETH for a token, raising its price. A searcher detects this in the mempool.
• Sub-step 2: Observe the searcher's actions. The searcher frontruns the transaction, buying the token first, and then backruns it, selling the token after the user's trade executes, profiting from the inflated price. The user receives fewer tokens than expected.
• Sub-step 3: Calculate the cost. If the user's swap was expected to yield 5000 USDC but, due to MEV, only yields 4800 USDC, the MEV cost is 200 USDC. Additionally, failed transactions from competing bots waste gas fees.

Tip: Users can check if their wallet address has been affected by past sandwich attacks using tools like EigenPhi's Sandwich Search.

Detailed Instructions

Users can protect themselves by avoiding the public transaction pool. This involves using private RPC endpoints and adjusting transaction parameters.

• Sub-step 1: Use a private RPC / MEV-protected RPC. Instead of a default public endpoint, configure your wallet (e.g., MetaMask) to use Flashbots Protect RPC (https://rpc.flashbots.net) or a similar service from BloXroute or Eden Network. This submits transactions directly to builders, bypassing the public mempool.
• Sub-step 2: Set appropriate transaction parameters. Increase maxPriorityFeePerGas to incentivize inclusion, but crucially, set a low maxFeePerGas to prevent overpaying during gas auctions. Use a gas estimator that accounts for MEV.
• Sub-step 3: Leverage eth_sendRawTransaction with conditional flags. When submitting programmatically, you can use flags to request privacy. For example, with Flashbots:

javascriptCopy
const flashbotsProvider = new FlashbotsProvider(wallet, 'https://relay.flashbots.net');
const txResponse = await flashbotsProvider.sendRawTransaction(signedTx, { maxBlockNumber: currentBlock + 5 });

Tip: For the best protection, combine a private RPC with a wallet that supports transaction simulation to preview MEV risks before signing.

Detailed Instructions

Long-term solutions involve changing blockchain infrastructure itself. SUAVE (Single Unified Auction for Value Expression) is a dedicated decentralized mempool and block builder network. Fair Sequencing Services (FSS) or Threshold Encryption protocols like Shutter Network aim to order transactions fairly.

• Sub-step 1: Understand SUAVE's flow. Users send preferences (e.g., maxTip: 10 gwei) to SUAVE. Searchers compete in a centralized auction within SUAVE to create optimal blocks. The winning block is relayed to Ethereum. This keeps intent private and aggregates competition.
• Sub-step 2: Examine Threshold Encryption. Shutter Network uses a Distributed Key Generation (DKG) process. Transactions are encrypted with a shared public key before entering the mempool and are only decrypted after being included in a block, preventing frontrunning. A user would send a transaction to a modified RPC endpoint like https://rpc.shutter.network.
• Sub-step 3: Assess adoption. Check if your preferred DApp integrates these solutions. For instance, a future Uniswap fork might route all swaps through SUAVE by default, significantly reducing sandwich attack surfaces.

Tip: As a user, supporting and using DApps built on these nascent protocols helps drive ecosystem adoption and long-term MEV mitigation.