Potential MEV

The most common source of MEV, where a searcher profits from price differences of the same asset across different decentralized exchanges (DEXs) or liquidity pools. This involves a single atomic transaction that buys low on one venue and sells high on another.

• Example: Buying ETH on Uniswap where it's priced at $3,000 and simultaneously selling it on SushiSwap where it's priced at $3,010.
• Key Driver: Price latency and fragmented liquidity across the DeFi ecosystem.

MEV extracted from undercollateralized loans in lending protocols like Aave or Compound. When a loan's collateral value falls below a required threshold, it becomes eligible for liquidation.

• Process: Searchers compete to be the first to submit a liquidation transaction, paying off the bad debt and receiving the collateral at a discount as a reward.
• Result: This mechanism is critical for protocol solvency but creates a competitive, gas-auction-driven environment for searchers.

A predatory form of MEV that exploits regular users' DEX trades. A searcher detects a large pending swap in the mempool that will move the market price.

• Front-run: The searcher buys the asset first, driving the price up.
• Back-run: After the user's trade executes at a worse price, the searcher sells the asset for a profit.
• Impact: This results in slippage and increased cost for the end-user, representing a direct extraction of value.

Profit extracted by manipulating the price feeds that DeFi protocols rely on. Many protocols use decentralized oracle networks or specific DEX pools as price oracles for functions like loan valuations.

• Method: A searcher can execute a series of trades to artificially inflate or depress an asset's price on the oracle source, then interact with a dependent protocol (e.g., minting a synthetic asset or taking a loan) at the incorrect price.
• Requirement: Often requires significant capital to move the market price on the target venue.

A theoretical, long-range form of MEV that exploits blockchain reorganizations (reorgs). If a miner or validator can produce a longer chain in secret, they can reorg the canonical chain to steal MEV that was captured in previous blocks.

• Scenario: A validator sees a profitable arbitrage opportunity was executed in block #100. They could mine blocks #101, #102, etc., in private, then mine an alternative block #100 where they capture that arbitrage themselves before publishing their longer chain.
• Risk: This undermines blockchain finality and is a significant security concern, mitigated by consensus design and penalties.

MEV opportunities specific to the NFT ecosystem. This includes:

• Minting: Front-running transactions to mint limited-edition NFTs from a popular collection.
• Marketplace Arbitrage: Buying an NFT listed below market price on one platform (like Blur) and instantly reselling it on another (like OpenSea).
• Bidding Sniping: Exploiting the end of an NFT auction by submitting a winning bid at the last possible moment, leaving no time for counter-bids.

These strategies target inefficiencies in NFT market mechanics and listing behaviors.

The most common MEV opportunity, where a searcher profits from price differences for the same asset across different Decentralized Exchanges (DEXs) or liquidity pools. A searcher's bot identifies the discrepancy and executes a series of transactions to buy low on one venue and sell high on another in a single atomic bundle.

• Example: Buying ETH on Uniswap where it's priced at $3,000 and simultaneously selling it on SushiSwap where it's priced at $3,010.
• The profit is the price difference minus gas fees, and competition often drives this spread to near zero.

Profiting from the forced closure of undercollateralized loans in lending protocols like Aave or Compound. When a loan's collateral value falls below a required threshold, it becomes eligible for liquidation. Searchers run bots to monitor these conditions and compete to be the first to submit a liquidation transaction, earning a liquidation fee as a reward.

• The opportunity involves frontrunning other liquidators to claim the fee.
• This activity is generally considered beneficial as it maintains protocol solvency.

A predatory form of MEV that targets large DEX trades. A searcher detects a pending large swap (the 'victim' trade) that will move the market price. They then:

1. Frontrun it by buying the same asset, driving the price up.
2. Let the victim's trade execute at this worse price.
3. Backrun it by selling the asset now at the inflated price, profiting from the victim's slippage.

• This extracts value directly from the end-user's trade, worsening their execution.

A sophisticated and potentially chain-destabilizing MEV opportunity that involves reorganizing past blocks (reorgs). A miner or validator who has mined a block containing valuable MEV might intentionally discard it and mine a competing block that includes the same profitable transactions for themselves, orphaning the original block.

• This undermines blockchain finality.
• More feasible in chains with probabilistic finality (like pre-Merge Ethereum) and is mitigated by proposer-builder separation (PBS).

Extracting value from Non-Fungible Token market dynamics. Common strategies include:

• Minting: Frontrunning the public mint of a popular NFT collection to acquire assets at list price before they sell out or trade at a premium on secondary markets.
• Marketplace Arbitrage: Buying an NFT listed below its floor price on one marketplace (e.g., Blur) and instantly reselling it on another (e.g., OpenSea).
• Bundling: Sniping multiple NFTs from a single wallet in a liquidation or bulk sale transaction.

Profiting by intentionally manipulating the price feeds that DeFi oracles (like Chainlink or a DEX's TWAP) provide to protocols. An attacker might execute a series of large, manipulative trades on a thinly-liquid DEX to artificially inflate or deflate the reported price, triggering downstream events.

• Example: Artificially lowering the price of a collateral asset to cause unjustified liquidations on a lending platform, which the attacker can then perform.
• This is often considered an exploit rather than a neutral MEV opportunity.

This group treats potential MEV as a quantifiable financial metric for investment and trading strategies. They build models to estimate the future MEV supply flowing to validators, which can be seen as a yield component for staked assets. Their analysis focuses on:

• Forecasting revenue from arbitrage and liquidations across DeFi protocols.
• Valuing searcher and block builder businesses.
• Assessing the impact of MEV burn or smoothing mechanisms on token economics.

For validators, potential MEV represents a primary source of proposer revenue beyond standard block rewards. Large staking pools and solo stakers use analysis to:

• Optimize block building strategies or select profitable relays.
• Calculate the real Annual Percentage Yield (APY) for stakers, including MEV rewards.
• Assess the risks and rewards of running MEV-Boost or proprietary block-building software.

These professionals use potential MEV as a lens for systemic risk assessment and regulatory analysis. They study how MEV flows impact network stability, user experience, and centralization pressures. Their work involves:

• Tracking the concentration of MEV revenue among a few block builders.
• Analyzing the correlation between MEV activity and network congestion.
• Providing audit reports on the MEV resilience of different Layer 1 and Layer 2 networks.

Searchers are the primary extractors, but they also deeply analyze potential MEV to discover and optimize profitable opportunities. Their continuous analysis focuses on:

• Scanning mempool transactions and smart contract states for arbitrage, liquidations, and NFT minting opportunities.
• Simulating bundle execution and gas optimization to maximize profit.
• Monitoring competitor activity and network conditions to stay ahead in priority fee auctions.

These are the most common forms of harmful MEV extraction. Frontrunning involves seeing a pending transaction (e.g., a large DEX trade) and placing one's own transaction ahead of it to profit from the anticipated price move. A sandwich attack is a specific form where an attacker places one order before and one after the target transaction, profiting from the artificial price movement they create. These attacks directly harm end-users through worse execution prices (slippage).

This is a severe consensus-level security risk. If the MEV in a previously mined block is high enough, it can incentivize miners or validators to attempt to reorganize the chain (a reorg) to steal that value. This undermines blockchain finality and user confidence. Protocols like proposer-builder separation (PBS) aim to mitigate this by separating the roles of block building and proposing.

MEV creates economic pressure towards centralization. Entities with advanced infrastructure (e.g., searchers, block builders) can capture disproportionate value, leading to:

• Proposer centralization: The most profitable builders may only work with a few large validators.
• Transaction censorship: A dominant builder could systematically exclude certain transactions (e.g., from sanctioned addresses).
• Relay centralization: In PBS designs, relays that connect builders and proposers can become centralized points of failure.

Solutions are emerging to redistribute or neutralize MEV's negative externalities. Proposer-Builder Separation (PBS) is a design that separates block construction from proposal, creating a competitive builder market. MEV-Burn (e.g., EIP-1559 on Ethereum) destroys a portion of transaction fees that would otherwise become MEV, benefiting all ETH holders through deflation. MEV smoothing protocols aim to distribute extracted MEV more evenly among validators.

Not all MEV is harmful. Arbitrage corrects price discrepancies across DEXs, improving market efficiency. Liquidations in lending protocols are necessary for solvency; searchers who execute them provide a vital service and are compensated with a liquidation bonus. This 'necessary' MEV helps maintain the health and efficiency of DeFi ecosystems, though it still represents value extraction from some users (e.g., those being liquidated).