Liquidator Bot

Liquidator bots operate by continuously polling or subscribing to blockchain events to track the health factor or collateralization ratio of user positions across protocols. They use optimized RPC nodes and WebSocket connections to achieve sub-second latency, which is critical in a competitive environment where the first bot to act claims the liquidation incentive.

To maximize profitability, bots employ sophisticated gas bidding and Maximal Extractable Value (MEV) tactics. This includes:

• Priority Gas Auctions (PGAs): Outbidding competitors to have their transaction included first in a block.
• Bundle Building: Combining liquidation transactions with arbitrage or other profitable actions in a single block.
• Gas Estimation: Precisely calculating gas costs to ensure the liquidation remains profitable after fees.

Before executing, a bot performs an on-chain simulation to verify the transaction will be profitable. It calculates:

• Liquidation Incentive: The fixed percentage bonus paid by the protocol (e.g., 5-10%).
• Estimated Gas Cost: Based on current network conditions.
• Slippage & Execution Risk: Potential losses from selling seized collateral on a DEX. The bot only proceeds if the net profit exceeds its configured threshold.

Professional liquidators are not limited to a single protocol. They monitor multiple DeFi lending markets (e.g., Aave, Compound, MakerDAO) simultaneously. This requires maintaining separate smart contract ABIs, price oracle integrations, and risk parameters for each protocol, diversifying opportunity and mitigating risk from low activity on any single platform.

Upon a successful liquidation, the bot receives the undercollateralized debt (e.g., borrowed ETH) and a portion of the user's collateral. It must immediately swap this seized collateral for the debt asset on a DEX (like Uniswap) to repay the protocol and realize the profit. This step involves managing slippage tolerances and liquidity depth to avoid significant losses.

To prevent catastrophic losses, bots implement robust safety logic:

• Revert Protection: Transactions are designed to revert if key conditions (like price) change unfavorably mid-execution.
• Rate Limiting: Capping the number or size of transactions to manage exposure.
• Health Monitoring: Continuous checks on the bot's own wallet balance for gas and its connection to data providers.

A liquidator bot's primary function is to monitor the health factor or collateralization ratio of user positions on lending protocols like Aave or Compound. When a position falls below the liquidation threshold, the bot automatically submits a transaction to repay part of the debt in exchange for the user's collateral, applying a liquidation penalty or liquidation bonus to the seized assets.

Liquidators are incentivized by a liquidation bonus, a discount (e.g., 5-15%) on the seized collateral's market value. This creates a competitive, profit-driven market. Key metrics include:

• Gas Optimization: Bots compete on transaction speed and efficiency.
• Maximum Extractable Value (MEV): Liquidations are a primary source of on-chain MEV, where searchers bid for block space to capture the arbitrage.
• Liquidation Call Data: Bots parse this public data to identify profitable opportunities.

A typical bot architecture involves several specialized components:

• Node Infrastructure: Connections to multiple RPC providers for low-latency data and transaction submission.
• Event Listeners: Monitor blockchain for LiquidationCall events or poll protocol smart contracts for unsafe positions.
• Simulation Engine: Uses tools like Tenderly or a local fork (e.g., via Foundry) to simulate transactions and calculate profitability before broadcasting.
• Transaction Management: Handles gas price bidding, nonce management, and private mempool routing (e.g., Flashbots Protect).

Liquidator bots interact with specific protocol mechanisms. For example:

• Compound's Comptroller: Bots call the liquidateBorrow function.
• Aave V3's Pool: Bots call the liquidationCall function.
• MakerDAO's Auctions: Bots participate in collateral auctions via the Flipper or Clipper contracts. Each protocol defines its own liquidation close factor, acceptable collateral, and penalty structure, which the bot must encode.

Operating a liquidator bot involves significant technical and financial risks:

• Gas Auction Wars: Profit can be erased in competitive gas bidding.
• Slippage & Failed TXs: Price volatility between simulation and execution can cause losses.
• Protocol Upgrades: Smart contract changes can break bot logic.
• Oracle Manipulation: Attacks on price oracles (like the bZx incident) can trigger false liquidations.
• Regulatory Scrutiny: The automated, profit-driven nature may attract regulatory attention in some jurisdictions.

A liquidator bot is an automated program that monitors lending protocols for positions that have fallen below the required collateralization ratio. Its primary function is to execute a liquidation, repaying the borrower's debt in exchange for their collateral at a discount. This mechanism is critical for maintaining protocol solvency and protecting lenders. Bots compete to be the first to submit a profitable liquidation transaction, a process known as MEV (Maximal Extractable Value) extraction.

For borrowers, liquidator bots represent a key risk of sudden capital loss. A sharp price drop can trigger a liquidation, where collateral is sold at a liquidation penalty (e.g., 5-15% discount). In volatile markets, this can cause cascading liquidations: one forced sale pushes the asset price down further, triggering more liquidations. This systemic risk is amplified by highly leveraged positions and low-liquidity collateral assets, potentially leading to significant bad debt for the protocol.

Protocols rely on liquidator bots to manage risk, but failures can lead to bad debt. Key vulnerabilities include:

• Oracle latency or failure: If price feeds are delayed or manipulated, positions may become undercollateralized without triggering timely liquidations.
• Insufficient bot incentives: If the liquidation reward is too low relative to gas costs, bots may not act, allowing bad debt to accumulate.
• Collateral illiquidity: Bots cannot sell seized collateral if market depth is insufficient, leaving the protocol holding devalued assets.

Operating a liquidator bot is highly competitive and carries its own financial risks. Operators face:

• Gas wars: Bots compete by bidding higher transaction fees (gas) to get their liquidation transaction mined first, often erasing profits.
• Sandwich attacks & front-running: Rival bots or generalized MEV searchers may front-run a profitable liquidation transaction, stealing the opportunity.
• Smart contract risk: Bots interact directly with protocol contracts; a bug in either the bot's code or the protocol can lead to total loss of the capital used for liquidation.

Modern protocols implement designs to mitigate liquidation risks:

• Gradual/Partial liquidations: Selling only enough collateral to restore health, reducing market impact.
• Dutch auctions: Collateral is sold at a price that declines over time, aiming for a fairer market price.
• Isolated markets & risk parameters: Limiting which assets can be used as collateral and setting appropriate Loan-to-Value (LTV) and liquidation threshold ratios.
• Robust oracle systems: Using decentralized or time-weighted average price (TWAP) feeds to resist manipulation.

Compound Finance provides a canonical example. Its Comptroller contract designates accounts for liquidation when their health factor falls below 1. Liquidator bots call the liquidateBorrow function, repaying up to 50% of a borrower's outstanding debt in a single transaction. In return, they receive the borrower's collateral at a discount defined by the liquidation incentive. This open, permissionless system has processed billions in liquidations, demonstrating both the mechanism's effectiveness and the intense bot competition it creates.