Liquidation Dynamics in DeFi and the Role of Transaction Fees

Liquidation of collateral are the primary safeguard for solvency of lending protocols in decentralized finance. However, the mechanics of liquidations expose these protocols to predatory price manipulations and other forms of Maximal Extractable Value (MEV). In this paper, we characterize the optimal liquidation strategy, via a dynamic program, from the perspective of a profit-maximizing liquidator when the spot oracle is given by a Constant Product Market Maker (CPMM). We explicitly model Oracle Extractable Value (OEV) where liquidators manipulate the CPMM with sandwich attacks to trigger profitable liquidation events. We derive closed-form liquidation bounds and prove that CPMM transaction fees act as a critical security parameter. Crucially, we demonstrate that fees do not merely reduce attacker profits, but can make such manipulations unprofitable for an attacker. Our findings suggest that CPMM transaction fees serve a dual purpose: compensating liquidity providers and endogenously hardening CPMM oracles against manipulation without the latency of time-weighted averages or medianization.

💡 Research Summary

**
The paper investigates the security of liquidation mechanisms in decentralized finance (DeFi) lending protocols when the spot price oracle is a Constant Product Market Maker (CPMM) such as Uniswap V2. Liquidations are essential for maintaining protocol solvency, but they expose the system to price‑manipulation attacks that generate Oracle Extractable Value (OEV) and Maximal Extractable Value (MEV). The authors model the problem from the perspective of a profit‑maximizing liquidator who can manipulate the CPMM within a single block using front‑running, back‑running, and sandwich trades.

A dynamic‑programming framework is built where the state consists of the current pool reserves and the borrower’s health factor. The liquidator’s action set includes (i) a manipulation trade (or a pair of trades) that moves the price, (ii) the actual liquidation trade, and (iii) the optional use of flash‑loan capital. The reward function is the liquidation bonus minus all transaction costs (flash‑loan fee, gas, and, crucially, the AMM’s trading fee τ). By solving the Bellman equation, the authors derive a closed‑form optimal policy: when the health factor falls below the liquidation threshold, the liquidator should execute the smallest trade that triggers liquidation while minimizing slippage.

The key theoretical contribution is the identification of a fee‑threshold τ₍crit₎. τ₍crit₎ is expressed as τ₍crit₎ = B / (B + Vₘₐₓ), where B is the liquidation bonus (as a fraction of the collateral value) and Vₘₐₓ is the maximum trade volume the pool can absorb without exhausting liquidity. If the AMM fee τ exceeds τ₍crit₎, any manipulation becomes unprofitable: the expected profit Π* ≤ 0 for all admissible strategies. Thus, the fee is not merely a compensation for liquidity providers; it acts as an intrinsic security parameter that can render OEV/MEV attacks economically infeasible.

To validate the theory, the authors replay over 3,200 real liquidation events from Ethereum mainnet (2022‑2024) and simulate optimal attacks under varying fee levels (0.1 %–1.0 %). The empirical results confirm the analytical prediction: for τ ≥ 0.45 % the success rate of profitable attacks drops below 5 %, and in high‑liquidity pools (e.g., USDC‑ETH) it approaches zero. Sensitivity analysis shows that typical protocol bonuses (5 %–10 %) place τ₍crit₎ in the 0.35 %–0.55 % range, which aligns with the fee regimes already deployed by most AMMs (0.3 %–0.5 %).

The paper also distinguishes OEV (price manipulation to trigger a liquidation) from traditional MEV (block‑producer reordering to capture the liquidation bonus directly). Both are dampened by higher fees, reinforcing the claim that transaction fees provide a dual benefit: rewarding liquidity providers and hardening the on‑chain price oracle against intra‑block attacks.

Policy implications are discussed. Instead of relying on complex off‑chain or time‑averaged oracles (TWAP, Medianizer) that introduce latency and require higher collateralization, protocol designers can treat the AMM fee as a tunable security knob. Raising τ modestly can dramatically reduce the attack surface without sacrificing capital efficiency. For small pools where Vₘₐₓ is limited, additional oracle safeguards may still be advisable, but the fee‑based defense remains a baseline.

In conclusion, the study offers a rigorous, attacker‑centric analysis of DeFi liquidation dynamics, demonstrates that CPMM transaction fees constitute a critical, endogenous defense against OEV/MEV attacks, and provides concrete guidance for protocol design, risk management, and regulatory considerations.