In decentralized finance, Miner Extractable Value (MEV)—or more broadly, Maximal Extractable Value—is a persistent threat to traders and protocols. MEV arises when validators, bots, or front-running actors reorder, insert, or censor transactions to profit at the expense of users. One of the most common forms is the sandwich attack, where an attacker detects a large trade in the mempool and places transactions before and after it, capturing value through price manipulation. Lorenzo addresses this challenge with an MEV-aware execution pipeline that integrates probabilistic route filtering and intelligent trade routing.
At the core of Lorenzo’s strategy is probabilistic route evaluation. Each potential liquidity path is not only evaluated for cost, slippage, and latency but also for MEV exposure risk. Using historical transaction data, mempool monitoring, and predictive heuristics, Lorenzo assigns a probabilistic MEV risk score to every candidate route. Routes that are highly visible to front-running bots or historically susceptible to sandwich attacks receive higher risk scores and are deprioritized unless no viable alternative exists.
Once candidate paths are scored, Lorenzo applies probabilistic filtering to mitigate predictable MEV exploitation. Instead of deterministically choosing the “cheapest” or “fastest” path—which may be highly observable in public mempools—the protocol introduces controlled randomness in execution. It may split orders across multiple routes, randomize transaction submission timing, or stagger partial fills. This obfuscates the trade footprint, making it statistically harder for attackers to predict or profit from any single transaction.
Integration with the Multi-Vector Routing Graph (MVRG) enhances MEV resistance. Each edge in the routing graph carries MEV exposure metrics alongside fees, liquidity, and slippage vectors. The routing algorithm selects paths that optimize a combined objective function: minimizing cost and slippage while reducing MEV probability. By considering MEV as an explicit cost vector, Lorenzo ensures that routes are not just economically optimal on paper but also safer from predatory trading behavior.
Lorenzo’s MEV-aware pipeline also benefits from cross-chain awareness. For multi-chain swaps, sandwich attacks are more challenging but still possible at bridge endpoints or high-liquidity pools. The system models MEV risk across chains, integrating bridge delays, transaction finality times, and pool depth into its probabilistic evaluation. This prevents users from inadvertently executing trades on vulnerable chains while providing efficient multi-chain liquidity routing.
The benefits of MEV-aware execution in Lorenzo are significant:
Reduced Slippage from Attacks: Probabilistic route selection prevents attackers from reliably front-running or sandwiching trades.
Improved Execution Certainty: Traders experience more predictable outcomes, even in high-volatility or highly-visible pools.
Higher Capital Efficiency: By avoiding value extraction by bots, more of the user’s capital is preserved during execution.
Enhanced Cross-Chain Security: MEV risk is modeled across multiple chains, making multi-hop trades safer from opportunistic actors.
In summary, Lorenzo’s MEV-aware execution pipelines combine intelligent risk scoring, probabilistic filtering, and multi-dimensional route optimization to defend against sandwich attacks. By treating MEV as a quantifiable cost and integrating it into routing decisions, Lorenzo transforms transaction execution from a reactive process into a proactive, MEV-resilient system, allowing traders to navigate DeFi networks with greater security and efficiency.
@Lorenzo Protocol #lorenzoprotocol $BANK
