Understanding MEV in DeFi and How Velora Protects Traders
Basics
What Maximal Extractable Value is, why it matters in DeFi, and how intent-based systems like Velora are shifting the execution landscape.
MEV: The Invisible Tax on DeFi
MEV, or Maximal Extractable Value, isn’t a future threat or an edge-case vulnerability. It’s already a defining force behind how value moves through DeFi.
Every onchain transaction is vulnerable to being exploited before it settles. It doesn’t matter how careful the user is or how well-designed the interface looks, if a transaction enters the public mempool, there’s a chance someone else profits from it. That profit is called MEV, and it’s become one of the most persistent structural flaws in DeFi.
MEV is the value captured by reordering, inserting, or censoring transactions before block finalization. It’s most visible in the form of frontrunning, sandwich attacks, and arbitrage interception, but its impact extends further. Users pay higher slippage, miss out on price opportunities, and face unpredictable execution, all while someone else earns a reward for exploiting network design.
This isn’t a side effect of DeFi. MEV is a direct outcome of how most decentralized systems handle execution. Transactions are public, blockspace is auctioned to the highest bidder, and execution logic sits entirely with the user. That combination opens the door to extraction, especially in high-value environments like DEXs, lending protocols, and crosschain workflows.
Attempts to address MEV have largely been reactive. Private mempools hide transactions. Order Flow Auctions (OFAs) auction order flow back to users. Some protocols add slippage buffers or routing constraints to reduce risk. But these are patches, not redesigns. They mitigate symptoms without addressing the root cause: users are forced to operate execution infrastructure they can’t control.
That’s the shift intent-based systems are enabling and where Velora is focused. By reframing transactions as outcomes, and execution as a competitive service, Velora eliminates many of the structural conditions that make MEV extraction possible.
In this article we’ll unpack how MEV works, why it persists, and how intent-based architecture can do more than reduce harm, it can build toward a fairer execution layer from the ground up.
What Is MEV and How Does It Work?
MEV, which is short for Maximal Extractable Value, refers to the value that can be captured by manipulating transaction order during block production. In its original context, this meant miners reordering transactions in a block to increase profits. Today, the term applies more broadly to any actor with influence over transaction sequencing, including validators, searchers, builders, and even relayers in more complex systems.
At its core, MEV is a product of how blockchains process transactions. When users submit a transaction, it enters the public mempool, which is a waiting room where anyone can inspect its contents before it's confirmed. Block producers then select which transactions to include in a block, in what order, and under what conditions. While base-layer consensus ensures that only valid transactions are included, it says nothing about fairness or optimality of execution.
That gap is where MEV emerges.
Block producers are typically incentivized to prioritize transactions with the highest gas fees. But fee sorting is only one dimension. With full discretion over ordering, block producers or the network of searchers they rely on can reorder or insert new transactions to extract value. This isn’t hypothetical. It happens constantly.
Common MEV Strategies
1. Frontrunning
A bot detects a large swap about to execute on a DEX. It copies the transaction and submits its own version with a higher gas fee, ensuring it lands first in the block. This drives the price up just before the user’s trade is executed.
Now, with the price elevated by the user’s market order, the bot immediately sells back into the pool at a higher price. The user ends up with a worse rate, and the bot captures a risk-free profit on the price movement they artificially induced.
2. Sandwich Attacks
A more aggressive variation, sandwiching involves two transactions: one before and one after the target trade. First, the bot frontruns the trade to push the price up. Then, after the user’s order executes at the inflated price, the bot sells in the next transaction, profiting again as the price resets.
The user absorbs the slippage on both ends of the sandwich, paying more for the asset and causing the pool to rebalance less favorably than expected.
3. Arbitrage
A price discrepancy appears between two liquidity pools, for example, ETH is trading at $3,000 on one DEX and $3,020 on another. A user spots the opportunity and initiates a trade to profit from the difference. Before their transaction settles, a bot detects it in the mempool, copies it, and resubmits it with a slightly higher gas fee to get priority. The bot captures the price difference and the user’s transaction either fails or executes at a worse price.
The value that would’ve gone to the user is extracted by the faster actor.
4. Liquidation
When a borrower’s collateral value falls below the required threshold, their loan becomes eligible for liquidation. This allows others to repay the debt and claim a portion of the collateral as a bonus.
Bots monitor lending protocols for these opportunities and race to execute the liquidation first. The fastest bot earns the reward, while slower ones get nothing and the borrower faces abrupt position closure. In volatile markets, this behavior can amplify sell pressure and destabilize protocols, as bots prioritize extraction over graceful system operation.
5. NFT and Time-Based Attacks
In thin markets like NFT listings or during chain reorgs, bots exploit latency or predictability to grab assets listed below fair value or to reorganize chains for retroactive MEV capture.
Each of these behaviors exploits visibility and latency, core properties of how public blockchains operate. Users don’t lose funds directly, but the value they could have received is captured by someone else. That’s MEV: not theft, but leakage that arises because of a system-level inefficiency monetized through speed, access, and execution advantage.
Understanding how MEV works is essential, but solving it requires rethinking execution itself.
Why MEV Matters: Cost, Complexity, and Centralization
MEV isn’t just a technical artifact, it’s a value drain that impacts users, protocols, and the broader integrity of onchain markets. Its effects are often invisible in isolation, but over time they degrade confidence, limit access, and skew incentives away from users and toward extractors. The cost is measurable, and it compounds.
User Cost: Execution Quality Degrades
Every sandwich attack, frontrun, or backrun results in worse execution for someone. For traders, this means higher slippage and worse pricing. For lenders, it can mean losing liquidation opportunities. For any user operating in an open mempool, it means uncertainty, and not just about whether a transaction will go through, but what it will cost once it does.
MEV transforms trading from a predictable process into a probabilistic one. Even simple swaps can behave unpredictably depending on the visibility of the intent and the presence of bots scanning for opportunity. The result is a degraded user experience that favors professional actors and penalizes everyone else.
Protocol Complexity: Execution Becomes a Liability
Protocols weren’t designed to protect users from MEV. Most DEXs, lending platforms, and bridges expose transaction data publicly and rely on users to manage routing, gas, and timing. This creates attack surfaces at every step of execution.
To compensate, protocols introduce additional layers like slippage settings, transaction simulators, routing strategies, or offchain quoting systems. But these are defensive mechanisms, not architectural fixes. They attempt to contain MEV without eliminating its source: public execution pathways governed by gas-first logic.
As MEV grows more sophisticated, protocols are forced to dedicate more resources to mitigation. What begins as a market design problem becomes an arms race between builders and extractors, with users caught in the middle.
Market Centralization: Scale Amplifies Extraction
MEV rewards speed, capital, and privileged access. Actors with more capital can pay higher gas fees. Actors with better infrastructure can simulate and submit faster. Actors with privileged access, whether through vertical integration with block builders or private relay networks, can extract more value with less risk.
Over time, this dynamic concentrates value capture into a small number of hands. Validators form partnerships with searchers. Builders consolidate order flow. MEV strategies are industrialized, not democratized. As a result, execution becomes gated, and the very premise of permissionless systems starts to erode.
This also affects validator economics. When MEV exceeds block rewards, validators are incentivized to reorganize blocks or collude with builders to maximize profit. This creates consensus instability, a risk that goes far beyond any individual transaction.
MEV may be unavoidable in an open system, but it isn’t unchangeable. Its severity depends on architecture. When execution is designed to expose user activity, value will be extracted. When execution is redesigned to prioritize outcomes and protect transaction privacy, that value can be preserved, or even returned to the user.
How the Ecosystem Is Responding
The scope of MEV is now widely recognized and so is the need to address it. But most mitigation efforts have evolved as overlays on top of existing architecture. They modify how transactions are submitted, routed, or prioritized, rather than changing how execution itself is structured. As a result, the ecosystem has fragmented into a range of mitigation strategies, each solving part of the problem while introducing new constraints.
1. Private Mempools and Transaction Obfuscation
The simplest way to avoid MEV is to prevent your transaction from being visible. Private mempools (like Flashbots Protect, MEV-Blocker, and RPC relays) allow users to bypass the public mempool and send transactions directly to block builders. This avoids frontrunning and sandwiching but depends on users knowing how to route their own order flow and depends on the trustworthiness of the private relay itself.
Relays sit between block proposers and builders, helping bridge the trust gap in private transaction routing. They act as reputation-based intermediaries that ensure transactions are only included under agreed-upon terms. If a builder attempts to front-run or reorder transactions, the relay can refuse to release the block. If the relay itself misbehaves, it risks losing trust and being excluded by the network.
Source: Radius
Tradeoffs:
❌ Execution still relies on user-defined logic
❌ No guarantee of top-of-block inclusion
❌ Trust shifts from the public mempool to private relays
This reduces visibility but doesn’t eliminate extraction risk, it just redirects it.
2. Order Flow Auctions (OFAs)
OFAs flip the transaction submission model: instead of paying to be included, users auction off the right to execute their trades. Systems like MEV-Share and MEV-Blocker let searchers bid for private order flow, and pass back a portion of the extracted value to the user.
RFQs (used by 0x/Matcha), batch auctions (CoWSwap), and Dutch auctions (1inch Fusion, UniswapX) are all variants of this approach. They internalize MEV, routing it through controlled mechanisms that benefit the user instead of third-party bots.
Tradeoffs:
❌ Requires integration with specific apps or endpoints
❌ Often slower than direct execution
❌ Still reliant on trusted solvers or resolvers
OFAs offer meaningful protection, but they’re still adaptations of user-signed transactions. And because execution logic still lives with the user, the core problem remains unsolved.
3. Intent-Based Execution
Intent systems shift the model entirely. Instead of defining how a transaction should be executed, users define what outcome they want (“swap X for Y at minimum Z received”). Solvers or agents then compete to fulfill that outcome using any available route.
This enables greater price discovery, offchain quoting, and automated protection from slippage or failure. Systems like CoWSwap, UniswapX, and 1inch Fusion all use variants of intent-based design, often layered over their legacy infrastructure.
Tradeoffs:
❌ Requires trusted parties (solvers, fillers) to act on user’s behalf
❌ Introduces new coordination layers and dependencies
❌ Offchain routing reduces transparency and introduces latency
Intents are structurally more resilient to MEV, but they also shift power to a new class of intermediaries. Without careful design, they risk replicating the same centralization dynamics seen with block builders and searchers.
4. General-Purpose Intent Infrastructure (In Progress)
Teams like Flashbots (SUAVE), Anoma, and Essential are building shared infrastructure for intent execution. These systems aim to decentralize not just order flow, but the sequencing and matching layers themselves.
If successful, this would move execution toward a modular, open-market structure where user preferences are fulfilled through composable, trust-minimized networks of solvers and builders.
Tradeoffs:
❌ Still under development; unproven at scale
❌ Requires new standards, coordination models, and consensus layers
❌ Unclear economic incentives and enforcement mechanisms
These approaches point toward the long-term direction of execution: user-defined outcomes fulfilled by open networks, not predefined transactions subject to extraction.
While progress is real, each response introduces new risks: opacity, latency, trust assumptions, or liquidity fragmentation. And most still leave the burden of managing execution on the user. The next section outlines how Velora takes a different path by making intent-based, MEV-resistant execution the default, not the add-on.
Velora’s Approach: Intents at the Core
Velora doesn’t treat MEV mitigation as a bolt-on. It treats it as a design constraint. Rather than building protective layers around legacy execution models, Velora rearchitects the transaction flow entirely, starting from user intent, not transaction structure. The result is a system that minimizes MEV not by hiding transactions, but by changing the rules of execution itself.
Portikus modular, composable infrastructure
Execution as a Service
In Velora, users don’t sign transactions, they sign intents. An intent is a statement of outcome: "Swap USDC on Base for ETH on Optimism." The user doesn’t choose the route, the liquidity pool, or the sequencing. They define the goal, and Velora handles the rest.
That intent is passed to Portikus, Velora’s coordination layer, which initiates a real-time auction among settlement agents. These agents compete to fulfill the user’s intent at the best available price, across any viable route, chain, or liquidity source.
This model abstracts complexity away from the user and creates a market for execution, where competition, not visibility, drives performance.
Private by Design
Unlike traditional DeFi workflows, Velora’s execution is private by default. Signed intents are routed through Portikus and executed by agents without touching the public mempool. There is no broadcast step, no window for frontrunning, and no transaction waiting to be exploited.
Because execution is competitive, not fee-based, there's also no need for the user to bid their way into a block. Inclusion is handled by the agent, who absorbs both the risk and the cost.
MEV Resistance Is Built In, Not Added On
Velora’s architecture avoids the primary failure modes that make MEV extraction possible:
No mempool exposure = no frontrunning or sandwiching
Atomic execution = no hanging crosschain transactions
Outcome-based logic = no slippage surprises or failed trades
Agent accountability = financial incentives for accurate execution
Because agents must win auctions to participate, they are continuously evaluated on price, reliability, and performance. Misbehavior isn’t tolerated by policy, it’s penalized economically.
Crosschain and Gasless by Default
Velora is a complete crosschain trading protocol. A user can swap tokens from one chain to another without bridging, approvals, or gas tokens. There’s no need to hold ETH on Ethereum and ARB on Arbitrum just to complete a transaction.
Gas is abstracted away. Agents cover transaction fees and recover them from the final output. This removes one of the largest barriers to multi-chain DeFi: the need for users to manually fund and manage execution across fragmented environments.
The implications are significant:
✅ More accessible onboarding
✅ No need for token bridging UIs
✅ No transaction reverts due to insufficient gas
Crosschain trading becomes as simple and as safe as a single click.
Liquidity Without Limits
Velora doesn’t rely solely on AMMs or aggregator routes. Agents can source liquidity from onchain DEXs, offchain inventory, or peer-to-peer matches. This unlocks better pricing, reduces slippage, and avoids the fragmentation that often drives users into worse execution just to complete a trade.
And because routing is handled by agents, not users, execution becomes more intelligent over time. Agents can continuously optimize routes based on real market conditions, not static heuristics.
Velora doesn’t just protect users from MEV. It eliminates the need for them to even think about it. By turning execution into a competitive service and making intent the primitive, Velora removes the structural exposure that legacy models can’t escape. This isn’t theoretical. It’s live and already protecting users.
The Role of Velora in the Intent Future
Velora isn’t speculating on what intent-based systems might become, it’s already building with them at the core. Velora Delta and its agent network are operational and intent-based by design.
Velora’s execution model shares the core principles emerging across next-generation intent networks: declarative user input, solver-based fulfillment, private competitive execution, and crosschain coordination as a base layer.
But it also solves practical problems today. Traders can execute gasless, crosschain swaps without relying on bridges or exposing transactions to the mempool. Protocols can access competitive routing and fulfillment logic without building their own solver infrastructure. And users benefit from tangible improvements in execution quality. This isn’t a future roadmap, it’s already the baseline.
The future of execution won’t be won by the fastest bot or the most privileged block builder. It will be won by systems that align incentives from input to outcome, where execution is a service, not a battlefield.
MEV will always exist. But in the right architecture, users won’t be the ones paying for it.
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