The Dangers of Front-Running Attacks: How Predatory Actors Exploit Blockchain Transparency

The Blockchain Daily by Cybersanctus Edition: Safeguarding Your Crypto Transactions

In the field of decentralized finance (DeFi), one of the most persistent and pernicious challenges is front-running. While blockchain technology promises fairness, openness, and a level playing field, the transparent nature of decentralized networks can also become an Achilles’ heel—allowing malicious actors to exploit early knowledge of transactions for personal gain.

Front-running in traditional finance is explicitly illegal and heavily regulated. On Wall Street, for instance, brokers caught exploiting clients’ pending orders can face severe fines, license revocations, or even prison time under SEC Rule 17(j)-1. Yet in the realm of DeFi—where markets are global, permissionless, and often regulatorily ambiguous—the same practice has found new life and scale. Since mid-2020, on just Ethereum alone, bots exploiting these tactics have earned at least $1 billion in cumulative profits. This figure, compiled by blockchain research firms and analytics platforms, underscores both the magnitude of the issue and the sophistication of the perpetrators.

Understanding Front-Running

What is front-running? At its core, it involves gaining knowledge of a pending, potentially lucrative transaction and inserting a new transaction ahead of it to profit from the anticipated outcome. Traditional markets rarely allow outsiders to see pending orders in real-time. However, public blockchain networks rely on mempools—public “waiting rooms” where transactions reside before miners or validators include them in blocks. Anyone can see and analyze these mempool transactions, including their recipients, amounts, and the smart contract functions being called. This transparency, while crucial for trustlessness and auditability, inadvertently sets the stage for front-runners.

• A Simple Analogy: Imagine standing in line at a store, waiting to buy a limited-edition product. Just before it’s your turn, someone sees your big purchase coming and bribes the cashier to serve them first. They buy the item and then immediately sell it back to you at a markup. On a blockchain, this “bribe” takes the form of a higher gas fee, incentivizing miners or validators to process the attacker’s transaction first.

Front-Running in Practice: Real-World Examples

1. The Sandwich Attack: One of the most notorious forms of front-running is the “sandwich attack,” which is rampant in decentralized exchanges (DEXs).

• Step-by-Step Breakdown: Victim’s Intent: Alice decides to buy 1,000 units of Token X, currently priced at $1.00 per token. This large order is broadcast to the mempool. Attacker Spots the Order: A bot scrutinizes the mempool, identifies Alice’s large buy order, and deduces that this purchase will drive the token’s price up. Front-Running (Insertion) Transaction: Before Alice’s order is mined, the attacker sends a buy order of their own with a slightly higher gas fee. The miner, motivated by higher fees, includes the attacker’s order first. The attacker purchases Token X at $1.00. Victim’s Transaction Executes at a Worse Price: Alice’s order is now processed. However, the attacker’s prior buy has nudged the price up—Alice ends up paying $1.05 per token instead of $1.00, costing her an extra $50. Back-Run Sell: Immediately after Alice’s order is confirmed, the attacker executes a sell order. The attacker offloads their tokens at the now-inflated price of $1.05, netting a quick profit of $5 per token on their holdings.

What would have been a fair trade for Alice turns into an exploitative scenario that enriches the attacker at her expense.

2. Liquidity Pool Manipulation: Decentralized exchanges and lending platforms rely on liquidity pools where tokens are priced according to mathematical formulas. A large liquidity addition (say, $1 million in stablecoins) might significantly affect the pool’s token price. By front-running that liquidity event, an attacker can pre-purchase tokens cheaply, watch the liquidity injection move the market, and then sell them back at a profit—all within a single block.

3. Arbitrage Front-Running: When arbitrageurs spot price differences between various DEXs, they execute trades to rebalance prices, earning a profit. Front-runners watch for these arbitrage trades and jump in line first, capturing the profit that the legitimate arbitrageur identified. The original trader either gets no profit or pays more than expected.

The Scale and Sophistication of MEV Bots

Maximum Extractable Value (MEV) refers to the additional profit miners, validators, and sophisticated traders can extract by reordering, inserting, or censoring transactions. MEV bots are automated programs that relentlessly scan mempools, searching for profitable opportunities. The profits are staggering:

• At Least $1 Billion Earned Since 2020: Analytics suggest MEV traders have collectively siphoned off more than a billion dollars from unsuspecting users, mostly retail traders. These bots are engineered with advanced algorithms and machine learning models to detect patterns, price changes, and big trades. They operate 24/7, adjusting their strategies in real time to stay ahead of the competition.
• A Highly Competitive Arena: Multiple MEV teams operate in the ecosystem, competing for the same opportunities. The most skilled groups can rake in tens or even hundreds of thousands of dollars per month, exploiting the very transparency and openness that DeFi markets tout as benefits.

Why Is Front-Running Such a Persistent Threat?

1. Blockchain Transparency: The very property that makes DeFi attractive—the open, verifiable ledgers—also makes every pending transaction visible before it’s final. Attackers know exactly what the next block’s potential contents might be.
2. Unregulated Frontiers: Unlike traditional finance, where securities laws and market surveillance deter front-runners, many DeFi protocols operate in regulatory grey areas. Without clear legal consequences or enforcement, attackers act with impunity.
3. Incentive Structures: Miners and validators are economically incentivized to pick transactions with the highest fees. Attacker transactions often pay premium fees to ensure priority inclusion, and the block producer simply follows the money.

Technical Example: How Front-Running Can Exploit a Vulnerable Swap

Full Code Example:

// SPDX-License-Identifier: MIT
pragma solidity ^0.8.0;

interface IUniswapLikeRouter {
    function swapExactETHForTokensSupportingFeeOnTransferTokens(
        uint amountOutMin,
        address[] calldata path,
        address to,
        uint deadline
    ) external payable;
}

contract VulnerableSwap {
    IUniswapLikeRouter public router;
    address public token;

    constructor(address _router, address _token) {
        router = IUniswapLikeRouter(_router);
        token = _token;
    }

    // This function allows users to swap ETH for another token.
    // Notice that the amountOutMin parameter is set to 0, offering no slippage protection.
    function swapETHForToken() external payable {
        require(msg.value > 0, "No ETH sent");

        address[] memory path = new address[](2);
        // Example path: WETH to the target token.
        path[0] = 0xC02aaa39b223FE8D0A0E5C4F27eAD9083C756Cc2; // WETH address on Ethereum mainnet (example)
        path[1] = token;

        // The vulnerability: no minimum output (amountOutMin = 0).
        // Attackers can exploit this by front-running the trade.
        router.swapExactETHForTokensSupportingFeeOnTransferTokens{value: msg.value}(
            0, 
            path, 
            msg.sender, 
            block.timestamp
        );
    }
}        

Key Snippet:

// The critical vulnerability is here: amountOutMin = 0.
// This gives attackers a free pass to manipulate the price before this trade is executed.
router.swapExactETHForTokensSupportingFeeOnTransferTokens{value: msg.value}(
    0,        // amountOutMin = 0, leaving the user fully exposed to slippage
    path, 
    msg.sender, 
    block.timestamp
);        

So, How Does it Work?

When the user calls swapETHForToken() with 1 ETH, the transaction enters the public mempool. The user expects a certain amount of tokens, but amountOutMin is set to 0, meaning no minimum token output is required.

function swapETHForToken() external payable {
    require(msg.value > 0, "No ETH sent");
    address[] memory path = new address[](2);
    path[0] = 0xC02aaa39b223FE8D0A0E5C4F27eAD9083C756Cc2; // WETH address (example)
    path[1] = token;
    
    // This call offers no minimum output (amountOutMin = 0).
    // Attackers can exploit the open mempool and buy tokens first, raising their price.
    router.swapExactETHForTokensSupportingFeeOnTransferTokens{value: msg.value}(
        0, 
        path, 
        msg.sender, 
        block.timestamp
    );
}        

Because the mempool is public, an attacker’s bot sees that the victim’s trade has no slippage protection. This indicates the victim will accept any price, no matter how unfavourable. The attacker then sends a transaction with a higher gas fee to be mined first. The attacker buys up the token, artificially inflating its price just moments before the victim’s transaction executes.

// Pseudocode: Attacker buys the same token first,
// driving up the token price moments before the victim’s trade executes.
attackerRouter.swapExactETHForTokensSupportingFeeOnTransferTokens{value: attackerETH}(
    attackerDesiredMinOutput, 
    path, 
    attackerAddress, 
    block.timestamp
);        

Once the attacker’s transaction is processed and the price is raised, the victim’s transaction runs next, forcing them to pay more ETH per token. As a result, the victim receives fewer tokens than they anticipated.

The attacker can sell their tokens at the inflated price immediately or simply enjoy the profit gained from this manipulation. The victim loses out because their transaction had no safeguard against slippage.

Result:

By not setting a minimum output (amountOutMin), the victim unknowingly allowed the attacker to manipulate the token price at the last moment, securing profit for the attacker and causing the victim to receive fewer tokens than expected.

Mitigation and Defense Strategies

While front-running is challenging to eliminate entirely, multiple approaches aim to mitigate it:

1. Private Transaction Relays (e.g., Flashbots): Platforms like Flashbots allow traders to submit transactions directly to miners privately, circumventing the public mempool. As a result, would-be attackers never see the transaction until it’s too late.

2. Commit-Reveal Schemes: Protocols can implement a two-phase trading process. In the commit phase, users submit a hash of their trade details, locking in their intentions without revealing specifics. In the reveal phase, after the transaction is included in a block, the details are disclosed. By then, the order is already final, making front-running impossible.

3. Randomized Block Ordering & Auction Mechanisms: Some research and experimental protocols suggest randomizing transaction order within a block or using off-chain auctions to determine order flow. This reduces the predictability that front-runners rely on.

4. Strict Slippage Controls and User Caution: Users can set low slippage tolerances, limiting how much worse a price they’re willing to accept. By doing so, even if front-runners attempt to manipulate the order, the transaction will fail rather than execute at a terrible rate. Additionally, performing large trades in smaller increments or using non-peak network times can help reduce exposure.

5. Layer 2 Solutions: Off-chain or Layer 2 platforms can batch transactions and present them to the main chain only after execution. Because the details remain hidden until settlement, front-running opportunities diminish.

The Fallout on Market Fairness and User Confidence

Front-running shakes the trust foundations of DeFi. Retail users may feel deterred from trading on-chain if they fear their transactions will be exploited. Over time, this can erode user confidence, reduce liquidity, and hamper the adoption of innovative financial tools. If left unchecked, front-running risks transforming DeFi from a democratized landscape into a field dominated by predatory insiders.

A Surprising Silver Lining: White Hat Front-Running

It’s worth noting that not all front-running is used maliciously. In some instances, “white hat” actors use front-running techniques to rescue funds from hacks. For example, if an attacker’s transaction to steal funds is visible in the mempool, a white hat hacker can front-run that transaction with a corrective one—intercepting and returning stolen assets to the rightful owners. While this doesn’t justify the practice, it demonstrates that the same transparency and speed exploited by attackers can also empower protectors.

Conclusion: Stay Vigilant, Stay Informed

Front-running exemplifies the growing pains of a revolutionary technology. DeFi is still in its infancy, and with its immense freedom comes profound responsibility. As a subscriber to The Blockchain Daily by Cybersanctus, you are better equipped to navigate these waters, understanding the mechanics, risks, and defenses against front-running.

• Educate Yourself: Keep abreast of best practices and new tools designed to curb MEV exploitation.
• Use Reputable Protocols: Prefer platforms that have implemented anti-front-running measures or have undergone thorough security audits.
• Adjust Trading Behavior: Set reasonable slippage thresholds, avoid telegraphing large trades, and consider experimenting with private ordering systems.

Front-running won’t vanish overnight, but with collective awareness, community-driven innovation, and sensible trading habits, its impact on the DeFi ecosystem can be significantly reduced—allowing blockchain markets to move closer to their core promise of fairness, inclusivity, and transparency.