Why Most Crypto Bots Get Sandwiched (And How to Prevent It)

If you’ve ever built or run a crypto trading bot, you’ve likely encountered the frustrating phenomenon of being "sandwiched." It’s a common issue in decentralized finance (DeFi), especially on automated market makers (AMMs) like Uniswap. Sandwich attacks are a form of Miner Extractable Value (MEV), where malicious actors exploit your transaction to profit at your expense. In this article, I’ll explain why sandwich attacks happen, how they work, and the practical steps you can take to prevent them using tools like Jito bundles.

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What Are Sandwich Attacks?

A sandwich attack occurs when a bot or trader monitors the mempool (the pool of pending transactions) for profitable opportunities. When they spot your transaction—say, a large swap on Uniswap—they front-run it by placing their own transaction just before yours, and back-run it by placing another transaction just after. This “sandwiches” your trade, manipulating the price to their advantage.

Here’s a breakdown:

1. Front-run: The attacker buys the asset you’re swapping into at the current price before your trade executes.
2. Your trade: Your trade executes, pushing the price in favor of the attacker.
3. Back-run: The attacker sells the asset at the new, higher price, profiting from the price movement your trade caused.

The result? You get worse execution, and the attacker pockets the difference.

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Why Do Sandwich Attacks Happen?

Sandwich attacks happen because blockchain transactions are public before they are confirmed. On Ethereum and other EVM-compatible chains, every pending transaction sits in the mempool, visible to anyone. Bots monitoring the mempool use sophisticated algorithms to identify profitable trades to exploit. The larger your trade size, the more attractive it is to sandwich attackers.

For example, let’s say you’re swapping 10 ETH for USDC. A bot might notice your transaction, buy USDC before your trade executes, and sell it after your trade pushes the price up. If your trade moves the price by 0.5%, the attacker could pocket a significant profit.

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Real Numbers: The Cost of Sandwich Attacks

To understand the impact, let’s look at some real numbers. According to recent data from Flashbots, sandwich attacks accounted for nearly $1.2 billion in MEV in 2023 alone. The average profit per attack is around $2,000, but larger trades can yield much more.

For example, if you’re swapping $100,000 worth of ETH, a 0.5% price impact could cost you $500 in slippage. A sandwich attacker could pocket most of that.

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How to Prevent Sandwich Attacks

Fortunately, there are ways to protect your trades from sandwich attacks. Here are the most effective strategies I’ve found:

1. Use Jito Bundles (On Solana)

While Ethereum-based chains are notorious for sandwich attacks, Solana offers a unique solution: Jito bundles. Jito bundles are a feature of the Jito-Solana client that allows you to submit multiple transactions as a single, atomic bundle. This prevents front-running because the entire bundle is executed together.

Here’s how to use Jito bundles in your Solana trading bot:

use jito_bundles::Bundle;

let bundle = Bundle::new()
    .add_transaction(tx1)
    .add_transaction(tx2)
    .add_transaction(tx3);

let result = client.send_bundle(bundle).await?;

By bundling your transactions, you ensure they are executed in the exact order you specify, eliminating the opportunity for sandwich attacks.

2. Use Private Transactions (On Ethereum)

On Ethereum, Flashbots is the go-to solution for private transactions. Flashbots allow you to submit transactions directly to miners, bypassing the public mempool. This makes your trade invisible to sandwich attackers.

Here’s how to use Flashbots with Ethers.js:

const flashbotsProvider = new FlashbotsProvider(ethereumProvider, signer);
const tx = {
  to: "0x...",
  value: ethers.utils.parseEther("1.0"),
};

const bundle = [
  {
    transaction: tx,
    signer: signer,
    hash: ethers.utils.keccak256(tx),
  },
];

await flashbotsProvider.sendBundle(bundle, targetBlockNumber);

3. Limit Trade Size

Another practical strategy is to limit the size of your trades. Smaller trades are less likely to attract sandwich attackers because the profit potential is lower. Instead of executing one large trade, split it into multiple smaller trades. This reduces your slippage and makes your transactions less appealing to MEV bots.

4. Use DEX Aggregators

DEX aggregators like 1inch and OpenOcean split your trade across multiple liquidity sources, minimizing price impact. They also often include protection mechanisms against MEV.

For example, here’s how to use 1inch's API:

const response = await axios.get(`https://api.1inch.io/v4.0/1/swap?fromTokenAddress=0x...&toTokenAddress=0x...&amount=1000000&fromAddress=0x...`);
const tx = response.data.tx;
await web3.eth.sendTransaction(tx);

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Lessons Learned

Through my experience building and running crypto bots, I’ve learned a few key lessons:

1. Mempool Visibility Is Dangerous: Submitting transactions to the public mempool is like painting a target on your back. Always consider privacy solutions like Flashbots or Jito bundles.
2. Trade Size Matters: Larger trades are more susceptible to MEV. Splitting trades can significantly reduce your risk.
3. Advanced Tools Are Worth It: Tools like Jito bundles and Flashbots may add complexity to your workflow, but they’re essential for protecting your trades.

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Conclusion

Sandwich attacks are a pervasive problem in DeFi, but they’re not insurmountable. By understanding how they work and leveraging tools like Jito bundles and Flashbots, you can protect your trades and avoid becoming a victim. Additionally, strategies like limiting trade size and using DEX aggregators can further reduce your exposure to MEV.

As the crypto space evolves, new solutions will continue to emerge. Stay informed, adapt your strategies, and always prioritize protecting your trades from exploitative actors. Happy trading!

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