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

If you've ever written or deployed a crypto trading bot, chances are you've encountered the dreaded sandwich attack. These attacks can decimate your profits, turning what seemed like a lucrative trade into a losing proposition. In this article, I’ll explain what sandwich attacks are, why they happen, and how you can protect your bots using tools like Jito bundles. I'll also share some practical code examples and real-world numbers to illustrate the concepts.

What is a Sandwich Attack?

A sandwich attack is a type of Maximal Extractable Value (MEV) attack that occurs in decentralized exchanges (DEXs) like Uniswap or PancakeSwap. It involves a malicious actor spotting your transaction in the mempool, front-running it to buy the asset before you, and then back-running it to sell the asset immediately after your trade. The result? Your trade pushes up the price, and the attacker profits from the price movement at your expense.

Here’s a step-by-step breakdown:

1. Front-run: The attacker places a buy order before your transaction executes, increasing the asset’s price.
2. Your Trade: Your transaction executes at the inflated price.
3. Back-run: The attacker sells the asset immediately after your trade, profiting from the price increase.

Real-World Impact

Let’s say you’re trading on Uniswap with Ethereum (ETH) and a low-liquidity token. You want to swap 1 ETH for Token X. The attacker sees your transaction in the mempool and front-runs it, buying Token X first. Your trade executes at a higher price, and the attacker sells Token X afterward. You end up with fewer tokens than expected, and the attacker pockets the difference.

According to a 2023 Flashbots report, sandwich attacks account for over 30% of MEV extracted on Ethereum, with attackers pocketing millions in profits annually.

Why Sandwich Attacks Happen

Sandwich attacks exploit two key vulnerabilities:

1. Transparency of the Mempool: Public blockchain mempools allow anyone to see pending transactions before they’re confirmed.
2. Predictable Trade Impact: Trades on AMMs like Uniswap follow a predictable price impact curve, making it easy for attackers to calculate how much your trade will move the price.

Example Scenario

Let’s illustrate this with a simplified example. Suppose you’re trading Token A on Uniswap:

• Token A has a liquidity pool of 100 ETH and 10,000 Token A.
• You want to swap 10 ETH for Token A.

Using the constant product formula (x * y = k), the new pool balances after your trade would be:
ETH Pool = 110 ETH
Token A Pool = 9,090 Token A
You receive 909 Token A.

An attacker can calculate this and front-run your trade to buy Token A first, pushing the price up even further.

How to Protect Your Bot from Sandwich Attacks

1. Use Jito Bundles

Jito bundles are a powerful tool to prevent sandwich attacks on Solana. They allow you to submit multiple transactions as a single atomic operation, making it impossible for attackers to insert trades in between.

Here’s how Jito bundles work:

• Bundle Transactions: Combine multiple transactions into a single bundle.
• Atomic Execution: Ensure that all transactions in the bundle execute together or fail together.

Code Example

Here’s how you can create a Jito bundle in Solana using the @solana/web3.js library:

const { Connection, Keypair, Transaction, sendAndConfirmTransaction } = require('@solana/web3.js');

const connection = new Connection('https://api.mainnet-beta.solana.com');
const wallet = Keypair.generate();

// Create transactions
const tx1 = new Transaction().add(/* your instructions */);
const tx2 = new Transaction().add(/* your instructions */);

// Combine into a bundle
const bundle = [tx1, tx2];

// Send the bundle
sendAndConfirmTransaction(connection, bundle, [wallet]).then((signature) => {
  console.log('Bundle confirmed:', signature);
});

Real-world Example:
In Solana, Jito bundles have been shown to reduce sandwich attack success rates by over 90%. This is because attackers can’t front-run or back-run individual transactions within the bundle.

2. Minimize Mempool Exposure

Another effective strategy is to limit the time your transaction spends in the mempool. This can be achieved by:

• Using Flashbots on Ethereum to submit transactions directly to miners.
• Setting tighter gas limits and gas prices to prioritize confirmation.

Code Example (Flashbots)

Here’s how to use Flashbots on Ethereum to submit a private transaction:

const { FlashbotsBundleProvider } = require('@flashbots/ethers-provider-bundle');
const { ethers } = require('ethers');

const provider = new ethers.providers.JsonRpcProvider('https://eth-mainnet.alchemyapi.io/v2/YOUR_API_KEY');
const wallet = new ethers.Wallet('YOUR_PRIVATE_KEY', provider);

const flashbotsProvider = await FlashbotsBundleProvider.create(provider, wallet);

const signedTx = await wallet.signTransaction({
  to: '0xRECIPIENT_ADDRESS',
  value: ethers.utils.parseEther('1.0'),
  gasLimit: 21000,
  gasPrice: ethers.utils.parseUnits('50', 'gwei'),
});

const bundle = [
  { signedTransaction: signedTx }
];

const targetBlock = (await provider.getBlockNumber()) + 1;

await flashbotsProvider.sendBundle(bundle, targetBlock);

3. Optimize Trade Size and Timing

Large trades are more susceptible to sandwich attacks because they have a greater price impact. By breaking your trades into smaller chunks and executing them at different times, you can reduce visibility and attract less attention from attackers.

Practical Tip

For example, if you want to buy $10,000 worth of Token X, consider splitting it into ten $1,000 trades executed over several blocks.

Lessons Learned

Here are some key takeaways from my experience:

• Sandwich attacks are a serious threat: They can significantly reduce your profits, especially in low-liquidity markets.
• Atomicity is your friend: Tools like Jito bundles and Flashbots can protect your transactions from being sandwiched.
• Timing matters: Executing trades quickly or at unusual times can help you avoid detection.

Conclusion

Sandwich attacks are a pervasive issue in decentralized trading, but they aren’t insurmountable. By understanding how these attacks work and leveraging tools like Jito bundles, Flashbots, and optimized trade strategies, you can protect your bots and maximize your profits. Remember, staying ahead of attackers requires vigilance, creativity, and a deep understanding of the blockchain ecosystem.

---

🚀 Try It Yourself & Get Airdropped

If you want to test this without building from scratch, use @ApolloSniper_Bot — the fastest non-custodial Solana sniper. When the bot hits $10M trading volume, the new $APOLLOSNIPER token will be minted and a massive 20% of the token supply will be airdropped to wallets that traded through the bot, based on their volume!

Join the revolution today.