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

If you've ever tried building a crypto trading bot, you've probably encountered the dreaded "sandwich attack." It’s one of the most frustrating experiences for DeFi traders and bot developers. Your bot submits a trade, and suddenly, the price moves against you before your transaction even executes. Worse, someone profits at your expense. This is MEV (Maximal Extractable Value) in action, specifically a "sandwich attack." Today, I’ll explain what sandwich attacks are, why they happen, and how you can protect your bots using techniques like Jito bundles.

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What Are MEV Sandwich Attacks?

MEV refers to the profit miners or validators can extract by reordering, inserting, or censoring transactions within a blockchain block. A sandwich attack is a specific type of MEV exploit where an attacker "sandwiches" your transaction between two of their own. Here’s how it works:

1. Front-Running: The attacker detects your pending buy order for an asset and submits their own buy order before yours.
2. Your Transaction: Your transaction executes at the higher price caused by the attacker’s front-run.
3. Back-Running: The attacker immediately sells the asset at the inflated price, profiting from your trade.

The result? You pay more for the asset, and the attacker pockets the difference.

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The Cost of Sandwich Attacks

Let’s look at some real numbers. Suppose you’re trading ETH/USDC on a decentralized exchange like Uniswap. You place a buy order for 1 ETH when the price is $1,800. Here’s what happens in a sandwich attack:

1. Attacker buys 5 ETH before your transaction, driving the price up to $1,810.
2. Your buy order executes at $1,810.
3. Attacker sells their 5 ETH at $1,810, pushing the price back down.

In this scenario:

• You overpay $10 per ETH.
• The attacker makes $50 profit (5 ETH * $10).

This might seem small, but when scaled across thousands of transactions, sandwich attacks drain millions from traders annually.

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Why Most Bots Are Vulnerable

Most crypto bots are vulnerable to sandwich attacks because they rely on straightforward on-chain transactions. Here are the common mistakes:

1. High Gas Fees: Many bots prioritize low gas fees to save costs, but this makes them easier targets for front-running.
2. Public Mempools: Transactions sit in public mempools before being mined, giving attackers time to exploit them.
3. No MEV Protection: Most bot developers don’t implement MEV protection strategies.

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How to Prevent Sandwich Attacks

Now for the good news: you can protect your bots. Here are proven strategies:

1. Use Private Mempools

Public mempools expose your transactions to attackers. Private mempools, like Flashbots, hide your transactions until they’re mined. Here’s how to use Flashbots in Python:

from web3 import Web3
from flashbots import flashbot

w3 = Web3(Web3.HTTPProvider("https://mainnet.infura.io/v3/YOUR_INFURA_PROJECT_ID"))
flashbot(w3, "YOUR_FLASHBOTS_SIGNATURE")

signed_tx = w3.eth.account.sign_transaction(
    {
        "to": "0xRecipientAddress",
        "value": w3.toWei(1, "ether"),
        "gas": 21000,
        "gasPrice": w3.toWei(20, "gwei"),
        "nonce": w3.eth.get_transaction_count("0xYourAddress"),
    },
    "YOUR_PRIVATE_KEY",
)

response = w3.eth.send_raw_transaction(signed_tx.rawTransaction)

2. Leverage Jito Bundles

Jito is a Solana-based solution that bundles transactions into a single unit, making them harder to sandwich. Here’s how to submit a Jito bundle:

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

const connection = new Connection('https://api.mainnet-beta.solana.com');
const payer = Keypair.fromSecretKey(Uint8Array.from([...]));

const tx1 = new Transaction().add(...);
const tx2 = new Transaction().add(...);

const bundle = new JitoBundle([tx1, tx2]);
const signature = await connection.sendBundle(bundle, [payer]);

3. Optimize Gas Strategies

Set gas prices strategically. For example, use tools like GasNow or Etherscan’s Gas Tracker to determine competitive gas prices. Avoid setting gas too low, as this makes your transaction an easy target.

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Lessons Learned

Here are key takeaways from my experience:

• MEV is Unavoidable: MEV exists in every blockchain ecosystem. The goal is to minimize its impact.
• Private Transactions Are Essential: Always use private mempools or off-chain solutions like Flashbots or Jito.
• Test Thoroughly: Before deploying your bot, simulate sandwich attacks in a test environment.
• Monitor Gas Fees: Stay updated on gas fee trends and adjust your bot’s strategy accordingly.

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Real-World Example

Let’s revisit our ETH/USDC trade, but this time with MEV protection:

1. Private Transaction: You submit your buy order via Flashbots, hiding it from public view.
2. Optimal Gas Price: You set a competitive gas price, ensuring your transaction is mined quickly.
3. Bundle Execution: If using Jito, your transaction is bundled with others, reducing the risk of being sandwiched.

Result:

• You buy ETH at $1,800, as intended.
• No sandwich attack occurs.

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Conclusion

Sandwich attacks are a harsh reality in DeFi, but they’re not unbeatable. By understanding MEV, leveraging tools like Flashbots and Jito, and optimizing your transaction strategy, you can protect your crypto bots from exploitation. Remember, the crypto space evolves rapidly—stay informed and adapt your strategies accordingly. Happy trading!

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