Front-running awareness in Blockchain / Solidity - Mini Project: Build & Apply

Front-running Awareness in Blockchain Transactions

📖 Scenario: You are working with blockchain transaction data. Front-running is when someone sees a transaction before it is confirmed and tries to act first to gain an advantage. We want to detect possible front-running by checking if a transaction with a higher gas price was submitted shortly after another transaction.

🎯 Goal: Build a simple program that stores a list of blockchain transactions, sets a time threshold, finds transactions that might be front-run based on gas price and time, and prints those suspicious transactions.

📋 What You'll Learn

Create a list of transactions with exact details

Add a time threshold variable

Use a loop to find transactions that might be front-run

Print the suspicious transactions

💡 Why This Matters

🌍 Real World

Detecting front-running helps protect users from unfair transaction ordering in blockchain networks.

💼 Career

Blockchain developers and security analysts use such techniques to monitor and improve transaction fairness.

1

Create the transaction list

Create a list called transactions with these exact dictionaries: {'tx_id': 'tx1', 'gas_price': 50, 'timestamp': 1000}, {'tx_id': 'tx2', 'gas_price': 70, 'timestamp': 1005}, {'tx_id': 'tx3', 'gas_price': 40, 'timestamp': 1010}, {'tx_id': 'tx4', 'gas_price': 80, 'timestamp': 1012}.

Blockchain / Solidity

# Create the list of transactions with exact entries
# Your code here

Need a hint?

Use a list of dictionaries with keys 'tx_id', 'gas_price', and 'timestamp'.

2

Set the time threshold

Create a variable called time_threshold and set it to 7.

Blockchain / Solidity

transactions = [
    {'tx_id': 'tx1', 'gas_price': 50, 'timestamp': 1000},
    {'tx_id': 'tx2', 'gas_price': 70, 'timestamp': 1005},
    {'tx_id': 'tx3', 'gas_price': 40, 'timestamp': 1010},
    {'tx_id': 'tx4', 'gas_price': 80, 'timestamp': 1012}
]
# Set the time threshold variable
# Your code here

Need a hint?

Just create a variable with the exact name and value.

3

Find possible front-running transactions

Create an empty list called front_running. Use a for loop with variables i and j to compare each pair of transactions in transactions. If transaction j has a higher gas_price than transaction i and the difference in timestamp is less than time_threshold, append a tuple (transactions[i]['tx_id'], transactions[j]['tx_id']) to front_running.

Blockchain / Solidity

transactions = [
    {'tx_id': 'tx1', 'gas_price': 50, 'timestamp': 1000},
    {'tx_id': 'tx2', 'gas_price': 70, 'timestamp': 1005},
    {'tx_id': 'tx3', 'gas_price': 40, 'timestamp': 1010},
    {'tx_id': 'tx4', 'gas_price': 80, 'timestamp': 1012}
]
time_threshold = 7
# Find front-running pairs and store in front_running
# Your code here

Need a hint?

Use nested loops to compare each transaction pair and check conditions.

4

Print suspicious transactions

Write a print statement to display the front_running list.

Blockchain / Solidity

transactions = [
    {'tx_id': 'tx1', 'gas_price': 50, 'timestamp': 1000},
    {'tx_id': 'tx2', 'gas_price': 70, 'timestamp': 1005},
    {'tx_id': 'tx3', 'gas_price': 40, 'timestamp': 1010},
    {'tx_id': 'tx4', 'gas_price': 80, 'timestamp': 1012}
]
time_threshold = 7
front_running = []
for i in range(len(transactions)):
    for j in range(i + 1, len(transactions)):
        if (transactions[j]['gas_price'] > transactions[i]['gas_price'] and
            transactions[j]['timestamp'] - transactions[i]['timestamp'] < time_threshold):
            front_running.append((transactions[i]['tx_id'], transactions[j]['tx_id']))
# Print the front_running list
# Your code here

Need a hint?

Just print the list variable front_running.