Exercise 13: Cloud-Based Credential Stuffing Attack

Objective:

Understand how attackers use credential stuffing to exploit cloud-based login systems by leveraging breached credentials. Learn best practices to secure login mechanisms against such attacks, including multi-factor authentication (MFA), rate-limiting, and anomaly detection.

Scenario:

A cloud-based application is using AWS Cognito or Firebase Authentication for user login. An attacker uses a list of previously breached credentials to attempt a credential stuffing attack and gain unauthorized access to user accounts. Your goal is to simulate this attack and demonstrate how to prevent it.

Lab Setup:

Prerequisites:

1. Access to a cloud authentication platform:
   • AWS Cognito or Firebase Authentication.
2. Installed tools:
   • Burp Suite (Download).
   • Hydra (Download).
   • A list of test credentials (mock breached credentials).

Steps to Set Up the Lab:

Set Up AWS Cognito or Firebase Authentication:

Option 1: AWS Cognito:

Navigate to AWS Cognito > Manage User Pools > Create a user pool.

Enable self-registration with attributes like email and password.

Set a simple password policy for demonstration purposes.

Create a test user with valid credentials (e.g., [email protected] with password Password123).

Option 2: Firebase Authentication:

Go to the Firebase Console > Authentication > Sign-in method.

Enable email/password authentication.

Add a test user with valid credentials.

Deploy a Test Application:

Use a pre-built or simple web app (e.g., React, Flask) connected to the authentication system for login.

Host the application publicly or locally using a service like AWS Amplify or Firebase Hosting.

Prepare Mock Breached Credentials:

Create a text file (breached-credentials.txt) with the following format:

user1@example.com:Password123
user2@example.com:WeakPassword
admin@example.com:Admin123

Include valid credentials for one or more test users to simulate successful credential stuffing attempts.

Exercise: Simulating a Credential Stuffing Attack

Objective:

Use automated tools to simulate a credential stuffing attack and demonstrate how attackers exploit weak login mechanisms.

Perform Credential Stuffing with Hydra:

Identify the login endpoint of your application.

Use Hydra to test the list of breached credentials:

hydra -l user1@example.com -P breached-credentials.txt <app-domain> http-post-form "/login:username=^USER^&password=^PASS^:Invalid credentials"

Observe successful login attempts.

Intercept Login Requests with Burp Suite:

Configure your browser to use Burp Suite as a proxy.

Navigate to the login page and capture a valid login request.

Use Burp Intruder to automate testing of the credentials in breached-credentials.txt.

Analyze Application Behavior:

Check if successful login attempts lead to unauthorized access.

Observe if the application implements rate-limiting or locks out accounts after repeated failed attempts.

Tools Required:

1. AWS Cognito or Firebase Authentication: For setting up the authentication service.
2. Hydra: For automating credential stuffing attacks.
3. Burp Suite: For intercepting and automating login requests.
4. Mock Breached Credentials: For testing the attack.

Deliverables:

1. Exploit Report:
   • Evidence of successful credential stuffing attempts.
   • Screenshots or logs showing the automation of login attempts.
2. Recommendations for Mitigating Credential Stuffing:
   • Steps to implement MFA, rate-limiting, and anomaly detection.

Solution:

Identified Vulnerabilities:

No Rate-Limiting: The application allowed repeated login attempts without restriction.

No MFA: Accounts could be accessed with just a username and password.

Weak Password Policies: Allowed predictable passwords that were easily guessed.

Consequences:

Account Takeover: Attackers gain unauthorized access to user accounts.

Data Breach: Access to sensitive user data or resources.

Compliance Violations: Failure to secure login mechanisms may violate GDPR, HIPAA, or other regulations.

Prevention Techniques:

Enforce Multi-Factor Authentication (MFA):

Require an additional factor, such as a TOTP app or SMS-based code.

Enable MFA in AWS Cognito or Firebase Authentication settings.

Implement Rate-Limiting and Lockouts:

Block IP addresses after a certain number of failed login attempts.

Example AWS WAF rule to limit requests:

{
  "RateBasedStatement": {
    "Limit": 100,
    "AggregateKeyType": "IP"
  }
}

Monitor for Anomalies:

Use CloudTrail (AWS) or Firebase Analytics to track login attempts and detect unusual activity.

Educate Users:

Notify users if their credentials are part of a breach and encourage password updates.

Use Strong Password Policies:

Enforce a minimum password length and complexity requirements.

Example AWS Cognito password policy:

Minimum length: 8 characters.

Require uppercase, lowercase, numbers, and special characters.

Conclusion:

This exercise demonstrates how attackers exploit credential stuffing to access cloud-based applications. By implementing MFA, rate-limiting, and anomaly detection, organizations can significantly reduce the risk of such attacks and secure user accounts.