Exercise 36: Cloud Database Misconfiguration and Data Exposure

Objective:

Understand how misconfigurations in cloud databases, such as weak authentication, excessive permissions, or public access, can lead to sensitive data exposure. Simulate attacks to exploit these misconfigurations and learn best practices to secure cloud databases.

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Scenario:

An organization deploys a cloud database, such as AWS RDS or Google Cloud SQL, with weak authentication settings, such as public access or default credentials. Attackers exploit these misconfigurations to gain unauthorized access and exfiltrate sensitive data. Your goal is to simulate this scenario, demonstrate its impact, and recommend mitigation strategies.

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Lab Setup:

Prerequisites:

1. Access to a cloud platform:
   • AWS (RDS) or Google Cloud (SQL).
2. Installed tools:
   • nmap (Download).
   • sqlmap (Installation Guide).
   • aws-cli or gcloud CLI.

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Steps to Set Up the Lab:

1. Deploy a Cloud Database:
   • AWS RDS:
     1. Create an RDS instance with public access:bashCopyEditaws rds create-db-instance \ --db-instance-identifier misconfigured-db \ --db-instance-class db.t2.micro \ --engine mysql \ --allocated-storage 20 \ --master-username admin \ --master-user-password admin123 \ --publicly-accessible
     2. Note the endpoint of the database.
   • Google Cloud SQL:
     1. Create a Cloud SQL instance with public access enabled:bashCopyEditgcloud sql instances create misconfigured-db \ --database-version=MYSQL_8_0 \ --tier=db-f1-micro \ --region=us-central1 \ --network=default
     2. Set a weak password for the root user:bashCopyEditgcloud sql users set-password root --instance=misconfigured-db --password=admin123
2. Create a Sample Database and Table:
   • Populate the database with sensitive data:
     • Use the MySQL CLI or a GUI tool (e.g., MySQL Workbench):sqlCopyEditCREATE DATABASE sensitive_data; USE sensitive_data; CREATE TABLE users ( id INT AUTO_INCREMENT PRIMARY KEY, name VARCHAR(50), email VARCHAR(100), password VARCHAR(50) ); INSERT INTO users (name, email, password) VALUES ('John Doe', '[email protected]', 'password123'), ('Jane Smith', '[email protected]', '12345');
3. Misconfigure Database Access:
   • AWS RDS:
     • Modify the RDS security group to allow inbound traffic from all IPs (0.0.0.0/0) on port 3306.
   • Google Cloud SQL:
     • Add a public IP for the database and allow traffic from all IPs.
4. Disable Logging or Auditing:
   • Disable database activity logging or fail to enable it during setup.

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Exercise: Exploiting the Misconfigured Database

Objective:

Simulate attacks to exploit weak authentication and public access.

1. Scan for Open Ports:
   • Use nmap to identify the open database port (3306):bashCopyEditnmap -Pn -p 3306 <db-endpoint>
2. Test Database Access:
   • Attempt to connect to the database using the default credentials:
     • MySQL CLI:bashCopyEditmysql -h <db-endpoint> -u admin -padmin123
3. Perform SQL Injection (Optional):
   • Use sqlmap to test for SQL injection vulnerabilities:bashCopyEditsqlmap -u "mysql://admin:admin123@<db-endpoint>:3306/sensitive_data" --tables
4. Exfiltrate Data:
   • Extract sensitive data from the database:sqlCopyEditSELECT * FROM users;
5. Analyze the Attack:
   • Identify how weak access controls and authentication enabled the attack.

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Tools Required:

1. AWS RDS or Google Cloud SQL: For deploying the database.
2. nmap: For port scanning and service enumeration.
3. sqlmap: For testing SQL injection and automating database exploitation.
4. MySQL CLI or GUI tools: For accessing and managing the database.

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Deliverables:

1. Exploit Report:
   • Evidence of accessing or extracting sensitive data using compromised credentials.
   • Logs or screenshots of unauthorized access.
2. Recommendations:
   • Best practices for securing cloud databases.

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Solution:

1. Identified Vulnerabilities:
   • Public Access: The database was accessible from any IP address.
   • Weak Credentials: Default or weak passwords allowed unauthorized access.
   • No Logging or Monitoring: There were no logs to detect suspicious activities.
2. Consequences:
   • Data Breach: Sensitive data, such as user credentials, was exposed.
   • Regulatory Violations: Non-compliance with data protection regulations, such as GDPR or HIPAA.
   • Operational Risks: Unauthorized access could lead to data modification or deletion.
3. Prevention Techniques:
   • Restrict Database Access:
     • Limit inbound traffic to trusted IP ranges in the security group or firewall:
       • AWS:bashCopyEditaws ec2 authorize-security-group-ingress \ --group-id <security-group-id> \ --protocol tcp \ --port 3306 \ --cidr <trusted-ip-range>/32
       • Google Cloud:
         • Add a private IP and restrict access using VPC.
   • Use Strong Authentication:
     • Enforce strong passwords and disable default accounts.
   • Enable SSL/TLS Encryption:
     • Require encrypted connections for all database traffic.
   • Enable Logging and Monitoring:
     • AWS:
       • Enable CloudTrail for database activity tracking.
     • Google Cloud:
       • Enable Cloud Audit Logs for Cloud SQL.
   • Perform Regular Audits:
     • Review database access logs and audit configurations periodically.
   • Implement Role-Based Access Control (RBAC):
     • Assign roles with the least privileges required for their tasks.

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Conclusion:

This exercise demonstrates how cloud database misconfigurations, such as weak authentication or public access, can lead to sensitive data exposure. By restricting access, enforcing secure authentication, and enabling logging, organizations can protect their cloud databases from unauthorized access and data breaches.