iCompaas Support

Profile Applicability

• Level 2

Description

Secrets, such as passwords, API keys, or sensitive data, that are embedded in EC2 Auto Scaling Launch Configurations (typically in the User Data field) can pose significant security risks. Since User Data is often accessible to users with sufficient permissions, sensitive information should be removed and stored securely in services like AWS Secrets Manager or Parameter Store.

Rationale

• Enhanced Security: Prevents exposure of sensitive information to unauthorized entities.

• Risk Mitigation: Reduces the potential for credential misuse and data breaches.

• Compliance: Helps align with industry security standards for protecting sensitive data.

Impact

Pros:

• Protects sensitive credentials and sensitive data from being exposed.

• Reduces the risk of unauthorized access or privilege escalation.

• Supports secure and scalable credential management practices.

Cons:

• Requires effort to refactor configurations for better secrets management.

• Increases complexity when migrating from embedded credentials to centralized secret management solutions.

Default Value

By default, EC2 Auto Scaling Launch Configurations may not enforce secure handling of embedded secrets. Sensitive data in the User Data field must be explicitly managed by the user.

Pre-Requisite

IAM Permissions Required:

• autoscaling:DescribeLaunchConfigurations

• AWS CLI installed and configured.

Remediation

Test Plan:

Using AWS Console:

1. Sign in to the AWS Management Console.

2. Navigate to Auto Scaling Groups and then to Launch Configurations.

3. Open each Launch Configuration and review the User Data field for hardcoded credentials or sensitive data.

Using AWS CLI:

1. List all Launch Configurations and their User Data:
   

   aws autoscaling describe-launch-configurations --query "LaunchConfigurations[*].{Name:LaunchConfigurationName,UserData:UserData}"

2. Decode and inspect the User Data (if Base64 encoded):
   

   echo "<Base64-encoded-UserData>" | base64 --decode

Implementation Steps:

Using AWS Console:

1. Identify Launch Configurations containing sensitive data.

2. Replace sensitive data in the User Data section with references to AWS Secrets Manager or Parameter Store.

3. Create a new Launch Configuration that retrieves secrets dynamically at runtime and update the Auto Scaling Group to use it.

Using AWS CLI:

1. Replace sensitive data with securely managed secrets:

   • Use AWS Secrets Manager:
     

     aws secretsmanager create-secret --name <secret-name> --secret-string <secret-value>

   • Use Parameter Store:
     

     aws ssm put-parameter --name <parameter-name> --value <secret-value> --type SecureString

2. Update the Launch Configuration with secure references:
   

   aws autoscaling create-launch-configuration --launch-configuration-name <new-config-name> --user-data file://updated-user-data.sh

3. Associate the new Launch Configuration with the Auto Scaling Group.

Backout Plan

Using AWS Console:

1. If modifying the Launch Configuration causes issues, revert to the previous Launch Configuration by restoring the original User Data (if available).

2. Save the changes and verify that the EC2 instances launched by Auto Scaling are not exposed to any secrets.

Using AWS CLI:

1. If you need to revert the changes made to User Data, use the original User Data content:
   

   aws autoscaling update-launch-configuration --launch-configuration-name <LAUNCH_CONFIG_NAME> --user-data <ORIGINAL_USER_DATA>

2. Verify the configuration:
   

   aws autoscaling describe-launch-configurations --launch-configuration-name <LAUNCH_CONFIG_NAME>

References

• AWS Secrets Manager Documentation

• AWS Systems Manager Parameter Store

• Best Practices for Managing Secrets in AWS

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