Event Information

  • The CreateAlias event in AWS Lambda refers to the action of creating an alias for a Lambda function.
  • An alias is a pointer to a specific version of a Lambda function, allowing you to decouple your application from the underlying function version.
  • By creating an alias, you can easily update the function version associated with the alias without changing the alias itself, providing flexibility and seamless updates to your application.

Examples

  • Unauthorized access: If the CreateAlias operation is not properly secured, it could potentially allow unauthorized users to create aliases for Lambda functions. This could lead to unauthorized access to sensitive data or resources within the AWS account.

  • Data leakage: If the CreateAlias operation is misconfigured, it could result in the creation of aliases that inadvertently expose sensitive data. This could occur if the alias is mistakenly associated with a Lambda function that has access to sensitive data sources or if the alias is used in a way that exposes sensitive information in the function’s output.

  • Privilege escalation: If the CreateAlias operation is not properly restricted, it could be abused to escalate privileges within the AWS account. An attacker could create an alias for a Lambda function with elevated permissions, allowing them to perform actions they are not authorized to do. This could lead to unauthorized access to resources or the ability to modify critical infrastructure components.

Remediation

Using Console

  1. Identify the specific issue or vulnerability in the AWS Lambda function by reviewing the event logs or security findings in the AWS console.

  2. Determine the appropriate remediation steps based on the examples provided in the previous response:

    a. Example 1: Excessive permissions for Lambda function

    • Access the AWS Lambda console.
    • Select the specific Lambda function that has excessive permissions.
    • Click on the “Permissions” tab.
    • Review the existing permissions and identify any unnecessary or excessive permissions.
    • Remove the unnecessary permissions by clicking on the “X” icon next to each permission.
    • Click on “Save” to apply the changes.

    b. Example 2: Insecure environment variables in Lambda function

    • Access the AWS Lambda console.
    • Select the specific Lambda function that has insecure environment variables.
    • Click on the “Configuration” tab.
    • Scroll down to the “Environment variables” section.
    • Review the existing environment variables and identify any sensitive information.
    • Remove or encrypt any sensitive environment variables.
    • Click on “Save” to apply the changes.

    c. Example 3: Unencrypted data storage in Lambda function

    • Access the AWS Lambda console.
    • Select the specific Lambda function that has unencrypted data storage.
    • Click on the “Configuration” tab.
    • Scroll down to the “Environment variables” section.
    • Review the existing environment variables and identify any variables related to data storage.
    • Ensure that the data storage variables are configured to use encrypted storage options such as AWS KMS.
    • Click on “Save” to apply the changes.
  3. Monitor the AWS Lambda function after applying the remediation steps to ensure that the issues have been resolved and the function is functioning as expected. Regularly review the event logs and security findings to identify any new issues or vulnerabilities that may arise.

Using CLI

  1. Enable VPC configuration for AWS Lambda:

    • Use the update-function-configuration command to update the Lambda function’s configuration.
    • Specify the --vpc-config parameter with the appropriate VPC configuration details, such as SubnetIds and SecurityGroupIds.
    • Example command: aws lambda update-function-configuration --function-name <function-name> --vpc-config SubnetIds=<subnet-ids>,SecurityGroupIds=<security-group-ids>
  2. Enable encryption at rest for AWS Lambda function code:

    • Use the update-function-configuration command to update the Lambda function’s configuration.
    • Specify the --kms-key-arn parameter with the ARN of the KMS key to be used for encryption.
    • Example command: aws lambda update-function-configuration --function-name <function-name> --kms-key-arn <kms-key-arn>
  3. Enable AWS CloudTrail logging for AWS Lambda:

    • Use the update-function-configuration command to update the Lambda function’s configuration.
    • Specify the --tracing-config parameter with the appropriate tracing configuration details, such as Mode set to Active.
    • Example command: aws lambda update-function-configuration --function-name <function-name> --tracing-config Mode=Active

Using Python

  1. Enable VPC configuration for AWS Lambda:

    • Use the update_function_configuration method from the AWS SDK to update the Lambda function’s configuration.
    • Set the VpcConfig parameter to specify the VPC and subnets to associate with the Lambda function.
    • Here’s an example Python script:
    import boto3
    
    lambda_client = boto3.client('lambda')
    
    def enable_vpc_config(lambda_function_name, vpc_id, subnet_ids):
        response = lambda_client.update_function_configuration(
            FunctionName=lambda_function_name,
            VpcConfig={
                'SubnetIds': subnet_ids,
                'SecurityGroupIds': [],
                'VpcId': vpc_id
            }
        )
        print(response)
    
    enable_vpc_config('my-lambda-function', 'vpc-12345678', ['subnet-12345678', 'subnet-87654321'])
    
  2. Enable encryption at rest for AWS Lambda function:

    • Use the update_function_configuration method from the AWS SDK to update the Lambda function’s configuration.
    • Set the KMSKeyArn parameter to specify the ARN of the AWS Key Management Service (KMS) key to use for encryption.
    • Here’s an example Python script:
    import boto3
    
    lambda_client = boto3.client('lambda')
    
    def enable_encryption_at_rest(lambda_function_name, kms_key_arn):
        response = lambda_client.update_function_configuration(
            FunctionName=lambda_function_name,
            KMSKeyArn=kms_key_arn
        )
        print(response)
    
    enable_encryption_at_rest('my-lambda-function', 'arn:aws:kms:us-east-1:123456789012:key/abcd1234-5678-90ab-cdef-1234567890ab')
    
  3. Enable AWS CloudTrail logging for AWS Lambda:

    • Use the AWS Management Console or the update_function_configuration method from the AWS SDK to update the Lambda function’s configuration.
    • Set the TracingConfig parameter to enable AWS X-Ray tracing for the Lambda function.
    • Here’s an example Python script:
    import boto3
    
    lambda_client = boto3.client('lambda')
    
    def enable_cloudtrail_logging(lambda_function_name):
        response = lambda_client.update_function_configuration(
            FunctionName=lambda_function_name,
            TracingConfig={
                'Mode': 'Active'
            }
        )
        print(response)
    
    enable_cloudtrail_logging('my-lambda-function')