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Event Information

  • The DeleteFunction event in AWS Lambda refers to the event that is triggered when a Lambda function is deleted.
  • This event can be used to track and log the deletion of Lambda functions for auditing and monitoring purposes.
  • By capturing the DeleteFunction event, you can keep track of when and by whom a Lambda function was deleted, which can be useful for troubleshooting or security purposes.

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Examples

  • Unauthorized deletion: If the DeleteFunction action is not properly secured, an unauthorized user may be able to delete Lambda functions, potentially causing disruption to the application or service that relies on those functions.
  • Data loss: If a Lambda function is deleted, any associated data or configurations may also be lost. This can result in data loss or the need to recreate the function and reconfigure it, leading to potential downtime or loss of critical information.
  • Impact on dependent resources: Deleting a Lambda function may have a cascading effect on other resources that depend on it, such as event sources, triggers, or other services. This can lead to unexpected behavior or disruption in the overall system architecture.

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Remediation

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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.

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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

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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 with the appropriate VPC settings, including SubnetIds and SecurityGroupIds.
    • Here’s an example Python script:
    import boto3

lambda_client = boto3.client('lambda')

def enable_vpc_config(lambda_function_name, subnet_ids, security_group_ids):
    response = lambda_client.update_function_configuration(
        FunctionName=lambda_function_name,
        VpcConfig={
            'SubnetIds': subnet_ids,
            'SecurityGroupIds': security_group_ids
        }
    )
    print(response)

enable_vpc_config('my-lambda-function', ['subnet-12345678'], ['sg-12345678'])

  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 with the ARN of the AWS Key Management Service (KMS) key to be used 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 update_function_configuration method from the AWS SDK to update the Lambda function’s configuration.
    • Set the TracingConfig parameter with the value 'Active' to enable AWS X-Ray tracing and CloudTrail logging.
    • 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')