​
Event Information

  • The UpdateFunctionCode event in AWS Lambda refers to an event that occurs when the code of a Lambda function is updated or modified.
  • This event is triggered when a new version of the function code is deployed, either through manual updates or through automated deployment pipelines.
  • The UpdateFunctionCode event allows developers to track and monitor changes to the function code, enabling them to ensure that the latest version of the code is being used and to troubleshoot any issues that may arise during the update process.

​
Examples

  1. Unauthorized code changes: If security is impacted with UpdateFunctionCode in AWS Lambda, one example could be unauthorized code changes. This can occur if an attacker gains access to the AWS account or the Lambda function’s IAM role and modifies the function’s code. To mitigate this, it is important to follow security best practices such as implementing strong access controls, regularly monitoring and reviewing function code changes, and enabling AWS CloudTrail to track API calls.

  2. Injection of malicious code: Another example of security impact with UpdateFunctionCode is the injection of malicious code. If an attacker gains access to the function’s code, they can inject malicious code that can compromise the security of the Lambda function or the underlying infrastructure. To prevent this, it is crucial to implement secure coding practices, perform code reviews, and use automated security scanning tools to detect and mitigate any potential vulnerabilities.

  3. Exposure of sensitive information: UpdateFunctionCode can also impact security by exposing sensitive information. If the updated code inadvertently includes sensitive data such as API keys, database credentials, or other confidential information, it can be accessed by unauthorized individuals. To prevent this, it is important to follow secure coding practices, implement proper access controls, and use environment variables or secure storage mechanisms to store sensitive information separately from the code. Regularly reviewing and testing the updated code for any potential exposure is also essential.

​
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 or S3 server-side encryption.
    • Click on “Save” to apply the changes.

  3. Monitor the AWS Lambda function after applying the remediation steps to ensure that the identified issues have been resolved and the function is now compliant with security best practices.

​
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. Example 1: Increase Lambda function timeout
    • Identify the Lambda function that requires a timeout increase.
    • Use the AWS SDK for Python (Boto3) to update the function’s configuration.
    • Set the timeout parameter to a higher value, such as 5 minutes (300 seconds).
    • Here’s an example Python script to achieve this:
import boto3

lambda_client = boto3.client('lambda')

def increase_timeout(lambda_function_name):
    response = lambda_client.update_function_configuration(
        FunctionName=lambda_function_name,
        Timeout=300
    )
    print(f"Timeout increased for Lambda function {lambda_function_name}")

increase_timeout('my-lambda-function')
  1. Example 2: Enable VPC configuration for Lambda function
    • Identify the Lambda function that needs to be associated with a VPC.
    • Use the AWS SDK for Python (Boto3) to update the function’s configuration.
    • Set the VpcConfig parameter with the appropriate VPC configuration details.
    • Here’s an example Python script to achieve this:
import boto3

lambda_client = boto3.client('lambda')

def enable_vpc(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(f"VPC configuration enabled for Lambda function {lambda_function_name}")

enable_vpc('my-lambda-function', 'vpc-12345678', ['subnet-12345678', 'subnet-87654321'])
  1. Example 3: Enable encryption at rest for Lambda function
    • Identify the Lambda function that needs encryption at rest.
    • Use the AWS SDK for Python (Boto3) to update the function’s configuration.
    • Set the KMSKeyArn parameter with the ARN of the KMS key to be used for encryption.
    • Here’s an example Python script to achieve this:
import boto3

lambda_client = boto3.client('lambda')

def enable_encryption(lambda_function_name, kms_key_arn):
    response = lambda_client.update_function_configuration(
        FunctionName=lambda_function_name,
        KMSKeyArn=kms_key_arn
    )
    print(f"Encryption at rest enabled for Lambda function {lambda_function_name}")

enable_encryption('my-lambda-function', 'arn:aws:kms:us-east-1:123456789012:key/abcd1234-5678-90ef-ghij-klmnopqrstuv')