1. Proactive AI Workload Defense with AWS FMS


    AWS Firewall Manager (FMS) is a security management service that allows you to centrally configure and manage firewall rules across your accounts and applications in AWS Organization. When talking about "Proactive AI Workload Defense," you are likely referring to implementing robust and automated security measures that protect your applications and workloads from various threats, using AI to proactively identify and mitigate potential risks.

    In this context, Pulumi can be used to configure AWS FMS policies in a declarative manner using infrastructure as code (IaC). Through IaC, you define your AWS FMS policies in code, which Pulumi then deploys and manages as infrastructure in the AWS Cloud.

    Here is a program written in Python using Pulumi that sets up an AWS FMS policy. The policy is configured to protect AWS resource types with necessary tags and applies security service data for a proactive defense using AWS Shield Advanced, which provides additional protection against Distributed Denial of Service (DDoS) attacks.

    Before running this Pulumi program, you should have the Pulumi CLI installed and configured with your AWS credentials. This program assumes you have already set up AWS Shield Advanced and have the proper IAM role for AWS FMS to deploy the security policy.

    Let's get started with the code:

    import pulumi import pulumi_aws as aws # An AWS FMS Policy for Security Management # Documentation: https://www.pulumi.com/registry/packages/aws/api-docs/fms/policy/ fms_policy = aws.fms.Policy("aiWorkloadDefensePolicy", # Define the name of your policy. name="ProactiveAIWorkloadDefense", # Add a description for your policy. description="Policy for proactive AI workload defense using AWS FMS and Shield Advanced", # Define whether to exclude resources that do not have the tags specified below. exclude_resource_tags=False, # Specify the AWS resource types that this policy should apply to. resource_type="AWS::ElasticLoadBalancing::LoadBalancer", # Specify the security service type (Shield Advanced, WAF, or SecurityGroupsCommon) and managed service data. security_service_policy_data=aws.fms.PolicySecurityServicePolicyDataArgs( type="SHIELD_ADVANCED", # For Shield Advanced, managedServiceData is not applicable, but would be a JSON string for WAF policies. managed_service_data=None, ), # Define a remediation action as enabled. This means AWS FMS will apply the necessary changes automatically. remediation_enabled=True, # Define tags to include resources in this policy. include_map=aws.fms.PolicyIncludeMapArgs( account=[pulumi.Config("aws").require("account_id")] # Replace with your AWS account ID ), # Tags for identifying the FMS Policy in AWS. tags={ "Purpose": "AIWorkloadDefense", } ) # Export the AWS FMS Policy ID pulumi.export("fms_policy_id", fms_policy.id)

    In the fms_policy, we are creating an FMS Policy resource with the following configurations:

    • name: The name given to the FMS policy.
    • description: A brief description to describe the purpose of this policy.
    • exclude_resource_tags: A boolean flag determining if the policy should exclude resources without specified tags. This is set to False to include all resources.
    • resource_type: Indicates that this policy applies to AWS Elastic Load Balancing resources.
    • security_service_policy_data: Includes the type of security service, in this case, SHIELD_ADVANCED, which engages AWS Shield Advanced for DDoS protection.
    • remediation_enabled: When set to True, AWS FMS will automatically apply remediation to the resources if they deviate from the policy.
    • include_map: Allows you to specify accounts or organizational units that the policy applies to. Here, the account ID from the Pulumi configuration is used.
    • tags: Tags that can be assigned for easy identification and governance.

    Note that to fill in account under include_map, you need to have the account ID available in the Pulumi configuration (Pulumi.<stack>.yaml) or replace the pulumi.Config("aws").require("account_id") with your AWS account ID in a string format.

    After running this program with Pulumi CLI (pulumi up), it will create the FMS policy in your AWS account, and you will be able to manage your organization's security posture proactively. The pulumi.export statement at the end of the program is used to output the ID of the created FMS policy, which can be useful for reference or integration with other systems or IaC code.

    Remember to review AWS FMS pricing and AWS Shield Advanced subscription details, as they may incur additional costs on your AWS bill.