1. AI Data Ingestion Endpoint Security with AWS WAF

    Python

    To secure a data ingestion endpoint, we can use AWS Web Application Firewall (WAF) to protect the endpoint from common web exploits, bots, and other threats. The WAF can be integrated with API Gateway, which is a common AWS service used to create data ingestion endpoints.

    In this Pulumi program, we are going to set up a secure data ingestion endpoint using AWS API Gateway and protecting it with AWS WAF. The resources we'll define in the program include:

    1. aws.wafv2.WebAcl: The Web ACL (Access Control List) which contains a set of rules that allow or block traffic based on conditions such as IP addresses, HTTP headers, HTTP body, URI strings, SQL injection and more.
    2. aws.apigatewayv2.Api: An API endpoint for data ingestion which will be integrated with the AWS WAF Web ACL.
    3. aws.wafv2.WebAclAssociation: This resource associates the Web ACL to the API Gateway, providing protection to the data ingestion endpoint.

    Here is what we will do in the Pulumi program:

    • Import the Pulumi AWS SDK and define a Pulumi Python stack.
    • Create a Web ACL with predefined AWS Managed Rule Sets that protect against common threats.
    • Define an API Gateway for AWS (v2) as the data ingestion endpoint.
    • Associate the Web ACL with the API Gateway to ensure traffic going through the API is inspected and filtered by WAF.

    Let's start the Pulumi program:

    import pulumi import pulumi_aws as aws # Create a Web ACL using AWS WAFv2 that specifies the default action for requests that do not match any rules. web_acl = aws.wafv2.WebAcl("webAcl", scope="REGIONAL", default_action=aws.wafv2.WebAclDefaultActionArgs( allow={}, # By default, we are allowing requests. You can change to 'block' to deny by default. ), visibility_config=aws.wafv2.WebAclVisibilityConfigArgs( cloudwatch_metrics_enabled=True, metric_name="dataIngestionWebAcl", sampled_requests_enabled=True, ), rules=[ aws.wafv2.WebAclRuleArgs( # Example of adding a managed rule group. name="AWSManagedRulesCommonRuleSet", priority=0, override_action=aws.wafv2.WebAclRuleOverrideActionArgs( none={}, ), statement=aws.wafv2.WebAclRuleStatementArgs( managed_rule_group_statement=aws.wafv2.WebAclRuleStatementManagedRuleGroupStatementArgs( name="AWSManagedRulesCommonRuleSet", vendor_name="AWS", excluded_rules=[], ), ), visibility_config=aws.wafv2.WebAclRuleVisibilityConfigArgs( cloudwatch_metrics_enabled=True, metric_name="CommonRuleSet", sampled_requests_enabled=True, ), ), # Add other rules or managed rule groups as needed. ] ) # Create an HTTP API endpoint using API Gateway v2 api_endpoint = aws.apigatewayv2.Api("apiEndpoint", protocol_type="HTTP", route_selection_expression="$request.method $request.path", # Add other configuration as needed, e.g., authentication, CORS, etc. ) # Associate the Web ACL with the API Gateway. waf_association = aws.wafv2.WebAclAssociation("wafAssociation", resource_arn=api_endpoint.execution_arn, # Replace with the correct ARN of the API Gateway web_acl_arn=web_acl.arn ) # Export the endpoint URL so it can be easily accessed. pulumi.export("endpoint_url", api_endpoint.api_endpoint)

    This program sets up a simple API Gateway (HTTP type) and associates it with a WAF Web ACL using the Pulumi AWS package. The Web ACL includes the AWS Managed Rules Common Rule Set, which consists of rules that protect against common web exploits. You can customize the included rules or add new ones as needed for your specific use case.

    By associating the Web ACL with the API Gateway, we are effectively filtering all incoming traffic through the WAF, providing a layer of security before the requests hit the actual API endpoint logic. The pulumi.export at the end of the program outputs the endpoint URL, which you can use to interact with your secured data ingestion endpoint.

    Remember to adjust the resource_arn to match the ARN of your API Gateway when creating the WebAclAssociation. If you use different types (e.g., REST API in API Gateway v1), make sure to reflect that in the resource.

    This setup addresses the security at the edge before the traffic reaches your server or cloud functions, providing a good layer of security to prevent exploitation and various attacks.