Securing AI APIs with CloudFront Custom Headers

Question

Pulumi · Accepted Answer

To secure AI APIs with CloudFront custom headers, we utilize AWS's CloudFront service along with AWS Lambda@Edge. CloudFront is Amazon's content delivery network (CDN) service that provides a fast and secure way to deliver content. Custom headers add an additional layer of security by verifying that incoming requests to your API have specific headers that you define.

With Pulumi, we can define infrastructure as code, which makes setting up and deploying CloudFront distributions with custom headers straightforward and reproducible.

Here is a step-by-step guide to how you can use Pulumi to secure your AI APIs with CloudFront custom headers:

1. **Create a CloudFront Distribution**: A CloudFront distribution is set up to route traffic to your API endpoint. CloudFront can cache responses at edge locations to reduce latency and has various security features.

2. **Lambda@Edge for Custom Headers**: AWS Lambda@Edge allows you to run functions that customize the content that CloudFront delivers, executing the function in AWS locations closer to the viewer. We'll attach a Lambda function to the CloudFront distribution to check or add custom headers for each request.

3. **Attach Custom Headers Policies**: We can define response header policies that dictate what headers are added to the responses CloudFront sends to viewers. This policy can provide security headers like `Content-Security-Policy`, `X-Content-Type-Options`, or custom headers.

We'll use the `aws.cloudfront.ResponseHeadersPolicy` resource to create a custom headers policy, and then we will associate it with a CloudFront distribution.

Below is the Pulumi program written in Python to set up CloudFront with custom headers for securing AI APIs:

```python
import pulumi
import pulumi_aws as aws

# Create the Lambda@Edge function that will inspect and modify the request headers
lambda_role = aws.iam.Role('lambdaRole',
    assume_role_policy="""{
        "Version": "2012-10-17",
        "Statement": [{
            "Action": "sts:AssumeRole",
            "Effect": "Allow",
            "Principal": {
                "Service": "lambda.amazonaws.com",
                "Service": "edgelambda.amazonaws.com"
            }
        }]
    }"""
)

lambda_function = aws.lambda_.Function('lambdaFunction',
    role=lambda_role.arn,
    handler='index.handler',
    runtime='python3.7',
    code=pulumi.FileArchive('./lambda_code.zip')  # Your Lambda function code archive here.
)

# Create a response headers policy
response_headers_policy = aws.cloudfront.ResponseHeadersPolicy('customHeadersPolicy',
    comment='Custom response headers for AI API',
    cors_config={
        "access_control_allow_methods": {"items": ["GET", "OPTIONS"]},
        "access_control_allow_origins": {"items": ["*"]},
        "access_control_max_age_sec": 3600,
    },
    custom_headers_config={
        "items": [{
            "header": "X-Custom-AI-Header",
            "value": "secure",
            "override": True
        }]
    }
)

# Associate the Lambda function with a CloudFront distribution
distribution = aws.cloudfront.Distribution('distribution',
    origins=[{
        'domain_name': 'your_api_endpoint_here',  # Your API domain name
        'origin_id': 'YourAPIOrigin',
    }],
    enabled=True,
    default_root_object='index.html',
    default_cache_behavior={
        'target_origin_id': 'YourAPIOrigin',
        'viewer_protocol_policy': 'redirect-to-https',
        'min_ttl': 0,
        'default_ttl': 3600,
        'max_ttl': 86400,
        "function_associations": [{
            "event_type": "viewer-request",
            "function_arn": lambda_function.qualified_arn
        }]
    },
    ordered_cache_behaviors=[{
        "path_pattern": "/api/*",
        "target_origin_id": "YourAPIOrigin",
        "viewer_protocol_policy": "https-only",
        "allowed_methods": ["GET", "HEAD", "OPTIONS"],
        "cached_methods": ["GET", "HEAD"],
        "forwarded_values": {
            "query_string": True,
            "cookies": {"forward": "none"},
        },
        "min_ttl": 0,
        "default_ttl": 0,
        "max_ttl": 0,
        "lambda_function_associations": [{
            "event_type": "origin-request",
            "lambda_arn": lambda_function.arn,
            "include_body": False,
        }],
    }],
    viewer_certificate={
        'cloudfront_default_certificate': True
    },
    restrictions={
        'geo_restriction': {
            'restriction_type': 'none'
        }
    },
    # Attach the response headers policy
    response_headers_policy_id=response_headers_policy.id
)

# Export the CloudFront distribution domain name to access our API
pulumi.export('distribution_domain_name', distribution.domain_name)
```

This program does the following:

- Defines an IAM Role that the Lambda function can assume so it has the necessary permissions to execute.
- Creates a new Lambda function that will be used to inspect and modify the headers of requests going through CloudFront (you'll need to provide the Lambda function code in `lambda_code.zip`).
- Creates a custom Response Headers Policy specifying a custom header `X-Custom-AI-Header`.
- Sets up a CloudFront distribution with the following:
    - An origin that is your AI API.
    - A default cache behavior that specifies how CloudFront should handle requests and where it should send them.
    - An association with our Lambda function to execute on `viewer-request` to modify any requests as needed.
    - The custom Response Headers Policy is attached to add headers or override them.
- Exports the CloudFront distribution domain name, which is the URL through which your secured AI API will be accessed.

Please replace `'your_api_endpoint_here'` with your actual AI API endpoint. When executed, this script will create all the required AWS infrastructure to secure your AI API with CloudFront custom headers.