Securing AI Data Ingestion Endpoints with AWS WAF

Question

Pulumi · Accepted Answer

When working on securing AI data ingestion endpoints, it's crucial to protect these endpoints from common web exploits that could affect their availability, compromise their security, or consume excessive resources. AWS WAF (Web Application Firewall) allows you to create custom rules that control the traffic reaching your endpoint, so you can allow, block, or monitor requests based on conditions like IP addresses, HTTP headers, HTTP body, or URI strings.

Below, I'll outline a Pulumi Python program that sets up AWS WAF rules to secure an AI data ingestion endpoint that could be exposed via an AWS Application Load Balancer (ALB) or an Amazon API Gateway.

The following resources will be used in the program:

1. `aws.wafregional.IpSet`: Defines a set of IP addresses that WAF will use to allow or block requests.
2. `aws.wafregional.Rule`: Contains a set of conditions and actions that WAF will evaluate against incoming requests.
3. `aws.wafregional.WebAcl`: Associates the rules to protect the specified AWS resource, like an ALB.
4. `aws.wafregional.WebAclAssociation`: Connects the created WebAcl to the ALB or API Gateway.

Assumptions for the program:
- An ALB or API Gateway is already set up, and its ARN will be integrated here for the WAF association.
- You have the necessary permissions to create and manage WAF resources.
- Pulumi and AWS CLI are already configured on your machine.

Detailed explanations will follow in the code comments.

```python
import pulumi
import pulumi_aws as aws

# Creating an IP set that we can use to allow requests only from specific IP addresses.
# IPs are added as an example. Replace them with the actual IP ranges you want to whitelist.
ip_set = aws.wafregional.IpSet("ipSet",
    ip_set_descriptors=[
        {"type": "IPV4", "value": "203.0.113.0/24"},
        {"type": "IPV4", "value": "198.51.100.0/24"},
    ])

# Creating a rule that allows requests from the IP addresses we defined in the IP set.
# We can also create other rules for conditions like SQL injection or cross-site scripting here.
# Replace `data_id` with the actual `ip_set.id` after deploying `IpSet`.
rule = aws.wafregional.Rule("allowRule",
    predicates=[{
        "dataId": ip_set.id,
        "negated": False,
        "type": "IPMatch",
    }],
    metric_name="AllowSpecificIPs")

# Assuming you have an ARN for an ALB or API Gateway, it can be used to create an association with the WAF.
# Replace `resource_arn` with the actual ARN of your ALB or API Gateway.
alb_arn = "arn:aws:elasticloadbalancing:region:account-id:loadbalancer/app/load-balancer-name"

# Creating a Web ACL that defines our rule action (ALLOW, BLOCK, or COUNT) and associates it with our rule.
web_acl = aws.wafregional.WebAcl("webAcl",
    default_action={"type": "ALLOW"},
    metric_name="WebAclMetric",
    rules=[{
        "action": {"type": "ALLOW"},
        "priority": 1,
        "rule_id": rule.id,
    }])

# Associating the above Web ACL with the ALB.
# This ensures that the rules defined in the Web ACL are enforced on the ALB.
web_acl_association = aws.wafregional.WebAclAssociation("webAclAssociation",
    resource_arn=alb_arn,
    web_acl_id=web_acl.id)

# Exporting the Web ACL ID to use in other stacks or reference it elsewhere.
pulumi.export('web_acl_id', web_acl.id)
```

**Explanation:**

- We started by defining a set of valid IP addresses (`IpSet`) from which we'll accept inbound traffic. This is especially useful if you know the specific range of IPs that should be allowed to interact with your AI data ingestion endpoints.
  
- Next, we created a WAF rule (`Rule`) that utilizes the `IpSet` for matching incoming requests based on their source IP. This rule is meant to allow requests that match the IPs we specified, effectively creating a whitelist.

- Then, we prepared a Web ACL (`WebAcl`) that specifies the default action for requests that do not match any rules. Since we want to explicitly allow only our matched IPs, the default action here allows all other requests not caught by rules.
  
- Finally, the `WebAclAssociation` binds the Web ACL we created to the specific AWS resource which, in this program, is represented by `alb_arn`. You'll replace this with the actual ARN for your ALB or API Gateway, completing the linkage that applies our WAF rules to the ingress traffic of your AI endpoints.

After deploying this Pulumi program, your data ingestion endpoints should only accept traffic from the predefined set of IP addresses, greatly reducing the surface area for potential attacks.

Remember, the Web ACL can contain various rules for different types of protections, and you can tailor the rules to the specific needs of your service. This basic setup primarily provides IP-based access control, but AWS WAF can do a lot more, including protecting against common web exploits like SQL injection and cross-site scripting (XSS). You can create additional rules as needed and append them to the `rules` list within the `WebAcl` resource.