Incident Response Automation for Compromised AI Services using AWS GuardDuty

Question

Pulumi · Accepted Answer

Automating incident response using AWS GuardDuty is a proactive approach to security management. AWS GuardDuty is a threat detection service that continuously monitors for malicious activity and unauthorized behavior to protect your AWS accounts and workloads. By leveraging GuardDuty findings, you can automate the process of responding to potential security threats.

Below is a Pulumi program in Python that sets up AWS GuardDuty for incident response. The program does the following:

- **GuardDuty Detector**: Sets up the AWS GuardDuty detector, which is the primary resource representing the threat detection service.
- **Threat Intel Set**: Creates a threat intelligence set of known malicious IP addresses to supplement GuardDuty's built-in threat intelligence.
-  **IPSet**: Defines a set of safe IP addresses that will not be reported by GuardDuty.
- **S3 Bucket**: Creates an S3 bucket where the findings will be exported.
- **GuardDuty Finding Export Configuration**: Configures GuardDuty to export findings to the created S3 bucket for further analysis or evidence preservation.

The exported findings can then be used by a separate workflow system like AWS Step Functions or AWS Lambda to trigger automated incident response actions, such as sending notifications, isolating compromised resources, or initiating a forensic investigation.

Here's the program to set up the initial structure for incident response automation:

```python
import pulumi
import pulumi_aws as aws

# Create a new S3 bucket to store the GuardDuty findings
findings_bucket = aws.s3.Bucket("findingsBucket")

# Initialize the GuardDuty detector
detector = aws.guardduty.Detector("myDetector", enable=True)

# Define a list of known bad IP addresses (this should be replaced with your actual threat intel data)
threat_intel_set = aws.guardduty.ThreatIntelSet("myThreatIntelSet",
    activate=True,
    detector_id=detector.id,
    format="TXT",
    location=pulumi.Output.concat("s3://", findings_bucket.bucket, "/threat-intel-set.txt")
)

# Define a set of trusted IPs that should be omitted from findings
ip_set = aws.guardduty.IpSet("myIPSet",
    activate=True,
    detector_id=detector.id,
    format="TXT",
    location=pulumi.Output.concat("s3://", findings_bucket.bucket, "/ip-set.txt")
)

# Configure exporting of findings to an S3 bucket
export_configuration = aws.guardduty.PublishingDestination("myPublishingDestination",
    bucket=findings_bucket.id, # Reference the S3 bucket created above
    detector_id=detector.id,
    destination_type="S3"
)

# Export URLs for easy access
pulumi.export("findings_bucket_url", findings_bucket.website_endpoint)
pulumi.export("detector_id", detector.id)
```

The `pulumi.export` calls at the end of the program will output the S3 bucket URL where the findings are stored and the detector ID for reference. To make this program operational, you will need to:

1. Replace the threat intelligence and IP set TXT file locations with your own data sources.
2. Add further automation by integrating event-driven services such as AWS Lambda functions that are triggered by new findings in the S3 bucket.

This program sets the foundation for a robust incident response automation system using AWS GuardDuty and Pulumi to manage and codify your cloud security deployment. After deploying this program, you can implement additional workflows based on the GuardDuty findings.