> For the complete documentation index, see [llms.txt](https://cortex-docs.paloaltonetworks.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cortex-docs.paloaltonetworks.com/appsec-rules/iac-security/ai-and-machine-learning/appsec2-gcp-25.md).

# Vertex AI featurestore is not configured to use a Customer Managed Key (CMK) misconfiguration detect

## Rule Details

|                        |                           |
| ---------------------- | ------------------------- |
| Cortex AppSec Rule ID  | APPSEC2\_GCP\_25          |
| Category - Subcategory | Storage - Encryption      |
| Provider               | GCP                       |
| Severity               | MEDIUM                    |
| Framework              | Terraform, Terraform Plan |

## Impact

This rule is examining whether a Vertex AI feature store is using a Customer Managed Key (CMK) for encryption. It is highly important to follow this rule because using a CMK provides greater control over the keys used for encryption. If a default key is used, it could potentially be more vulnerable to certain types of risks such as unauthorized access. With a Customer Managed Key, the user has complete control over the key's rotation, disablement, and deletion, which significantly improves data security.

## How to Fix

*Resource:* google\_vertex\_ai\_featurestore

* *Arguments:* encryption\_spec

To fix this issue, you need to designate a Customer-Managed Encryption Key (CMEK) for your GCP Vertex AI feature store. You can do this by specifying the "encryption\_spec" block and pointing to your Customer-Managed Key in your terraform resource for the feature store.

## The updated Terraform code now includes the "encryption\_spec" configuration, which is set to utilize a Customer-Managed Encryption Key. Now, the feature store data is encrypted using the customer-managed key which enhances the security of sensitive data, as the customer has direct control over key management activities. \[source,go]

## data "google\_vertex\_ai\_featurestore" "example" { ... encryption\_spec { kms\_key\_name = "some\_name" } ... }


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