> 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-35.md).

# Vertex AI runtime is not encrypted with a Customer Managed Key (CMK) misconfiguration detected in co

## Rule Details

|                        |                           |
| ---------------------- | ------------------------- |
| Cortex AppSec Rule ID  | APPSEC2\_GCP\_35          |
| Category - Subcategory | Storage - Encryption      |
| Provider               | GCP                       |
| Severity               | MEDIUM                    |
| Framework              | Terraform, Terraform Plan |

## Impact

This rule's function is to assure that the runtime for Vertex AI, a Google Cloud service focused on machine learning, is encrypted using a Customer Managed Key, or CMK, rather than a default or auto-generated key.

The lack of such encryption could expose data to security threats. A CMK offers an additional protection layer, since the customer fully manages the key's rotation, revocation, and audit logging. If one doesn't use a CMK, control over these elements is lost, increasing the risk of unauthorized access or data breaches.

## How to Fix

*Resource:* google\_notebooks\_runtime

* *Arguments:* virtual\_machine.virtual\_machine\_config.encryption\_config.kms\_key

To fix this issue, you need to ensure that the Vertex AI runtime is set to be encrypted with a customer-managed key (CMK).

## In general, managing keys on your own adds an extra layer of security to your applications. It also gives you more control over how and when those keys are used and retired. \[source,go]

## resource "google\_notebooks\_runtime" "example" { ... virtual\_machine { virtual\_machine\_config { encryption\_config { kms\_key = "an-actual-key" } ... } } }


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://cortex-docs.paloaltonetworks.com/appsec-rules/iac-security/ai-and-machine-learning/appsec2-gcp-35.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.