> 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/appsec-aws-372.md).

# AWS SageMaker Flow Definition does not use KMS for output configurations misconfiguration detected i

## Rule Details

|                        |                                           |
| ---------------------- | ----------------------------------------- |
| Cortex AppSec Rule ID  | APPSEC\_AWS\_372                          |
| Category - Subcategory | Storage - Encryption                      |
| Provider               | AWS                                       |
| Severity               | LOW                                       |
| Framework              | CloudFormation, Terraform, Terraform Plan |

## Impact

This rule checks whether Amazon SageMaker Flow Definitions leverage Key Management Service (KMS) for output configurations. Unencrypted outputs expose sensitive data, increasing the risk of unauthorized access and breaches. KMS ensures data security by encrypting it before storage and physically separating the storage of key material. This strengthens your security posture and adheres to data protection regulations.

## How to Fix

*Resource:* aws\_sagemaker\_flow\_definition

* *Arguments:* output\_config/kms\_key\_id

## Add a KMS key to your SageMaker Flow Definition output configurations, by defining a `kms_key_id` property in the `output_config` block of your AWS SageMaker Flow Definition. \[source,go]

resource "aws\_sagemaker\_flow\_definition" "example" { ... output\_config {

* kms\_key\_id = "example" } }

***


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