> 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-383.md).

# AWS Bedrock agent is not associated with Bedrock guardrails misconfiguration detected in code

## Rule Details

|                        |                                      |
| ---------------------- | ------------------------------------ |
| Cortex AppSec Rule ID  | APPSEC\_AWS\_383                     |
| Category - Subcategory | AI/ML - Guardrails                   |
| Provider               | AWS                                  |
| Severity               | LOW                                  |
| Framework              | Terraform, Terraform Plan            |
| Mapped CSPM/KSPM Rule  | 4a122e5c-6bc6-4e4f-a757-fb9bcb3c9cc4 |

## Impact

This rule detects whether the AWS Bedrock agent is associated with Bedrock guardrails. Amazon Bedrock Guardrails provides crucial governance and compliance controls for generative AI applications, ensuring their safe and responsible use. Associating Guardrails with the Bedrock agent is essential for enforcing these controls, mitigating the risk of non-compliance and potentially harmful outputs. Not associating Guardrails may expose organizations to various risks, including generating biased, inappropriate, or harmful content. By linking Guardrails, organizations can implement safeguards and prevent unwanted behavior in model responses or user messages.

## How to Fix

*Resource:* aws\_bedrockagent\_agent

* *Arguments:* guardrail\_configuration.guardrail\_identifier

To mitigate this issue, configure the `guardrail_configuration` block in your Terraform configuration to include a valid `guardrail_identifier` argument. This ensures that the appropriate guardrails are associated with the Bedrock agent.

## Example: \[source,go]

resource "aws\_bedrockagent\_agent" "example" { ...

* guardrail\_configuration {
* guardrail\_identifier = "your-guardrail-id" # Replace with a valid guardrail identifier
* } }

***


---

# 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 by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://cortex-docs.paloaltonetworks.com/appsec-rules/iac-security/ai-and-machine-learning/appsec-aws-383.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.