Use Content Safety in Azure AI Foundry portal

Azure AI Foundry includes a Content Safety try it out page that lets you use the core detection models and other content safety features.

Prerequisites

• An Azure account. If you don't have one, you can create one for free.
• An Azure AI resource.

Setup

Follow these steps to use the Content Safety try it out page:

1. Go to Azure AI Foundry and navigate to your project/hub. Then select the Safety+ Security tab on the left nav and select the Try it out tab.
2. On the Try it out page, you can experiment with various content safety features such as text and image content, using adjustable thresholds to filter for inappropriate or harmful content.

Analyze text

1. Select the Moderate text content panel.
2. Add text to the input field, or select sample text from the panels on the page.
3. Select Run test. The service returns all the categories that were detected, with the severity level for each: 0-Safe, 2-Low, 4-Medium, 6-High. It also returns a binary Accepted/Rejected result, based on the filters you configure. Use the matrix in the Configure filters tab to set your allowed/prohibited severity levels for each category. Then you can run the text again to see how the filter works.

Use a blocklist

The Use blocklist tab lets you create, edit, and add a blocklist to the moderation workflow. If you have a blocklist enabled when you run the test, you get a Blocklist detection panel under Results. It reports any matches with the blocklist.

Analyze images

The Moderate image page provides capability for you to quickly try out image moderation.

1. Select the Moderate image content panel.
2. Select a sample image from the panels on the page, or upload your own image.
3. Select Run test. The service returns all the categories that were detected, with the severity level for each: 0-Safe, 2-Low, 4-Medium, 6-High. It also returns a binary Accepted/Rejected result, based on the filters you configure. Use the matrix in the Configure filters tab on the right to set your allowed/prohibited severity levels for each category. Then you can run the text again to see how the filter works.

View and export code

You can use the View Code feature in either the Analyze text content or Analyze image content pages to view and copy the sample code, which includes configuration for severity filtering, blocklists, and moderation functions. You can then deploy the code on your end.

Use Prompt Shields

The Prompt Shields panel lets you try out user input risk detection. Detect User Prompts designed to provoke the Generative AI model into exhibiting behaviors it was trained to avoid or break the rules set in the System Message. These attacks can vary from intricate role-play to subtle subversion of the safety objective.

1. Select the Prompt Shields panel.
2. Select a sample text on the page, or input your own content for testing.
3. Select Run test. The service returns the risk flag and type for each sample.

For more information, see the Prompt Shields conceptual guide.

Use Groundedness detection

The Groundedness detection panel lets you detect whether the text responses of large language models (LLMs) are grounded in the source materials provided by the users.

1. Select the Groundedness detection panel.
2. Select a sample content set on the page, or input your own for testing.
3. Optionally, enable the reasoning feature and select your Azure OpenAI resource from the dropdown.
4. Select Run test. The service returns the groundedness detection result.

For more information, see the Groundedness detection conceptual guide.

Use Protected material detection

This feature scans AI-generated text for known text content (for example, song lyrics, articles, recipes, selected web content).

1. Select the Protected material detection for text or Protected material detection for code panel.
2. Select a sample text on the page, or input your own for testing.
3. Select Run test. The service returns the protected content result.

For more information, see the Protected material conceptual guide.

Use custom categories

This feature lets you create and train your own custom content categories and scan text for matches.

1. Select the Custom categories panel.
2. Select Add a new category to open a dialog box. Enter your category name and a text description, and connect a blob storage container with text training data. Select Create and train.
3. Select a category and enter your sample input text, and select Run test. The service returns the custom category result.

For more information, see the Custom categories conceptual guide.

Next step

To use Azure AI Content Safety features with your Generative AI models, see the Content filtering guide.