Databricks Connection Method

Table of Contents

Open AI and Hugging Face Connection Method

Databricks Connection Method

Use Databricks connection method for adding targets.

Where Can I Use This?	What Do I Need?
Prisma AIRS (AI Red Teaming)	Prisma AIRS AI Red Teaming license Prisma AIRS AI Red Teaming deployment profile A Databricks workspace with a deployed model endpoint A personal access token or OAuth service principal credentials

Databricks connection methods use the Databricks Connect client library for IDEs, the JDBC/ODBC drivers for BI tools like Excel, and, HTTP connections for connecting to external services (for example, IBM's Watsonx). When you use the Databricks connection method you set the authentication method and additional details about the connection.

After specifying Target Details, set the Connection Method to Databricks.
Select Next: Add/Verify Parameters.
In the Add/Verify Parameters page, you'll need to set the authentication mechanism and additional connection details. In the Databricks Authentication Mechanism section, select the Authentication Type (either an Access Token, or a Service Principal):
1. Select Access Token to authenticate using a personal Databricks access token.
2. Enter an Access Token.
3. Alternately, you can use a OAuth as the Authentication Type for the connection. In this scenario, you'll authenticate using service principals for programmatic access.
4. For the OAuth authentication type, specify the Client ID and enter the corresponding Secret.
In the Databricks Connection Details section:
1. Specify the API Endpoint (for example, www.google.co.in).
2. Enter a Model Name (for example, gpt-3.5-turbo).
Click Next: Verify & Edit JSON.
In the Verify & Edit JSON page, specify the JSON structure of the request.
Click Next: Advanced Configurations.
In the Advanced Configurations page you'll configure Rate Limits and set Guardrails/Content Filters.
(Optional) Enable Rate Limits for applications on the target endpoint.
1. Specify the Endpoint Rate Limit. This value represents the maximum number of allowed requests per minute for the specified endpoint.
2. Specify the Endpoint Rate Limit Error Code. This field represents the error code your system uses for rate limiting violations.
3. Provide a Sample Exception JSON.
(Optional) Enable Guardrails/Content Filters. These fields are used for output guardrails or content filters applicable on the target endpoint.
1. Specify the Error code for Guardrails or Content Filters. This field represents the error code your system uses when a response is prevented by filters or safeguards.
2. Provide a Sample Exception JSON.
3. Select Validate Target.
  
  Only after a target is successfully validated, you can add target background information.
(Mandatory) Configure Target Background.

AI Red Teaming collects and organizes the Target background information about your target endpoint. Target background encompasses mandatory elements such as, industry classification, use case definition, and competitive landscape analysis, along with optional documentation uploads including company policy documents and other relevant materials.

Target background information is mandatory for all the target types.
1. Add Industry information.
2. Add Use Case, that is specific role of the target such as customer service or additional comments.
3. (Optional) Select Add Competitor to add the list of Competitors.
4. Enable Agentic Profiling.
  Agentic Profiling in AI Red Teaming helps gather all relevant context about a target endpoint such as its business use case, background, key capabilities, technical architecture and other critical information. This is carried out by an autonomous agent probing the target endpoint with the right prompts. All information gathered through this exercise is presented as the Target's profile and is used downstream in AI Red Teaming Scans using the Agent.
Select Submit.
Once the target is created you can start a scan, or view previously created targets: