A unified data governance solution that helps manage, protect, and discover data across your organization
To set up blocking of sensitive content for AI systems using Microsoft Purview, you need to ensure that your Data Loss Prevention (DLP) policies are correctly configured to target the specific applications you want to control. Here are some insights regarding your questions:
- Blocking of Sensitive Test Data: If you are still able to transfer sensitive data despite having set up an inline web traffic policy, it may indicate that the policy is not correctly applied or that the conditions for blocking are not fully met. Ensure that the sensitive data types you want to block are correctly defined in your DLP policy and that the actions specified (e.g., blocking) are properly configured. You may also want to verify that the policy is active and that there are no exceptions or exclusions that might allow the data transfer.
- DLP Inline Web Traffic Policy and SSO: You are correct that the DLP inline web traffic policy can block data transfer for applications that do not utilize Single Sign-On (SSO). If an application is integrated with EntraID as an identity provider, it is generally considered corporate, and therefore, the DLP policy may not block data transfer for that application. To achieve your goal of blocking only for the public Gemini AI while allowing access to the corporate version, you will need to ensure that your policy specifically targets the public version and that the conditions for allowing the corporate version are clearly defined.
In summary, check the configuration of your DLP policies, ensure they are actively monitoring the right applications, and clarify the conditions for blocking versus allowing data transfer based on your requirements.
References: