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Microsoft Purview | Insider Risk Management: DLP alerts as indicators

Microsoft Purview | Insider Risk Management: DLP alerts as indicators

Coming soon to Microsoft Purview Insider Risk Management (IRM) admins will be able to select Data Loss Prevention (DLP) alerts as indicators in IRM policies. After this rollout, IRM admins can select DLP policies that they would like to bring into IRM and detect if a user has alerts for the pre-selected DLP policies. When an IRM alert is generated, admin and analysts can see if there are any high-risk alerts for this user within DLP for the policies that are enabled as indicators. This feature will help admins and analysts view this information in IRM without switching to DLP. This message is associated with Microsoft 365 Roadmap ID 475057. When this will happen: Public Preview: We will begin rolling out early March 2025 and expect to complete by late March 2025. General Availability (Worldwide, GCC, GCC High, DoD): We will begin rolling out late May 2025 and expect to complete by mid-June 2025. How this will affect your organization: Admins will be able to enable this indicator in IRM’s global settings for policy indicators. When enabled, this indicator can be selected in the Data Theft by departing users, Data leaks, Data leaks by risky users, Data leaks by priority users, and Risky AI Usage policy templates. Using the indicator 1. In Settings > Insider Risk Management > Policy indicators > Built-in Indicators: Open the Data loss prevention (DLP) alerts indicators (preview) drop-down menu. Select Add DLP policies and choose the DLP policies to bring into IRM. Check the box for Generating alerts from selected DLP policies. Save the changes. Note: This indicator will not work if no DLP policies are added and if the checkbox is not selected. View image in new tab 3. Example of an alert generated by this indicator: The indicator will be available by default for admins to configure. What you need to do to prepare: 2. To use in a policy: In the policy wizard for Data theft by departing users, Data leaks, Data leaks by risky users, Data leaks by priority users, and Risky AI usage policy templates, configure the policies as applicable […]

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by João Ferreira

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