Purview DLP Behaviours in Outlook Desktop
We are currently testing Microsoft Purview DLP policies for user awareness, where sensitive information shared externally triggers a policy tip, with override allowed (justification options enabled) and no blocking action configured. We are observing the following behaviours in Outlook Desktop: Inconsistent policy tip display (across Outlook Desktop Windows clients) – For some users, the policy tip renders correctly, while for others it appears with duplicated/stacked lines of text. This is occurring across users with similar configurations. Override without justification – Users are able to click “Send Anyway/Confirm and send” without selecting any justification option (e.g. business justification, manager approval, etc.), which bypasses the intended control. New Outlook: Classic Outlook: This has been observed on Outlook Desktop (Microsoft 365 Apps), including: Version 2602 (Build 19725.20170 Click-to-Run) Version 2602 (Build 16.0.19725.20126 MSO) Has anyone experienced similar behaviour with DLP policy tips or override enforcement in Outlook Desktop? Keen to understand if this is a known issue or if there are any recommended fixes or workarounds.Why UK Enterprise Cybersecurity Is Failing in 2026 (And What Leaders Must Change)
Enterprise cybersecurity in large organisations has always been an asymmetric game. But with the rise of AI‑enabled cyber attacks, that imbalance has widened dramatically - particularly for UK and EMEA enterprises operating complex cloud, SaaS, and identity‑driven environments. Microsoft Threat Intelligence and Microsoft Defender Security Research have publicly reported a clear shift in how attackers operate: AI is now embedded across the entire attack lifecycle. Threat actors use AI to accelerate reconnaissance, generate highly targeted phishing at scale, automate infrastructure, and adapt tactics in real time - dramatically reducing the time required to move from initial access to business impact. In recent months, Microsoft has documented AI‑enabled phishing campaigns abusing legitimate authentication mechanisms, including OAuth and device‑code flows, to compromise enterprise accounts at scale. These attacks rely on automation, dynamic code generation, and highly personalised lures - not on exploiting traditional vulnerabilities or stealing passwords. The Reality Gap: Adaptive Attackers vs. Static Enterprise Defences Meanwhile, many UK enterprises still rely on legacy cybersecurity controls designed for a very different threat model - one rooted in a far more predictable world. This creates a dangerous "Resilience Gap." Here is why your current stack is failing- and the C-Suite strategy required to fix it. 1. The Failure of Traditional Antivirus in the AI Era Traditional antivirus (AV) relies on static signatures and hashes. It assumes malicious code remains identical across different targets. AI has rendered this assumption obsolete. Modern malware now uses automated mutation to generate unique code variants at execution time, and adapts behaviour based on its environment. Microsoft Threat Intelligence has observed threat actors using AI‑assisted tooling to rapidly rewrite payload components, ensuring that every deployment looks subtly different. In this model, there is no reliable signature to detect. By the time a pattern exists, the attacker has already moved on. Signature‑based detection is not just slow - it is structurally misaligned with AI‑driven attacks. The Risk: If your security relies on "recognising" a threat, you are already breached. By the time a signature exists, the attacker has evolved. The C-Suite Pivot: Shift investment from artifact detection to EDR/XDR (Extended Detection and Response). We must prioritise behavioural analytics and machine learning models that identify intent rather than file names. 2. Why Perimeter Firewalls Fail in a Cloud-First World Many UK enterprise still rely on firewalls enforcing static allow/deny rules based on IP addresses and ports. This model worked when applications were predictable and networks clearly segmented. Today, enterprise traffic is encrypted, cloud‑hosted, API‑driven, and deeply integrated with SaaS and identity services. AI‑assisted phishing campaigns abusing OAuth and device‑code flows demonstrate this clearly. From a network perspective, everything looks legitimate: HTTPS traffic to trusted identity providers. No suspicious port. No malicious domain. Yet the attacker successfully compromises identity. The Risk: Traditional firewalls are "blind" to identity-based breaches in cloud environments. The C-Suite Pivot: Move to Identity-First Security. Treat Identity as the new Control Plane, integrating signals like user risk, device health, and geolocation into every access decision. 3. The Critical Weakness of Single-Factor Authentication Despite clear NCSC guidance, single-factor passwords remain a common vulnerability in legacy applications and VPNs. AI-driven credential abuse has changed the economics of these attacks. Threat actors now deploy adaptive phishing campaigns that evolve in real-time. Microsoft has observed attackers using AI to hyper-target high-value UK identities- specifically CEOs, Finance Directors, and Procurement leads. The Risk: Static passwords are now the primary weak link in UK supply chain security. The C-Suite Pivot: Mandate Phishing‑resistant MFA (Passkeys or hardware security keys). Implement Conditional Access policies that evaluate risk dynamically at the moment of access, not just at login. Legacy Security vs. AI‑Era Reality 4. The Inherent Risk of VPN-Centric Security VPNs were built on a flawed assumption: that anyone "inside" the network is trustworthy. In 2026, this logic is a liability. AI-assisted attackers now use automation to map internal networks and identify escalation paths the moment they gain VPN access. Furthermore, Microsoft has tracked nation-state actors using AI to create synthetic employee identities- complete with fake resumes and deepfake communication. In these scenarios, VPN access isn't "hacked"; it is legally granted to a fraudster. The Risk: A compromised VPN gives an attacker the "keys to the kingdom." The C-Suite Pivot: Transition to Zero Trust Architecture (ZTA). Access must be explicit, scoped to the specific application, and continuously re‑evaluated using behavioural signals. 5. Data: The High-Velocity Target Sensitive data sitting unencrypted in legacy databases or backups is a ticking time bomb. In the AI era, data discovery is no longer a slow, manual process for a hacker. Attackers now use AI to instantly analyse your directory structures, classify your files, and prioritise high-value data for theft. Unencrypted data significantly increases your "blast radius," turning a containable incident into a catastrophic board-level crisis. The Risk: Beyond the technical breach, unencrypted data leads to massive UK GDPR fines and irreparable brand damage. The C-Suite Pivot: Adopt Data-Centric Security. Implement encryption by default, classify data while adding sensitivity labels and start board-level discussions regarding post‑quantum cryptography (PQC) to future-proof your most sensitive assets. 6. The Failure of Static IDS Traditional Intrusion Detection Systems (IDS) rely on known indicators of compromise - assuming attackers reuse the same tools and techniques. AI‑driven attacks deliberately avoid that assumption. Threat actors are now using Large Language Models (LLMs) to weaponize newly disclosed vulnerabilities within hours. While your team waits for a "known pattern" to be updated in your system, the attacker is already using a custom, AI-generated exploit. The Risk: Your team is defending against yesterday's news while the attacker is moving at machine speed. The C-Suite Pivot: Invest in Adaptive Threat Detection. Move toward Graph‑based XDR platforms that correlate signals across email, endpoint, and cloud to automate investigation and response before the damage spreads. From Static Security to Continuous Security Closing Thought: Security Is a Journey, Not a Destination For UK enterprises, the shift toward adaptive cybersecurity is no longer optional - it is increasingly driven by regulatory expectation, board oversight, and accountability for operational resilience. Recent UK cyber resilience reforms and evolving regulatory frameworks signal a clear direction of travel: cybersecurity is now a board‑level responsibility, not a back‑office technical concern. Directors and executive leaders are expected to demonstrate effective governance, risk ownership, and preparedness for cyber disruption - particularly as AI reshapes the threat landscape. AI is not a future cybersecurity problem. It is a current force multiplier for attackers, exposing the limits of legacy enterprise security architectures faster than many organisations are willing to admit. The uncomfortable truth for boards in 2026 is that no enterprise is 100% secure. Intrusions are inevitable. Credentials will be compromised. Controls will be tested. The difference between a resilient enterprise and a vulnerable one is not the absence of incidents, but how risk is managed when they occur. In mature organisations, this means assuming breach and designing for containment: Access controls that limit blast radius Least privilege and conditional access restricting attackers to the smallest possible scope if an identity is compromised Data‑centric security using automated classification and encryption, ensuring that even when access is misused, sensitive data cannot be freely exfiltrated As a Senior Enterprise Cybersecurity Architect, I see this moment as a unique opportunity. AI adoption does not have to repeat the mistakes of earlier technology waves, where innovation moved fast and security followed years later. We now have a rare chance to embed security from day one - designing identity controls, data boundaries, automated monitoring, and governance before AI systems become business‑critical. When security is built in upfront, enterprises don’t just reduce risk - they gain the confidence to move faster and unlock AI’s value safely. Security is no longer a “department”. In the age of AI, it is a continuous business function - essential to preserving trust and maintaining operational continuity as attackers move at machine speed. References: Inside an AI‑enabled device code phishing campaign | Microsoft Security Blog AI as tradecraft: How threat actors operationalize AI | Microsoft Security Blog Detecting and analyzing prompt abuse in AI tools | Microsoft Security Blog Post-Quantum Cryptography | CSRC Microsoft Digital Defense Report 2025 | Microsoft https://www.ncsc.gov.uk/news/government-adopt-passkey-technology-digital-servicesWelcome to the Microsoft Security Community!
Microsoft Security Community Hub | Protect it all with Microsoft Security Eliminate gaps and get the simplified, comprehensive protection, expertise, and AI-powered solutions you need to innovate and grow in a changing world. The Microsoft Security Community is your gateway to connect, learn, and collaborate with peers, experts, and product teams. Gain access to technical discussions, webinars, and help shape Microsoft’s security products. Get there fast To stay up to date on upcoming opportunities and the latest Microsoft Security Community news, make sure to subscribe to our email list. Find the latest skilling content and on-demand videos – subscribe to the Microsoft Security Community YouTube channel. Catch the latest announcements and connect with us on LinkedIn – Microsoft Security Community and Microsoft Entra Community. Read the latest in the the Microsoft Security Community blog. Upcoming Community Calls April 2026 Apr. 23 | 8:00am | Security Copilot Skilling Series | Getting started with Security Copilot New to Security Copilot? This session walks through what you actually need to get started, including E5 inclusion requirements and a practical overview of the core experiences and agents you will use on day one. RESCHEDULED Apr. 28 | 8:00am | Security Copilot Skilling Series | Security Copilot Agents, DSPM AI Observability, and IRM for Agents This session covers an overview of how Microsoft Purview supports AI risk visibility and investigation through Data Security Posture Management (DSPM) and Insider Risk Management (IRM), alongside Security Copilot–powered agents. This session will go over what is AI Observability in DSPM as well as IRM for Agents in Copilot Studio and Azure AI Foundry. Attendees will learn about the IRM Triage Agent and DSPM Posture Agent and their deployment. Attendees will gain an understanding of how DSPM and IRM capabilities could be leveraged to improve visibility, context, and response for AI-related data risks in Microsoft Purview. Apr. 30 | 8:00am | Microsoft Security Community Presents | Purview Lightning Talks Join the Microsoft Security Community for Purview Lightning Talks; quick technical sessions delivered by the community, for the community. You’ll pick up practical Purview gems: must-know Compliance Manager tips, smart data security tricks, real-world scenarios, and actionable governance recommendations all in one energizing event. Hear directly from Purview customers, partners, and community members and walk away with ideas you can put to work right immediately. Register now; full agenda coming soon! May 2026 May 12 | 9:00am | Microsoft Sentinel | Hyper scale your SOC: Manage delegated access and role-based scoping in Microsoft Defender In this session we'll discuss Unified role based access control (RBAC) and granular delegated admin privileges (GDAP) expansions including: How to use RBAC to -Allow multiple SOC teams to operate securely within a shared Sentinel environment-Support granular, row-level access without requiring workspace separation-Get consistent and reusable scope definitions across tables and experiences How to use GDAP to -Manage MSSPs and hyper-scaler organizations with delegated- access to governed tenants within the Defender portal-Manage delegated access for Sentinel. Looking for more? Join the Security Advisors! As a Security Advisor, you’ll gain early visibility into product roadmaps, participate in focus groups, and access private preview features before public release. You’ll have a direct channel to share feedback with engineering teams, influencing the direction of Microsoft Security products. The program also offers opportunities to collaborate and network with fellow end users and Microsoft product teams. Join the Security Advisors program that best fits your interests: www.aka.ms/joincommunity. Additional resources Microsoft Security Hub on Tech Community Virtual Ninja Training Courses Microsoft Security Documentation Azure Network Security GitHub Microsoft Defender for Cloud GitHub Microsoft Sentinel GitHub Microsoft Defender XDR GitHub Microsoft Defender for Cloud Apps GitHub Microsoft Defender for Identity GitHub Microsoft Purview GitHub
Credential Exposure Risk & Response Workbook
How to set up the Workbook Use the steps outlined in the Identify and Remediate Credentials article to get the right rules in place to start capturing credential data. You may choose to use custom regex patterns or more specific SITs that align with your scenario. This workbook will help you once that is done. This workbook transforms credential leakage detection into a measurable, executive-ready capability. End‑to‑end situational awareness: Correlates alerts across workloads, departments, credential types, and users to surface material exposure quickly. Actionable triage & forensics: Drill from trends to the artifact (message/file/URL), accelerating containment and root‑cause analysis. Risk‑aligned decisions: Quantifies exposure and response performance (creation vs. resolution trends) to guide investment and policy changes. Audit‑ready governance: Captures decisions, timelines, and outcomes for PCI/PII controls, identity hygiene, and secrets management. Prerequisites License requirements for Microsoft Purview Information Protection depend on the scenarios and features you use. To understand your licensing requirements and options for Microsoft Purview Information Protection, see the Information Protection sections from Microsoft 365 guidance for security & compliance and the related PDF download for feature-level licensing requirements. Before you start, all endpoint interaction with Sensitive content is already being included in the audit logging with Endpoint DLP enabled (Endpoint DLP must be enabled). For Microsoft 365 SharePoint, OneDrive Exchange, and Teams you can enable policies that generate events but not incidents for important sensitive information types. Install Power BI Desktop to make use of the templates Downloads - Microsoft Power BI Step-by-step guided walkthrough In this guide, we will provide high-level steps to get started using the new tooling. Get the latest version of the report that you are interested in. In this case, we will show the Board report. Open the report. If Power BI Desktop is installed, it should look like this: 3. You must authenticate with the https://api.security.microsoft.com, select Organizational account, and sign in. Then click Connect. 4. You will also have to authenticate with httpps://api.security.microsoft.com/api/advancedhunting, select Organizational account, and sign in. Then click Connect. What the Workbook Delivers The workbook moves programs to something that is measurable. Combined with customers' outcome‑based metrics (operational risk, control risk, end‑user impact), it enables an executive‑level, data‑driven narrative for investment and policy decisions. End‑to‑end situational awareness: Correlates alerts across workloads, departments, credential types, and users to surface material exposure quickly. Actionable triage & forensics: Drill from trends to the artifact (message/file/URL), accelerating containment and root‑cause analysis. Risk‑aligned decisions: Quantifies exposure and response performance (creation vs. resolution trends) to guide investment and policy changes. Audit‑ready governance: Captures decisions, timelines, and outcomes for PCI/PII controls, identity hygiene, and secrets management. Troubleshooting tips: If you are receiving a (400): Bad request error, it is likely that you do not have the necessary tables from the endpoint in Advanced Hunting. Those errors may also show if there are empty values passed from the left-hand side of the KQL queries. Detection trend Apply filtering to this view based on the DLP policies that monitor credentials. Trend Analysis Over Time Displays daily detection counts, helping identify spikes in credential leakage activity and enabling proactive investigation. Workload and Credential Type Breakdown Shows which workloads (e.g., Endpoint, Exchange, OneDrive) and credential types are most affected, guiding targeted security measures. Detection Source Visibility Highlight which security tools (Sentinel, Cloud App Security, Defender) are catching leaks, ensuring monitoring coverage, and identifying gaps. Detailed Credential Exposure Lists exposed credentials for quick validation and remediation, reducing the risk of misuse or compromise. (This part is dependent on the AI component) Supports Incident Response Enables rapid triage by correlating detection trends with specific credentials and sources, improving response times. Compliance and Audit Readiness Provides clear evidence of credential monitoring and leakage detection for regulatory and governance reporting. Credential incident trends Lifecycle Tracking of Credential Alerts Visualizes creation and resolution trends over time, helping teams measure response efficiency and identify periods of heightened risk. Workload and Credential Type Breakdown Shows which workloads (Endpoint, Exchange, OneDrive) and credential types are most impacted, enabling targeted mitigation strategies. Incident Type Analysis Highlights the distribution of alerts by category (e.g., CredRisk, Agent), supporting prioritization of critical incidents. Detailed Alert Context Provides message IDs and associated credentials for precise investigation and remediation, reducing time to contain threats. Performance and SLA Monitoring Tracks resolution timelines to ensure compliance with internal security SLAs and regulatory requirements. Audit and Governance Support Offers clear evidence of alert handling and closure, strengthening accountability and reporting. Content view Workload-Level Risk Visibility Highlights which workloads (e.g., SharePoint, Endpoint) have the highest credential exposure, enabling targeted security hardening. Departmental Risk Breakdown Shows which departments (Security, Logistics, Sales) are most impacted, helping prioritise remediation for critical business areas. Credential Type Analysis Identifies exposed credential types such as API keys, shared access keys, and tokens, guiding policy enforcement and rotation strategies. User and Document Correlation Links exposed credentials to specific users and documents, supporting rapid investigation and containment of leaks. Comprehensive Drill-Down Enables navigation from department → credential type → user → document for precise root cause analysis. Governance and Compliance Support Provides auditable evidence of credential exposure across workloads and departments, strengthening regulatory reporting. For endpoint, this view is an excellent way to catch applications that are not treating secrets in a safe way and expose them in temporary files. Force-directed graph Visual Alert Correlation Displays a force-directed graph linking users to alert categories, making it easy to identify patterns and clusters of credential-related risks. High-Risk User Identification Highlights users with multiple or severe alerts, enabling prioritisation for investigation and remediation. Credential Type and Department Context Shows which credential types and departments are most associated with alerts, supporting targeted security measures. Alert Severity and Details Provides a detailed table of alerts with severity and category, helping analysts quickly assess impact and urgency. Improved Threat Hunting Enables analysts to trace relationships between users, alert types, and credential exposure for deeper root cause analysis. Compliance and Reporting Offers clear evidence of monitoring and categorisation of credential-related alerts for governance and audit purposes. Security incidents correlated to credential leakage Focused on Credential Leakage Provides a dedicated view of alerts related to exposed credentials, enabling quick detection and response. Role-Based Risk Analysis Breaks down incidents by department and role, helping prioritise remediation for high-risk groups such as developers and security teams. User-Level Investigation Allows drill-down to individual users involved in credential-related alerts for rapid containment and corrective action. Credential Type Insights Highlight which types of credentials (e.g., API keys, passwords) are most vulnerable, guiding policy improvements and rotation strategies. Alert Source Correlation Displays which security tools (Sentinel, MCAS, Defender) are detecting leaks, ensuring coverage and identifying monitoring gaps. Compliance and Governance Support Offers auditable evidence of credential monitoring, supporting regulatory and internal security requirements. App and Network correlated to credential leakage For network detection, adjust the query in production to remove standard applications if they are too noisy. We have seen cases where Word and other commonly used applications make calls using FTP services as an example. While other applications may add too much noise. Token Detection Event Traceability Shows detected Token credentials events linked directly to individual User IDs and Device IDs for investigation. Application Usage Context Identifies that the detected activity is associated with the application ms‑teams.exe as an example. External URL Association Displays the Remote URL connected to the token detection event. Remote IP Visibility Lists the Remote IP addresses associated with the activity. Entity-Level Correlation Links UserId, DeviceId, Application, Remote URL, and Remote IP within a single event flow. You can select port used or how Apps are linked as well. Detection Count Aggregation Summarises the number of credential events tied to each correlated entity path. Turn detection into decisions. Deploy the workbook today to get measurable insights, accelerate triage, and deliver audit-ready governance. Start driving risk-aligned investment and policy changes with confidence. The PBI report is located here. Based on what you identify, you may be using tools such as Data Security Investigations to go deeper. We are also working on surfacing the AI triaging in a context that will enrich the DLP analyst experience.Unable to use MS Graph DLP Api's to use with my Entra Registered App
In purview, I have set of policies in DLP, where I have registered to block the US SSN in the text contents and I have created different policies in all of them I have selected the available locations: Exchange email - All accounts SharePoint sites OneDrive accounts - All accounts Teams chat and channel messages - All accounts Devices - All accounts Microsoft Defender for Cloud Apps On-premises repositories And selected action as block all, in all of them for the rule and enabled the rule (not in simulation mode) Now, I have the app registered in Entra and I try to use the following API's https://learn.microsoft.com/en-us/graph/api/userprotectionscopecontainer-compute?view=graph-rest-1.0 https://learn.microsoft.com/en-us/graph/api/userdatasecurityandgovernance-processcontent?view=graph-rest-1.0&tabs=http But whenever I use the compute api I can see i'm only getting curl -X POST https://graph.microsoft.com/v1.0/users/5fd51e08-c5f1-4298-b79b-a357eaa414ff/dataSecurityAndGovernance/protectionScopes/compute\ -H 'Authorization: Bearer <ACCESS_TOKEN>'\ -H 'Content-Type: application/json' -d '{ "activities": "uploadText,downloadText" }' { "@odata.context": "https://graph.microsoft.com/v1.0/$metadata#Collection(microsoft.graph.policyUserScope)", "value": [ { "activities": "uploadText,downloadText", "executionMode": "evaluateOffline", "locations": [ { "@odata.type": "#microsoft.graph.policyLocationApplication", "value": "b48106d9-1cdb-4d90-9485-fe2b6ee78acf" } ], "policyActions": [] } ] } My sample App's Id is showing up but always with `evaluateOffline` I don't know why it always gives 'evaluteOffline' and policyActions is always empty array Also, I can see my Entra registered app is showing up here in the value of the locations And when I use the processContent api , I always get modified in the response and nothing else like below: curl -XPOST https://graph.microsoft.com/v1.0/users/5fd51e08-c5f1-4298-b79b-a357eaa414ff/dataSecurityAndGovernance/processContent \ -H 'Authorization: <ACCESS TOKEN>'\ -H 'Content-Type: application/json' -d '{ "contentToProcess": { "contentEntries": [ { "@odata.type": "microsoft.graph.processConversationMetadata", "identifier": "07785517-9081-4fe7-a9dc-85bcdf5e9075", "content": { "@odata.type": "microsoft.graph.textContent", "data": "Please process this application for John VSmith, his SSN is 121-98-1437 and credit card number is 4532667785213500" }, "name": "Postman message", "correlationId": "d63eafd2-e3a9-4c1a-b726-a2e9b9d9580d", "sequenceNumber": 0, "isTruncated": false, "createdDateTime": "2026-04-06T00:23:20", "modifiedDateTime": "2026-04-06T00:23:20" } ], "activityMetadata": { "activity": "uploadText" }, "deviceMetadata": { "operatingSystemSpecifications": { "operatingSystemPlatform": "Windows 11", "operatingSystemVersion": "10.0.26100.0" }, "ipAddress": "127.0.0.1" }, "protectedAppMetadata": { "name": "Postman", "version": "1.0", "applicationLocation": { "@odata.type": "microsoft.graph.policyLocationApplication", "value": "b48106d9-1cdb-4d90-9485-fe2b6ee78acf" } }, "integratedAppMetadata": { "name": "Postman", "version": "1.0" } } }' In the above request I have mentioned some sample US Security SSN, but the response I get is { "@odata.context": "https://graph.microsoft.com/v1.0/$metadata#microsoft.graph.processContentResponse", "protectionScopeState": "notModified", "policyActions": [], "processingErrors": [] } But Ideally I want to see whether I can get the content is valid or not, for example in the above request, it has SSN, so ideally I should get restrictAction or something right? Or is that evaluateInline is not available or something? Note that I have purchased E5 and assigned to the user who is trying this Also, whenever I choose to create a Policy in DLP , I got two options And Lets say I choose "Enterprise applications & devices", what happens is in the Locations, I'm seeing only these as the options: And If I choose the "Inline Traffic", i'm seeing only these options In Unmanaged, I'm seeing the following And in the Enforcement Options, I have the following : And in the "Advanced DLP rules" I'm seeing only these So, can you tell me the exact steps in the Purview suite, I couldn't where to mention the Entra registered App, I searched and I couldn't find one But in the compute endpoint, https://learn.microsoft.com/en-us/graph/api/userprotectionscopecontainer-compute?view=graph-rest-1.0 I'm getting my app but only with "evaluateOffline" and with that ETag, If I use the processContent Api, its not giving anything except as I mentioned above in the postRegistration Open: Community-Led Purview Lightning Talks
Get ready for an electrifying event! The Microsoft Security Community proudly presents Purview Lightning Talks; an action-packed series featuring your fellow Microsoft users, partners and passionate Microsoft Security community members of all sorts. Each 3-12 minute talk cuts straight to the chase, delivering expert insights, real-world use cases, and even a few game-changing tips and tricks. Don’t miss this opportunity to learn, connect, and be inspired! Secure your spot now for the big day: April 30th at 8am Redmond Time. 💙 See agenda details below and follow this blog post (sign in and click the "follow" heart in the upper right) to receive notifications. We have more speaker details and community connection information coming soon! AGENDA The Day Offboarding Exposed Infinite Retention - Nikki Chapple nikkichapple A real-world discovery of orphaned OneDrives and retention debt caused by retain-only policies, and how Adaptive Scopes help prevent it. Topic: Data Lifecycle Management Securing Data in the Age of AI - Julio Cesar Goncalves Vasconcelos How Microsoft Purview enables organizations to accelerate AI adoption while maintaining security, compliance, and transparency. Topic: Purview for AI What’s In My Compliance Manager Toolbox - Jerrad Dahlager j-dahl7 A practical walkthrough of using Compliance Manager to map controls, track improvements, and simplify multi-framework compliance. Topic: Compliance Manager Why You Should Create Your Own Sensitive Information Types (SITs) - Niels Jakobsen Niels_Jakobsen An in-depth analysis of why built-in SITs are not one-size-fits-all, and how to tailor them for real enterprise needs. Topic: Information Protection Beyond eDiscovery – Purview DSI for Security Investigation - Susantha Silva How to turn DLP alerts and Insider Risk signals into structured data investigations without jumping between portals. Topic: Data Security (DSI) Four Labels Max for Daily Use: Which Ones & Why? - Romain Dalle Romain DALLE A minimalist sensitivity labeling baseline designed for real-world adoption and usability. Topic: Information Protection Elevating Purview DLP with a Real-World Use Case - Victor Wingsing vicwingsing Hardening Purview DLP beyond default configurations to close real-world data loss gaps. Topic: Data Loss Prevention (DLP) Stop, Think, Protect: Data Security in Real Life with Purview - Oliver Sahlmann Oliver Sahlmann A traffic-light approach showing how simple labels and DLP policies still deliver meaningful protection. Topic: Data Security The Purview Label Engine: Automated Classification & Documentation - Michael Kirst Neshva MichaelKirst1970 A scalable framework for rolling out Microsoft Purview labels across global, multilingual enterprises. Topic: Information Protection Data-Driven Endpoint DLP with Advanced Hunting - Tatu Seppälä tatuseppala Using KQL queries and usage patterns to refine endpoint DLP policies based on real behavior. Topic: Data Loss Prevention (DLP) Improving Discovery, Trust, and Reuse of Analytics with Purview Data Products - Craig Wyndowe CraigWyndowe How Purview Governance Domains and Data Products create a trusted, reusable analytics ecosystem. Topic: Data Governance From Zero to First Signal: Insider Risk Management Prerequisites That Matter - Sathish Veerapandian Sathish Veerapandian A focused look at the configurations required for Insider Risk Management to actually generate alerts. Topic: Insider Risk Management The Purview Hack No One Talks About: Container Sensitivity Labels - Nikki Chapple nikkichapple How container sensitivity labels instantly fix oversharing for Teams, Groups, and SharePoint sites. Topic: Information Protection Using Purview to Prevent Oversharing with AI Services - Viktor Hedberg headburgh How Information Protection and DLP prevent Copilot and AI services from exposing sensitive data. Topic: Information Protection & DLP How I Helped Customers Understand Their AI Usage (and Protect Data) - Bram de Jager Bram de Jager Exposing risky AI usage patterns and protecting sensitive data entered into public AI tools. Topic: Data Security Posture Management for AI Bulk Sensitivity Label Removal with Microsoft Purview Information Protection (MPIP) - Zak Hepler A practical demo on safely removing sensitivity labels at scale from SharePoint libraries. Topic: Information Protection Does M365 Support eDiscovery? (Mythbusting) - Julian Kusenberg Leprechaun91 A myth-busting session separating perception from reality in Microsoft 365 eDiscovery. Topic: eDiscoveryAuthorization and Governance for AI Agents: Runtime Authorization Beyond Identity at Scale
Designing Authorization‑Aware AI Agents at Scale Enforcing Runtime RBAC + ABAC with Approval Injection (JIT) Microsoft Entra Agent Identity enables organizations to govern and manage AI agent identities in Copilot Studio, improving visibility and identity-level control. However, as enterprises deploy multiple autonomous AI agents, identity and OAuth permissions alone cannot answer a more critical question: “Should this action be executed now, by this agent, for this user, under the current business and regulatory context?” This post introduces a reusable Authorization Fabric—combining a Policy Enforcement Point (PEP) and Policy Decision Point (PDP)—implemented as a Microsoft Entra‑protected endpoint using Azure Functions/App Service authentication. Every AI agent (Copilot Studio or AI Foundry/Semantic Kernel) calls this fabric before tool execution, receiving a deterministic runtime decision: ALLOW / DENY / REQUIRE_APPROVAL / MASK Who this is for Anyone building AI agents (Copilot Studio, AI Foundry/Semantic Kernel) that call tools, workflows, or APIs Organizations scaling to multiple agents and needing consistent runtime controls Teams operating in regulated or security‑sensitive environments, where decisions must be deterministic and auditable Why a V2? Identity is necessary—runtime authorization is missing Entra Agent Identity (preview) integrates Copilot Studio agents with Microsoft Entra so that newly created agents automatically get an Entra agent identity, manageable in the Entra admin center, and identity activity is logged in Entra. That solves who the agent is and improves identity governance visibility. But multi-agent deployments introduce a new risk class: Autonomous execution sprawl — many agents, operating with delegated privileges, invoking the same backends independently. OAuth and API permissions answer “can the agent call this API?” They do not answer “should the agent execute this action under business policy, compliance constraints, data boundaries, and approval thresholds?” This is where a runtime authorization decision plane becomes essential. The pattern: Microsoft Entra‑Protected Authorization Fabric (PEP + PDP) Instead of embedding RBAC logic independently inside every agent, use a shared fabric: PEP (Policy Enforcement Point): Gatekeeper invoked before any tool/action PDP (Policy Decision Point): Evaluates RBAC + ABAC + approval policies Decision output: ALLOW / DENY / REQUIRE_APPROVAL / MASK This Authorization Fabric functions as a shared enterprise control plane, decoupling authorization logic from individual agents and enforcing policies consistently across all autonomous execution paths. Architecture (POC reference architecture) Use a single runtime decision plane that sits between agents and tools. What’s important here Every agent (Copilot Studio or AI Foundry/SK) calls the Authorization Fabric API first The fabric is a protected endpoint (Microsoft Entra‑protected endpoint required) Tools (Graph/ERP/CRM/custom APIs) are invoked only after an ALLOW decision (or approval) Trust boundaries enforced by this architecture Agents never call business tools directly without a prior authorization decision The Authorization Fabric validates caller identity via Microsoft Entra Authorization decisions are centralized, consistent, and auditable Approval workflows act as a runtime “break-glass” control for high-impact actions This ensures identity, intent, and execution are independently enforced, rather than implicitly trusted. Runtime flow (Decision → Approval → Execution) Here is the runtime sequence as a simple flow (you can keep your Mermaid diagram too). ```mermaid flowchart TD START(["START"]) --> S1["[1] User Request"] S1 --> S2["[2] Agent Extracts Intent\n(action, resource, attributes)"] S2 --> S3["[3] Call /authorize\n(Entra protected)"] S3 --> S4 subgraph S4["[4] PDP Evaluation"] ABAC["ABAC: Tenant · Region · Data Sensitivity"] RBAC["RBAC: Entitlement Check"] Threshold["Approval Threshold"] ABAC --> RBAC --> Threshold end S4 --> Decision{"[5] Decision?"} Decision -->|"ALLOW"| Exec["Execute Tool / API"] Decision -->|"MASK"| Masked["Execute with Masked Data"] Decision -->|"DENY"| Block["Block Request"] Decision -->|"REQUIRE_APPROVAL"| Approve{"[6] Approval Flow"} Approve -->|"Approved"| Exec Approve -->|"Rejected"| Block Exec --> Audit["[7] Audit & Telemetry"] Masked --> Audit Block --> Audit Audit --> ENDNODE(["END"]) style START fill:#4A90D9,stroke:#333,color:#fff style ENDNODE fill:#4A90D9,stroke:#333,color:#fff style S1 fill:#5B5FC7,stroke:#333,color:#fff style S2 fill:#5B5FC7,stroke:#333,color:#fff style S3 fill:#E8A838,stroke:#333,color:#fff style S4 fill:#FFF3E0,stroke:#E8A838,stroke-width:2px style ABAC fill:#FCE4B2,stroke:#999 style RBAC fill:#FCE4B2,stroke:#999 style Threshold fill:#FCE4B2,stroke:#999 style Decision fill:#fff,stroke:#333 style Exec fill:#2ECC71,stroke:#333,color:#fff style Masked fill:#27AE60,stroke:#333,color:#fff style Block fill:#C0392B,stroke:#333,color:#fff style Approve fill:#F39C12,stroke:#333,color:#fff style Audit fill:#3498DB,stroke:#333,color:#fff ``` Design principle: No tool execution occurs until the Authorization Fabric returns ALLOW or REQUIRE_APPROVAL is satisfied via an approval workflow. Where Power Automate fits (important for readers) In most Copilot Studio implementations, Agents calls Power Automate (agent flows), is the practical integration layer that calls enterprise services and APIs. Copilot Studio supports “agent flows” as a way to extend agent capabilities with low-code workflows. For this pattern, Power Automate typically: acquires/uses the right identity context for the call (depending on your tenant setup), and calls the /authorize endpoint of the Authorization Fabric, returns the decision payload to the agent for branching. Copilot Studio also supports calling REST endpoints directly using the HTTP Request node, including passing headers such as Authorization: Bearer <token>. Protected endpoint only: Securing the Authorization Fabric with Microsoft Entra For this V2 pattern, the Authorization Fabric must be protected using Microsoft Entra‑protected endpoint on Azure Functions/App Service (built‑in auth). Microsoft Learn provides the configuration guidance for enabling Microsoft Entra as the authentication provider for Azure App Service / Azure Functions. Step 1 — Create the Authorization Fabric API (Azure Function) Expose an authorization endpoint: HTTP Step 2 — Enable Microsoft Entra‑protected endpoint on the Function App In Azure Portal: Function App → Authentication Add identity provider → Microsoft Choose Workforce configuration (enterprise tenant) Set Require authentication for all requests This ensures the Authorization Fabric is not callable without a valid Entra token. Step 3 — Optional hardening (recommended) Depending on enterprise posture, layer: IP restrictions / Private endpoints APIM in front of the Function for rate limiting, request normalization, centralized logging (For a POC, keep it minimal—add hardening incrementally.) Externalizing policy (so governance scales) To make this pattern reusable across multiple agents, policies should not be hardcoded inside each agent. Instead, store policy definitions in a central policy store such as Cosmos DB (or equivalent configuration store), and have the PDP load/evaluate policies at runtime. Why this matters: Policy changes apply across all agents instantly (no agent republish) Central governance + versioning + rollback becomes possible Audit and reporting become consistent across environments (For the POC, a single JSON document per policy pack in Cosmos DB is sufficient. For production, add versioning and staged rollout.) Store one PolicyPack JSON document per environment (dev/test/prod). Include version, effectiveFrom, priority for safe rollout/rollback. Minimal decision contract (standard request / response) To keep the fabric reusable across agents, standardize the request payload. Request payload (example) Decision response (deterministic) Example scenario (1 minute to understand) Scenario: A user asks a Finance agent to create a Purchase Order for 70,000. Even if the user has API permission and the agent can technically call the ERP API, runtime policy should return: REQUIRE_APPROVAL (threshold exceeded) trigger an approval workflow execute only after approval is granted This is the difference between API access and authorized business execution. Sample Policy Model (RBAC + ABAC + Approval) This POC policy model intentionally stays simple while demonstrating both coarse and fine-grained governance. 1) Coarse‑grained RBAC (roles → actions) FinanceAnalyst CreatePO up to 50,000 ViewVendor FinanceManager CreatePO up to 100,000 and/or approve higher spend 2) Fine‑grained ABAC (conditions at runtime) ABAC evaluates context such as region, classification, tenant boundary, and risk: 3) Approval injection (Agent‑level JIT execution) For higher-risk/high-impact actions, the fabric returns REQUIRE_APPROVAL rather than hard deny (when appropriate): How policies should be evaluated (deterministic order) To ensure predictable and auditable behavior, evaluate in a deterministic order: Tenant isolation & residency (ABAC hard deny first) Classification rules (deny or mask) RBAC entitlement validation Threshold/risk evaluation Approval injection (JIT step-up) This prevents approval workflows from bypassing foundational security boundaries such as tenant isolation or data sovereignty. Copilot Studio integration (enforcing runtime authorization) Copilot Studio can call external REST APIs using the HTTP Request node, including passing headers such as Authorization: Bearer <token> and binding response schema for branching logic. Copilot Studio also supports using flows with agents (“agent flows”) to extend capabilities and orchestrate actions. Option A (Recommended): Copilot Studio → Agent Flow (Power Automate) → Authorization Fabric Why: Flows are a practical place to handle token acquisition patterns, approval orchestration, and standardized logging. Topic flow: Extract user intent + parameters Call an agent flow that: calls /authorize returns decision payload Branch in the topic: If ALLOW → proceed to tool call If REQUIRE_APPROVAL → trigger approval flow; proceed only if approved If DENY → stop and explain policy reason Important: Tool execution must never be reachable through an alternate topic path that bypasses the authorization check. Option B: Direct HTTP Request node to Authorization Fabric Use the Send HTTP request node to call the authorization endpoint and branch using the response schema. This approach is clean, but token acquisition and secure secretless authentication are often simpler when handled via a managed integration layer (flow + connector). AI Foundry / Semantic Kernel integration (tool invocation gate) For Foundry/SK agents, the integration point is before tool execution. Semantic Kernel supports Azure AI agent patterns and tool integration, making it a natural place to enforce a pre-tool authorization check. Pseudo-pattern: Agent extracts intent + context Calls Authorization Fabric Enforces decision Executes tool only when allowed (or after approval) Telemetry & audit (what Security Architects will ask for) Even the best policy engine is incomplete without audit trails. At minimum, log: agentId, userUPN, action, resource decision + reason + policyIds approval outcome (if any) correlationId for downstream tool execution Why it matters: you now have a defensible answer to: “Why did an autonomous agent execute this action?” Security signal bonus: Denials, unusual approval rates, and repeated policy mismatches can also indicate prompt injection attempts, mis-scoped agents, or governance drift. What this enables (and why it scales) With a shared Authorization Fabric: Avoid duplicating authorization logic across agents Standardize decisions across Copilot Studio + Foundry agents Update governance once (policy change) and apply everywhere Make autonomy safer without blocking productivity Closing: Identity gets you who. Runtime authorization gets you whether/when/how. Copilot Studio can automatically create Entra agent identities (preview), improving identity governance and visibility for agents. But safe autonomy requires a runtime decision plane. Securing that plane as an Entra-protected endpoint is foundational for enterprise deployments. In enterprise environments, autonomous execution without runtime authorization is equivalent to privileged access without PIM—powerful, fast, and operationally risky.
Authorization and Identity Governance Inside AI Agents
Designing Authorization‑Aware AI Agents Enforcing Microsoft Entra ID RBAC in Copilot Studio As AI agents move from experimentation to enterprise execution, authorization becomes the defining line between innovation and risk. AI agents are rapidly evolving from experimental assistants into enterprise operators—retrieving user data, triggering workflows, and invoking protected APIs. While many early implementations rely on prompt‑level instructions to control access, regulated enterprise environments require authorization to be enforced by identity systems, not language models. This article presents a production‑ready, identity‑first architecture for building authorization‑aware AI agents using Copilot Studio, Power Automate, Microsoft Entra ID, and Microsoft Graph, ensuring every agent action executes strictly within the requesting user’s permissions. Why Prompt‑Level Security Is Not Enough Large Language Models interpret intent—they do not enforce policy. Even the most carefully written prompts cannot: Validate Microsoft Entra ID group or role membership Reliably distinguish delegated user identity from application identity Enforce deterministic access decisions Produce auditable authorization outcomes Relying on prompts for authorization introduces silent security failures, over‑privileged access, and compliance gaps—particularly in Financial Services, Healthcare, and other regulated industries. Authorization is not a reasoning problem. It is an identity enforcement problem. Common Authorization Anti‑Patterns in AI Agents The following patterns frequently appear in early AI agent implementations and should be avoided in enterprise environments: Hard‑coded role or group checks embedded in prompts Trusting group names passed as plain‑text parameters Using application permissions for user‑initiated actions Skipping verification of the user’s Entra ID identity Lacking an auditable authorization decision point These approaches may work in demos, but they do not survive security reviews, compliance audits, or real‑world misuse scenarios. Authorization‑Aware Agent Architecture In an authorization‑aware design, the agent never decides access. Authorization is enforced externally, by identity‑aware workflows that sit outside the language model’s reasoning boundary. High‑Level Flow The Copilot Studio agent receives a user request The agent passes the User Principal Name (UPN) and intended action A Power Automate flow validates permissions using Microsoft Entra ID via Microsoft Graph Only authorized requests are allowed to proceed Unauthorized requests fail fast with a deterministic outcome Authorization‑aware Copilot Studio architecture enforces Entra ID RBAC before executing any business action. The agent orchestrates intent. Identity systems enforce access. Enforcing Entra ID RBAC with Microsoft Graph Power Automate acts as the authorization enforcement layer: Resolve user identity from the supplied UPN Retrieve group or role memberships using Microsoft Graph Normalize and compare memberships against approved RBAC groups Explicitly deny execution when authorization fails This keeps authorization logic: Centralized Deterministic Auditable Independent of the AI model Reference Implementation: Power Automate RBAC Enforcement Flow The following import‑ready Power Automate cloud flow demonstrates a secure RBAC enforcement pattern for Copilot Studio agents. It validates Microsoft Entra ID group membership before allowing any business action. Scenario Trigger: User‑initiated agent action Identity model: Delegated user identity Input: userUPN, requestedAction Outcome: Authorized or denied based on Entra ID RBAC { "$schema": "https://schema.management.azure.com/providers/Microsoft.Logic/schemas/2016-06-01/workflowdefinition.json#", "contentVersion": "1.0.0.0", "triggers": { "Copilot_Request": { "type": "Request", "kind": "Http", "inputs": { "schema": { "type": "object", "properties": { "userUPN": { "type": "string" }, "requestedAction": { "type": "string" } }, "required": [ "userUPN" ] } } } }, "actions": { "Get_User_Groups": { "type": "Http", "inputs": { "method": "GET", "uri": "https://graph.microsoft.com/v1.0/users/@{triggerBody()?['userUPN']}/memberOf?$select=displayName", "authentication": { "type": "ManagedServiceIdentity" } } }, "Normalize_Group_Names": { "type": "Select", "inputs": { "from": "@body('Get_User_Groups')?['value']", "select": { "groupName": "@toLower(item()?['displayName'])" } }, "runAfter": { "Get_User_Groups": [ "Succeeded" ] } }, "Check_Authorization": { "type": "Condition", "expression": "@contains(body('Normalize_Group_Names'), 'ai-authorized-users')", "runAfter": { "Normalize_Group_Names": [ "Succeeded" ] }, "actions": { "Authorized_Action": { "type": "Compose", "inputs": "User authorized via Entra ID RBAC" } }, "else": { "actions": { "Access_Denied": { "type": "Terminate", "inputs": { "status": "Failed", "message": "Access denied. User not authorized via Entra ID RBAC." } } } } } } } This pattern enforces authorization outside the agent, aligns with Zero Trust principles, and creates a clear audit boundary suitable for enterprise and regulated environments. Flow Diagram: Agent Integrated with RBAC Authorization Flow and Sample Prompt Execution: Delegated vs Application Permissions Scenario Recommended Permission Model User‑initiated agent actions Delegated permissions Background or system automation Application permissions Using delegated permissions ensures agent execution remains strictly within the requesting user’s identity boundary. Auditing and Compliance Benefits Deterministic and explainable authorization decisions Centralized enforcement aligned with identity governance Clear audit trails for security and compliance reviews Readiness for SOC, ISO, PCI, and FSI assessments Enterprise Security Takeaways Authorization belongs in Microsoft Entra ID, not prompts AI agents must respect enterprise identity boundaries Copilot Studio + Power Automate + Microsoft Graph enable secure‑by‑design AI agents By treating AI agents as first‑class enterprise actors and enforcing authorization at the identity layer, organizations can scale AI adoption with confidence, trust, and compliance.
