Authorization 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.Announcing public preview of custom graphs in Microsoft Sentinel
Security attacks span identities, devices, resources, and activity, making it critical to understand how these elements connect to expose real risk. In November, we shared how Sentinel graph brings these signals together into a relationship-aware view to help uncover hidden security risks. We’re excited to announce the public preview of custom graphs in Sentinel, available starting April 1 st . Custom graphs let defenders model relationships that are unique to their organization, then run graph analytics to surface blast radius, attack paths, privilege chains, chokepoints, and anomalies that are difficult to spot in tables alone. In this post, we’ll cover what custom graphs are, how they work, and how to get started so the entire team can use them. Custom graphs Security data is inherently connected: a sign-in leads to a token, a token touches a workload, a workload accesses data, and data movement triggers new activity. Graphs represent these relationships as nodes (entities) and edges (relationships), helping you answer questions like: “Who received the phishing email, who clicked, and which clicks were allowed by the proxy?” or “Show me users who exported notebooks, staged files in storage, then uploaded data to personal cloud storage- the full, three‑phase exfiltration chain through one identity.” With custom graphs, security teams can build, query, and visualize tailored security graphs using data from the Sentinel data lake and non-Microsoft sources, powered by Fabric. By uncovering hidden patterns and attack paths, graphs provide the relationship context needed to surface real risk. This context strengthens AI‑powered agent experiences, speeds investigations, clarifies blast radius, and helps teams move from noisy, disconnected alerts to confident decisions. In the words of our preview customers: “We ingested our Databricks management-plane telemetry into the Sentinel data lake and built a custom security graph. Without writing a single detection rule, the graph surfaced unusual patterns of activity and overprivileged access that we escalated for investigation. We didn't know what we were looking for, the graph surfaced the risk for us by revealing anomalous activity patterns and unusual access combinations driven by relationships, not alerts.” – SVP, Security Solutions | Financial Services organization Use cases Sentinel graph offers embedded, Microsoft managed, security graphs in Defender and Microsoft Purview experiences to help you at every stage of defense, from pre-breach to post-breach and across assets, activities, and threat intelligence. See here for more details. The new custom graph capability gives you full control to create your own graphs combining data from Microsoft sources, non-Microsoft sources, and federated sources in the Sentinel data lake. With custom graphs you can: Understand blast radius – Trace phishing campaigns, malware spread, OAuth abuse, or privilege escalation paths across identities, devices, apps, and data, without stitching together dozens of tables. Reconstruct real attack chains – Model multi-step attacker behavior (MITRE techniques, lateral movement, before/after malware) as connected sequences so investigations are complete and explainable, not a set of partial pivots. Reconstruct these chains from historical data in the Sentinel data lake. Figure 2: Drill into which specific MITRE techniques each IP is executing and in which tactic category Spot hidden risks and anomalies – Detect structural outliers like users with unusually broad access, anomalous email exfiltration, or dangerous permission combinations that are invisible in flat logs. Figure 3: OAuth consent chain – a single compromised user consented four dangerous permissions Creating custom graph Using the Sentinel VS Code extension, you can generate graphs to validate hunting hypotheses, such as understanding attack paths and blast radius of a phishing campaign, reconstructing multi‑step attack chains, and identifying structurally unusual or high‑risk behavior, making it accessible to your team and AI agents. Once persisted via a schedule job, you can access these custom graphs from the ready-to-use section in the graphs section in the Defender portal. Figure 4: Use AI-assisted vibe coding in Visual Studio Code to create tailored security graphs powered by Sentinel data lake and Fabric Graphs experience in the Microsoft Defender portal After creating your custom graphs, you can access them in the Graphs section of the Microsoft Defender portal under Sentinel. From there, you can perform interactive, graph-based investigations, for example, using a graph built for phishing analysis to quickly evaluate the impact of a recent incident, profile the attacker, and trace paths across Microsoft telemetry and third-party data. The graph experience lets you run Graph Query Language (GQL) queries, view the graph schema, visualize results, see results in a table, and interactively traverse to the next hop with a single click. Figure 5: Query, visualize, and traverse custom graphs with the new graph experience in Sentinel Billing Custom graph API usage for creating graph and querying graph is billed according to the Sentinel graph meter. Get started To use custom graphs, you’ll need Microsoft Sentinel data lake enabled in your tenant, since the lake provides the scalable, open-format foundation that custom graphs build on. Use the Sentinel data lake onboarding flow to provision the data lake if it isn’t already enabled. Ensure the required connectors are configured to populate your data lake. See Manage data tiers and retention in Microsoft Sentinel | Microsoft Learn. Create and persist a custom graph. See Get started with custom graphs in Microsoft Sentinel (preview) | Microsoft Learn. Run adhoc graph queries and visualize graph results. See Visualize custom graphs in Microsoft Sentinel graph (preview) | Microsoft Learn. [Optional] Schedule jobs to write graph query results to the lake tier and analytics tier using notebooks. See Exploring and interacting with lake data using Jupyter Notebooks - Microsoft Security | Microsoft Learn. Learn more Earlier posts (Sentinel graph general availability) RSAC 2026 announcement roundup Custom graphs documentation Custom graph billingSecurity as the core primitive - Securing AI agents and apps
This week at Microsoft Ignite, we shared our vision for Microsoft security -- In the agentic era, security must be ambient and autonomous, like the AI it protects. It must be woven into and around everything we build—from silicon to OS, to agents, apps, data, platforms, and clouds—and throughout everything we do. In this blog, we are going to dive deeper into many of the new innovations we are introducing this week to secure AI agents and apps. As I spend time with our customers and partners, there are four consistent themes that have emerged as core security challenges to secure AI workloads. These are: preventing agent sprawl and access to resources, protecting against data oversharing and data leaks, defending against new AI threats and vulnerabilities, and adhering to evolving regulations. Addressing these challenges holistically requires a coordinated effort across IT, developers, and security leaders, not just within security teams and to enable this, we are introducing several new innovations: Microsoft Agent 365 for IT, Foundry Control Plane in Microsoft Foundry for developers, and the Security Dashboard for AI for security leaders. In addition, we are releasing several new purpose-built capabilities to protect and govern AI apps and agents across Microsoft Defender, Microsoft Entra, and Microsoft Purview. Observability at every layer of the stack To facilitate the organization-wide effort that it takes to secure and govern AI agents and apps – IT, developers, and security leaders need observability (security, management, and monitoring) at every level. IT teams need to enable the development and deployment of any agent in their environment. To ensure the responsible and secure deployment of agents into an organization, IT needs a unified agent registry, the ability to assign an identity to every agent, manage the agent’s access to data and resources, and manage the agent’s entire lifecycle. In addition, IT needs to be able to assign access to common productivity and collaboration tools, such as email and file storage, and be able to observe their entire agent estate for risks such as over-permissioned agents. Development teams need to build and test agents, apply security and compliance controls by default, and ensure AI models are evaluated for safety guardrails and security vulnerabilities. Post deployment, development teams must observe agents to ensure they are staying on task, accessing applications and data sources appropriately, and operating within their cost and performance expectations. Security & compliance teams must ensure overall security of their AI estate, including their AI infrastructure, platforms, data, apps, and agents. They need comprehensive visibility into all their security risks- including agent sprawl and resource access, data oversharing and leaks, AI threats and vulnerabilities, and complying with global regulations. They want to address these risks by extending their existing security investments that they are already invested in and familiar with, rather than using siloed or bolt-on tools. These teams can be most effective in delivering trustworthy AI to their organizations if security is natively integrated into the tools and platforms that they use every day, and if those tools and platforms share consistent security primitives such as agent identities from Entra; data security and compliance controls from Purview; and security posture, detections, and protections from Defender. With the new capabilities being released today, we are delivering observability at every layer of the AI stack, meeting IT, developers, and security teams where they are in the tools they already use to innovate with confidence. For IT Teams - Introducing Microsoft Agent 365, the control plane for agents, now in preview The best infrastructure for managing your agents is the one you already use to manage your users. With Agent 365, organizations can extend familiar tools and policies to confidently deploy and secure agents, without reinventing the wheel. By using the same trusted Microsoft 365 infrastructure, productivity apps, and protections, organizations can now apply consistent and familiar governance and security controls that are purpose-built to protect against agent-specific threats and risks. gement and governance of agents across organizations Microsoft Agent 365 delivers a unified agent Registry, Access Control, Visualization, Interoperability, and Security capabilities for your organization. These capabilities work together to help organizations manage agents and drive business value. The Registry powered by the Entra provides a complete and unified inventory of all the agents deployed and used in your organization including both Microsoft and third-party agents. Access Control allows you to limit the access privileges of your agents to only the resources that they need and protect their access to resources in real time. Visualization gives organizations the ability to see what matters most and gain insights through a unified dashboard, advanced analytics, and role-based reporting. Interop allows agents to access organizational data through Work IQ for added context, and to integrate with Microsoft 365 apps such as Outlook, Word, and Excel so they can create and collaborate alongside users. Security enables the proactive detection of vulnerabilities and misconfigurations, protects against common attacks such as prompt injections, prevents agents from processing or leaking sensitive data, and gives organizations the ability to audit agent interactions, assess compliance readiness and policy violations, and recommend controls for evolving regulatory requirements. Microsoft Agent 365 also includes the Agent 365 SDK, part of Microsoft Agent Framework, which empowers developers and ISVs to build agents on their own AI stack. The SDK enables agents to automatically inherit Microsoft's security and governance protections, such as identity controls, data security policies, and compliance capabilities, without the need for custom integration. For more details on Agent 365, read the blog here. For Developers - Introducing Microsoft Foundry Control Plane to observe, secure and manage agents, now in preview Developers are moving fast to bring agents into production, but operating them at scale introduces new challenges and responsibilities. Agents can access tools, take actions, and make decisions in real time, which means development teams must ensure that every agent behaves safely, securely, and consistently. Today, developers need to work across multiple disparate tools to get a holistic picture of the cybersecurity and safety risks that their agents may have. Once they understand the risk, they then need a unified and simplified way to monitor and manage their entire agent fleet and apply controls and guardrails as needed. Microsoft Foundry provides a unified platform for developers to build, evaluate and deploy AI apps and agents in a responsible way. Today we are excited to announce that Foundry Control Plane is available in preview. This enables developers to observe, secure, and manage their agent fleets with built-in security, and centralized governance controls. With this unified approach, developers can now identify risks and correlate disparate signals across their models, agents, and tools; enforce consistent policies and quality gates; and continuously monitor task adherence and runtime risks. Foundry Control Plane is deeply integrated with Microsoft’s security portfolio to provide a ‘secure by design’ foundation for developers. With Microsoft Entra, developers can ensure an agent identity (Agent ID) and access controls are built into every agent, mitigating the risk of unmanaged agents and over permissioned resources. With Microsoft Defender built in, developers gain contextualized alerts and posture recommendations for agents directly within the Foundry Control Plane. This integration proactively prevents configuration and access risks, while also defending agents from runtime threats in real time. Microsoft Purview’s native integration into Foundry Control Plane makes it easy to enable data security and compliance for every Foundry-built application or agent. This allows Purview to discover data security and compliance risks and apply policies to prevent user prompts and AI responses from safety and policy violations. In addition, agent interactions can be logged and searched for compliance and legal audits. This integration of the shared security capabilities, including identity and access, data security and compliance, and threat protection and posture ensures that security is not an afterthought; it’s embedded at every stage of the agent lifecycle, enabling you to start secure and stay secure. For more details, read the blog. For Security Teams - Introducing Security Dashboard for AI - unified risk visibility for CISOs and AI risk leaders, coming soon AI proliferation in the enterprise, combined with the emergence of AI governance committees and evolving AI regulations, leaves CISOs and AI risk leaders needing a clear view of their AI risks, such as data leaks, model vulnerabilities, misconfigurations, and unethical agent actions across their entire AI estate, spanning AI platforms, apps, and agents. 90% of security professionals, including CISOs, report that their responsibilities have expanded to include data governance and AI oversight within the past year. 1 At the same time, 86% of risk managers say disconnected data and systems lead to duplicated efforts and gaps in risk coverage. 2 To address these needs, we are excited to introduce the Security Dashboard for AI. This serves as a unified dashboard that aggregates posture and real-time risk signals from Microsoft Defender, Microsoft Entra, and Microsoft Purview. This unified dashboard allows CISOs and AI risk leaders to discover agents and AI apps, track AI posture and drift, and correlate risk signals to investigate and act across their entire AI ecosystem. For example, you can see your full AI inventory and get visibility into a quarantined agent, flagged for high data risk due to oversharing sensitive information in Purview. The dashboard then correlates that signal with identity insights from Entra and threat protection alerts from Defender to provide a complete picture of exposure. From there, you can delegate tasks to the appropriate teams to enforce policies and remediate issues quickly. With the Security Dashboard for AI, CISOs and risk leaders gain a clear, consolidated view of AI risks across agents, apps, and platforms—eliminating fragmented visibility, disconnected posture insights, and governance gaps as AI adoption scales. Best of all, there’s nothing new to buy. If you’re already using Microsoft security products to secure AI, you’re already a Security Dashboard for AI customer. Figure 5: Security Dashboard for AI provides CISOs and AI risk leaders with a unified view of their AI risk by bringing together their AI inventory, AI risk, and security recommendations to strengthen overall posture Together, these innovations deliver observability and security across IT, development, and security teams, powered by Microsoft’s shared security capabilities. With Microsoft Agent 365, IT teams can manage and secure agents alongside users. Foundry Control Plane gives developers unified governance and lifecycle controls for agent fleets. Security Dashboard for AI provides CISOs and AI risk leaders with a consolidated view of AI risks across platforms, apps, and agents. Added innovation to secure and govern your AI workloads In addition to the IT, developer, and security leader-focused innovations outlined above, we continue to accelerate our pace of innovation in Microsoft Entra, Microsoft Purview, and Microsoft Defender to address the most pressing needs for securing and governing your AI workloads. These needs are: Manage agent sprawl and resource access e.g. managing agent identity, access to resources, and permissions lifecycle at scale Prevent data oversharing and leaks e.g. protecting sensitive information shared in prompts, responses, and agent interactions Defend against shadow AI, new threats, and vulnerabilities e.g. managing unsanctioned applications, preventing prompt injection attacks, and detecting AI supply chain vulnerabilities Enable AI governance for regulatory compliance e.g. ensuring AI development, operations, and usage comply with evolving global regulations and frameworks Manage agent sprawl and resource access 76% of business leaders expect employees to manage agents within the next 2–3 years. 3 Widespread adoption of agents is driving the need for visibility and control, which includes the need for a unified registry, agent identities, lifecycle governance, and secure access to resources. Today, Microsoft Entra provides robust identity protection and secure access for applications and users. However, organizations lack a unified way to manage, govern, and protect agents in the same way they manage their users. Organizations need a purpose-built identity and access framework for agents. Introducing Microsoft Entra Agent ID, now in preview Microsoft Entra Agent ID offers enterprise-grade capabilities that enable organizations to prevent agent sprawl and protect agent identities and their access to resources. These new purpose-built capabilities enable organizations to: Register and manage agents: Get a complete inventory of the agent fleet and ensure all new agents are created with an identity built-in and are automatically protected by organization policies to accelerate adoption. Govern agent identities and lifecycle: Keep the agent fleet under control with lifecycle management and IT-defined guardrails for both agents and people who create and manage them. Protect agent access to resources: Reduce risk of breaches, block risky agents, and prevent agent access to malicious resources with conditional access and traffic inspection. Agents built in Microsoft Copilot Studio, Microsoft Foundry, and Security Copilot get an Entra Agent ID built-in at creation. Developers can also adopt Entra Agent ID for agents they build through Microsoft Agent Framework, Microsoft Agent 365 SDK, or Microsoft Entra Agent ID SDK. Read the Microsoft Entra blog to learn more. Prevent data oversharing and leaks Data security is more complex than ever. Information Security Media Group (ISMG) reports that 80% of leaders cite leakage of sensitive data as their top concern. 4 In addition to data security and compliance risks of generative AI (GenAI) apps, agents introduces new data risks such as unsupervised data access, highlighting the need to protect all types of corporate data, whether it is accessed by employees or agents. To mitigate these risks, we are introducing new Microsoft Purview data security and compliance capabilities for Microsoft 365 Copilot and for agents and AI apps built with Copilot Studio and Microsoft Foundry, providing unified protection, visibility, and control for users, AI Apps, and Agents. New Microsoft Purview controls safeguard Microsoft 365 Copilot with real-time protection and bulk remediation of oversharing risks Microsoft Purview and Microsoft 365 Copilot deliver a fully integrated solution for protecting sensitive data in AI workflows. Based on ongoing customer feedback, we’re introducing new capabilities to deliver real-time protection for sensitive data in M365 Copilot and accelerated remediation of oversharing risks: Data risk assessments: Previously, admins could monitor oversharing risks such as SharePoint sites with unprotected sensitive data. Now, they can perform item-level investigations and bulk remediation for overshared files in SharePoint and OneDrive to quickly reduce oversharing exposure. Data Loss Prevention (DLP) for M365 Copilot: DLP previously excluded files with sensitivity labels from Copilot processing. Now in preview, DLP also prevents prompts that include sensitive data from being processed in M365 Copilot, Copilot Chat, and Copilot agents, and prevents Copilot from using sensitive data in prompts for web grounding. Priority cleanup for M365 Copilot assets: Many organizations have org-wide policies to retain or delete data. Priority cleanup, now generally available, lets admins delete assets that are frequently processed by Copilot, such as meeting transcripts and recordings, on an independent schedule from the org-wide policies while maintaining regulatory compliance. On-demand classification for meeting transcripts: Purview can now detect sensitive information in meeting transcripts on-demand. This enables data security admins to apply DLP policies and enforce Priority cleanup based on the sensitive information detected. & bulk remediation Read the full Data Security blog to learn more. Introducing new Microsoft Purview data security capabilities for agents and apps built with Copilot Studio and Microsoft Foundry, now in preview Microsoft Purview now extends the same data security and compliance for users and Copilots to agents and apps. These new capabilities are: Enhanced Data Security Posture Management: A centralized DSPM dashboard that provides observability, risk assessment, and guided remediation across users, AI apps, and agents. Insider Risk Management (IRM) for Agents: Uniquely designed for agents, using dedicated behavioral analytics, Purview dynamically assigns risk levels to agents based on their risky handing of sensitive data and enables admins to apply conditional policies based on that risk level. Sensitive data protection with Azure AI Search: Azure AI Search enables fast, AI-driven retrieval across large document collections, essential for building AI Apps. When apps or agents use Azure AI Search to index or retrieve data, Purview sensitivity labels are preserved in the search index, ensuring that any sensitive information remains protected under the organization’s data security & compliance policies. For more information on preventing data oversharing and data leaks - Learn how Purview protects and governs agents in the Data Security and Compliance for Agents blog. Defend against shadow AI, new threats, and vulnerabilities AI workloads are subject to new AI-specific threats like prompt injections attacks, model poisoning, and data exfiltration of AI generated content. Although security admins and SOC analysts have similar tasks when securing agents, the attack methods and surfaces differ significantly. To help customers defend against these novel attacks, we are introducing new capabilities in Microsoft Defender that deliver end-to-end protection, from security posture management to runtime defense. Introducing Security Posture Management for agents, now in preview As organizations adopt AI agents to automate critical workflows, they become high-value targets and potential points of compromise, creating a critical need to ensure agents are hardened, compliant, and resilient by preventing misconfigurations and safeguarding against adversarial manipulation. Security Posture Management for agents in Microsoft Defender now provides an agent inventory for security teams across Microsoft Foundry and Copilot Studio agents. Here, analysts can assess the overall security posture of an agent, easily implement security recommendations, and identify vulnerabilities such as misconfigurations and excessive permissions, all aligned to the MITRE ATT&CK framework. Additionally, the new agent attack path analysis visualizes how an agent’s weak security posture can create broader organizational risk, so you can quickly limit exposure and prevent lateral movement. Introducing Threat Protection for agents, now in preview Attack techniques and attack surfaces for agents are fundamentally different from other assets in your environment. That’s why Defender is delivering purpose-built protections and detections to help defend against them. Defender is introducing runtime protection for Copilot Studio agents that automatically block prompt injection attacks in real time. In addition, we are announcing agent-specific threat detections for Copilot Studio and Microsoft Foundry agents coming soon. Defender automatically correlates these alerts with Microsoft’s industry-leading threat intelligence and cross-domain security signals to deliver richer, contextualized alerts and security incident views for the SOC analyst. Defender’s risk and threat signals are natively integrated into the new Microsoft Foundry Control Plane, giving development teams full observability and the ability to act directly from within their familiar environment. Finally, security analysts will be able to hunt across all agent telemetry in the Advanced Hunting experience in Defender, and the new Agent 365 SDK extends Defender’s visibility and hunting capabilities to third-party agents, starting with Genspark and Kasisto, giving security teams even more coverage across their AI landscape. To learn more about how you can harden the security posture of your agents and defend against threats, read the Microsoft Defender blog. Enable AI governance for regulatory compliance Global AI regulations like the EU AI Act and NIST AI RMF are evolving rapidly; yet, according to ISMG, 55% of leaders report lacking clarity on current and future AI regulatory requirements. 5 As enterprises adopt AI, they must ensure that their AI innovation aligns with global regulations and standards to avoid costly compliance gaps. Introducing new Microsoft Purview Compliance Manager capabilities to stay ahead of evolving AI regulations, now in preview Today, Purview Compliance Manager provides over 300 pre-built assessments for common industry, regional, and global standards and regulations. However, the pace of change for new AI regulations requires controls to be continuously re-evaluated and updated so that organizations can adapt to ongoing changes in regulations and stay compliant. To address this need, Compliance Manager now includes AI-powered regulatory templates. AI-powered regulatory templates enable real-time ingestion and analysis of global regulatory documents, allowing compliance teams to quickly adapt to changes as they happen. As regulations evolve, the updated regulatory documents can be uploaded to Compliance Manager, and the new requirements are automatically mapped to applicable recommended actions to implement controls across Microsoft Defender, Microsoft Entra, Microsoft Purview, Microsoft 365, and Microsoft Foundry. Automated actions by Compliance Manager further streamline governance, reduce manual workload, and strengthen regulatory accountability. Introducing expanded Microsoft Purview compliance capabilities for agents and AI apps now in preview Microsoft Purview now extends its compliance capabilities across agent-generated interactions, ensuring responsible use and regulatory alignment as AI becomes deeply embedded across business processes. New capabilities include expanded coverage for: Audit: Surface agent interactions, lifecycle events, and data usage with Purview Audit. Unified audit logs across user and agent activities, paired with traceability for every agent using an Entra Agent ID, support investigation, anomaly detection, and regulatory reporting. Communication Compliance: Detect prompts sent to agents and agent-generated responses containing inappropriate, unethical, or risky language, including attempts to manipulate agents into bypassing policies, generating risky content, or producing noncompliant outputs. When issues arise, data security admins get full context, including the prompt, the agent’s output, and relevant metadata, so they can investigate and take corrective action Data Lifecycle Management: Apply retention and deletion policies to agent-generated content and communication flows to automate lifecycle controls and reduce regulatory risk. Read about Microsoft Purview data security for agents to learn more. Finally, we are extending our data security, threat protection, and identity access capabilities to third-party apps and agents via the network. Advancing Microsoft Entra Internet Access Secure Web + AI Gateway - extend runtime protections to the network, now in preview Microsoft Entra Internet Access, part of the Microsoft Entra Suite, has new capabilities to secure access to and usage of GenAI at the network level, marking a transition from Secure Web Gateway to Secure Web and AI Gateway. Enterprises can accelerate GenAI adoption while maintaining compliance and reducing risk, empowering employees to experiment with new AI tools safely. The new capabilities include: Prompt injection protection which blocks malicious prompts in real time by extending Azure AI Prompt Shields to the network layer. Network file filtering which extends Microsoft Purview to inspect files in transit and prevents regulated or confidential data from being uploaded to unsanctioned AI services. Shadow AI Detection that provides visibility into unsanctioned AI applications through Cloud Application Analytics and Defender for Cloud Apps risk scoring, empowering security teams to monitor usage trends, apply Conditional Access, or block high-risk apps instantly. Unsanctioned MCP server blocking prevents access to MCP servers from unauthorized agents. With these controls, you can accelerate GenAI adoption while maintaining compliance and reducing risk, so employees can experiment with new AI tools safely. Read the Microsoft Entra blog to learn more. As AI transforms the enterprise, security must evolve to meet new challenges—spanning agent sprawl, data protection, emerging threats, and regulatory compliance. Our approach is to empower IT, developers, and security leaders with purpose-built innovations like Agent 365, Foundry Control Plane, and the Security Dashboard for AI. These solutions bring observability, governance, and protection to every layer of the AI stack, leveraging familiar tools and integrated controls across Microsoft Defender, Microsoft Entra, and Microsoft Purview. The future of security is ambient, autonomous, and deeply woven into the fabric of how we build, deploy, and govern AI systems. Explore additional resources Learn more about Security for AI solutions on our webpage Learn more about Microsoft Agent 365 Learn more about Microsoft Entra Agent ID Get started with Microsoft 365 Copilot Get started with Microsoft Copilot Studio Get started with Microsoft Foundry Get started with Microsoft Defender for Cloud Get started with Microsoft Entra Get started with Microsoft Purview Get started with Microsoft Purview Compliance Manager Sign up for a free Microsoft 365 E5 Security Trial and Microsoft Purview Trial 1 Bedrock Security, 2025 Data Security Confidence Index, published Mar 17, 2025. 2 AuditBoard & Ascend2, Connected Risk Report 2024; as cited by MIT Sloan Management Review, Spring 2025. 3 KPMG AI Quarterly Pulse Survey | Q3 2025. September 2025. n= 130 U.S.-based C-suite and business leaders representing organizations with annual revenue of $1 billion or more 4 First Annual Generative AI study: Business Rewards vs. Security Risks, , Q3 2023, ISMG, N=400 5 First Annual Generative AI study: Business Rewards vs. Security Risks, Q3 2023, ISMG, N=400
Building Secure, Enterprise Ready AI Agents with Purview SDK and Agent Framework
At Microsoft Ignite, we announced the public preview of Purview integration with the Agent Framework SDK—making it easier to build AI agents that are secure, compliant, and enterprise‑ready from day one. AI agents are quickly moving from demos to production. They reason over enterprise data, collaborate with other agents, and take real actions. As that happens, one thing becomes non‑negotiable: Governance has to be built in. That’s where Purview SDK comes in. Agentic AI Changes the Security Model Traditional apps expose risks at the UI or API layer. AI agents are different. Agents can: Process sensitive enterprise data in prompts and responses Collaborate with other agents across workflows Act autonomously on behalf of users Without built‑in controls, even a well‑designed agent can create compliance gaps. Purview SDK brings Microsoft’s enterprise data security and compliance directly into the agent runtime, so governance travels with the agent—not after it. What You Get with Purview SDK + Agent Framework This integration delivers a few key things developers and enterprises care about most: Inline Data Protection Evaluate prompts and responses against Data Loss Prevention (DLP) policies in real time. Content can be allowed or blocked automatically. Built‑In Governance Send AI interactions to Purview for audit, eDiscovery, communication compliance, and lifecycle management—without custom plumbing. Enterprise‑Ready by Design Ship agents that meet enterprise security expectations from the start, not as a follow‑up project. All of this is done natively through Agent Framework middleware, so governance feels like part of the platform—not an add‑on. How Enforcement Works (Quickly) When an agent runs: Prompts and responses flow through the Agent Framework pipeline Purview SDK evaluates content against configured policies A decision is returned: allow, redact, or block Governance signals are logged for audit and compliance This same model works for: User‑to‑agent interactions Agent‑to‑agent communication Multi‑agent workflows Try It: Add Purview SDK in Minutes Here’s a minimal Python example using Agent Framework: That’s it! From that point on: Prompts and responses are evaluated against Purview policies setup within the enterprise tenant Sensitive data can be automatically blocked Interactions are logged for governance and audit Designed for Real Agent Systems Most production AI apps aren’t single‑agent systems. Purview SDK supports: Agent‑level enforcement for fine‑grained control Workflow‑level enforcement across orchestration steps Agent‑to‑agent governance to protect data as agents collaborate This makes it a natural fit for enterprise‑scale, multi‑agent architectures. Get Started Today You can start experimenting right away: Try the Purview SDK with Agent Framework Follow the Microsoft Learn docs to configure Purview SDK with Agent Framework. Explore the GitHub samples See examples of policy‑enforced agents in Python and .NET. Secure AI, Without Slowing It Down AI agents are quickly becoming production systems—not experiments. By integrating Purview SDK directly into the Agent Framework, Microsoft is making governance a default capability, not a deployment blocker. Build intelligent agents. Protect sensitive data. Scale with confidence.Microsoft Purview securing data and enabling apps and agents across your AI stack
As agentic AI moves from experimentation to enterprise execution, it fundamentally reshapes the data risk landscape—because AI apps and autonomous agents can access, reason over, and act on sensitive information at unprecedented speed and scale. This blog explains how Microsoft Purview extends security, compliance, and risk management across the AI stack (from data and prompts to copilots, custom agents, and even third‑party AI services) with capabilities like DSPM, sensitivity labels, DLP, insider risk, and audit/eDiscovery. It also highlights recent innovations such as inline DLP for Copilot Studio agents, upcoming DLM insights and policy recommendations for Copilot/AI app interactions, and expanded protections for Copilot web search and network/browser enforcement through partners.Security Dashboard for AI - Now Generally Available
AI proliferation in the enterprise, combined with the emergence of AI governance committees and evolving AI regulations, leaves CISOs and AI risk leaders needing a clear view of their AI risks, such as data leaks, model vulnerabilities, misconfigurations, and unethical agent actions across their entire AI estate, spanning AI platforms, apps, and agents. 53% of security professionals say their current AI risk management needs improvement, presenting an opportunity to better identify, assess and manage risk effectively. 1 At the same time, 86% of leaders prefer integrated platforms over fragmented tools, citing better visibility, fewer alerts and improved efficiency. 2 To address these needs, we are excited to announce the Security Dashboard for AI, previously announced at Microsoft Ignite, is now generally available. This unified dashboard aggregates posture and real-time risk signals from Microsoft Defender, Microsoft Entra, and Microsoft Purview - enabling users to see left-to-right across purpose-built security tools from within a single pane of glass. The dashboard equips CISOs and AI risk leaders with a governance tool to discover agents and AI apps, track AI posture and drift, and correlate risk signals to investigate and act across their entire AI ecosystem. Security teams can continue using the tools they trust while empowering security leaders to govern and collaborate effectively. Gain Unified AI Risk Visibility Consolidating risk signals from across purpose-built tools can simplify AI asset visibility and oversight, increase security teams’ efficiency, and reduce the opportunity for human error. The Security Dashboard for AI provides leaders with unified AI risk visibility by aggregating security, identity, and data risk across Defender, Entra, Purview into a single interactive dashboard experience. The Overview tab of the dashboard provides users with an AI risk scorecard, providing immediate visibility to where there may be risks for security teams to address. It also assesses an organization's implementation of Microsoft security for AI capabilities and provides recommendations for improving AI security posture. The dashboard also features an AI inventory with comprehensive views to support AI assets discovery, risk assessments, and remediation actions for broad coverage of AI agents, models, MCP servers, and applications. The dashboard provides coverage for all Microsoft AI solutions supported by Entra, Defender and Purview—including Microsoft 365 Copilot, Microsoft Copilot Studio agents, and Microsoft Foundry applications and agents—as well as third-party AI models, applications, and agents, such as Google Gemini, OpenAI ChatGPT, and MCP servers. This supports comprehensive visibility and control, regardless of where applications and agents are built. Prioritize Critical Risk with Security Copilots AI-Powered Insights Risk leaders must do more than just recognize existing risks—they also need to determine which ones pose the greatest threat to their business. The dashboard provides a consolidated view of AI-related security risks and leverages Security Copilot’s AI-powered insights to help find the most critical risks within an environment. For example, Security Copilot natural language interaction improves agent discovery and categorization, helping leaders identify unmanaged and shadow AI agents to enhance security posture. Furthermore, Security Copilot allows leaders to investigate AI risks and agent activities through prompt-based exploration, putting them in the driver’s seat for additional risk investigation. Drive Risk Mitigation By streamlining risk mitigation recommendations and automated task delegation, organizations can significantly improve the efficiency of their AI risk management processes. This approach can reduce the potential hidden AI risk and accelerate compliance efforts, helping to ensure that risk mitigation is timely and accurate. To address this, the Security Dashboard for AI evaluates how organizations put Microsoft’s AI security features into practice and offers tailored suggestions to strengthen AI security posture. It leverages Microsoft’s productivity tools for immediate action within the practitioner portal, making it easy for administrators to delegate recommendation tasks to designated users. With the Security Dashboard for AI, CISOs and risk leaders gain a clear, consolidated view of AI risks across agents, apps, and platforms—eliminating fragmented visibility, disconnected posture insights, and governance gaps as AI adoption scales. Best of all, the Security Dashboard for AI is included with eligible Microsoft security products customers already use. If an organization is already using Microsoft security products to secure AI, they are already a Security Dashboard for AI customer. Getting Started Existing Microsoft Security customers can start using Security Dashboard for AI today. It is included when a customer has the Microsoft Security products—Defender, Entra and Purview—with no additional licensing required. To begin using the Security Dashboard for AI, visit http://ai.security.microsoft.com or access the dashboard from the Defender, Entra or Purview portals. Learn more about the Security Dashboard for AI at Microsoft Security MS Learn. 1AuditBoard & Ascend2 Research. The Connected Risk Report: Uniting Teams and Insights to Drive Organizational Resilience. AuditBoard, October 2024. 2Microsoft. 2026 Data Security Index: Unifying Data Protection and AI Innovation. Microsoft Security, 2026New Microsoft Purview innovations for Fabric to safely accelerate your AI transformation
As organizations adopt AI, security and governance remain core primitives for safe AI transformation and acceleration. After all, data leaders are aware of the notion that: Your AI is only as good as your data. Organizations are skeptical about AI transformation due to concerns of sensitive data oversharing and poor data quality. In fact, 86% of organizations lack visibility into AI data flows, operating in darkness about what information employees share with AI systems [1]. Compounding on this challenge, about 67% of executives are uncomfortable using data for AI due to quality concerns [2]. The challenges of data oversharing and poor data quality requires organizations to solve these issues seamlessly for the safe usage of AI. Microsoft Purview offers a modern, unified approach to help organizations secure and govern data across their entire data estate, in particular best in class integrations with M365, Microsoft Fabric, and Azure data estates, streamlining oversight and reducing complexity across the estate. At FabCon Atlanta, we’re announcing new Microsoft Purview innovations for Fabric to help seamlessly secure and confidently activate your data for AI transformation. These updates span data security and data governance, granting Fabric users to both Discover risks and prevent data oversharing in Fabric Improve governance processes and data quality across their data estate 1. Discover risks and prevent data oversharing in Fabric As data volume increases with AI usage, Microsoft Purview secures your data with capabilities such as Information Protection, Data Loss Prevention (DLP), Insider Risk Management (IRM), and Data Security Posture Management (DSPM). These capabilities work together to secure data throughout its lifecycle and now specifically for your Fabric data estate. Here are a few new Purview innovations for your Fabric estate: Microsoft Purview DLP policies to prevent data leakage for Fabric Warehouse and KQL/SQL DBs Now generally available, Microsoft Purview DLP policies allow Fabric admins to prevent data oversharing in Fabric through policy tip triggering when sensitive data is detected in assets uploaded to Warehouses. Additionally, in preview, Purview DLP enables Fabric admins to restrict access to assets with sensitive data in KQL/SQL DBs and Fabric Warehouses to prevent data oversharing. This helps admins limit access to sensitive data detected in these data sources and data stores to just asset owners and allowed collaborators. These DLP innovations expand upon the depth and breadth of existing DLP policies to ensure sensitive data in Fabric is protected. Figure 1. DLP restrict access preventing data oversharing of customer information stored in a KQL database. Microsoft Purview Insider Risk Management (IRM) indicators for Lakehouse, IRM data theft quick policy for Fabric, and IRM pay-as-you-go usage report for Fabric Microsoft Purview Insider Risk Management is now generally available for Microsoft Fabric extending its risk-detection capabilities to Microsoft Fabric lakehouses (in addition to Power BI which is supported today) by offering ready-to-use risk indicators based on risky user activities in Fabric lakehouses, such as sharing data from a Fabric lakehouse with people outside the organization . Additionally, IRM data theft policy is now generally available for security admins to create a data theft policy to detect Fabric data exfiltration, such as exporting Power BI reports. Also, organizations now have visibility into how much they are billed with the IRM pay-as-you-go usage report for Fabric, providing customers with an easy-to-use dashboard to track their consumption and predictability on costs. Figure 2. IRM identifying risky user behavior when handling data in a Fabric Lakehouse. Figure 3. Security admins can create a data theft policy to detect Fabric data exfiltration. Figure 4. Security admins can check the pay-as-you-go usage (processing units) across different workloads and activities such as the downgrading of sensitivity labels of a lakehouse through the usage report. Microsoft Purview for all Fabric Copilots and Agents Microsoft Purview currently provides capabilities in preview for all Copilots and Agents in Fabric. Organizations can: Discover data risks such as sensitive data in user prompts and responses and receive recommended actions to reduce these risks. Detect and remediate oversharing risks with Data Risk Assessments on DSPM, that identify potentially overshared, unprotected, or sensitive Fabric assets, giving teams clear visibility into where data exposure exists and enabling targeted actions—like applying labels or policies—to reduce risk and ensure Fabric data is AI‑ready and governed by design. Identify risky AI usage with Microsoft Purview Insider Risk Management to investigate risky AI usage, such as an inadvertent user who has neglected security best practices and shared sensitive data in AI. Govern AI usage with Microsoft Purview Audit, Microsoft Purview eDiscovery, retention policies, and non-compliant usage detection. Figure 5. Purview DSPM provides admins with the ability to discover data risks such as a user’s attempt to obtain historical data within a data agent in the Data Science workload in Fabric. DSPM subsequently provides actions to solve this risk. Now that we’ve covered how Purview helps secure Fabric data and AI, the next focus is ensuring Fabric users can use that data responsibly. 2. Improve governance processes and data quality across their data estate Once an organization’s data is secured for AI, the next challenge is ensuring consumers can easily find and trust the data needed for AI. This is where the Purview Unified Catalog comes in, serving as the foundation for enterprise data governance. Estate-wide data discovery provides a holistic view of the data landscape, helping prevent valuable data from being underutilized. Built-in data quality tools enable teams to measure, monitor, and remediate issues such as incomplete records, inconsistencies, and redundancies, ensuring decisions and AI outcomes are based on trusted, reliable data. Purview provides additional governance capabilities for all data consumers and governance teams and supplement those who utilize the Fabric OneLake catalog. Here are a few new innovations within the Purview Unified Catalog: Publication workflows for data products and glossary terms Now generally available, data owners can leverage Workflows in the Purview Unified Catalog to manage how data products and glossary terms are published. Customizable workflows enable governance teams to work faster to create a well curated catalog, specifically by ensuring that data products and glossary terms are published and governed responsibly. Data consumers can request access to data products and be reassured that the data is held to a certain governance standard by governance teams. Figure 6. Customizing a Workflow for publishing a glossary term in your catalog. Data quality for ungoverned assets in the Unified Catalog, including Fabric data In the Unified Catalog, Data Quality for ungoverned data assets allows organizations to run data quality on data assets, including Fabric assets, without linking them to data products. This approach enables data quality stewards to run data quality at a faster speed and on greater scale, ensuring that their organizations can democratize high quality data for AI use cases. Figure 7. Running data quality on data assets without it being associated with a data product. Looking Forward As organizations accelerate their AI ambitions, data security and governance become essential. Microsoft Purview and Microsoft Fabric deliver an integrated and unified foundation that enables organizations to innovate with confidence, ensuring data is protected, governed, and trusted for responsible AI activation. We’re committed to helping you stay ahead of evolving challenges and opportunities as you unlock more value from your data. Explore these new capabilities and join us on the journey toward a more secure, governed, and AI‑ready data future. [1] 2025 AI Security Gap: 83% of Organizations Flying Blind [2] The Importance Of Data Quality: Metrics That Drive Business SuccessBeyond Visibility: The new Microsoft Purview Data Security Posture Management (DSPM) experience
In today’s AI-powered enterprises, understanding your data estate—and the risks that come with it—is both more complex and more critical than ever. Meanwhile, many organizations still grapple with a fragmented data security landscape, relying on a patchwork of disconnected tools that obscure visibility and hinder effective data security posture management. As AI adoption accelerates, entirely new data risk vectors are emerging—ranging from oversharing and compliance gaps to operational inefficiencies. According to recent research[1], 40% of data security incidents now occur within AI applications, and 78% of AI users are bringing their own AI tools to work. This challenge is further compounded by the rise of AI agents, creating a scenario that demands a unified, context-aware approach to understanding and securing data within trusted workflows. This is where data security posture management helps organizations - by providing the visibility and control they need across sprawling data estates and evolving risk surfaces. By continuously assessing data security posture, organizations can better identify gaps and remediate risks, avoiding fragmented efforts. However, even with these capabilities, many organizations still struggle to stay focused on the ultimate goal—achieving meaningful security outcomes rather than simply managing tools or processes. To overcome this, organizations must shift their perspective: seeing data security not as a collection of individual solutions, but as a holistic program anchored in desired business and security outcomes. Managing data security posture should become the foundation for building a sustainable and healthy data security program—one that continuously improves, drives measurable resilience, strengthens trust, and systematically reduces risk across the enterprise. At Microsoft Ignite, we’re excited to share the newly enhanced Microsoft Purview Data Security Posture Management (DSPM) experience—an AI-powered, centralized solution that focuses on the goals your organization needs to accomplish, and helps you strengthen data security to confidently embrace AI apps and agents with actionable insights, new third-party signals, and Security Copilot agents. Enabling AI and agents confidently with enhanced data security posture The enhanced DSPM experience is designed to simplify data security posture by stitching together the scenarios and goals customers need to achieve when it comes to their data. We are combining the depth of Purview visibility and controls with the breadth of external signals and agentic activities, complemented by Security Copilot agents, to provide a strong, proactive DSPM experience. See what’s new in Purview DSPM: ▪ Outcome-based guided workflows: To avoid the guesswork of interpreting insights and determining the next best actions, now customers can manage their data security posture by selecting which data security outcome to prioritize and the risks related to each—shifting from reactive visibility to actionable, outcome-driven insights. For each outcome, this experience will guide customers through the key metrics and risk patterns present in their organization, as well as a recommended action plan, including the expected impact of taking those actions. For example, if an admin chooses to address the risk of “Preventing sensitive data exfiltration to risky destinations,” DSPM will show how many sensitive files are at risk, how many have been exfiltrated to personal domains or external cloud services in the past 30 days, and provide recommended actions to mitigate these risks. These actions may include creating a new DLP policy and an IRM policy to detect and prevent such exfiltration to personal emails, and admins can see the impact each of these actions will have. After that, they can continuously assess their data security posture through the outcome metrics. [Figure 1: List of data security objectives, with metrics and remediation plans per objective] ▪ External data source visibility: Organizations trust Microsoft for collaboration and productivity, but their footprint spans to external data platforms too. To provide a more complete and comprehensive view of data risks across the digital estate, we’re excited to announce the advancement of the Purview partner ecosystem, with the inclusion of third-party signals in DSPM through the collaboration with our partners Varonis, BigID, Cyera and OneTrust. This partnership, possible via integration with Microsoft Sentinel Data Lake, is designed to help organizations see and understand more of their data—wherever it resides. Through DSPM, a customer will be able to easily turn on these external data signals and evaluate data asset information (such as permissions, location, sensitive information types) in these environments. Available sources initially will be: Salesforce (provided by Varonis), Databricks (provided by BigID), Snowflake (provided by Cyera), and Google Cloud Platform (provided by OneTrust), with additional external data coverage coming soon. By integrating these external data sources into Purview, data security teams gain extended visibility into sensitive data across third-party platforms alongside their Microsoft data, which also empowers teams to raise their confidence when adopting AI apps and agents by expanding visibility on external data that is referenced by those tools. This collaboration not only eliminates blind spots and strengthens risk posture, but also simplifies data security operations with a single, streamlined experience. These signals will be offered using pay-as-you-go billing through Microsoft Sentinel consumptive meters. Learn more here. [Figure 2: Asset explorer with external data from Databricks, Snowflake, Google Cloud Platform, and Salesforce] ▪ New out-of-the-box reports for posture insights: DSPM also extends visibility by presenting new out-of-the-box reports that deliver immediate visibility into top-of-mind metrics organizations care about, such as protection coverage via Sensitivity labels, Data Loss Prevention (DLP) policy triggers, and posture trends over time. With advanced filtering options and deep drilldowns, security teams can quickly identify unprotected sensitive data, track label adoption, monitor policy effectiveness, and surface potential risks earlier. These actionable insights streamline monitoring and support precise policy fine-tuning, enabling data security teams to shift from reactive operations to proactive, data-driven strategic decisions. ▪ Expanded coverage and remediation on Data Risk Assessments: DSPM now extends Data Risk Assessments to item-level analysis with automated new remediation actions like—enabling bulk disabling of overshared SharePoint links and direct activation of protection policies. Starting from an outcome-based remediation plan or the Data Risk Assessment tab, teams can take targeted actions such as removing or tightening sharing links, notifying owners, and applying or updating sensitivity labels—including new support for bulk manual labeling from search—so fixes occur where the risky items reside, and progress is immediately reflected in posture metrics. Beyond Microsoft 365, Data Risk Assessments have also expanded to Microsoft Fabric, surfacing Fabric assets in a new default assessment and proactive actions to protect new Fabric assets with DLP policies or sensitivity labels. These enhancements address key customer challenges around visibility gaps, fragmented remediation workflows, and governance across hybrid environments. AI agents are growing rapidly in enterprise environments, bringing unique data risks that traditional security can’t address. Their autonomous actions and broad access to sensitive information create complex risk profiles tied to behavior, not just identity. To stay secure, organizations need data protection strategies that treat agents as first-class entities with tailored visibility, risk scoring, and policy controls. DSPM is also adapting to this new scenario: ▪ AI Observability for agents: We’re introducing a dedicated view within DSPM that treats agents—such as the ones created on Microsoft 365 Copilot, Copilot Studio, and Azure AI Foundry—as first-class entities in your organizations when it comes to data security posture. It provides a unified inventory of all agents – including third-party agents – as well as the assigned insider risk level based on the agent behavior, posture metrics, and activity trends of each agent. Security teams can drill down into individual agents to see contextual insights like risky behaviors, oversharing patterns, and can take recommended actions, such as the creation of retention policies. AI Observability gives customers clear visibility across agents and connects insights to guided actions— simplifying governance, facilitating risk prioritization, and enabling secure AI adoption without slowing innovation. [Figure 3: AI Observability plane with inventory of 1st and 3rd party agents within the organization, as well as assigned risk level per agent] Learn more about all the innovations we are announcing to help you safely adopt agents. Redefining data security posture for the AI-powered era The new DSPM experience marks a pivotal moment in Microsoft Purview’s journey to secure the modern enterprise. By unifying visibility, protection, and investigation across human and agentic data activity, Purview empowers organizations to embrace AI responsibly, reduce risk, and drive continuous improvement in their data security posture. When it comes to leveraging built-in AI within data security solutions, admins can view proactive or summary insights and launch a Data Security Investigation (DSI) directly from DSPM. This important integration allows admins to utilize the power and scale of DSI analysis to take a closer look at data risks. Furthermore, applying AI to strengthen data security is just as critical as securing AI itself, as AI-powered solutions help organizations anticipate and neutralize risks at scale, and agents have the potential to take data security processes to another level, increasing automation and allowing teams to focus on the most pressing risks. That’s why we’re thrilled to introduce the Data Security Posture Agent, designed to augment the new Purview DSPM experience even further. This agent leverages LLMs to understand context and intent, going beyond traditional classifiers that can often miss nuance. It analyzes selected file sets and generates precise reports on requested information, such as merger & acquisition details or PO numbers. Armed with these insights, admins can decide on their own next steps, whether that’s applying new labels, updating policies, or initiating investigations, streamlining discovery and risk reduction in one intelligent, outcome-driven experience. This capability tackles the challenges of manual, time-consuming data analysis and limited visibility into sensitive information, helping organizations achieve faster resolution, stronger compliance posture, and greater operational efficiency. [Figure 4: Data Security Posture Agent to discover sensitive data and take appropriate actions] Combined with the Data Security Triage agent and other Security Copilot capabilities integrated within Purview, the Data Security Posture agent creates a robust AI-powered foundation for modern data security teams. To make the agents easily accessible and help teams get started more quickly, we are excited to announce that Security Copilot will be available to all Microsoft 365 E5 customers. Rollout starts today for existing Security Copilot customers with Microsoft 365 E5 and will continue in the upcoming months for all Microsoft 365 E5 customers. Customers will receive advanced notice before activation. Learn more: https://aka.ms/SCP-Ignite25 Building the future of data security alongside customers As organizations navigate this new era of AI-driven innovation, the ability to secure data confidently and proactively is no longer optional—it’s mission-critical. Microsoft Purview DSPM delivers a unified, outcome-based approach that transforms complexity into clarity, guiding teams from insight to action with precision. Current solutions Purview DSPM and DSPM for AI will remain available until June, when the new Purview DSPM experience becomes the centralized solution. Costumers’ top-of-mind capabilities within current workflows, such as Data Risk Assessments and Security Copilot prompt gallery, will also be available within the new DSPM experience. The new DSPM experience and capabilities will roll out in Public Preview within the next few weeks, and will be available for customers with Microsoft 365 E5 and E5 Compliance licenses. By extending visibility across external sources, introducing AI observability, and empowering remediation through intelligent agents, Purview enables enterprises to embrace AI and agents without compromise—strengthening trust, reducing risk, and driving continuous improvement in data security posture. The future of secure AI adoption starts here. Getting connected with Microsoft Purview Read our blog with the main announcements across the Purview data security solutions at Ignite. Try Microsoft Purview data security. Learn more about Microsoft Purview on our website and Microsoft Learn. [1] July 2025 multi-national survey of over 1700 data security professionals commissioned by Microsoft from Hypothesis GroupHow to deploy Microsoft Purview DSPM for AI to secure your AI apps
Microsoft Purview Data Security Posture Management (DSPM for AI) is designed to enhance data security for the following AI applications: Microsoft Copilot experiences, including Microsoft 365 Copilot. Enterprise AI apps, including ChatGPT enterprise integration. Other AI apps, including all other AI applications like ChatGPT consumer, Microsoft Copilot, DeepSeek, and Google Gemini, accessed through the browser. In this blog, we will dive into the different policies and reporting we have to discover, protect and govern these three types of AI applications. Prerequisites Please refer to the prerequisites for DSPM for AI in the Microsoft Learn Docs. Login to the Purview portal To begin, start by logging into Microsoft 365 Purview portal with your admin credentials: In the Microsoft Purview portal, go to the Home page. Find DSPM for AI under solutions. 1. Securing Microsoft 365 Copilot Be sure to check out our blog on How to use the DSPM for AI data assessment report to help you address oversharing concerns when you deploy Microsoft 365 Copilot. Discover potential data security risks in Microsoft 365 Copilot interactions In the Overview tab of DSPM for AI, start with the tasks in “Get Started” and Activate Purview Audit if you have not yet activated it in your tenant to get insights into user interactions with Microsoft Copilot experiences In the Recommendations tab, review the recommendations that are under “Not Started”. Create the following data discovery policy to discover sensitive information in AI interactions by clicking into it. Detect risky interactions in AI apps - This public preview Purview Insider Risk Management policy helps calculate user risk by detecting risky prompts and responses in Microsoft 365 Copilot experiences. Click here to learn more about Risky AI usage policy. With the policies to discover sensitive information in Microsoft Copilot experiences in place, head back to the Reports tab of DSPM for AI to discover any AI interactions that may be risky, with the option to filter to Microsoft Copilot Experiences, and review the following for Microsoft Copilot experiences: Total interactions over time (Microsoft Copilot) Sensitive interactions per AI app Top unethical AI interactions Top sensitivity labels references in Microsoft 365 Copilot Insider Risk severity Insider risk severity per AI app Potential risky AI usage Protect sensitive data in Microsoft 365 Copilot interactions From the Reports tab, click on “View details” for each of the report graphs to view detailed activities in the Activity Explorer. Using available filters, filter the results to view activities from Microsoft Copilot experiences based on different Activity type, AI app category and App type, Scope, which support administrative units for DSPM for AI, and more. Then drill down to each activity to view details including the capability to view prompts and response with the right permissions. To protect the sensitive data in interactions for Microsoft 365 Copilot, review the Not Started policies in the Recommendations tab and create these policies: Information Protection Policy for Sensitivity Labels - This option creates default sensitivity labels and sensitivity label policies. If you've already configured sensitivity labels and their policies, this configuration is skipped. Protect sensitive data referenced in Microsoft 365 Copilot - This guides you through the process of creating a Purview Data Loss Prevention (DLP) policy to restrict the processing of content with specific sensitivity labels in Copilot interactions. Click here to learn more about Data Loss Prevention for Microsoft 365 Copilot. Protect sensitive data referenced in Copilot responses - Sensitivity labels help protect files by controlling user access to data. Microsoft 365 Copilot honors sensitivity labels on files and only shows users files they already have access to in prompts and responses. Use Data assessments to identify potential oversharing risks, including unlabeled files. Stay tuned for an upcoming blog post on using DSPM for AI data assessments! Use Copilot to improve your data security posture - Data Security Posture Management combines deep insights with Security Copilot capabilities to help you identify and address security risks in your org. Once you have created policies from the Recommendations tab, you can go to the Policies tab to review and manage all the policies you have created across your organization to discover and safeguard AI activity in one centralized place, as well as edit the policies or investigate alerts associated with those policies in solution. Note that additional policies not from the Recommendations tab will also appear in the Policies tab when DSPM for AI identifies them as policies to Secure and govern all AI apps. Govern the prompts and responses in Microsoft 365 Copilot interactions Understand and comply with AI regulations by selecting “Guided assistance to AI regulations” in the Recommendations tab and walking through the “Actions to take”. From the Recommendations tab, create a Control unethical behavior in AI Purview Communications Compliance policy to detect sensitive information in prompts and responses and address potentially unethical behavior in Microsoft Copilot experiences and ChatGPT for Enterprise. This policy covers all users and groups in your organization. To retain and/or delete Microsoft 365 Copilot prompts and responses, setup a Data Lifecycle policy by navigating to Microsoft Purview Data Lifecycle Management and find Retention Policies under the Policies header. You can also preserve, collect, analyze, review, and export Microsoft 365 Copilot interactions by creating an eDiscovery case. 2. Securing Enterprise AI apps Please refer to this amazing blog on Unlocking the Power of Microsoft Purview for ChatGPT Enterprise | Microsoft Community Hub for detailed information on how to integrate with ChatGPT for enterprise, the Purview solutions it currently supports through Purview Communication Compliance, Insider Risk Management, eDiscovery, and Data Lifecycle Management. Learn more about the feature also through our public documentation. 3. Securing other AI Microsoft Purview DSPM for AI currently supports the following list of AI sites. Be sure to also check out our blog on the new Microsoft Purview data security controls for the browser & network to secure other AI apps. Discover potential data security risks in prompts sent to other AI apps In the Overview tab of DSPM for AI, go through these three steps in “Get Started” to discover potential data security risk in other AI interactions: Install Microsoft Purview browser extension For Windows users: The Purview extension is not necessary for the enforcement of data loss prevention on the Edge browser but required for Chrome to detect sensitive info pasted or uploaded to AI sites. The extension is also required to detect browsing to other AI sites through an Insider Risk Management policy for both Edge and Chrome browser. Therefore, Purview browser extension is required for both Edge and Chrome in Windows. For MacOS users: The Purview extension is not necessary for the enforcement of data loss prevention on macOS devices, and currently, browsing to other AI sites through Purview Insider Risk Management is not supported on MacOS, therefore, no Purview browser extension is required for MacOS. Extend your insights for data discovery – this one-click collection policy will setup three separate Purview detection policies for other AI apps: Detect sensitive info shared in AI prompts in Edge – a Purview collection policy that detects prompts sent to ChatGPT consumer, Micrsoft Copilot, DeepSeek, and Google Gemini in Microsoft Edge and discovers sensitive information shared in prompt contents. This policy covers all users and groups in your organization in audit mode only. Detect when users visit AI sites – a Purview Insider Risk Management policy that detects when users use a browser to visit AI sites. Detect sensitive info pasted or uploaded to AI sites – a Purview Endpoint Data loss prevention (eDLP) policy that discovers sensitive content pasted or uploaded in Microsoft Edge, Chrome, and Firefox to AI sites. This policy covers all users and groups in your org in audit mode only. With the policies to discover sensitive information in other AI apps in place, head back to the Reports tab of DSPM for AI to discover any AI interactions that may be risky, with the option to filter by Other AI Apps, and review the following for other AI apps: Total interactions over time (other AI apps) Total visits (other AI apps) Sensitive interactions per AI app Insider Risk severity Insider risk severity per AI app Protect sensitive info shared with other AI apps From the Reports tab, click on “View details” for each of the report graphs to view detailed activities in the Activity Explorer. Using available filters, filter the results to view activities based on different Activity type, AI app category and App type, Scope, which support administrative units for DSPM for AI, and more. To protect the sensitive data in interactions for other AI apps, review the Not Started policies in the Recommendations tab and create these policies: Fortify your data security – This will create three policies to manage your data security risks with other AI apps: 1) Block elevated risk users from pasting or uploading sensitive info on AI sites – this will create a Microsoft Purview endpoint data loss prevention (eDLP) policy that uses adaptive protection to give a warn-with-override to elevated risk users attempting to paste or upload sensitive information to other AI apps in Edge, Chrome, and Firefox. This policy covers all users and groups in your org in test mode. Learn more about adaptive protection in Data loss prevention. 2) Block elevated risk users from submitting prompts to AI apps in Microsoft Edge – this will create a Microsoft Purview browser data loss prevention (DLP) policy, and using adaptive protection, this policy will block elevated, moderate, and minor risk users attempting to put information in other AI apps using Microsoft Edge. This integration is built-in to Microsoft Edge. Learn more about adaptive protection in Data loss prevention. 3) Block sensitive info from being sent to AI apps in Microsoft Edge - this will create a Microsoft Purview browser data loss prevention (DLP) policy to detect inline for a selection of common sensitive information types and blocks prompts being sent to AI apps while using Microsoft Edge. This integration is built-in to Microsoft Edge. Once you have created policies from the Recommendations tab, you can go to the Policies tab to review and manage all the policies you have created across your organization to discover and safeguard AI activity in one centralized place, as well as edit the policies or investigate alerts associated with those policies in solution. Note that additional policies not from the Recommendations tab will also appear in the Policies tab when DSPM for AI identifies them as policies to Secure and govern all AI apps. Conclusion Microsoft Purview DSPM for AI can help you discover, protect, and govern the interactions from AI applications in Microsoft Copilot experiences, Enterprise AI apps, and other AI apps. We recommend you review the Reports in DSPM for AI routinely to discover any new interactions that may be of concern, and to create policies to secure and govern those interactions as necessary. We also recommend you utilize the Activity Explorer in DSPM for AI to review different Activity explorer events while users interacting with AI, including the capability to view prompts and response with the right permissions. We will continue to update this blog with new features that become available in DSPM for AI, so be sure to bookmark this page! Follow-up Reading Check out this blog on the details of each recommended policies in DSPM for AI: Microsoft Purview – Data Security Posture Management (DSPM) for AI | Microsoft Community Hub Address oversharing concerns with Microsoft 365 blueprint - aka.ms/Copilot/Oversharing Microsoft Purview data security and compliance protections for Microsoft 365 Copilot and other generative AI apps | Microsoft Learn Considerations for deploying Microsoft Purview AI Hub and data security and compliance protections for Microsoft 365 Copilot and Microsoft Copilot | Microsoft Learn Commonly used properties in Copilot audit logs - Audit logs for Copilot and AI activities | Microsoft Learn Supported AI sites by Microsoft Purview for data security and compliance protections | Microsoft Learn Where Copilot usage data is stored and how you can audit it - Microsoft 365 Copilot data protection and auditing architecture | Microsoft Learn Downloadable whitepaper: Data Security for AI Adoption | Microsoft Public roadmap for DSPM for AI - Microsoft 365 Roadmap | Microsoft 365New Microsoft Purview Deployment Blueprint | Lightweight guide to mitigate data leakage
We’re excited to share our latest Data Security deployment blueprint: “Lightweight guide to mitigate data leakage”—a practical resource designed to help organizations quickly enable core data security features across their Microsoft 365 estate with minimal setup. The blueprint follows a good / better / best model that maps protections to your licensing. “Good” highlights foundational features included in Business Premium SKUs, while “Better” and “Best” layer in advanced E5 Compliance capabilities, such as auto-labeling, Endpoint DLP, insider risk signals and much more. With the new E5 Compliance Add-On for Business Premium, this guide shows how organizations can capture quick wins today while building toward stronger, long-term security practices. This blueprint is designed for IT administrators, security teams, and compliance stakeholders tasked with protecting sensitive data – and it’s equally valuable for Microsoft partners and consultants supporting customers on their data security journey. Whether you’re enabling basic safeguards or advancing towards automated protection, this guide provides clear, actionable steps to strengthen your data security posture. Ready to get started? Visit our Purview deployment blueprint page or jump straight to the direct PPT link for a step-by-step walkthrough. Securing your data doesn’t have to be complex – this lightweight blueprint makes it achievable for organizations of any size.
