Scaling Data Governance- Does a Purview in a Day Framework Exist?
Hello Purview Community, I’ve been exploring the available acceleration resources for Microsoft Purview, and one thing I noticed is a potential gap in the "In a Day" workshop series. While we have excellent programs like Power BI in a Day or Fabric in a Day, I haven't yet seen a formalized Purview in a Day framework designed to help organizations jumpstart their governance journey in a single, cohesive session. I am reaching out because my team is currently preparing something in this area that we believe will be very useful to the community and Microsoft in the future. Rather than working in isolation, we want to ensure we are aligned with the official roadmap. I wanted to reach out to the community and the Microsoft product team to ask: Is there an official "In a Day" initiative for Purview currently in the works? If not, who would be the best point of contact to discuss alignment? Looking forward to hearing your thoughts and seeing if we can build something impactful together! #MicrosoftPurview #Purview
From “No” to “Now”: A 7-Layer Strategy for Enterprise AI Safety
The “block” posture on Generative AI has failed. In a global enterprise, banning these tools doesn't stop usage; it simply pushes intellectual property into unmanaged channels and creates a massive visibility gap in corporate telemetry. The priority has now shifted from stopping AI to hardening the environment so that innovation can run at velocity without compromising data sovereignty. Traditional security perimeters are ineffective against the “slow bleed” of AI leakage - where data moves through prompts, clipboards, and autonomous agents rather than bulk file transfers. To secure this environment, a 7-layer defense-in-depth model is required to treat the conversation itself as the new perimeter. 1. Identity: The Only Verifiable Perimeter Identity is the primary control plane. Access to AI services must be treated with the same rigor as administrative access to core infrastructure. The strategy centers on enforcing device-bound Conditional Access, where access is strictly contingent on device health. To solve the "Account Leak" problem, the deployment of Tenant Restrictions v2 (TRv2) is essential to prevent users from signing into personal tenants using corporate-managed devices. For enhanced coverage, Universal Tenant Restrictions (UTR) via Global Secure Access (GSA) allows for consistent enforcement at the cloud edge. While TRv2 authentication-plane is GA, data-plane protection is GA for the Microsoft 365 admin center and remains in preview for other workloads such as SharePoint and Teams. 2. Eliminating the Visibility Gap (Shadow AI) You can’t secure what you can't see. Microsoft Defender for Cloud Apps (MDCA) serves to discover and govern the enterprise AI footprint, while Purview DSPM for AI (formerly AI Hub) monitors Copilot and third-party interactions. By categorizing tools using MDCA risk scores and compliance attributes, organizations can apply automated sanctioning decisions and enforce session controls for high-risk endpoints. 3. Data Hygiene: Hardening the “Work IQ” AI acts as a mirror of internal permissions. In a "flat" environment, AI acts like a search engine for your over-shared data. Hardening the foundation requires automated sensitivity labeling in Purview Information Protection. Identifying PII and proprietary code before assigning AI licenses ensures that labels travel with the data, preventing labeled content from being exfiltrated via prompts or unauthorized sharing. 4. Session Governance: Solving the “Clipboard Leak” The most common leak in 2025 is not a file upload; it’s a simple copy-paste action or a USB transfer. Deploying Conditional Access App Control (CAAC) via MDCA session policies allows sanctioned apps to function while specifically blocking cut/copy/paste. This is complemented by Endpoint DLP, which extends governance to the physical device level, preventing sensitive data from being moved to unmanaged USB storage or printers during an AI-assisted workflow. Purview Information Protection with IRM rounds this out by enforcing encryption and usage rights on the files themselves. When a user tries to print a "Do Not Print" document, Purview triggers an alert that flows into Microsoft Sentinel. This gives the SOC visibility into actual policy violations instead of them having to hunt through generic activity logs. 5. The “Agentic” Era: Agent 365 & Sharing Controls Now that we're moving from "Chat" to "Agents", Agent 365 and Entra Agent ID provide the necessary identity and control plane for autonomous entities. A quick tip: in large-scale tenants, default settings often present a governance risk. A critical first step is navigating to the Microsoft 365 admin center (Copilot > Agents) to disable the default “Anyone in organization” sharing option. Restricting agent creation and sharing to a validated security group is essential to prevent unvetted agent sprawl and ensure that only compliant agents are discoverable. 6. The Human Layer: “Safe Harbors” over Bans Security fails when it creates more friction than the risk it seeks to mitigate. Instead of an outright ban, investment in AI skilling-teaching users context minimization (redacting specifics before interacting with a model) - is the better path. Providing a sanctioned, enterprise-grade "Safe Harbor" like M365 Copilot offers a superior tool that naturally cuts down the use of Shadow AI. 7. Continuous Ops: Monitoring & Regulatory Audit Security is not a “set and forget” project, particularly with the EU AI Act on the horizon. Correlating AI interactions and DLP alerts in Microsoft Sentinel using Purview Audit (specifically the CopilotInteraction logs) data allows for real-time responses. Automated SOAR playbooks can then trigger protective actions - such as revoking an Agent ID - if an entity attempts to access sensitive HR or financial data. Final Thoughts Securing AI at scale is an architectural shift. By layering Identity, Session Governance, and Agentic Identity, AI moves from being a fragmented risk to a governed tool that actually works for the modern workplace.
Enterprise Strategy for Secure Agentic AI: From Compliance to Implementation
Imagine an AI system that doesn’t just answer questions but takes action querying your databases, updating records, triggering workflows, even processing refunds without human intervention. That’s Agentic AI and it’s here. But with great power comes great responsibility. This autonomy introduces new attack surfaces and regulatory obligations. The Model Context Protocol (MCP) Server the gateway between your AI agent and critical systems becomes your Tier-0 control point. If it fails, the blast radius is enormous. This is the story of how enterprises can secure Agentic AI, stay compliant and implement Zero Trust architectures using Azure AI Foundry. Think of it as a roadmap a journey with three milestones - Milestone 1: Securing the Foundation Our journey starts with understanding the paradigm shift. Traditional AI with RAG (Retrieval-Augmented Generation) is like a librarian: It retrieves pre-indexed data. It summarizes information. It never changes the books or places orders. Security here is simple: protect the index, validate queries, prevent data leaks. But Agentic AI? It’s a staffer with system access. It can: Execute tools and business logic autonomously. Chain operations: read → analyze → write → notify. Modify data and trigger workflows. Bottom line: RAG is a “smart librarian.” Agentic AI is a “staffer with system access.” Treat the security model accordingly. And that means new risks: unauthorized access, privilege escalation, financial impact, data corruption. So what’s the defense? Ten critical security controls your first line of protection: Here’s what a production‑grade, Zero Trust MCP gateway needs. Its intentionally simplified in the demo (e.g., no auth) to highlight where you must harden in production. (https://github.com/davisanc/ai-foundry-mcp-gateway) Authentication Demo: None Prod: Microsoft Entra ID, JWT validation, Managed Identity, automatic credential rotation Authorization & RBAC Demo: None Prod: Tool‑level RBAC via Entra; least privilege; explicit allow‑lists per agent/capability Input Validation Demo: Basic (ext whitelist, 10MB, filename sanitize) Prod: JSON Schema validation, injection guards (SQL/command), business‑rule checks Rate Limiting Demo: None Prod: Multi‑tier (per‑agent, per‑tool, global), adaptive throttling, backoff Audit Logging Demo: Console → App Service logs Prod: Structured logs w/ correlation IDs, compliance metadata, PII redaction Session Management Demo: In‑memory UUID sessions Prod: Encrypted distributed storage (Redis/Cosmos DB), tenant isolation, expirations File Upload Security Demo: Ext whitelist, size limits, memory‑only Prod: 7‑layer defense (validate, MIME, malware scanning via Defender for Storage), encryption at rest, signed URLs Network Security Demo: Public App Service + HTTPS Prod: Private Endpoints, VNet integration, NSGs, Azure Firewall no public exposure Secrets Management Demo: App Service env vars (not in code) Prod: Azure Key Vault + Managed Identity, rotation, access audit Observability & Threat Detection (5‑Layer Stack) Layer 1: Application Insights (requests, dependencies, custom security events) Layer 2: Azure AI Content Safety (harmful content, jailbreaks) Layer 3: Microsoft Defender for AI (prompt injection incl. ASCII smuggling, credential theft, anomalous tool usage) Layer 4: Microsoft Purview for AI (PII/PHI classification, DLP on outputs, lineage, policy) Layer 5: Microsoft Sentinel (SIEM correlation, custom rules, automated response) Note: Azure AI Content Safety is built into Azure AI Foundry for real‑time filtering on both prompts and completions. Picture this as an airport security model: multiple checkpoints, each catching what the previous missed. That’s defense-in-depth. Zero Trust in Practice ~ A Day in the Life of a Prompt Every agent request passes through 8 sequential checkpoints, mapped to MITRE ATLAS tactics/mitigations (e.g., AML.M0011 Input Validation, AML.M0004 Output Filtering, AML.M0015 Adversarial Input Detection). The design goal is defense‑in‑depth: multiple independent controls, different detection signals, and layered failure modes. Checkpoints 1‑7: Enforcement (deny/contain before business systems) Checkpoint 8: Monitoring (detect/respond, hunt, learn, harden) AML.M0009 – Control Access to ML Models AML.M0011 – Validate ML Model Inputs AML.M0000 – Limit ML Model Availability AML.M0014 – ML Artifact Logging AML.M0004 – Output Filtering AML.M0015 – Adversarial Input Detection If one control slips, the others still stand. Resilience is the product of layers. Milestone 2: Navigating Compliance Next stop: regulatory readiness. The EU AI Act is the world’s first comprehensive AI law. If your AI system operates in or impacts the EU market, compliance isn’t optional, it’s mandatory. Agentic AI often falls under high-risk classification. That means: Risk management systems. Technical documentation. Logging and traceability. Transparency and human oversight. Fail to comply? Fines up to €30M or 6% of global turnover. Azure helps you meet these obligations: Entra ID for identity and RBAC. Purview for data classification and DLP. Defender for AI for prompt injection detection. Content Safety for harmful content filtering. Sentinel for SIEM correlation and incident response. And this isn’t just about today. Future regulations are coming US AI Executive Orders, UK AI Roadmap, ISO/IEC 42001 standards. The trend is clear: transparency, explainability, and continuous monitoring will be universal. Milestone 3: Implementation Deep-Dive Now, the hands-on part. How do you build this strategy into reality? Step 1: Entra ID Authentication Register your MCP app in Entra ID. Configure OAuth2 and JWT validation. Enable Managed Identity for downstream resources. Step 2: Apply the 10 Controls RBAC: Tool-level access checks. Validation: JSON schema + injection prevention. Rate Limiting: Express middleware or Azure API Management. Audit Logging: Structured logs with correlation IDs. Session Mgmt: Redis with encryption. File Security: MIME checks + Defender for Storage. Network: Private Endpoints + VNet. Secrets: Azure Key Vault. Observability: App Insights + Defender for AI + Purview + Sentinel. Step 3: Secure CI/CD Pipelines Embed compliance checks in Azure DevOps: Pre-build: Secret scanning. Build: RBAC & validation tests. Deploy: Managed Identity for service connections. Post-deploy: Compliance scans via Azure Policy. Step 4: Build the 5-Layer Observability Stack App Insights → Telemetry. Content Safety → Harmful content detection. Defender for AI → Prompt injection monitoring. Purview → PII/PHI classification and lineage. Sentinel → SIEM correlation and automated response. The Destination: A Secure, Compliant Future By now, you’ve seen the full roadmap: Secure the foundation with Zero Trust and layered controls. Navigate compliance with EU AI Act and prepare for global regulations. Implement the strategy using Azure-native tools and CI/CD best practices. Because in the world of Agentic AI, security isn’t optional, compliance isn’t negotiable, and observability is your lifeline. Resources https://learn.microsoft.com/en-us/azure/ai-foundry/what-is-azure-ai-foundry https://learn.microsoft.com/en-us/azure/defender-for-cloud/ai-threat-protection https://learn.microsoft.com/en-us/purview/ai-microsoft-purview https://atlas.mitre.org/ https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence https://techcommunity.microsoft.com/blog/microsoft-security-blog/microsoft-sentinel-mcp-server---generally-available-with-exciting-new-capabiliti/4470125
Survey: Microsoft Purview Retention Labels in Outlook Mobile (iOS/Andriod)
We need your input! Today, in Outlook for Windows, Outlook for the Web, and (currently rolling out) Outlook for Mac, end-users can manually apply Microsoft Purview retention labels and MRM personal tags to individual emails and non-default (user-created) folders. The Outlook and Data Lifecycle Management product groups are interested in learning from our customers how important that same functionality would be in Outlook for Mobile (iOS/Android). Please consider filling out and sharing the following survey to let us know how this feature would or would not be useful to you and your organization: https://aka.ms/RetentionLabels-OutlookMobile Please note that your responses will remain anonymous unless you choose to provide contact information at the end of the survey.
Getting Contextual Summary from SIT(Sensitive info types) via PowerShell cmd
Hi, I am using a PowerShell command(Export-ContentExplorerData) to extract data from an SIT. In the response, I am getting most of the data but I am interested in getting the matching primary element from Contextual summary(Content explorer) https://learn.microsoft.com/en-us/powershell/module/exchange/export-contentexplorerdataHelp! Sensitivity label applied to whole tenant mistakenly with Watermark
We create a sensitivity label to have a watermark to be applied on the files on where it assigned but accidentally or due to misconfiguration, the watermark applied to whole tenant and the files, need a solution to automatically removed these watermarks from the files wherever it is applied. Please assist, TIA... .New Blog | Embracing the Data Protection and Data Privacy Act
By Manny Sahota In an era where data breaches and privacy concerns are at the forefront of concerns, the Data Protection and Data Privacy (DPDP) Act 2023 emerges to enhance protection for individuals' personal information. This landmark legislation signifies a pivotal shift in the global data privacy landscape, imposing rigorous standards for data handling and compelling organizations to elevate their data protection measures. As we navigate the intricacies of compliance with the DPDP. Microsoft Compliance Manager emerges as a tool to help our customers meet regulatory obligations. Compliance regulations protect customers and the organizations they serve, and Microsoft Compliance Manager is here to help protect private data. Unpacking the DPDP Act 2023 The DPDP Act 2023 introduces a stringent legal framework aimed at safeguarding personal data against misuse, unauthorized access, and breaches. It mandates comprehensive data protection protocols, consent mechanisms for data collection, and stringent penalties for non-compliance, thereby setting a new benchmark for data privacy. This act underscores the importance of responsible data stewardship, emphasizing transparency, security, and the individual's right to privacy. For organizations, the enactment of the DPDP Act 2023 signifies a call to action—a mandate to reassess and fortify their data handling practices. It necessitates a holistic approach to data privacy, requiring robust governance, risk management, and compliance (GRC) frameworks to ensure adherence to the law. This is where the strategic deployment of Microsoft's Compliance Manager can make a substantial difference. Read the full post here: Embracing the Data Protection and Data Privacy Act: A Strategic Approach with Microsoft's ComplianceMeet Your New Cybersecurity Sidekick - Microsoft Security Copilot Agents
Imagine if your security team had a super-smart assistant that never sleeps, learns from every task, and helps stop cyber threats before they become disasters. That’s exactly what Microsoft’s new Security Copilot Agents are designed to do. Why Do We Need Them? Cyberattacks are getting sneakier and faster many now use AI to trick people or break into systems. In fact, 67% of phishing attacks in 2024 used AI. Meanwhile, security teams are drowning in alerts 66 per day on average and 73% of experts admit they’ve missed important ones. That’s where Security Copilot comes in. It’s like having an AI-powered teammate that helps you investigate threats, fix issues, and stay ahead of attackers. What Are Security Copilot Agents? Think of these agents as mini digital coworkers. They’re not just chatbots they’re smart, adaptable tools that: Learn from your feedback Work with your existing Microsoft security tools Help you make faster, better decisions Keep you in control while they handle the heavy lifting They’re built to be flexible and smart unlike traditional automation that breaks when things change. Real-World Examples of What They Do Here are a few of the agents already available: Phishing Triage Agent: Automatically checks if a suspicious email is a real threat or just spam. It explains its reasoning in plain language and learns from your feedback. Alert Triage Agents (in Microsoft Purview): Helps prioritize which security alerts matter most, so your team can focus on the big stuff first. Conditional Access Optimization Agent (in Microsoft Entra): Keeps an eye on who has access to what and flags any gaps in your security policies. Vulnerability Remediation Agent (in Microsoft Intune): Spots the most urgent software vulnerabilities and tells you what to fix first. Threat Intelligence Briefing Agent: Gives you a quick, customized report on the latest threats that could affect your organization. Even More Help from Partners Microsoft is also teaming up with other companies to build even more agents. For example: OneTrust helps with privacy breach responses. Tanium helps analysts make faster decisions on alerts. Fletch helps reduce alert fatigue by showing what’s most important. Aviatrix helps diagnose network issues like VPN or gateway failures. BlueVoyant: helps to assess your SOC and recommends improvements. Why It Matters These agents don’t just save time they help your team stay ahead of threats, reduce stress, and focus on what really matters. They’re like having a team of AI-powered interns who never get tired and are always learning. Learn More 📢 Microsoft Security Blog: Security Copilot Agents Launch 🎥 https://aka.ms/SecurityCopilotAgentsVideo
