Secure and govern AI apps and agents with Microsoft Purview
The Microsoft Purview family is here to help you secure and govern data across third party IaaS and Saas, multi-platform data environment, while helping you meet compliance requirements you may be subject to. Purview brings simplicity with a comprehensive set of solutions built on a platform of shared capabilities, that helps keep your most important asset, data, safe. With the introduction of AI technology, Purview also expanded its data coverage to include discovering, protecting, and governing the interactions of AI apps and agents, such as Microsoft Copilots like Microsoft 365 Copilot and Security Copilot, Enterprise built AI apps like Chat GPT enterprise, and other consumer AI apps like DeepSeek, accessed through the browser. To help you view, investigate interactions with all those AI apps, and to create and manage policies to secure and govern them in one centralized place, we have launched Purview Data Security Posture Management (DSPM) for AI. You can learn more about DSPM for AI here with short video walkthroughs: Learn how Microsoft Purview Data Security Posture Management (DSPM) for AI provides data security and compliance protections for Copilots and other generative AI apps | Microsoft Learn Purview capabilities for AI apps and agents To understand our current set of capabilities within Purview to discover, protect, and govern various AI apps and agents, please refer to our Learn doc here: Microsoft Purview data security and compliance protections for Microsoft 365 Copilot and other generative AI apps | Microsoft Learn Here is a quick reference guide for the capabilities available today: Note that currently, DLP for Copilot and adhering to sensitivity label are currently designed to protect content in Microsoft 365. Thus, Security Copilot and Copilot in Fabric, along with Copilot studio custom agents that do not use Microsoft 365 as a content source, do not have these features available. Please see list of AI sites supported by Microsoft Purview DSPM for AI here Conclusion Microsoft Purview can help you discover, protect, and govern the prompts and responses from AI applications in Microsoft Copilot experiences, Enterprise AI apps, and other AI apps through its data security and data compliance solutions, while allowing you to view, investigate, and manage interactions in one centralized place in DSPM for AI. Follow up reading Check out the deployment guides for DSPM for AI How to deploy DSPM for AI - https://aka.ms/DSPMforAI/deploy How to use DSPM for AI data risk assessment to address oversharing - https://aka.ms/dspmforai/oversharing Address oversharing concerns with Microsoft 365 blueprint - aka.ms/Copilot/Oversharing Explore the Purview SDK Microsoft Purview SDK Public Preview | Microsoft Community Hub (blog) Microsoft Purview documentation - purview-sdk | Microsoft Learn Build secure and compliant AI applications with Microsoft Purview (video) References for DSPM for AI 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 Block Users From Sharing Sensitive Information to Unmanaged AI Apps Via Edge on Managed Devices (preview) | Microsoft Learn as part of Scenario 7 of Create and deploy a data loss prevention policy | 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 Explore the roadmap for DSPM for AI Public roadmap for DSPM for AI - Microsoft 365 Roadmap | Microsoft 365PMPur
Microsoft Authenticator Passkeys for Entra ID on unmanaged devices
Hello, has anyone successfully registered passkeys on an unmanaged phone in an organisation with device compliance policies? Use case is to provide a phishing-resistant MFA option via Authenticator app for logging into apps on their desktop. Users already have authenticator app on their phone and do number matching MFA. https://learn.microsoft.com/en-us/entra/identity/authentication/how-to-register-passkey-authenticator?tabs=iOS When I select "Create a passkey" - I need to log into my account. However I'm blocked from successful authentication because I have conditional access policies to require compliant devices. As my mobile phone is not enrolled into Intune, I never get to the step where the passkey is created and registered. Based on the constraints - it seems like passkeys cannot be used for unmanaged/BYOD devices for organisations that have device compliance policies. It can only be used for users who have enrolled their mobile phone. Looking to see if anyone has tips or different experience using passkeys on unmanaged mobile phones to log into Entra?
Sharing folders
Hello Can someone save me pease from going mad! I was able to share my folder between my old and new computers for few days after installing W11 and having trouble sharing. Now it suddenly stopped for no reason. I have not changed or played with anything. I went through all the advice available in Communities/videos/ microsoft support.... from ensuring internet the same, discovery on, advance sharing, permission.......etc. I did that several times in vain . For work reasons I need to work on different laptops in different rooms (same internet). I have a deadline and I need help please! Thank you MohgaKY"gmail.com
Windows 11 22H2 Upgrade from Windows 10 – Stuck at 48%
Trying to upgrade to Windows 11 22H2 keeps getting stuck at 48%. Tried so far: All Updates/Clean Boot/DISM/SFC/Chkdsk-F Saw this as an option. Has anyone tried it? If updates continually get stuck due to drivers, open Command Prompt as administrator and run: rundll32.exe pnpclean.dll,RunDLL_PnpClean /DRIVERS /MAXCLEAN Dell E6540 Latitude Windows 10 22H2 Processor Intel(R) Core(TM) i7-4800MQ CPU @ 2.70GHz, 2701 Mhz, 4 Core(s), 8 Logical Processor(s) 16GB Ram
How to open password protected PDF without password on Windows 11?
Hi everyone, I'm reaching out to the community for some assistance with a PDF issue I'm facing. I have a PDF document that is password protected, and unfortunately, I no longer have the password. I'm looking for a way to access this document without the password. Here's what I've tried so far: Checking if I've saved the password somewhere securely. Contacting the original sender of the PDF for the password (no luck there). Searching for basic software solutions that might help with this. My questions is: Are there any reliable tools or methods that can help in this situation without compromising the integrity of the document? I'd appreciate any guidance or advice the community can offer. Thanks in advance for your help!Sharing a Folder Issue
I have 4 computers and all share a folder off one of the machines. Recently power went out for a few hours and 2 of the coimputers stopped sharing the folder and kept popping up to enter the password. I did this to no avail. I have gone so far as to remove all passwords and tell the networking to allow people to access the shared folder without a password. Again it still pops up asking for a password. Here is what I have done Rebooted Removed all Passwords Made sure everything was on a private server Used CMD Prompt to make sure the account was unlocked Tried to share a completely different folder (same results) Rebooted the modem Made sure everything was updated. Tried resetting passwords to ones I know Checked Credentials and there was nothing there. Any help?Announcing AI Entity Analyzer in Microsoft Sentinel MCP Server - Public Preview
What is the Entity Analyzer? Assessing the risk of entities is a core task for SOC teams - whether triaging incidents, investigating threats, or automating response workflows. Traditionally, this has required building complex playbooks or custom logic to gather and analyze fragmented security data from multiple sources. With Entity Analyzer, this complexity starts to fade away. The tool leverages your organization’s security data in Sentinel to deliver comprehensive, reasoned risk assessments for any entity you encounter - starting with users and urls. By providing this unified, out-of-the-box solution for entity analysis, Entity Analyzer also enables the AI agents you build to make smarter decisions and automate more tasks - without the need to manually engineer risk evaluation logic for each entity type. And for those building SOAR workflows, Entity Analyzer is natively integrated with Logic Apps, making it easy to enrich incidents and automate verdicts within your playbooks. *Entity Analyzer is rolling out in Public Preview to Sentinel MCP server and within Logic Apps starting today. Learn more here. Deep Dive: How the User Analyzer is already solving problems for security teams Problem: Drowning in identity alerts Security operations centers (SOCs) are inundated with identity-based threats and alert noise. Triaging these alerts requires analyzing numerous data sources across sign-in logs, cloud app events, identity info, behavior analytics, threat intel, and more, all in tandem with each other to reach a verdict - something very challenging to do without a human in the loop today. So, we introduced the User Analyzer, a specialized analyzer that unifies, correlates, and analyzes user activity across all these security data sources. Government of Nunavut: solving identity alert overload with User Analyzer Hear the below from Arshad Sheikh, Security Expert at Government of Nunavut, on how they're using the User Analyzer today: How it's making a difference "Before the User Analyzer, when we received identity alerts we had to check a large amount of data related to users’ activity (user agents, anomalies, IP reputation, etc.). We had to write queries, wait for them to run, and then manually reason over the results. We attempted to automate some of this, but maintaining and updating that retrieval, parsing, and reasoning automation was difficult and we didn’t have the resources to support it. With the User Analyzer, we now have a plug-and-play solution that represents a step toward the AI-driven automation of the future. It gathers all the context such as what the anomalies are and presents it to our analysts so they can make quick, confident decisions, eliminating the time previously spent manually gathering this data from portals." Solving a real problem "For example, every 24 hours we create a low severity incident of our users who successfully sign-in to our network non interactively from outside of our GEO fence. This type of activity is not high-enough fidelity to auto-disable, requiring us to manually analyze the flagged users each time. But with User Analyzer, this analysis is performed automatically. The User Analyzer has also significantly reduced the time required to determine whether identity-based incidents like these are false positives or true positives. Instead of spending around 20 minutes investigating each incident, our analysts can now reach a conclusion in about 5 minutes using the automatically generated summary." Looking ahead "Looking ahead, we see even more potential. In the future, the User Analyzer could be integrated directly with Microsoft Sentinel playbooks to take automated, definitive action such as blocking user or device access based on the analyzer’s results. This would further streamline our incident response and move us closer to fully automated security operations." Want similar benefits in your SOC? Get started with our Entity Analyzer Logic Apps template here. User Analyzer architecture: how does it work? Let’s take a look at how the User Analyzer works. The User Analyzer aggregates and correlates signals from multiple data sources to deliver a comprehensive analysis, enabling informed actions based on user activity. The diagram below gives an overview of this architecture: Step 1: Retrieve Data The analyzer starts by retrieving relevant data from the following sources: Sign-In Logs (Interactive & Non-Interactive): Tracks authentication and login activity. Security Alerts: Alerts from Microsoft Defender solutions. Behavior Analytics: Surfaces behavioral anomalies through advanced analytics. Cloud App Events: Captures activity from Microsoft Defender for Cloud Apps. Identity Information: Enriches user context with identity records. Microsoft Threat Intelligence: Enriches IP addresses with Microsoft Threat Intelligence. Steps 2: Correlate signals Signals are correlated using identifiers such as user IDs, IP addresses, and threat intelligence. Rather than treating each alert or behavior in isolation, the User Analyzer fuses signals to build a holistic risk profile. Step 3: AI-based reasoning In the User Analyzer, multiple AI-powered agents collaborate to evaluate the evidence and reach consensus. This architecture not only improves accuracy and reduces bias in verdicts, but also provides transparent, justifiable decisions. Leveraging AI within the User Analyzer introduces a new dimension of intelligence to threat detection. Instead of relying on static signatures or rigid regex rules, AI-based reasoning can uncover subtle anomalies that traditional detection methods and automation playbooks often miss. For example, an attacker might try to evade detection by slightly altering a user-agent string or by targeting and exfiltrating only a few files of specific types. While these changes could bypass conventional pattern matching, an AI-powered analyzer understands the semantic context and behavioral patterns behind these artifacts, allowing it to flag suspicious deviations even when the syntax looks benign. Step 4: Verdict & analysis Each user is given a verdict. The analyzer outputs any of the following verdicts based on the analysis: Compromised Suspicious activity found No evidence of compromise Based on the verdict, a corresponding recommendation is given. This helps teams make an informed decision whether action should be taken against the user. *AI-generated content from the User Analyzer may be incorrect - check it for accuracy. User Analyzer Example Output See the following example output from the user analyzer within an incident comment: *IP addresses have been redacted for this blog* &CK techniques, a list of malicious IP addresses the user signed in from (redacted for this blog), and a few suspicious user agents the user's activity originated from. Conclusion Entity Analyzer in Microsoft Sentinel MCP server represents a leap forward in alert triage & analysis. By correlating signals and harnessing AI-based reasoning, it empowers SOC teams to act on investigations with greater speed, precision, and confidence.
Azure passowrd protection
We have a hybrid Azure infrastructure with an AD Connector installed on-prem and configured for PTA. We installed the password protection server and registered it with the Azure tenant, then deployed the DC agent on all domain controllers. Both the proxy and agents are operational. We published a few banned words to block in case anyone uses them. For testing, I changed my password to include one of the banned words. To my surprise, I was able to change the password. I checked the corresponding logon server, and the DC event viewer showed that the password was validated, but the banned word was in the password list that Azure set to enforce. Why is it not blocking the change?
