Microsoft Purview | Share block at external users
Hello community. I have an issue with Microsoft Purview DLP policies. I am trying to create a policy that prevents documents from being shared through OneDrive with external users, while allowing certain exceptions. However, when I select the option "Block Access to external domains and users" and assign a specific email address to be blocked, it does not work. The configured email address is not being blocked. I was reviewing this with Copilot, and it mentioned that if the external user you are sharing with already exists in Entra ID, the tenant may treat the user differently (not necessarily as an external user). My external user exists in Entra ID as a Guest account. The external user is registered as follows: Displayname: User Name Userprincipalname: user.name_external.domain#EXT#@company.onmicrosoft.com User Type: Guest Has anyone else experienced this issue? I am sharing evidence of the policy configuration.
Insider Risk Level not being correctly picked up by DLP
I have two users currently with assigned Insider Risk levels, one elevated and one minor. I have taken the templated DLP policy (DSPM for AI - Block sensitive info from AI sites) which looks for sensitive information being pasted to generative AI sites, and applies a block if the user is an elevated risk user, and a block with override for a moderate/minor risk user (this was audit only originally). For each advanced DLP rule within that policy, I have a separate policy tip which shows so I know which Advanced DLP rule has been hit. However, I'm having some discrepancies with the correct insider risk level being identified by Purview and therefore the wrong advanced DLP rule is being applied. Testing examples: Logged into a Windows 11 PC with the account, and using Medium confidence UK NINO's I try pasting the content into ChatGPT: Elevated risk user: Block with Override Minor Risk user: Block with Override If I try the exact same scenario on a different PC, I can sometimes get to the point where even though its the same set of data, Purview allows me to paste it at after checking the data. Or in another scenario, I was getting both users hitting the "elevated risk" advanced DLP rule. The Devices are all showing as up to date sync wise with DLP policies, and the policy itself is showing as fully synced. Assigned insider risk levels: DLP Rules: Elevated: Moderate/Minor:Sensitivity Auto-labelling via Document Property
Why is this needed? Sensitivity labels are generally relevant within an organisation only. If a file is labelled within one environment and then moved to another environment, sensitivity label content markings may be visible, but by default, the applied sensitivity label will not be understood. This can lead to scenarios where information that has been generated externally is not adequately protected. My favourite analogy for these scenarios is to consider the parallels between receiving sensitive information and unpacking groceries. When unpacking groceries, you might sit your grocery bag on a counter or on the floor next to the pantry. You’ll likely then unpack each item, take a look at it and then decide where to place it. Without looking at an item to determine its correct location, you might place it in the wrong location. Porridge might be safe from the kids on the bottom shelf. If you place items that need to be protected, such as chocolate, on the bottom shelf, it’s not likely to last very long. So, I affectionately refer to information that hasn’t been evaluated as ‘porridge’, as until it has been checked, it will end up on the bottom shelf of the pantry where it is quite accessible. Label-based security controls, such as Data Loss Prevention (DLP) policies using conditions of ‘content contains sensitivity label’ will not apply to these items. To ensure the security of any contained sensitive information, we should look for potential clues to its sensitivity and then utilize these clues to ensure that the contained information is adequately protected - We take a closer look at the ‘porridge’, determine whether it’s an item that needs protection and if so, move it to a higher shelf in the pantry so that it’s out of reach for the kids. Effective use of Purview revolves around the use of ‘know your data’ strategies. We should be using as many methods as possible to try to determine the sensitivity of items. This can include the use of Sensitive Information Types (SITs) containing keyword or pattern-based classifiers, trainable classifiers, Exact Data Match, Document fingerprinting, etc. Matching items via SITs present in the items content can be problematic due to false positives. Keywords like ‘Sensitive’ or ‘Protected’ may be mentioned out of context, such as when referring to a classification or an environment. When classifications have been stamped via a property, it allows us to match via context rather than content. We don’t need to guess at an item’s sensitivity if another system has already established what the item’s classification is. These methods are much less prone to false positives. Why isn’t everyone doing this? Document properties are often not considered in Purview deployments. SharePoint metadata management seems to be a dying artform and most compliance or security resources completing Purview configurations don’t have this skill set. There’s also a lack of understanding of the relevance of checking for item properties. Microsoft haven’t helped as the documentation in this space is somewhat lacking and needs to be unpicked via some aligning DLP guidance (Create a DLP policy to protect documents with FCI or other properties). Many of these configurations will also be tied to regional requirements. Document properties being used by systems where I’m from, in Australia, will likely be very different to those used in other parts of the world. In the following sections, we’ll take a look at applicable use cases and walk through how to enable these configurations. Scenarios for use Labelling via document property isn’t for everyone. If your organisation is new to classification or you don’t have external partners that you collaborate with at higher sensitivity levels, then this likely isn’t for you. For those that collaborate heavily and have a shared classification framework, as is often seen across government, this is a must! This approach will also be highly relevant to multi-tenant organisations or conglomerates where information is regularly shared between environments. The following scenarios are examples of where this configuration will be relevant: 1. Migrating from 3 rd party classification tools If an item has been previously stamped by a 3 rd party classification tool, then evaluating its applied document properties will provide a clear picture of its security classification. These properties can then be used in service-based auto-labelling policies to effectively transition items from 3 rd party tools to Microsoft Purview sensitivity labels. As labels are applied to items, they will be brought into scope of label-based controls. 2. Detecting data spill Data spill is a term that is used to define situations where information that is of a higher than permitted security classification land in an environment. Consider a Microsoft 365 tenant that is approved for the storage of Official information but Top Secret files are uploaded to it. Document properties that align with higher than permitted classifications provide us with an almost guaranteed method of identifying spilled items. Pairing this document property with an auto-labelling policy allows for the application of encryption to lock unauthorized users out of the items. Tools like Content Explorer and eDiscovery can then be used to easily perform cleanup activities. If using document properties and auto-labelling for this purpose, keep in mind that you’ll need to create sensitivity labels for higher than permitted classifications in order to catch spilled items. These labels won’t impact usability as you won’t publish them to users. You will, however, need to publish them to a single user or break glass account so that they’re not ignored by auto-labelling. 3. Blocking access by AI tools If your organization was concerned about items with certain properties applied being accessed by generative AI tools, such as Copilot, you could use Auto-labelling to apply a sensitivity label that restricts EXTRACT permissions. You can find some information on this at Microsoft 365 Copilot data protection architecture | Microsoft Learn. This should be relevant for spilled data, but might also be useful in situations where there are certain records that have been marked via properties and which should not be Copilot accessible. 4. External Microsoft Purview Configurations Sensitivity labels are relevant internally only. A label, in its raw form, is essentially a piece of metadata with an ID (or GUID) that we stamp on pieces of information. These GUIDs are understood by your tenant only. If an item marked with a GUID shows up in another Microsoft 365 tenant, the GUID won’t correspond with any of that tenant’s labels or label-based controls. The art in Microsoft Purview lies in interpreting the sensitivity of items based on content markings and other identifiers, so that data security can be maintained. Document properties applied by Purview, such as ClassificationContentMarkingHeaderText are not relevant to a specific tenant, which makes them portable. We can use these properties to help maintain classifications as items move between environments. 5. Utilizing metadata applied by Records Management solutions Some EDRMS, Records or Content Management solutions will apply properties to items. If an item has been previously managed and then stamped with properties, potentially including a security classification, via one of these systems, we could use this information to inform sensitivity label application. 6. 3 rd party classification tools used externally Even if your organisation hasn’t been using 3rd party classification tools, you should consider that partner organisations, such as other Government departments, might be. Evaluating the properties applied by external organisations to items that you receive will allow you to extend protections to these items. If classification tools like Janus or Titus are used in your geography/industry, then you may want to consider checking for their properties. Regarding the use of auto-classification tools Some organisations, particularly those in Government, will have organisational policies that prevent the use of automatic classification capabilities. These policies are intended to ensure that each item is assessed by an actual person for risk of disclosure rather than via an automated service that could be prone to error. However, when auto-labelling is used to interpret and honour existing classifications, we are lowering rather than raising the risk profile. If the item’s existing classification (applied via property) is ignored, the item will be treated as porridge and is likely to be at risk. If auto-labelling is able to identify a high-risk item and apply the relevant label, it will then be within scope of Purview’s data security controls, including label-based DLP, groups and sites data out of place alerting, and potentially even item encryption. The outcome is that, through the use of auto-labelling, we are able to significantly reduce risk of inappropriate or unintended disclosure. Configuration Process Setting up document property-based auto-labelling is fairly straightforward. We need to setup a managed property and then utilize it an auto-labelling policy. Below, I've split this process into 6 steps: Step 1 – Prepare your files In order to make use of document properties, an item with the properties applied will first need to be indexed by SharePoint. SharePoint will record the properties as ‘crawled properties’, which we’ll then need to convert into ‘managed properties’ to make them useful. If you already have items with the relevant properties stored in SharePoint, then they are likely already indexed. If not, you’ll need to upload or create an item or items with the properties applied. For testing, you’ll want to create a file with each property/value combination so that you can confirm that your auto-labelling policies are all working correctly. This could require quite a few files depending on the number of properties you’re looking for. To kick off your crawled property generation though, you could create or upload a single file with the correct properties applied. For example: In the above, I’ve created properties for ClassificationContentMarkingHeaderText and ClassificationContentMarkingFooterText, which you’ll often see applied by Purview when an item has a sensitivity label content marking applied to it. I’ve also included properties to help identify items classified via JanusSeal, Titus and Objective. Step 2 – Index the files After creating or uploading your file, we then need SharePoint to index it. This should happen fairly quickly depending on the size of your environment. I'd expect to wait sometime between 10 minutes and 24 hrs. If you're not in a hurry, then I'd recommend just checking back the next day. You'll know when this has been completed when you head into SharePoint Admin > Search > Managed Search Schema > Crawled Properties and can find your newly indexed properties: Step 3 – Configure managed properties Next, the properties need to be configured as managed properties. To do this, go to SharePoint Admin > More features > Search > Managed Search Schema > Managed Properties. Create a new managed property and give it a name. Note that there are some character restrictions in naming, but you should be able to get it close to your document property name. Set the property’s type to text, select queryable and retrievable. Under ‘mappings to crawled properties’, choose add mapping, search for and select the property indexed from the file property. Note that the crawled property will have the same name as your document property, so there’s no need to browse through all of them: Repeat this so that you have a managed property for each document property that you want to look for. Step 4 – Configure Auto-labelling policies Next up, create some auto-labelling policies. You’ll need one for each label that you want to apply, not one per property as you can check multiple properties within the one auto-labelling policy. - From within Purview, head to Information Protection > Policies > Auto-labelling policies. - Create a new policy using the custom policy template. - Give your policy an appropriate name (e.g. Label PROTECTED via property). - Select the label that you want to apply (e.g. PROTECTED). - Select SharePoint based services (SharePoint and OneDrive). - Name your auto-labelling rules appropriately (e.g. SPO – Contains PROTECTED property) - Enter your conditions as a long string with property and value separated via a colon and multiple entries separated with a comma. For example: ClassificationContentMarkingHeaderText:PROTECTED,ClassificationContentMarkingFooterText:PROTECTED,Objective-Classification:PROTECTED,PMDisplay:PROTECTED,TitusSEC:PROTECTED Note that the properties that you are referencing are the Managed Property rather than the document property. This will be relevant if your managed property ended up having a different name due to character restrictions. After pasting in your string into the UI, the resultant rule should look something like this: When done, you can either leave your policy in simulation mode or save it and then turn it on from the auto-labelling policies screen. Just be aware of any potential impacts, such as accidently locking users out by automatically deploying a label with encryption configuration. You can reduce any potential impact by targeting your auto-labelling policy at a site or set of sites initially and then expanding its scope after testing. Step 5 - Test Testing your configuration will be as easy as uploading or creating a set of files with the relevant document properties in place. Once uploaded, you’ll need to give SharePoint some time to index the items and then the auto-labelling policy some time to apply sensitivity labels to them. To confirm label application, you can head to the document library where your test files are located and enable the sensitivity column. Files that have been auto-labelled will have their label listed: You could also check for auto-labelling activity in Purview via Activity explorer: Step 6 – Expand into DLP If you’ve spent the time setting up managed properties, then you really should consider capitalizing on them in your DLP configurations. DLP policy conditions can be configured in the same manner that we configured Auto-labelling in Step 3 above. The document property also gives us an anchor for DLP conditions that is independent of an item’s sensitivity label. You may wish to consider the following: DLP policies blocking external sharing of items with certain properties applied. This might be handy for situations where auto-labelling hasn’t yet labelled an item. DLP policies blocking the external sharing of items where the applied sensitivity label doesn’t match the applied document property. This could provide an indication of risky label downgrade. You could extend such policies into Insider Risk Management (IRM) by creating IRM policies that are aligned with the above DLP policies. This will allow for document properties to be considered in user risk calculation, which can inform controls like Adaptive Protection. Here's an example of a policy from the DLP rule summary screen that shows conditions of item contains a label or one of our configured document properties: Thanks for reading and I hope this article has been of use. If you have any questions or feedback, please feel free to reach out.
I just want to secure AI. DLP vs Info Protection vs DSPM vs Governance vs...
I'm with an MSP, and I've avoided Purview like the plague, because it seems to be suffering from the same 'made by marketing teams' 'strategy' the 365 documentation is. However, it's my understanding Purview policies are needed for Data control of Copilot. Here's my issue: all of these different 'solutions' sound like the exact same thing, but are pitched as if they are something different. i'm going to post a couple of descriptions for these 'solutions' to illustrate this. 'discover, label, and protect sensitive and business-critical info' 'make sure your organization can identify, monitor, and protect sensitive info across the expanding Microsoft 365 landscape' 'discover and secure all your sensitive data across Microsoft 365 and non-365 data sources' 'Discover, label, and protect sensitive and business-critical info across your multicloud data estate.' I genuinely do not have time to figure out what each of these 'solutions' are, then figure out their policies, then their giant library of settings (below)... It's not even clear to me what's active NOW, considering we never licensed Purview - but somehow have been roped into it. It SEEMS like these are all variations of marketing terms, which all point to 3-4 actual technical implementations in obscure ways. Can someone advise on the ACTUAL technical policies we want to target and enable? Or just give some clarity? I've never felt so overwhelmed or disconnected from Microsoft's environment. We just want to secure our tenant's AI usage.
Purview SDK
I've been spending quite a bit of time working with Purview APIs, The APIs themselves are fine, but after a while I realized I was writing the same authentication, pagination and relationship handling code over and over again. So instead of construction the same code from project to project, I turned it into a python package, and now it's available on PyPI pip install purview-unified-sdk Right now, the SDK supports most of the common operations, such as creating, retrieving, updating and deleting business domains, data products, glossary terms, objectives, key results and etc., It also make it much easier to work with relationships, add group id as a owner, navigate resources and retrieve metadata across the unified catalog. https://niki9001.github.io/purview-unified-sdk/ https://github.com/purview-unified-sdk Feel free to fork the project, submit a pull request or open an issue if you have ideas or suggestions
Feature Request: Extend Security Copilot inclusion (M365 E5) to M365 A5 Education tenants
Background At Ignite 2025, Microsoft announced that Security Copilot is included for all Microsoft 365 E5 customers, with a phased rollout starting November 18, 2025. This is a significant step forward for security operations. The gap Microsoft 365 A5 for Education is the academic equivalent of E5 — it includes the same core security stack: Microsoft Defender, Entra, Intune, and Purview. However, the Security Copilot inclusion explicitly covers only commercial E5 customers. There is no public roadmap or timeline for extending this benefit to A5 education tenants. Why this matters Education institutions face the same cybersecurity threats as commercial organizations — often with fewer dedicated security resources. The A5 license was positioned as the premium security offering for education. Excluding it from Security Copilot inclusion creates an inequity between commercial and education customers holding functionally equivalent license tiers. Request We would like Microsoft to: Confirm whether Security Copilot inclusion will be extended to M365 A5 Education tenants If yes, provide an indicative timeline If no, clarify the rationale and what alternative paths exist for education customers Are other EDU admins in the same situation? Would appreciate any upvotes or comments to help raise visibility with the product team.Understanding Microsoft 365 Copilot Risk Surface and Mitigations
Microsoft 365 Copilot acts on the access users already have. It does not grant new permissions — it is a force multiplier that makes existing access faster and easier to discover, aggregate, and act on across Microsoft 365. That speed and accessibility can also amplify existing security and governance gaps. In environments with overshared content, excessive permissions, or inconsistent governance, users may gain faster access to sensitive information than organizations realize. It’s a shift that carries important security implications organizations should understand before scaling deployment. Customers with Microsoft 365 E5 licensing may already have access to many of the tools that can help identify and reduce Copilot-related risk, but licensing alone does not reduce exposure. What’s often missing during early Copilot deployments is a clear understanding of the risk surface itself: what data is exposed, who can access it, and through which vectors.Secure the age of AI: Redefining trust, data and access
There is no question that AI is transforming the enterprise: changing how data moves, how decisions are made, and how risk takes shape. As agents access, interpret, and act on sensitive data, unmanaged AI use expands and traditional boundaries blur. Kicking off our series on Securing Data and Access in the Era of AI, Microsoft Entra VP of Product Sinead O’Donovan and Microsoft Purview GM of Product Maithili Dandige explain why legacy security models fall short in the age of AI—and why you need a strategy that brings together identity, access, and data protection. Want to adopt and enable AI innovation with greater control and confidence? Join us to learn how leading organizations are securing access, protecting data, and establishing trust for the next generation of AI-powered work. This session is part of Securing data and access in the era of AI with Microsoft Entra and Microsoft Purview. View the full series for more insights to help you move from experimenting with AI to deploying it at scale, securing sensitive data, access, and AI usage.Securing data and access in the era of AI with Microsoft Entra and Microsoft Purview
As organizations move from experimenting with AI to deploying it at scale, securing sensitive data, access, and AI usage has become mission critical. In this series, Microsoft experts will show how Microsoft Entra and Microsoft Purview help you: Protect sensitive data across networks, apps, and AI interactions Govern access for users, applications, and AI agents Reduce risk while enabling innovation at scale Whether you're shaping your security strategy or implementing controls, you’ll walk away with the guidance you need to secure data and access to AI as one unified strategy. Now on demand! Secure the age of AI: Redefining trust, data and access Data and identity controls for the browser and network Unlock AI agents without sacrificing security Not able to watch here due to organizational policies? Use a personal account or visit each session page for an option to view on LinkedIn.Unlock AI agents without sacrificing security
AI agents are reaching into mailboxes, files, line-of-business apps, and the open web on behalf of your users—and the business wants more of them, faster. To scale agents safely, your security teams need to be able to verify each agent, govern what it can access, and enforce clear boundaries across every interaction. Learn how Microsoft Entra helps you discover shadow AI agents, govern agent permissions, keep BYOD and endpoint-based agents in scope, and apply Conditional Access to AI prompts and responses. Then see how Microsoft Purview provides visibility into agent activity, strengthens runtime data protection, helps detect agentic risk, and supports auditability across local agents developed on GitHub Copilot CLI, Claude Code, OpenAI Codex, and OpenClaw. Walk away with practical ways to unlock AI agents while keeping access and data protection aligned with your enterprise security needs. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. If you are unable to watch the session here due to your organizational policies, you can also tune in on LinkedIn. This session is part of Securing data and access in the era of AI with Microsoft Entra and Microsoft Purview. View the full agenda for more insights to help you move from experimenting with AI to deploying it at scale, securing sensitive data, access, and AI usage.
