Retired: The Data Loss Prevention Ninja Training is here!
August 2025: New Ninja training can be found at https://aka.ms/DLPNinja RETIRED July 2025: Under Construction for new hosting location The Microsoft Purview Data Loss Prevention Ninja Training is here! We are very excited and pleased to announce this rendition of the Ninja Training Series. With all the other training out there, our team has been working diligently to get this content out there. There are several videos and resources out there and the overall purpose of the Microsoft Purview Data Loss Prevention Ninja training is to help you master this realm. We aim to get you up-to-date links to the community blogs, training videos, Interactive Guides, learning paths, and any other relevant documentation. To make it easier for you to start and advance your knowledge gradually without throwing you in deep waters, we split content in each offering into three levels: beginner, intermediate, and advanced. Please find the Microsoft Purview Information Protection Ninja Training here. In addition, after each section, there will be a knowledge check based on the training material you’d have just finished! Since there’s a lot of content, the goal of these knowledge checks is to help you determine if you were able to get a few of the major key takeaways. There’ll be a fun certificate issued at the end of the training: Disclaimer: This is NOT an official Microsoft certification and only acts as a way of recognizing your participation in this training content. Lastly, this training will be updated one to two times a year to ensure you all have the latest and greatest material! If there's any topic you'd like for us to include and/or have any thoughts on this training, please let us know what you think below in the comments! Legend/Acronyms (D) Microsoft Documentation (V) Video (B) Blog (P) PDF (S) Site (SBD) Scenario Based Demo (Video) (DAG) Deployment Acceleration Guide MIP Microsoft Information Protection (old terminology for Microsoft Purview Information Protection) AIP Azure Information Protection ULC Unified Labeling Client SIT Sensitive Information Type RBAC Role-based access control eDLP Endpoint DLP OME Office 365 Message Encryption EDM Exact Data Match DLP Data Loss Prevention SPO SharePoint Online OCR Optical character recognition MCAS Microsoft Cloud App Security (old terminology for Microsoft Defender for Cloud Apps) TC Trainable Classifiers ODSP OneDrive SharePoint EXO Exchange Online Microsoft Purview Data Loss Prevention (DLP) Microsoft’s DLP solution provides a broad range of capabilities to address the modern workplace and the unique challenges represented by these very different scenarios. One of the key investment areas is in providing a unified and comprehensive solution across the many different kinds of environments and services where sensitive data is stored, used or shared. This includes platforms native to Microsoft and also non-Microsoft services and apps. Beginner Training Public forums to contact the overall information protection team Yammer Tech Community Introducing Microsoft Purview (V) In this video, hear from Microsoft executives on this new product family and our vision for the future of data governance. Introduction to Microsoft Purview Data Loss Prevention? (V) In this video, you’ll find an overview on Microsoft Purview Data Loss Prevention. Quick overview on new Exchange DLP Predicates (V) This video provides a quick walk through on creating an Exchange DLP policy and a soft focus on the new predicates and actions. Microsoft Purview Information Protection Framework (D) Check out the above documentation to see how Microsoft Purview Information Protection uses 3 pillars to deploy an information protection solution. Protect Data with Zero Trust (LP) Zero Trust isn't a tool or product, it's an essential security strategy, with data at its core. Here, you'll learn how to identify and protect your data using a Zero Trust approach. Learn about data loss prevention (D) Learn about DLP basics and Microsoft Unified DLP and why it’s uniquely positioned to protect your data in the cloud. How to secure your data with Microsoft Security (V) The above video is a quick summary on how to protect your data. Microsoft Purview Information Protection and Data Loss Prevention Roadmap (S) Please check out the above site on the latest items on our public roadmap. Microsoft Purview Information Protection support for PDF and GitHub (V) and Ignite Conversation (V) The above videos walk through announcements regarding support for PDF and GitHub Microsoft Defender for Cloud Apps integration (D) Please visit the above documentation to learn more about how Microsoft Purview Information Protection integrates with Microsoft Defender for Cloud Apps Trainable Classifiers (D) Check out the documentation to create custom trainable classifiers. Retrain a classifier in content explorer (D) The above documentation shows you how to improve the performance of custom trainable classifiers by providing them more feedback. Explain data loss prevention reporting capabilities (LP) The above learning path walks you through reporting in the Microsoft Purview Compliance Portal. Review and analyze data loss prevention reports (LP) The above learning path walks you through analyzing reports in the Microsoft Purview Compliance Portal. Beginner Knowledge Check Intermediate Training Microsoft Compliance Extension for Chrome (B) aka Microsoft Purview Extension (D) Please check out the above blog and Microsoft Doc to understand what we’re doing to expand our DLP capabilities to Chrome. Microsoft Purview extension for Firefox (D) The above documentation details procedures to roll out the Microsoft Purview extension for Firefox. Data Loss Prevention and Endpoint DLP (V) This video details how Microsoft approaches information protection across Files, emails, Teams, endpoints and others. How DLP works between the Compliance portal and Exchange admin center (D) You can create a data loss prevention (DLP) policy in two different admin centers; the above document walks through the differences and similarities. Data Loss Prevention across endpoints, apps, & services | Microsoft Purview (V) This video walks you through how to protect sensitive data everywhere you create, view, and access information with one Data Loss Prevention policy in Microsoft Purview. Data Loss Prevention Policy Tips Reference Guide (D) and Quick Overview (V) Please check out the above documentation and short video on where we support policy tips. Create a DLP Policy for Microsoft 365 Online Services (IG) Please use the above interactive guide to see how to create DLP policies. Apply Microsoft Purview Endpoint DLP to Devices (IG) Please use the above interactive guide to see how to create Endpoint DLP policies. Sites for testing documentation (S) The above site details locations where you can get sample data. Scope of DLP Protection for Microsoft Teams (D) The above documentation walks through how DLP protection is applied differently to Teams entities. Manage DLP alerts in the Microsoft Purview compliance portal (LP) The above learning path walks you through managing DLP alerts. Endpoint activities you can monitor and best practices (LP) The above learning path walks you through Endpoint DLP activities and best practices. Troubleshoot and Manage Microsoft Purview Data Loss Prevention for your Endpoint Devices (B) The above blog goes through a quick guide to troubleshooting Endpoint DLP. Microsoft Purview DLP Interactive Guides (IG) Please visit the above home page to see the latest interactive guides walking you through DLP. Learn how to investigate Microsoft Purview Data Loss Prevention alerts in Microsoft 365 Defender (B) This blog is a step-by-step guided walkthrough of the Microsoft 365 Defender Analyst experience for Microsoft Purview Data Loss Prevention (DLP) incident management. Intermediate Knowledge Check Advanced Training Microsoft Defender for Cloud Apps and Data Loss Preventions (D) Please check out the documentation above detailing how the integration to Microsoft Defender for Cloud Apps further enhances your data loss prevention plan. Power BI: Learn about centralized data loss prevention policies (V) This video highlights DLP capabilities with Power BI. Take a unified and comprehensive approach to prevent data exfiltration with Microsoft (V) This video helps show how we can help you prevent unauthorized sharing, use, and transfer of sensitive information across your applications, services, endpoints, and on-premises file shares – all from a single place. Onboard macOS devices into Microsoft 365 (D), capability announcement (B), and additional screengrabs (B) Please use the documentation above to deploy macOS devices into Endpoint DLP and check out the blog to see a few screengrabs on how the user experience. Troubleshooting Guides (D) Resolve issues that affect DLP policy tips Changes to a data loss prevention policy don't take effect in Outlook 2013 in Microsoft 365 DLP policy tips in Security and Compliance Center don't work in OWA/Outlook How to troubleshoot data loss prevention policy tips in Exchange Online Protection in Microsoft 365 Please check out the below documentation to find guides on common issues. Securing data in an AI-first world with Microsoft Purview (B) The above blog details some new updates on AI with Microsoft Purview. Common questions on Microsoft Purview Data Loss Prevention for endpoints (B) This guide covers the top-of-mind FAQs on Microsoft Purview Data Loss Prevention for endpoints (referred to as Endpoint DLP in the blog). Guidance for investigating Microsoft Purview Data Loss Prevention incidents (B) This blog provides guidance for choosing the best investigation experience suited for your organization when using Microsoft Purview Data Loss Prevention. Data Loss Prevention: From on-premises to cloud (PDF) This whitepaper focuses on why you should move to cloud-native data loss prevention. The Microsoft Purview DLP Migration Assistant for Symantec (IG) Follow the above IG to get guidance on migrating from Symantec to Microsoft Purview DLP. Migrating from Windows Information Protection to Microsoft Purview (B) The above blog gives guidance on how to migrate from WIP to the Microsoft Purview stack. Insider Risk in Conditional Access | Microsoft Entra + Microsoft Purview Adaptive Protection (V) The above video goes through how to protect your organization from insider threats with Microsoft Entra's Conditional Access and Adaptive Protection in Microsoft Purview. Please check out this link for a blog with more details. (B) Protect sensitive data throughout its Copilot journey (B) The above details how the native integration enables organizations to leverage the power of GenAI when working with sensitive data as Copilot can understand and honor the controls such as encryption and provide comprehensive visibility into usage. Protect at the speed and scale of AI with Copilot for Security in Microsoft Purview (B) The above blog details the embedded experiences of Copilot for Security in Microsoft Purview (Communication Compliance, Data Loss Prevention, Insider Risk Management, and eDiscovery. Strengthen protection to mitigate data overexposure in GenAI tools with data classification/labeling (B) The blog above goes into detail on OCR, its cost, and how it goes into the AI Realm with Microsoft Purview Information Protection and Data Loss Prevention. Microsoft Purview Exact Data Match (EDM) support for multi-token corroborative evidence (B) The above blog goes into the new feature that improves the accuracy and effectiveness of EDM detection. Advanced Knowledge Check Once you’ve finished the training and the knowledge checks, please go to our attestation portal to generate your certificate; you'll see it in your inbox within 3-5 business days (Coming Soon). We hope you enjoy this training!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.Hacking Made Easy, Patching Made Optional: A Modern Cyber Tragedy
In today’s cyber threat landscape, the tools and techniques required to compromise enterprise environments are no longer confined to highly skilled adversaries or state-sponsored actors. While artificial intelligence is increasingly being used to enhance the sophistication of attacks, the majority of breaches still rely on simple, publicly accessible tools and well-established social engineering tactics. Another major issue is the persistent failure of enterprises to patch common vulnerabilities in a timely manner—despite the availability of fixes and public warnings. This negligence continues to be a key enabler of large-scale breaches, as demonstrated in several recent incidents. The Rise of AI-Enhanced Attacks Attackers are now leveraging AI to increase the credibility and effectiveness of their campaigns. One notable example is the use of deepfake technology—synthetic media generated using AI—to impersonate individuals in video or voice calls. North Korean threat actors, for instance, have been observed using deepfake videos and AI-generated personas to conduct fraudulent job interviews with HR departments at Western technology companies. These scams are designed to gain insider access to corporate systems or to exfiltrate sensitive intellectual property under the guise of legitimate employment. Social Engineering: Still the Most Effective Entry Point And yet, many recent breaches have begun with classic social engineering techniques. In the cases of Coinbase and Marks & Spencer, attackers impersonated employees through phishing or fraudulent communications. Once they had gathered sufficient personal information, they contacted support desks or mobile carriers, convincingly posing as the victims to request password resets or SIM swaps. This impersonation enabled attackers to bypass authentication controls and gain initial access to sensitive systems, which they then leveraged to escalate privileges and move laterally within the network. Threat groups such as Scattered Spider have demonstrated mastery of these techniques, often combining phishing with SIM swap attacks and MFA bypass to infiltrate telecom and cloud infrastructure. Similarly, Solt Thypoon (formerly DEV-0343), linked to North Korean operations, has used AI-generated personas and deepfake content to conduct fraudulent job interviews—gaining insider access under the guise of legitimate employment. These examples underscore the evolving sophistication of social engineering and the need for robust identity verification protocols. Built for Defense, Used for Breach Despite the emergence of AI-driven threats, many of the most successful attacks continue to rely on simple, freely available tools that require minimal technical expertise. These tools are widely used by security professionals for legitimate purposes such as penetration testing, red teaming, and vulnerability assessments. However, they are also routinely abused by attackers to compromise systems Case studies for tools like Nmap, Metasploit, Mimikatz, BloodHound, Cobalt Strike, etc. The dual-use nature of these tools underscores the importance of not only detecting their presence but also understanding the context in which they are being used. From CVE to Compromise While social engineering remains a common entry point, many breaches are ultimately enabled by known vulnerabilities that remain unpatched for extended periods. For example, the MOVEit Transfer vulnerability (CVE-2023-34362) was exploited by the Cl0p ransomware group to compromise hundreds of organizations, despite a patch being available. Similarly, the OpenMetadata vulnerability (CVE-2024-28255, CVE-2024-28847) allowed attackers to gain access to Kubernetes workloads and leverage them for cryptomining activity days after a fix had been issued. Advanced persistent threat groups such as APT29 (also known as Cozy Bear) have historically exploited unpatched systems to maintain long-term access and conduct stealthy operations. Their use of credential harvesting tools like Mimikatz and lateral movement frameworks such as Cobalt Strike highlights the critical importance of timely patch management—not just for ransomware defense, but also for countering nation-state actors. Recommendations To reduce the risk of enterprise breaches stemming from tool misuse, social engineering, and unpatched vulnerabilities, organizations should adopt the following practices: 1. Patch Promptly and Systematically Ensure that software updates and security patches are applied in a timely and consistent manner. This involves automating patch management processes to reduce human error and delay, while prioritizing vulnerabilities based on their exploitability and exposure. Microsoft Intune can be used to enforce update policies across devices, while Windows Autopatch simplifies the deployment of updates for Windows and Microsoft 365 applications. To identify and rank vulnerabilities, Microsoft Defender Vulnerability Management offers risk-based insights that help focus remediation efforts where they matter most. 2. Implement Multi-Factor Authentication (MFA) To mitigate credential-based attacks, MFA should be enforced across all user accounts. Conditional access policies should be configured to adapt authentication requirements based on contextual risk factors such as user behavior, device health, and location. Microsoft Entra Conditional Access allows for dynamic policy enforcement, while Microsoft Entra ID Protection identifies and responds to risky sign-ins. Organizations should also adopt phishing-resistant MFA methods, including FIDO2 security keys and certificate-based authentication, to further reduce exposure. 3. Identity Protection Access Reviews and Least Privilege Enforcement Conducting regular access reviews ensures that users retain only the permissions necessary for their roles. Applying least privilege principles and adopting Microsoft Zero Trust Architecture limits the potential for lateral movement in the event of a compromise. Microsoft Entra Access Reviews automates these processes, while Privileged Identity Management (PIM) provides just-in-time access and approval workflows for elevated roles. Just-in-Time Access and Risk-Based Controls Standing privileges should be minimized to reduce the attack surface. Risk-based conditional access policies can block high-risk sign-ins and enforce additional verification steps. Microsoft Entra ID Protection identifies risky behaviors and applies automated controls, while Conditional Access ensures access decisions are based on real-time risk assessments to block or challenge high-risk authentication attempts. Password Hygiene and Secure Authentication Promoting strong password practices and transitioning to passwordless authentication enhances security and user experience. Microsoft Authenticator supports multi-factor and passwordless sign-ins, while Windows Hello for Business enables biometric authentication using secure hardware-backed credentials. 4. Deploy SIEM and XDR for Detection and Response A robust detection and response capability is vital for identifying and mitigating threats across endpoints, identities, and cloud environments. Microsoft Sentinel serves as a cloud-native SIEM that aggregates and analyses security data, while Microsoft Defender XDR integrates signals from multiple sources to provide a unified view of threats and automate response actions. 5. Map and Harden Attack Paths Organizations should regularly assess their environments for attack paths such as privilege escalation and lateral movement. Tools like Microsoft Defender for Identity help uncover Lateral Movement Paths, while Microsoft Identity Threat Detection and Response (ITDR) integrates identity signals with threat intelligence to automate response. These capabilities are accessible via the Microsoft Defender portal, which includes an attack path analysis feature for prioritizing multicloud risks. 6. Stay Current with Threat Actor TTPs Monitor the evolving tactics, techniques, and procedures (TTPs) employed by sophisticated threat actors. Understanding these behaviours enables organizations to anticipate attacks and strengthen defenses proactively. Microsoft Defender Threat Intelligence provides detailed profiles of threat actors and maps their activities to the MITRE ATT&CK framework. Complementing this, Microsoft Sentinel allows security teams to hunt for these TTPs across enterprise telemetry and correlate signals to detect emerging threats. 7. Build Organizational Awareness Organizations should train staff to identify phishing, impersonation, and deepfake threats. Simulated attacks help improve response readiness and reduce human error. Use Attack Simulation Training, in Microsoft Defender for Office 365 to run realistic phishing scenarios and assess user vulnerability. Additionally, educate users about consent phishing, where attackers trick individuals into granting access to malicious apps. Conclusion The democratization of offensive security tooling, combined with the persistent failure to patch known vulnerabilities, has significantly lowered the barrier to entry for cyber attackers. Organizations must recognize that the tools used against them are often the same ones available to their own security teams. The key to resilience lies not in avoiding these tools, but in mastering them—using them to simulate attacks, identify weaknesses, and build a proactive defense. Cybersecurity is no longer a matter of if, but when. The question is: will you detect the attacker before they achieve their objective? Will you be able to stop them before reaching your most sensitive data? Additional read: Gartner Predicts 30% of Enterprises Will Consider Identity Verification and Authentication Solutions Unreliable in Isolation Due to AI-Generated Deepfakes by 2026 Cyber security breaches survey 2025 - GOV.UK Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations | Microsoft Security Blog MOVEit Transfer vulnerability Solt Thypoon Scattered Spider SIM swaps Attackers exploiting new critical OpenMetadata vulnerabilities on Kubernetes clusters | Microsoft Security Blog Microsoft Defender Vulnerability Management - Microsoft Defender Vulnerability Management | Microsoft Learn Zero Trust Architecture | NIST tactics, techniques, and procedures (TTP) - Glossary | CSRC https://learn.microsoft.com/en-us/security/zero-trust/deploy/overviewUsing Copilot in Fabric with Confidence: Data Security, Compliance & Governance with DSPM for AI
Introduction As organizations embrace AI to drive innovation and productivity, ensuring data security, compliance, and governance becomes paramount. Copilot in Microsoft Fabric offers powerful AI-driven insights. But without proper oversight, users can misuse copilot to expose sensitive data or violate regulatory requirements. Enter Microsoft Purview’s Data Security Posture Management (DSPM) for AI—a unified solution that empowers enterprises to monitor, protect, and govern AI interactions across Microsoft and third-party platforms. We are excited to announce the general availability of Microsoft Purview capabilities for Copilot in Fabric, starting with Copilot in Power BI. This blog explores how Purview DSPM for AI integrates with Copilot in Fabric to deliver robust data protection and governance and provides a step-by-step guide to enable this integration. Capabilities of Purview DSPM for AI As organizations adopt AI, implementing data controls and Zero Trust approach is crucial to mitigate risks like data oversharing and leakage, and potential non-compliant usage in AI. We are excited to announce Microsoft Purview capabilities for Copilot in Fabric, starting with Copilot for Power BI, By combining Microsoft Purview and Copilot for Power BI, users can: Discover data risks such as sensitive data in user prompts and responses in Activity Explorer and receive recommended actions in their Microsoft Purview DSPM for AI Reports to reduce these risks. DSPM for AI Activity Explorer DSPM for AI Reports If you find Copilot in Fabric actions in DSPM for AI Activity Explorer or reports to be potentially inappropriate or malicious, you can look for further information in Insider Risk Management (IRM), through an eDiscovery case, Communication Compliance (CC), or Data Lifecycle Management (DLM). 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 or unethical AI usage detection with Purview Communication Compliance. Purview Audit provides a detailed log of user and admin activity within Copilot in Fabric, enabling organizations to track access, monitor usage patterns, and support forensic investigations. Purview eDiscovery enables legal and investigative teams to identify, collect, and review Copilot in Fabric interactions as part of case workflows, supporting defensible investigations Communication Compliance helps detect potential policy violations or risky behavior in administrator interactions, enabling proactive monitoring and remediation for Copilot in Fabric Data Lifecycle Management allows teams to automate the retention, deletion, and classification of Copilot in Fabric data—reducing storage costs and minimizing risk from outdated or unnecessary information Steps to Enable the Integration To use DSPM for AI from the Microsoft Purview portal, you must have the following prerequisites, Activate Purview Audit which requires user to have the role of Entra Compliance Admin or Entra Global admin to enable Purview Audit. More details on DSPM pre-requisites can be found here, Considerations for deploying Microsoft Purview Data Security Posture Management (DSPM) for AI | Microsoft Learn To enable Purview DSPM for AI for Copilot for Power BI, Step 1: Enable DSPM for AI Policies Navigate to Microsoft Purview DSPM for AI. Enable the one-click policy: “DSPM for AI – Capture interactions for Copilot experiences”. Optionally enable additional policies: Detect risky AI usage Detect unethical behavior in AI apps These policies can be configured in the Microsoft Purview DSPM for AI portal and tailored to your organization’s risk profile. Step 2: Monitor and Act Use DSPM for AI Reports and Activity Explorer to monitor AI interactions. Apply IRM, DLM, CC and eDiscovery actions as needed. Purview Roles and Permissions Needed by Users To manage and operate DSPM for AI effectively, assign the following roles: Role Responsibilities Purview Compliance Administrator Full access to configure policies and DSPM for AI setup Purview Security Reader View reports, dashboards, policies and AI Activity Content Explorer Content Viewer Additional Permission to view the actual prompts and responses on top of the above permissions More details on Purview DSPM for AI Roles & permissions can be found here, Permissions for Microsoft Purview Data Security Posture Management for AI | Microsoft Learn Purview Costs Microsoft Purview now offers a combination of entitlement-based (per-user-per-month) and Pay-As-You-Go (PAYG) pricing models. The PAYG model applies to a broader set of Purview capabilities—including Insider Risk Management, Communication Compliance, eDiscovery, and other data security and governance solutions—based on copilot for Power BI usage volume or complexity. Purview Audit logging of Copilot for Power BI activity remains included at no additional cost as part of Microsoft 365 E5 licensing. This flexible pricing structure ensures that organizations only pay for what they use as data flows through AI models, networks, and applications. For further details, please refer to this blog: New Purview pricing options for protecting AI apps and agents | Microsoft Community Hub Conclusion Microsoft Purview DSPM for AI is a game-changer for organizations looking to adopt AI responsibly. By integrating with Copilot in Fabric, it provides a comprehensive framework to discover, protect, and govern AI interactions—ensuring compliance, reducing risk, and enabling secure innovation. Whether you're a Fabric Admin, compliance admin or security admin, enabling this integration is a strategic step toward building a secure, AI-ready enterprise. Additional resources Use Microsoft Purview to manage data security & compliance for Microsoft Copilot in Fabric | Microsoft Learn How to deploy Microsoft Purview DSPM for AI to secure your AI apps 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 Considerations for deploying Microsoft Purview Data Security Posture Management (DSPM) for AI | Microsoft Learn Learn about Microsoft Purview billing models | Microsoft Learn
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-contentexplorerdataSecure 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 Coplot 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 365PMPurMicrosoft Purview Powering Data Security and Compliance for Security Copilot
Microsoft Purview provides Security and Compliance teams with extensive visibility into admin actions within Security Copilot. It offers tools for enriched users and data insights to identify, review, and manage Security Copilot interaction data in DSPM for AI. Data security and compliance administrators can also utilize Purview’s capabilities for data lifecycle management and information protection, advanced retention, eDiscovery, and more. These features support detailed investigations into logs to demonstrate compliance within the Copilot tenant. Prerequisites Please refer to the prerequisites for Security Copilot and DSPM for AI in the Microsoft Learn Docs. Key Capabilities and Features Heightened Context and Clarity As organizations adopt AI, implementing data controls and a Zero Trust approach is essential to mitigate risks like data oversharing, leakage, and non-compliant usage. Microsoft Purview, combined with Data Security Posture Management (DSPM) for AI, empowers security and compliance teams to manage these risks across Security Copilot interactions. With this integration, organizations can: Discover data risks by identifying sensitive information in user prompts and responses. Microsoft Purview surfaces these insights in the DSPM for AI dashboard and recommends actions to reduce exposure. Identify risky AI usage using Microsoft Purview Insider Risk Management to investigate behaviors such as inadvertent sharing of sensitive data or to detect suspicious activity within Security Copilot usage. These capabilities provide heightened visibility into how AI is used across the organization, helping teams proactively address potential risks before they escalate. Compliance and Governance Building on this visibility, organizations can take action using Microsoft Purview’s integrated compliance and governance solutions. Here are some examples of how teams are leveraging these capabilities to govern Security Copilot interactions: Audit provides a detailed log of user and admin activity within Security Copilot, enabling organizations to track access, monitor usage patterns, and support forensic investigations. eDiscovery enables legal and investigative teams to identify, collect, and review Security Copilot interactions as part of case workflows, supporting defensible investigations. Communication Compliance helps detect potential policy violations or risky behavior in administrator interactions, enabling proactive monitoring and remediation. Data Lifecycle Management allows teams to automate the retention, deletion, and classification of Security Copilot data—reducing storage costs and minimizing risk from outdated or unnecessary information. Together, these tools provide a comprehensive governance framework that supports secure, compliant, and responsible AI adoption across the enterprise. Getting Started Enable Purview Audit for Security Copilot Sign into your Copilot tenant at https://securitycopilot.microsoft.com/, and with the Security Administrator permissions, navigate to the Security Copilot owner settings and ensure Audit logging is enabled. Microsoft Purview To start using DSPM for AI and the Microsoft Purview capabilities, please complete the following steps to get set up and then feel free to experiment yourself. Navigate to Purview (Purview.Microsoft.com) and ensure you have adequate permissions to access the different Purview solutions as described here. DSPM for AI Select the DSPM for AI “Solution” option on the left-most navigation. Go to the policies or recommendations tab turn on the following: a. “DSPM for AI – Capture interactions for Copilot Experiences”: Captures prompts and responses for data security posture and regulatory compliance from Security Copilot and other Copilot experiences. b. “Detect Risky AI Usage”: Helps to calculate user risk by detecting risky prompts and responses in Copilot experiences. c. “Detect unethical behavior in AI apps”: Detects sensitive info and inappropriate use of AI in prompts and responses in Copilot experiences. To begin reviewing Security Copilot usage within your organization and identifying interactions that contain sensitive information, select Reports from the left navigation panel. a. The "Sensitive interactions per AI app" report shows the most common sensitive information types used in Security Copilot interactions and their frequency. For instance, this tenant has a significant amount of IT and IP Address information within these interactions. Therefore, it is important to ensure that all sensitive information used in Security Copilot interactions is utilized for legitimate workplace purposes and does not involve any malicious or non-compliant use of Security Copilot. b. “Top unethical AI interactions” will show an overview of any potentially unsafe or inappropriate interactions with AI apps. In this case, Security Copilot only has seven potentially unsafe interactions that included unauthorized disclosure and regulatory collusion. c. “Insider risk severity per AI app” shows the number of high risk, medium risk, low risk and no risk users that are interacting with Security Copilot. In this tenant, there are about 1.9K Security Copilot users, but very few of them have an insider risk concern. d. To check the interaction details of this potentially risky activity, head over to Activity Explorer for more information. 5. In Activity Explorer, you should filter the App to Security Copilot. You will also have the option to filter based on the user risk level and sensitive information type. To identify the highest risk behaviors, filter for users with a medium to high risk level or those associated with the most sensitive information types. a. Once you have filtered, you can start looking through the activity details for more information like the user details, the sensitive information types, the prompt and response data, and more. b. Based on the details shown, you may decide to investigate the activity and the user further. To do so, we have data security investigation and governance tools. Data Security Investigations and Governance If you find Security Copilot actions in DSPM for AI Activity Explorer to be potentially inappropriate or malicious, you can look for further information in Insider Risk Management (IRM), through an eDiscovery case, Communication Compliance (CC), or Data Lifecycle Management (DLM). Insider Risk Management By enabling the quick policy in DSPM for AI to monitor risky Copilot usage, alerts will start appearing in IRM. Customize this policy based on your organization's risk tolerance by adjusting triggering events, thresholds, and indicators for detected activity. Examine the alerts associated with the "DSPM for AI – Detect risky AI usage" policy, potentially sorting them by severity from high to low. For these alerts, you will find a User Activity scatter plot that provides insights into the activities preceding and following the user's engagement with a risky prompt in Security Copilot. This assists the Data Security administrator in understanding the necessary triage actions for this user/alert. After thoroughly investigating these details and determining whether the activity was malicious or an inadvertent insider risk, appropriate actions can be taken, including issuing a user warning, resolving the case, sharing the case with an email recipient, or escalating the case to eDiscovery for further investigation. eDiscovery To identify, review and manage your Security Copilot logs to support your investigations, use the eDiscovery tool. Here are the steps to take in eDiscovery: a. Create an eDiscovery Case b. Create a new search c. In Search, go to condition builder and select Add conditions -> KeyQL d. Enter the query as: - KQL Equal (ItemClass=IPM.SkypeTeams.Message.Copilot.Security.SecurityCopilot) e. Run the query f. Once completed, add the search to a review set (Button at the top) g. In the review set, view details of the Security Copilot conversation Communication Compliance In Communication Compliance, like IRM, you can investigate details around the Security Copilot interactions. Specifically, in CC, you can determine if these interactions contained non-compliant usage of Security Copilot or inappropriate text. After identifying the sentiment of the Security Copilot communication, you can take action by resolving the alert, sending a warning notice to the user, escalating the alert to a reviewer, or escalating the alert for investigation, which will create a new eDiscovery case. Data Lifecycle Management For regulatory compliance or investigation purposes, navigate to Data Lifecycle Management to create a new retention policy for Security Copilot activities. a. Provide a friendly name for the retention policy and select Next b. Skip Policy Scope section for this validation c. Select “Static” type of retention policy and select Next d. Choose “Microsoft Copilot Experiences” to apply retention policy to Security Copilot interactions Billing Model Microsoft Purview audit logging of Security Copilot activity remains included at no additional cost as part of Microsoft 365 E5 licensing. However, Microsoft Purview now offers a combination of entitlement-based (per-user-per-month) and Pay-As-You-Go (PAYG) pricing models. The PAYG model applies to a broader set of Purview capabilities—including Insider Risk Management, Communication Compliance, eDiscovery, and other data security and governance solutions—based on usage volume or complexity. This flexible pricing structure ensures that organizations only pay for what they use as data flows through AI models, networks, and applications. For further details, please refer to this Microsoft Security Community Blog: New Purview pricing options for protecting AI apps and agents | Microsoft Community Hub Looking Ahead By following these steps, organizations can leverage the full potential of Microsoft Purview to enhance the security and compliance of their Security Copilot interactions. This integration not only provides peace of mind but also empowers organizations to manage their data more effectively. Please reach out to us if you have any questions or additional requirements. Additional Resources Use Microsoft Purview to manage data security & compliance for Microsoft Security Copilot | Microsoft Learn How to deploy Microsoft Purview DSPM for AI to secure your AI apps 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 Considerations for deploying Microsoft Purview Data Security Posture Management (DSPM) for AI | Microsoft Learn Learn about Microsoft Purview billing models | Microsoft LearnHelp! 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... .
