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 LearnSecure 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 365PMPurStep by Step: 2-Tier PKI Lab
Purpose of this blog Public Key Infrastructure (PKI) is the backbone of secure digital identity management, enabling encryption, digital signatures, and certificate-based authentication. However, neither setting up a PKI nor management of certificates is something most IT pros do on a regular basis and given the complexity and vastness of the subject it only makes sense to revisit the topic from time to time. What I have found works best for me is to just set up a lab and get my hands dirty with the topic that I want to revisit. One such topic that I keep coming back to is PKI - be it for creating certificate templates, enrolling clients, or flat out creating a new PKI itself. But every time I start deploying a lab or start planning a PKI setup, I end up spending too much time sifting through the documentations and trying to figure out why my issuing certificate authority won't come online! To make my life easier I decided to create a cheatsheet to deploy a simple but secure 2-tier PKI lab based on industry best practices that I thought would be beneficial for others like me, so I decided to polish it and make it into a blog. This blog walks through deploying a two-tier PKI hierarchy using Active Directory Certificate Services (AD CS) on Windows Server: an offline Root Certification Authority (Root CA) and an online Issuing Certification Authority (Issuing CA). We’ll cover step-by-step deployment and best practices for securing the root CA, conducting key ceremonies, and maintaining Certificate Revocation Lists (CRLs). Overview: Two-Tier PKI Architecture and Components In a two-tier PKI, the Root CA sits at the top of the trust hierarchy and issues a certificate only to the subordinate Issuing CA. The Root CA is kept offline (disconnected from networks) to protect its private key and is typically a standalone CA (not domain-joined). The Issuing CA (sometimes called a subordinate or intermediate CA) is kept online to issue certificates to end-entities (users, computers, services) and is usually an enterprise CA integrated with Active Directory for automation and certificate template support. Key components: Offline Root CA: A standalone CA, often on a workgroup server, powered on only when necessary (initial setup, subordinate CA certificate signing, or periodic CRL publishing). By staying offline, it is insulated from network threats. Its self-signed certificate serves as the trust anchor for the entire PKI. The Root CA’s private key must be rigorously protected (ideally by a Hardware Security Module) because if the root is compromised, all certificates in the hierarchy are compromised. Online Issuing CA: An enterprise subordinate CA (domain-joined) that handles day-to-day certificate issuance for the organization. It trusts the Root CA (via the root’s certificate) and is the one actually responding to certificate requests. Being online, it must also be secured, but its key is kept online for operations. Typically, the Issuing CA publishes certificates and CRLs to Active Directory and/or HTTP locations for clients to download. The following diagram shows the simplified view of this implementations: The table below summarizes the roles and differences: Aspect Offline Root CA Online Issuing CA Role Standalone Root CA (workgroup) Enterprise Subordinate CA (domain member) Network Connectivity Kept offline (powered off or disconnected when not issuing) Online (running continuously to serve requests) Usage Signs only one certificate (the subordinate CA’s cert) and CRLs Issues end-entity certificates (users, computers, services) Active Directory Not a member of AD domain; doesn’t use templates or auto-enrollment Integrated with AD DS; uses certificate templates for streamlined issuance Security Extremely high: physically secured, limited access, often protected by HSM Very High: server hardened, but accessible on network; HSM recommended for private key CRL Publication Manual. Admin must periodically connect, generate, and distribute CRL. Delta CRLs usually disabled. Automatic. Publishes CRLs to configured CDP locations (AD DS, HTTP) at scheduled intervals. Validity Period Longer (e.g. 5-10+ years for the CA certificate) to reduce frequency of renewal. Shorter (e.g. 2 years) to align with organizational policy; renewed under the root when needed. In this lab setup, we will create a Contoso Root CA (offline) and a Contoso Issuing CA (online) as an example. This mirrors real-world best practices which is to "deploy a standalone offline root CA and an online enterprise subordinate CA”. Deploying the Offline Root CA Setting up the offline Root CA involves preparing a dedicated server, installing AD CS, configuring it as a root CA, and then securing it. We’ll also configure certificate CDP/AIA (CRL Distribution Point and Authority Information Access) locations so that issued certificates will point clients to the correct locations to fetch the CA’s certificate and revocation list. Step 1: Prepare the Root CA Server (Offline) Provision an isolated server: Install a Windows Server OS (e.g., Windows Server 2022) on the machine designated to be the Root CA. Preferably on a portable enterprise grade physical server that can be stored in a safe. Do not join this server to any domain – it should function in a Workgroup to remain independent of your AD forest. System configuration: Give the server a descriptive name (e.g., ROOTCA) and assign a static IP (even though it will be offline, a static IP helps when connecting it temporarily for management). Install the latest updates and security patches while it’s still able to go online. Lock down network access: Once setup is complete, disable or unplug network connections. If the server must remain powered on for any reason, ensure all unnecessary services/ports are disabled to minimize exposure. In practice, you will keep this server shut down or physically disconnected except when performing CA maintenance. Step 2: Install the AD CS Role on the Root CA Add the Certification Authority role: On the Root CA server, open Server Manager and add the Active Directory Certificate Services role. During the wizard, select the Certification Authority role service (no need for web enrollment or others on the root). Proceed through the wizard and complete the installation. You can also install the CA role and management tools via PowerShell: Install-WindowsFeature AD-Certificate -IncludeManagementToolsThis Role Services: Choose Certification Authority. Setup Type: Select Standalone CA (since this root CA is not domain-joined). CA Type: Select Root CA. Private Key: Choose “Create a new private key.” Cryptography: If using an HSM, select the HSM’s Cryptographic Service Provider (CSP) here; otherwise use default. Choose a strong key length (e.g., 2048 or 4096 bits) and a secure hash algorithm (SHA-256 or higher). CA Name: Provide a common name for the CA (e.g., “Contoso Root CA”). This name will appear in issued certificates as the Issuer. Avoid using a machine DNS name here for security – pick a name without revealing the server’s actual hostname. Validity Period: Set a long validity (e.g., 10 years) for the root CA’s self-signed certificate. A decade is common for enterprise roots, reducing how often you must touch the offline CA for renewal. Database: Specify locations for the CA database and logs (the defaults are fine for a lab). Review settings and complete the configuration. This process will generate the root CA’s key pair and self-signed certificate, establishing the Root CA.Post-install configuration: After the binary installation, click Configure Active Directory Certificate Services (a notification in Server Manager). In the configuration wizard: You can also perform this configuration via PowerShell in one line: Install-AdcsCertificationAuthority ` -CAType StandaloneRootCA ` -CryptoProviderName "YourHSMProvider" ` -HashAlgorithmName SHA256 -KeyLength 2048 ` -CACommonName "Contoso Root CA" ` -ValidityPeriod Years -ValidityPeriodUnits 10 This would set up a standalone Root CA named "Contoso Root CA" with a 2048-bit key on an HSM provider, valid for 10 years. Step 3: Integrate an HSM (Optional but Recommended) If your lab has a Hardware Security Module, use it to secure the Root CA’s keys. Using an HSM provides a dedicated, tamper-resistant storage for CA private keys and can further protect against key compromise. To integrate: Install the HSM vendor’s software and drivers on the Root CA server. Initialize the HSM and create a security world or partition as per the vendor instructions. Before or during the CA configuration (Step 2 above), ensure the HSM is ready to generate/store the key. When running the AD CS configuration, select the HSM’s CSP/KSP for the cryptographic provider so that the CA’s private key is generated on the HSM. Secure any HSM admin tokens or smartcards. For a root CA, you might employ M of N key splits – requiring multiple key custodians to collaborate to activate the HSM or key – as part of the key ceremony (discussed later). (If an HSM is not available, the root key will be stored on the server’s disk. At minimum, protect it with a strong admin passphrase when prompted, and consider enabling the option to require administrator interaction (e.g., a password) whenever the key is accessed.) Step 4: Configure CA Extensions (CDP/AIA) It’s critical to configure how the Root CA publishes its certificate and revocation list, since the root is offline and cannot use Active Directory auto-publishing. Open the Certification Authority management console (certsrv.msc), right-click the CA name > Properties, and go to the Extensions tab. We will set the CRL Distribution Points (CDP) and Authority Information Access (AIA) URLs: CRL Distribution Point (CDP): This is where certificates will tell clients to fetch the CRL for the Root CA. By default, a standalone CA might have a file:// path or no HTTP URL. Click Add and specify an HTTP URL that will be accessible to all network clients, such as: http://<IssuingCA_Server>/CertEnroll/<CaName><CRLNameSuffix><DeltaCRLAllowed>.crl For example, if your issuing CA’s server name is ISSUINGCA.contoso.local, the URL might be http://issuingca.contoso.local/CertEnroll/Contoso%20Root%20CA.crl This assumes the Issuing CA (or another web server) will host the Root CA’s CRL in the CertEnroll directory. Check the boxes for “Include in the CDP extension of issued certificates” and “Include in all CRLs. Clients use this to find Delta CRLs” (you can uncheck the delta CRL publication on the root, as we won’t use delta CRLs on an offline root). Since the root CA won’t often revoke its single issued cert (the subordinate CA), delta CRLs aren’t necessary. Note: If your Active Directory is in use and you want to publish the Root CA’s CRL to AD, you can also add an ldap:///CN=... path and check “Publish in Active Directory”. However, publishing to AD from an offline CA must be done manually using the following command when the root is temporarily connected. certutil -dspublish Many setups skip LDAP for offline roots and rely on HTTP distribution. Authority Information Access (AIA): This is where the Root CA’s certificate will be published for clients to download (to build certificate chains). Add an HTTP URL similarly, for example: http://<IssuingCA_Server>/CertEnroll/<ServerDNSName>_<CaName><CertificateName>.crt This would point to a copy of the Root CA’s certificate that will be hosted on the issuing CA web server. Check “Include in the AIA extension of issued certificates”. This way, any certificate signed by the Root CA (like your subordinate CA’s cert) contains a URL where clients can fetch the Root CA’s cert if they don’t already have it. After adding these, remove any default entries that are not applicable (e.g., LDAP if the root isn’t going to publish to AD, or file paths that won’t be used by clients). These settings ensure that certificates issued by the Root CA (in practice, just the subordinate CA’s certificate) will carry the correct URLs for chain building and revocation checking. Step 5: Back Up the Root CA and Issue the Subordinate Certificate With the Root CA configured, we need to issue a certificate for the Issuing CA (subordinate). We’ll perform that in the next section from the Issuing CA’s side via a request file. Before taking the root offline, ensure you: Back up the CA’s private key and certificate: In the Certification Authority console, or via the CA Backup wizard, export the Root CA’s key pair and CA certificate. Protect this backup (store it offline in a secure location, e.g., on encrypted removable media in a safe). This backup is crucial for disaster recovery or if the Root CA needs to be migrated or restored. Save the Root CA Certificate: You will need the Root CA’s public certificate (*.crt) to distribute to other systems. Have it exported (Base-64 or DER format) for use on the Issuing CA and for clients. Initial CRL publication: Manually publish the first CRL so that it can be distributed. Open an elevated Command Prompt on the Root CA and run: certutil -crl This generates a new CRL file (in the CA’s configured CRL folder, typically %windir%\system32\CertSrv\CertEnroll). Take that CRL file and copy it to the designated distribution point (for example, to the CertEnroll directory on the Issuing CA’s web server, as per the HTTP URL configured). If using Active Directory for CRL distribution, you would also publish it to AD now (e.g., certutil -dspublish -f RootCA.crl on a domain-connected machine). In most lab setups, copying to an HTTP share is sufficient. With these tasks done, the Root CA is ready. At this point, disconnect or power off the Root CA and store it securely – it should remain offline except when it’s absolutely needed (like publishing a new CRL or renewing the subordinate CA’s certificate in the far future). Keeping the root CA offline maximizes its security by minimizing exposure to compromise. Best Practices for Securing the Root CA: The Root CA is the trust anchor, so apply stringent security practices: Physical security: Store the Root CA machine in a locked, secure location. If it’s a virtual machine, consider storing it on a disconnected hypervisor or a USB drive locked in a safe. Only authorized PKI team members should have access. An offline CA should be treated like crown jewels – offline CAs should be stored in secure locations. Minimal exposure: Keep the Root CA powered off and disconnected when not in use. It should not be left running or connected to any network. Routine operations (like issuing end-entity certs) should never involve the root. Admin access control: Limit administrative access on the Root CA server. Use dedicated accounts for PKI administration. Enable auditing on the CA for any changes or issuance events. No additional roles or software: Do not use the Root CA server for any other function (no web browsing, no email, etc.). Fewer installed components means fewer potential vulnerabilities. Protect the private key: Use an HSM if possible; if not, ensure the key is at least protected by a strong password and consider splitting knowledge of that password among multiple people (so no single person can activate the CA). Many organizations opt for an offline root key ceremony (see below) to generate and handle the root key with multiple witnesses and strict procedures. Keep system time and settings consistent: If the Root CA is powered off for long periods, ensure its clock is accurate whenever it is started (to avoid issuing a CRL or certificate with a wrong date). Don’t change the server name or CA name after installation (doing so invalidates issued certs). Periodic health checks: Even though offline, plan to turn on the Root CA at a secure interval (e.g., semi-annually or annually) to perform tasks like CRL publishing and system updates. Make sure to apply OS security updates during these maintenance windows, as offline does not mean immune to vulnerabilities (especially if it ever connects to a network for CRL publication or uses removable media). Deploying the Online Issuing CA Next, set up the Issuing CA server which will actually issue certificates to end entities in the lab. This server will be domain-joined (if using AD integration) and will obtain its CA certificate from the Root CA we just configured. Step 1: Prepare the Issuing CA Server Provision the server: Install Windows Server on a new machine (or VM) that will be the Issuing CA. Join this server to the Active Directory domain (e.g., Contoso.local). Being an enterprise CA, it needs domain membership to publish templates and integrate with AD security groups. Rename the server to something descriptive like ISSUINGCA for clarity. Assign a static IP and ensure it can communicate on the network. IIS for web enrollment (optional): If you plan to use the Web Enrollment or Certificate Enrollment Web Services, ensure IIS is installed. (The AD CS installation wizard can add it if you include those role services.) For this guide, we will include the Web Enrollment role so that the CertEnroll directory is set up for hosting certificate and CRL files. Step 2: Install AD CS Role on Issuing CA On the Issuing CA server, add the Active Directory Certificate Services role via Server Manager or PowerShell. This time, select both Certification Authority and Certification Authority Web Enrollment role services (Web Enrollment will set up the HTTP endpoints for certificate requests if needed). For example, using PowerShell: Install-WindowsFeature AD-Certificate, ADCS-Web-Enrollment -IncludeManagementTools After installation, launch the AD CS configuration wizard: Role Services: Choose Certification Authority (and Web Enrollment if prompted). Setup Type: Select Enterprise CA (since this CA will integrate with AD DS). CA Type: Select Subordinate CA (this indicates it will get its cert from an existing root CA). Private Key: Choose “Create a new private key” (we’ll generate a new key pair for this CA). Cryptography: If using an HSM here as well, select the HSM’s CSP/KSP for the issuing CA’s key. Otherwise, choose a strong key length (2048+ bits, SHA256 or better for hash). CA Name: Provide a name (e.g., “Contoso Issuing CA”). This name will appear as the Issuer on certificates it issues. Certificate Request: The wizard will ask how you want to get the subordinate CA’s certificate. Choose “Save a certificate request to file”. Specify a path, e.g., C:\CertRequest\issuingCA.req. The wizard will generate a request file that we need to take to the Root CA for signing. (Since our Root CA is offline, this file transfer might be via secure USB or a network share when the root is temporarily online.) CA Database: Choose locations or accept defaults for the certificate DB and logs. Finish the configuration wizard, which will complete pending because the CA doesn’t have a certificate yet. The AD CS service on this server won’t start until we import the issued cert from the root. Step 3: Integrate HSM on Issuing CA (Optional) If available, repeat the HSM setup on the Issuing CA: install HSM drivers, initialize it, and generate/secure the key for the subordinate CA on the HSM. Ensure you chose the HSM provider during the above configuration so that the issuing CA’s private key is stored in the HSM. Even though this CA is online, an HSM still greatly enhances security by protecting the private key from extraction. The issuing CA’s HSM may not require multiple custodians to activate (as it needs to run continuously), but should still be physically secured. Step 4: Obtain the Issuing CA’s Certificate from the Root CA Now we have a pending request (issuingCA.req) for the subordinate CA. To get its certificate: Transport the request to the Root CA: Copy the request file to the offline Root CA (via secure means – e.g., formatted new USB stick). Start up the Root CA (in a secure, offline setting) and open the Certification Authority console. Submit the request on Root CA: Right-click the Root CA in the CA console -> All Tasks -> Submit new request, and select the .req file. The request will appear in the Pending Requests on the root. Issue the subordinate CA certificate: Find the pending request (it will list the Issuing CA’s name). Right-click and choose All Tasks > Issue. The subordinate CA’s certificate is now issued by the Root CA. Export the issued certificate: Still on the Root CA, go to Issued Certificates, find the newly issued subordinate CA cert (you can identify it by the Request ID or by the name). Right-click it and choose Open or All Tasks > Export to get the certificate in a file form. If using the console’s built-in “Export” it might only allow binary; alternatively use the certutil command: certutil -dup <RequestID> .\ContosoIssuingCA.cer or simply open and copy to file. Save the certificate as issuingCA.cer. Also make sure you have a copy of the Root CA’s certificate (if not already done). Publish Root CA cert and CRL as needed: Before leaving the Root CA, you may also want to ensure the Root’s own certificate and latest CRL are available to the issuing CA and clients. If not already done in Step 5 of root deployment, export the Root CA cert (DER format) and copy the CRL file. You might use certutil -crl again if some time has passed since initial CRL. Now take the issuingCA.cer file (and root cert/CRL files) and move them back to the Issuing CA server. Step 5: Install the Issuing CA’s Certificate and Complete Configuration On the Issuing CA server (which is still waiting for its CA cert): Install the subordinate CA certificate: In Server Manager or the Certification Authority console on the Issuing CA, there should be an option to “Install CA Certificate” (if the AD CS configuration wizard is still open, it will prompt for the file; or otherwise, in the CA console right-click the CA name > All Tasks > Install CA Certificate). Provide the issuingCA.cer file obtained from the root. This will install the CA’s own certificate and start the CA service. The Issuing CA is now operational as a subordinate CA. Alternatively, use PowerShell: certutil -installcert C:\CertRequest\issuingCA.cer This installs the cert and associates it with the pending key. Trust the Root CA certificate: Because the Issuing CA is domain-joined, when you install the subordinate cert, it might automatically place the Root CA’s certificate in the Trusted Root Certification Authorities store on that server (and possibly publish it to AD). If not, you should manually install the Root CA’s certificate into the Trusted Root CA store on the Issuing CA machine (using the Certificates MMC or certutil -addstore -f Root rootCA.cer). This step prevents any “chain not trusted” warnings on the Issuing CA and ensures it trusts its parent. In an enterprise environment, you would also distribute the root certificate to all client machines (e.g., via Group Policy) so that they trust the whole chain. Import Root CRL: Copy the Root CA’s CRL (*.crl file) to the Issuing CA’s CRL distribution point location (e.g., C:\Windows\System32\CertSrv\CertEnroll\ if that’s the directory served by the web server). This matches the HTTP URL we configured on the root. Place the CRL file there and ensure it is accessible (the Issuing CA’s IIS might need to serve static .crl files; often, if Web Enrollment is installed, the CertEnroll folder is under C:\Inetpub\wwwroot\CertEnroll). At this point, the subordinate CA and any client hitting the HTTP URL can retrieve the root’s CRL. The subordinate CA is now fully established. It holds a certificate issued by the Root CA (forming a complete chain of trust), and it’s ready to issue end-entity certificates. Step 6: Configure Issuing CA Settings and Start Services Start the Certificate Services: If the CA service (CertSvc) isn’t started automatically, start or restart it. On PowerShell: Restart-Service certsvc The CA should show as running in the CA console with the name “Contoso Issuing CA” (or your chosen name). Configure Certificate Templates: Because this is an Enterprise CA, it can utilize certificate templates stored in Active Directory to simplify issuing common cert types (user auth, computer auth, web server SSL, etc.). By default, some templates (e.g., User, Computer) are available but not issued. In the Certification Authority console under Certificate Templates, you can choose which templates to issue (e.g., right-click > New > Certificate Template to Issue, then select templates like “User” or “Computer”). This lab guide doesn’t require specific templates but know that only Enterprise CAs can use templates. Templates define the policies and settings (cryptography, enrollment permissions, etc.) for issued certificates. Ensure you enable only the templates needed and configure their permissions appropriately (e.g., allow the appropriate groups to enroll). Set CRL publishing schedule: The Issuing CA will automatically publish its own CRL (for certificates it issues) at intervals. You can adjust the CRL and Delta CRL publication interval in the CA’s Properties > CRL Period. A common practice is a small base CRL period (e.g., 1 week or 2 weeks) for issuing CAs, because they may revoke user certs more frequently; and enable Delta CRLs (published daily) for timely revocation information. Make sure the CDP/AIA for the Issuing CA itself are properly configured too (the wizard usually sets LDAP and HTTP locations, but verify in the Extensions tab). In a lab, the default settings are fine. Web Enrollment (if installed): You can verify the web enrollment by browsing to http://<IssuingCA>/certsrv. This web UI allows browser-based certificate requests. It’s a legacy interface mostly, but for testing it can be used if your clients aren’t domain-joined or if you want a manual request method. In modern use, the Certificate Enrollment Web Service/Policy roles or auto-enrollment via Group Policy are preferred for remote and automated enrollment. At this stage, your PKI is operational: the Issuing CA trusts the offline Root CA and can issue certificates. The Root CA can be kept offline with confidence that the subordinate will handle all regular work. Validation and Testing of the PKI It’s important to verify that the PKI is configured correctly: Check CA status: On the Issuing CA, open the Certification Authority console and ensure no errors. Verify that the Issuing CA’s certificate shows OK (no red X). On the Root CA (offline most of the time), you can use the Pkiview.msc snap-in (Microsoft PKI Health Tool) on a domain-connected machine to check the health of the PKI. This tool will show if the CDPs/AIA are reachable and if certificates are properly published. Trust chain on clients: On a domain-joined client PC, the Root CA certificate should be present in the Trusted Root Certification Authorities store (if the Issuing CA was installed as Enterprise CA, it likely published the root cert to AD automatically; you can also distribute it via Group Policy or manually). The Issuing CA’s certificate should appear in the Intermediate Certification Authorities store. This establishes the chain of trust. If not, import the root cert into the domain’s Group Policy for Trusted Roots. A quick test: on a client, run certutil -config "ISSUINGCA\\Contoso Issuing CA" -ping to see if it can contact the CA (or use the Certification Authority MMC targeting the issuing CA). Enroll a test certificate: Try to enroll for a certificate from the Issuing CA. For instance, from a domain-joined client, use the Certificates MMC (in Current User or Computer context) and initiate a certificate request for a User or Computer certificate (depending on templates issued). If auto-enrollment is configured via Group Policy for a template, you can simply log on a client and see if it automatically receives a certificate. Alternatively, use the web enrollment page or certreq command to submit a request. The request should be approved and a certificate issued by "Contoso Issuing CA". After enrollment, inspect the issued certificate: it should chain up to "Contoso Root CA" without errors. Ensure that the certificate’s CDP points to the URL we set (and try to browse that URL to see the CRL file), and that the AIA points to the root cert location. Revocation test (optional): To test CRL behavior, you could revoke a test certificate on the Issuing CA (using the CA console) and publish a new CRL. On the client, after updating the CRL, the revoked certificate should show as revoked. For the Root CA, since it shouldn’t issue end-entity certs, you wouldn’t normally revoke anything except potentially the subordinate CA’s certificate (which would be a drastic action in case of compromise). By issuing a test certificate and validating the chain and revocation, you confirm that your two-tier PKI lab is functioning correctly. Maintaining the PKI: CRLs, Key Ceremonies, and Security Procedures Deploying the PKI is only the beginning. Proper maintenance and operational procedures are crucial to ensure the PKI remains secure and reliable over time. Periodic CRL Updates for the Offline Root: The Root CA’s CRL has a defined validity period (set during configuration, often 6 or 12 months for offline roots). Before the CRL expires, the Root CA must be brought online (in a secure environment) to issue a new CRL. It’s recommended to schedule CRL updates periodically (e.g., semi-annually) to prevent the CRL from expiring. An expired CRL can cause certificate chain validation to fail, potentially disrupting services. Typically, organizations set the offline root CRL validity so that publishing 1-2 times a year is sufficient. When the time comes: Start the Root CA (ensuring the system clock is correct). Run certutil -crl to issue a fresh CRL. Distribute the new CRL: copy it to the HTTP CDP location (overwrite the old file) and, if applicable, use certutil -dspublish -f RootCA.crl to update it in Active Directory. Verify that the new CRL’s next update date is extended appropriately (e.g., another 6 months out). Clients and the Issuing CA will automatically pick up the new CRL when checking for revocation. (The Issuing CA, if configured, might cache the root CRL and need a restart or certutil -setreg ca\CRLFlags +CRLF_REVCHECK_IGNORE_OFFLINE tweak if the root CRL expires unexpectedly. Keeping the schedule prevents such issues.) Issuing CA CRL and OCSP: The Issuing CA’s CRLs are published automatically as it is online. Ensure the IIS or file share hosting the CRL is accessible. Optionally, consider setting up an Online Responder (OCSP) for real-time status checking, especially if CRLs are large or you need faster revocation information. OCSP is another AD CS role service that can be configured on the issuing CA or another server to answer certificate status queries. This might be beyond a simple lab, but it’s worth mentioning for completeness. Key Ceremonies and Documentation: For production environments (and good practice even in labs), formalize the process of handling CA keys in a Key Ceremony. A key ceremony is a carefully controlled process for activities like generating the Root CA’s key pair, installing the CA, and signing subordinate certificates. It often involves multiple people to ensure no single person has unilateral control (principle of dual control) and to witness the process. Best practices for a Root CA key ceremony include: Advance Planning: Create a step-by-step script of the ceremony tasks. Include who will do what, what materials are needed (HSMs, installation media, backup devices, etc.), and the order of operations. Multiple trusted individuals present: Roles might include a Ceremony Administrator (leads the process), a Security Officer (responsible for HSM or key material handling), an Auditor (to observe and record), etc. This prevents any one person from manipulating the process and increases trust. Secure environment: Conduct the ceremony in a secure location (e.g., a locked room) free of recording devices or unauthorized personnel. Ensure the Root CA machine is isolated (no network), and ideally that BIOS/USB access controls are in place to prevent any malware. Generate keys with proper controls: If using an HSM, initialize and generate the key with the required number of key custodians each providing part of the activation material (e.g., smartcards or passphrases). Immediately back up the HSM partition or key to secure media (requiring the same custodians to restore). Sign subordinate CA certificate: As part of the ceremony, once the root key is ready, sign the subordinate’s request. This might also be a witnessed step. Document every action: Write down each command run, each key generated, serial numbers of devices used, and have all participants sign an acknowledgment of the outcomes. Also record the fingerprints of the generated Root CA certificate and any subordinate certificate to ensure they are exactly as expected. Secure storage: After the ceremony, store the Root CA machine (if it’s a laptop or VM) and HSM tokens in a tamper-evident bag or safe. The idea is to make it evident if someone tries to access the root outside of an authorized ceremony. While a full key ceremony might be overkill for a small lab, understanding these practices is important. Even in a lab, you can simulate some aspects (for learning), like documenting the procedure of taking the root online to sign the request and then locking it away. These practices greatly increase the trust in a production PKI by ensuring transparency and accountability for critical operations. Backup and Recovery Plans: Both CAs’ data should be regularly backed up: For the Root CA: since it’s rarely online, backup after any change. Typically, you’d back up the CA’s private key and certificate once (right after setup or any renewal). Store this securely offline (separate from the server itself). Also back up the CA database if it ever issues more than one cert (for root it might not issue many). For the Issuing CA: schedule automated backups of the CA database and private key. You can use the built-in certutil -backup or Windows Server Backup (which is aware of the AD CS database). Keep backups secure and test restoration procedures. Having a documented recovery procedure for the CA is crucial for continuity. Also consider backup of templates and any scripts. Maintain spare hardware or VMs in case you need to restore the CA on new hardware (especially for the root, having a procedure to restore on a new machine if the original is destroyed). Security maintenance: Apply OS updates to the CAs carefully. For the offline root, patch it offline if possible (offline servicing or connecting it briefly to a management network). For the issuing CA, treat it as a critical infrastructure server: limit its exposure (firewall it so only required services are reachable), monitor its event logs (enable auditing for Certificate Services events, which can log each issuance and revocation), and employ anti-malware tools with caution (whitelisting the CA processes to avoid interference). Also, periodically review the CA’s configuration and certificate templates to ensure they meet current security standards (for example, deprecate any weak cryptography or adjust validity periods if needed). By following these maintenance steps and best practices, your two-tier PKI will remain secure and trustworthy over time. Remember that PKI is not “set and forget” – it requires operational diligence, but the payoff is a robust trust infrastructure for your organization’s security. Additional AD CS Features and References Active Directory Certificate Services provides more capabilities than covered in this basic lab. Depending on your needs, you might explore: Certificate Templates: We touched on templates; they are a powerful feature on Enterprise CAs to enforce standardized certificate settings. Administrators can create custom templates for various use cases (SSL, S/MIME email, code signing) and control enrollment permissions. Understanding template versions and permissions is key for enterprise deployments. (Refer to Microsoft’s documentation on Certificate template concepts in Windows Server for details on how templates work and can be customized.) Web Services for Enrollment: In scenarios with remote or non-domain clients, AD CS offers the Certificate Enrollment Web Service (CES) and Certificate Enrollment Policy Web Service (CEP) role services. These allow clients to fetch enrollment policy information and request certificates over HTTP or HTTPS, even when not connected directly to the domain. They work with the certificate templates to enable similar auto-enrollment experiences over the web. See Microsoft’s guides on the Certificate Enrollment Web Service overview and Certificate Enrollment Policy Web Service overview for when to use these. Network Device Enrollment Service (NDES): This AD CS role service implements the Simple Certificate Enrollment Protocol (SCEP) to allow devices like routers, switches, and mobile devices to obtain certificates from the CA without domain credentials. NDES acts as a proxy (Registration Authority) between devices and the CA, using one-time passwords for authentication. If you need to issue certificates to network equipment or MDM-managed mobile devices, NDES is the solution. Microsoft Docs provide a Network Device Enrollment Service(NDES) overview and even details on using a policy module with NDES for advanced scenarios (like customizing how requests are processed or integrating with custom policies). Online Responders (OCSP): As mentioned, an Online Responder can be configured to answer revocation status queries more efficiently than CRLs, especially useful if your CRLs grow large or you have high-volume certificate validation (VPNs, etc.). AD CS’s Online Responder role service can be installed on a member server and configured with the OCSP Response Signing certificate from your Issuing CA. Monitoring and Auditing: Windows Servers have options to audit CA events. Enabling auditing can log events such as certificate issuance, revocation, or changes to the CA configuration. These logs are important in enterprise PKI to track who did what (for compliance and security forensics). Also, tools like the PKI Health Tool (pkiview.msc) and PowerShell cmdlets (like Get-CertificationAuthority, Get-CertificationAuthorityCertificate) can help monitor the health and configuration of your CAs. Conclusion By following this guide, you have set up a secure two-tier PKI environment consisting of an offline Root CA and an online Issuing CA. This design, which uses an offline root, is considered a security best practice for enterprise PKI deployments because it reduces the risk of your root key being compromised. With the offline Root CA acting as a hardened trust anchor and the enterprise Issuing CA handling day-to-day certificate issuance, your lab PKI can issue certificates for various purposes (HTTPS, code signing, user authentication, etc.) in a way that models real-world deployments. As you expand this lab or move to production, always remember that PKI security is as much about process as technology. Applying strict controls to protect CA keys, keeping software up to date, and monitoring your PKI’s health are all part of the journey. For further reading and official guidance, refer to these Microsoft documentation resources: 📖 AD CS PKI Design Considerations: PKI design considerations using Active Directory Certificate Services in Windows Server helps in planning a PKI deployment (number of CAs, hierarchy depth, naming, key lengths, validity periods, etc.). This is useful to read when adapting this lab design to a production environment. It also covers configuring CDP/AIA and why offline roots usually don’t need delta CRLs. 📖 AD CS Step-by-Step Guides: Microsoft’s Test Lab Guide Test Lab Guide: Deploying an AD CS Two-Tier PKI Hierarchy walk through a similar scenario.How to deploy Microsoft Purview DSPM for AI to secure your AI apps
Microsoft Purview Data Security Posture Management (DSPM for AI) is designed to enhance data security for the following AI applications: Microsoft Copilot experiences, including Microsoft 365 Copilot. Enterprise AI apps, including ChatGPT enterprise integration. Other AI apps, including all other AI applications like ChatGPT consumer, Microsoft Copilot, DeepSeek, and Google Gemini, accessed through the browser. In this blog, we will dive into the different policies and reporting we have to discover, protect and govern these three types of AI applications. Prerequisites Please refer to the prerequisites for DSPM for AI in the Microsoft Learn Docs. Login to the Purview portal To begin, start by logging into Microsoft 365 Purview portal with your admin credentials: In the Microsoft Purview portal, go to the Home page. Find DSPM for AI under solutions. 1. Securing Microsoft 365 Copilot Be sure to check out our blog on How to use the DSPM for AI data assessment report to help you address oversharing concerns when you deploy Microsoft 365 Copilot. Discover potential data security risks in Microsoft 365 Copilot interactions In the Overview tab of DSPM for AI, start with the tasks in “Get Started” and Activate Purview Audit if you have not yet activated it in your tenant to get insights into user interactions with Microsoft Copilot experiences In the Recommendations tab, review the recommendations that are under “Not Started”. Create the following data discovery policy to discover sensitive information in AI interactions by clicking into it. Detect risky interactions in AI apps - This public preview Purview Insider Risk Management policy helps calculate user risk by detecting risky prompts and responses in Microsoft 365 Copilot experiences. Click here to learn more about Risky AI usage policy. With the policies to discover sensitive information in Microsoft Copilot experiences in place, head back to the Reports tab of DSPM for AI to discover any AI interactions that may be risky, with the option to filter to Microsoft Copilot Experiences, and review the following for Microsoft Copilot experiences: Total interactions over time (Microsoft Copilot) Sensitive interactions per AI app Top unethical AI interactions Top sensitivity labels references in Microsoft 365 Copilot Insider Risk severity Insider risk severity per AI app Potential risky AI usage Protect sensitive data in Microsoft 365 Copilot interactions From the Reports tab, click on “View details” for each of the report graphs to view detailed activities in the Activity Explorer. Using available filters, filter the results to view activities from Microsoft Copilot experiences based on different Activity type, AI app category and App type, Scope, which support administrative units for DSPM for AI, and more. Then drill down to each activity to view details including the capability to view prompts and response with the right permissions. To protect the sensitive data in interactions for Microsoft 365 Copilot, review the Not Started policies in the Recommendations tab and create these policies: Information Protection Policy for Sensitivity Labels - This option creates default sensitivity labels and sensitivity label policies. If you've already configured sensitivity labels and their policies, this configuration is skipped. Protect sensitive data referenced in Microsoft 365 Copilot - This guides you through the process of creating a Purview Data Loss Prevention (DLP) policy to restrict the processing of content with specific sensitivity labels in Copilot interactions. Click here to learn more about Data Loss Prevention for Microsoft 365 Copilot. Protect sensitive data referenced in Copilot responses - Sensitivity labels help protect files by controlling user access to data. Microsoft 365 Copilot honors sensitivity labels on files and only shows users files they already have access to in prompts and responses. Use Data assessments to identify potential oversharing risks, including unlabeled files. Stay tuned for an upcoming blog post on using DSPM for AI data assessments! Use Copilot to improve your data security posture - Data Security Posture Management combines deep insights with Security Copilot capabilities to help you identify and address security risks in your org. Once you have created policies from the Recommendations tab, you can go to the Policies tab to review and manage all the policies you have created across your organization to discover and safeguard AI activity in one centralized place, as well as edit the policies or investigate alerts associated with those policies in solution. Note that additional policies not from the Recommendations tab will also appear in the Policies tab when DSPM for AI identifies them as policies to Secure and govern all AI apps. Govern the prompts and responses in Microsoft 365 Copilot interactions Understand and comply with AI regulations by selecting “Guided assistance to AI regulations” in the Recommendations tab and walking through the “Actions to take”. From the Recommendations tab, create a Control unethical behavior in AI Purview Communications Compliance policy to detect sensitive information in prompts and responses and address potentially unethical behavior in Microsoft Copilot experiences and ChatGPT for Enterprise. This policy covers all users and groups in your organization. To retain and/or delete Microsoft 365 Copilot prompts and responses, setup a Data Lifecycle policy by navigating to Microsoft Purview Data Lifecycle Management and find Retention Policies under the Policies header. You can also preserve, collect, analyze, review, and export Microsoft 365 Copilot interactions by creating an eDiscovery case. 2. Securing Enterprise AI apps Please refer to this amazing blog on Unlocking the Power of Microsoft Purview for ChatGPT Enterprise | Microsoft Community Hub for detailed information on how to integrate with ChatGPT for enterprise, the Purview solutions it currently supports through Purview Communication Compliance, Insider Risk Management, eDiscovery, and Data Lifecycle Management. Learn more about the feature also through our public documentation. 3. Securing other AI Microsoft Purview DSPM for AI currently supports the following list of AI sites. Be sure to also check out our blog on the new Microsoft Purview data security controls for the browser & network to secure other AI apps. Discover potential data security risks in prompts sent to other AI apps In the Overview tab of DSPM for AI, go through these three steps in “Get Started” to discover potential data security risk in other AI interactions: Install Microsoft Purview browser extension For Windows users: The Purview extension is not necessary for the enforcement of data loss prevention on the Edge browser but required for Chrome to detect sensitive info pasted or uploaded to AI sites. The extension is also required to detect browsing to other AI sites through an Insider Risk Management policy for both Edge and Chrome browser. Therefore, Purview browser extension is required for both Edge and Chrome in Windows. For MacOS users: The Purview extension is not necessary for the enforcement of data loss prevention on macOS devices, and currently, browsing to other AI sites through Purview Insider Risk Management is not supported on MacOS, therefore, no Purview browser extension is required for MacOS. Extend your insights for data discovery – this one-click collection policy will setup three separate Purview detection policies for other AI apps: Detect sensitive info shared in AI prompts in Edge – a Purview collection policy that detects prompts sent to ChatGPT consumer, Micrsoft Copilot, DeepSeek, and Google Gemini in Microsoft Edge and discovers sensitive information shared in prompt contents. This policy covers all users and groups in your organization in audit mode only. Detect when users visit AI sites – a Purview Insider Risk Management policy that detects when users use a browser to visit AI sites. Detect sensitive info pasted or uploaded to AI sites – a Purview Endpoint Data loss prevention (eDLP) policy that discovers sensitive content pasted or uploaded in Microsoft Edge, Chrome, and Firefox to AI sites. This policy covers all users and groups in your org in audit mode only. With the policies to discover sensitive information in other AI apps in place, head back to the Reports tab of DSPM for AI to discover any AI interactions that may be risky, with the option to filter by Other AI Apps, and review the following for other AI apps: Total interactions over time (other AI apps) Total visits (other AI apps) Sensitive interactions per AI app Insider Risk severity Insider risk severity per AI app Protect sensitive info shared with other AI apps From the Reports tab, click on “View details” for each of the report graphs to view detailed activities in the Activity Explorer. Using available filters, filter the results to view activities based on different Activity type, AI app category and App type, Scope, which support administrative units for DSPM for AI, and more. To protect the sensitive data in interactions for other AI apps, review the Not Started policies in the Recommendations tab and create these policies: Fortify your data security – This will create three policies to manage your data security risks with other AI apps: 1) Block elevated risk users from pasting or uploading sensitive info on AI sites – this will create a Microsoft Purview endpoint data loss prevention (eDLP) policy that uses adaptive protection to give a warn-with-override to elevated risk users attempting to paste or upload sensitive information to other AI apps in Edge, Chrome, and Firefox. This policy covers all users and groups in your org in test mode. Learn more about adaptive protection in Data loss prevention. 2) Block elevated risk users from submitting prompts to AI apps in Microsoft Edge – this will create a Microsoft Purview browser data loss prevention (DLP) policy, and using adaptive protection, this policy will block elevated, moderate, and minor risk users attempting to put information in other AI apps using Microsoft Edge. This integration is built-in to Microsoft Edge. Learn more about adaptive protection in Data loss prevention. 3) Block sensitive info from being sent to AI apps in Microsoft Edge - this will create a Microsoft Purview browser data loss prevention (DLP) policy to detect inline for a selection of common sensitive information types and blocks prompts being sent to AI apps while using Microsoft Edge. This integration is built-in to Microsoft Edge. Once you have created policies from the Recommendations tab, you can go to the Policies tab to review and manage all the policies you have created across your organization to discover and safeguard AI activity in one centralized place, as well as edit the policies or investigate alerts associated with those policies in solution. Note that additional policies not from the Recommendations tab will also appear in the Policies tab when DSPM for AI identifies them as policies to Secure and govern all AI apps. Conclusion Microsoft Purview DSPM for AI can help you discover, protect, and govern the interactions from AI applications in Microsoft Copilot experiences, Enterprise AI apps, and other AI apps. We recommend you review the Reports in DSPM for AI routinely to discover any new interactions that may be of concern, and to create policies to secure and govern those interactions as necessary. We also recommend you utilize the Activity Explorer in DSPM for AI to review different Activity explorer events while users interacting with AI, including the capability to view prompts and response with the right permissions. We will continue to update this blog with new features that become available in DSPM for AI, so be sure to bookmark this page! Follow-up Reading Check out this blog on the details of each recommended policies in DSPM for AI: Microsoft Purview – Data Security Posture Management (DSPM) for AI | Microsoft Community Hub Address oversharing concerns with Microsoft 365 blueprint - aka.ms/Copilot/Oversharing Microsoft Purview data security and compliance protections for Microsoft 365 Copilot and other generative AI apps | Microsoft Learn Considerations for deploying Microsoft Purview AI Hub and data security and compliance protections for Microsoft 365 Copilot and Microsoft Copilot | Microsoft Learn Commonly used properties in Copilot audit logs - Audit logs for Copilot and AI activities | Microsoft Learn Supported AI sites by Microsoft Purview for data security and compliance protections | Microsoft Learn Where Copilot usage data is stored and how you can audit it - Microsoft 365 Copilot data protection and auditing architecture | Microsoft Learn Downloadable whitepaper: Data Security for AI Adoption | Microsoft Public roadmap for DSPM for AI - Microsoft 365 Roadmap | Microsoft 365Enterprise-grade controls for AI apps and agents built with Azure AI Foundry and Copilot Studio
AI innovation is moving faster than ever, and more AI projects are moving beyond experimentation into deployment, to drive tangible business impact. As organizations accelerate innovation with custom AI applications and agents, new risks emerge across the software development lifecycle and AI stack related to data oversharing and leaks, new vulnerabilities and threats, and non-compliance with stringent regulatory requirements Through 2025, poisoning of software supply chains and infrastructure technology stacks will constitute more than 70% of malicious attacks against AI used in the enterprise 1 , highlighting potential threats that originate early in development. Today, the average cost of a data breach is $4.88 million, but when security issues are caught early in the development process, that number drops dramatically to just $80 per incident 2 . The message is very clear; security can’t be an afterthought anymore. It must be a team sport across the organization, embedded from the start and throughout the development lifecycle. That's why developers and security teams should align on processes and tools that bring security into every stage of the AI development lifecycle and give security practitioners visibility into and the ability to mitigate risks. To address these growing challenges and help customers secure and govern their AI workloads across development and security teams, we are: Enabling Azure AI Foundry and Microsoft Copilot Studio to provide best-in-class foundational capabilities to secure and govern AI workloads Deeply integrating and embedding industry-leading capabilities from Microsoft Purview, Microsoft Defender, and Microsoft Entra into Azure AI Foundry and Microsoft Copilot Studio This week, 3,000 developers are gathering in Seattle for the annual Microsoft Build conference, with many more tuning in online, to learn practical skills for accelerating their AI apps and agents' innovation. To support their AI innovation journey, today we are excited to announce several new capabilities to help developers and organizations secure and govern AI apps and agents. New Azure AI Foundry foundational capabilities to secure and govern AI workloads Azure AI Foundry enhancements for AI security and safety With 70,000 customers, 100 trillion tokens processed this quarter, and 2 billion enterprise search queries each day, Azure AI Foundry has grown beyond just an application layer—it's now a comprehensive platform for building agents that can plan, take action, and continuously learn to drive real business outcomes. To help organizations build and deploy AI with confidence, we’re introducing new security and safety capabilities and insights for developers in Azure AI Foundry Introducing Spotlighting to detect and block prompt injection attacks in real time As AI systems increasingly rely on external data sources, a new class of threats has emerged. Indirect prompt injection attacks embed hidden instructions in documents, emails, and web content, tricking models into taking unauthorized actions without any direct user input. These attacks are difficult to detect and hard to prevent using traditional filters alone. To address this, Azure AI Content Safety is introducing Spotlighting, now available in preview. Spotlighting strengthens the Prompt Shields guardrail by improving its ability to detect and handle potential indirect prompt injections, where hidden adversarial instructions are embedded in external content. This new capability helps prevent the model from inadvertently acting on malicious prompts that are not directly visible to the user. Enable Spotlighting in Azure AI Content Safety to detect potential indirect prompt injection attacks New capabilities for task adherence evaluation and task adherence mitigation to ensure agents remain within scope As developers build more capable agents, organizations face growing pressure to help confirm those agents act within defined instructions and policy boundaries. Even small deviations can lead to tool misuse, broken workflows, or risks like unintended exposure of sensitive data. To solve this, Azure AI Foundry now includes task adherence for agents, now in preview and powered by two components: a real-time evaluation and a new control within Azure AI Content Safety. At the core is a real-time task adherence evaluation API, part of Azure AI Content Safety. This API assesses whether an agent’s behavior is aligned with its assigned task by analyzing the user’s query, system instructions, planned tool calls, and the agent’s response. The evaluation framework is built on Microsoft’s Agent Evaluators, which measure intent resolution, tool selection accuracy, completeness of response, and overall alignment to the original request. Developers can run this scoring logic locally using the Task Adherence Evaluator in the Azure AI Evaluation SDK, with a five-point scale that ranges from fully nonadherent to fully adherent. This gives teams a flexible and transparent way to inspect task-level behavior before it causes downstream issues. Task adherence is enforced through a new control in Azure AI Content Safety. If an agent goes off-task, the control can block tool use, pause execution, or trigger human review. In Azure AI Agent Service, it is available as an opt-in feature and runs automatically. Combined with real-time evaluation, this control helps to ensure that agents stay on task, follow instructions, and operate according to enterprise policies. Learn more about Prompt Shields in Azure AI Content Safety. Azure AI Foundry continuous evaluation and monitoring of agentic systems Maintaining high performance and compliance for AI agents after deployment is a growing challenge. Without ongoing oversight, issues like performance degradation, safety risks, or unintentional misuse of resources can slip through unnoticed. To address this, Azure AI Foundry introduces continuous evaluation and monitoring of agentic systems, now in preview, provides a single pane of glass dashboard to track key metrics such as performance, quality, safety, and resource usage in real time. Continuous evaluation runs quality and safety evaluations at a sampled rate of production usage with results made available in the Azure AI Foundry Monitoring dashboard and published to Application Insights. Developers can set alerts to detect drift or regressions and use Azure Monitor to gain full-stack visibility into their AI systems. For example, an organization using an AI agent to assist with customer-facing tasks can monitor groundedness and detect a decline in quality when the agent begins referencing irrelevant information, helping teams to act before it potentially negatively affects trust of users. Azure AI Foundry evaluation integrations with Microsoft Purview Compliance Manager, Credo AI, and Saidot for streamlined compliance AI regulations and standards introduce new requirements for transparency, documentation, and risk management for high-risk AI systems. As developers build AI applications and agents, they may need guidance and tools to help them evaluate risks based on these requirements and seamlessly share control and evaluation insights with compliance and risk teams. Today, we are announcing previews for Azure AI Foundry evaluation tool’s integration with a compliance management solution, Microsoft Purview Compliance Manager, and AI governance solutions, Credo AI and Saidot. These integrations help define risk parameters, run suggested compliance evaluations, and collect evidence for control testing and auditing. For example, for a developer who’s building an AI agent in Europe may be required by their compliance team to complete a Data Protection Impact Assets (DPIA) and Algorithmic Impact Assessment (AIA) to meet internal risk management and technical documentation requirements aligned with emerging AI governance standards and best practices. Based on Purview Compliance Manager’s step-by-step guidance on controls implementation and testing, the compliance teams can evaluate risks such as potential bias, cybersecurity vulnerabilities, or lack of transparency in model behavior. Once the evaluation is conducted in Azure AI Foundry, the developer can obtain a report with documented risk, mitigation, and residual risk for compliance teams to upload to Compliance Manager to support audits and provide evidence to regulators or external stakeholders. Assess controls for Azure AI Foundry against emerging AI governance standards Learn more about Purview Compliance Manager. Learn more about the integration with Credo AI and Saidot in this blogpost. Leading Microsoft Entra, Defender and Purview value extended to Azure AI Foundry and Microsoft Copilot Studio Introducing Microsoft Entra Agent ID to help address agent sprawl and manage agent identity Organizations are rapidly building their own AI agents, leading to agent sprawl and a lack of centralized visibility and management. Security teams often struggle to keep up, unable to see which agents exist and whether they introduce security or compliance risks. Without proper oversight, agent sprawl increases the attack surface and makes it harder to manage these non-human identities. To address this challenge, we’re announcing the public preview of Microsoft Entra Agent ID, a new capability in the Microsoft Entra admin center that gives security admins visibility and control over AI agents built with Copilot Studio and Azure AI Foundry. With Microsoft Entra Agent ID, an agent created through Copilot Studio or Azure AI Foundry is automatically assigned an identity with no additional work required from the developers building them. This is the first step in a broader initiative to manage and protect non-human identities as organizations continue to build AI agents. : Security and identity admins can gain visibility into AI agents built in Copilot Studio and Azure AI Foundry in the Microsoft Entra Admin Center This new capability lays the foundation for more advanced capabilities coming soon to Microsoft Entra. We also know that no one can do it alone. Security has always been a team sport, and that’s especially true as we enter this new era of protecting AI agents and their identities. We’re energized by the momentum across the industry; two weeks ago, we announced support for the Agent-to-Agent (A2A) protocol and began collaborating with partners to shape the future of AI identity workflows. Today, we’re also excited to announce new partnerships with ServiceNow and Workday. As part of this, we’ll integrate Microsoft Entra Agent ID with the ServiceNow AI Platform and the Workday Agent System of Record. This will allow for automated provisioning of identities for future digital employees. Learn more about Microsoft Entra Agent ID. Microsoft Defender security alerts and recommendations now available in Azure AI Foundry As more AI applications are deployed to production, organizations need to predict and prevent potential AI threats with natively integrated security controls backed by industry-leading Gen AI and threat intelligence for AI deployments. Developers need critical signals from security teams to effectively mitigate security risks related to their AI deployments. When these critical signals live in separate systems outside the developer experience, this can create delays in mitigation, leaving opportunities for AI apps and agents to become liabilities and exposing organizations to various threats and compliance violations. Now in preview, Microsoft Defender for Cloud integrates AI security posture management recommendations and runtime threat protection alerts directly into the Azure AI Foundry portal. These capabilities, previously announced as part of the broader Microsoft Defender for Cloud solution, are extended natively into Azure AI Foundry enabling developers to access alerts and recommendations without leaving their workflows. This provides real-time visibility into security risks, misconfigurations, and active threats targeting their AI applications on specific Azure AI projects, without needing to switch tools or wait on security teams to provide details. Security insights from Microsoft Defender for Cloud help developers identify and respond to threats like jailbreak attacks, sensitive data leakage, and misuse of system resources. These insights include: AI security posture recommendations that identify misconfigurations and vulnerabilities in AI services and provide best practices to reduce risk Threat protection alerts for AI services that notify developers of active threats and provide guidance for mitigation, across more than 15 detection types For example, a developer building an AI-powered agent can receive security recommendations suggesting the use of Azure Private Link for Azure AI Services resources. This reduces the risk of data leakage by handling the connectivity between consumers and services over the Azure backbone network. Each recommendation includes actionable remediation steps, helping teams identify and mitigate risks in both pre- and post-deployment phases. This helps to reduce risks without slowing down innovation. : Developers can view security alerts on the Risks + alerts page in Azure AI Foundry : Developers can view recommendations on the Guardrails + controls page in Azure AI Foundry This integration is currently in preview and will be generally available in June 2025 in Azure AI Foundry. Learn more about protecting AI services with Microsoft Defender for Cloud. Microsoft Purview capabilities extended to secure and govern data in custom-built AI apps and agents Data oversharing and leakage are among the top concerns for AI adoption, and central to many regulatory requirements. For organizations to confidently deploy AI applications and agents, both low code and pro code developers need a seamless way to embed security and compliance controls into their AI creations. Without simple, developer-friendly solutions, security gaps can quickly become blockers, delaying deployment and increasing risks as applications move from development to production. Today, Purview is extending its enterprise-grade data security and compliance capabilities, making it easier for both low code and pro code developers to integrate data security and compliance into their AI applications and agents, regardless of which tools or platforms they use. For example, with this update, Microsoft Purview DSPM for AI becomes the one place data security teams can see all the data risk insights across Microsoft Copilots, agents built in Agent Builder and Copilot Studio, and custom AI apps and agents built in Azure AI Foundry and other platforms. Admins can easily drill into security and compliance insights for specific AI apps or agents, making it easier to investigate and take action on potential risks. : Data security admins can now find data security and compliance insights across Microsoft Copilots, agents built with Agent Builder and Copilot Studio, and custom AI apps and agents in Microsoft Purview DSPM for AI In the following sections, we will provide more details about the updates to Purview capabilities in various AI workloads. 1. Microsoft Purview data security and compliance controls can be extended to any custom-built AI application and agent via the new Purview SDK or the native Purview integration with Azure AI Foundry. The new capabilities make it easy and effortless for security teams to bring the same enterprise-grade data security compliance controls available today for Microsoft 365 Copilot to custom AI applications and agents, so organizations can: Discover data security risks, such as sensitive data in user prompts, and data compliance risks, such as harmful content, and get recommended actions to mitigate risks proactively in Microsoft Purview Data Security Posture Management (DSPM) for AI. Protect sensitive data against data leakage and insider risks with Microsoft Purview data security policies. Govern AI interactions with Audit, Data Lifecycle Management, eDiscovery, and Communication Compliance. Microsoft Purview SDK Microsoft Purview now offers Purview SDK, a set of REST APIs, documentation, and code samples, currently in preview, enabling developers to integrate Purview's data security and compliance capabilities into AI applications or agents within any integrated development environment (IDE). : By embedding Purview APIs into the IDE, developers help enable their AI apps to be secured and governed at runtime For example, a developer building an AI agent using an AWS model can use the Purview SDK to enable their AI app to automatically identify and block sensitive data entered by users before it’s exposed to the model, while also providing security teams with valuable signals that support compliance. With Purview SDK, startups, ISVs, and partners can now embed Purview industry-leading capabilities directly into their AI software solutions, making these solutions Purview aware and easier for their customers to secure and govern data in their AI solutions. For example, Infosys Vice President and Delivery Head of Cyber Security Practice, Ashish Adhvaryu indicates, “Infosys Cyber Next platform integrates Microsoft Purview to provide enhanced AI security capabilities. Our solution, the Cyber Next AI assistant (Cyber Advisor) for the SOC analyst, leverages Purview SDK to drive proactive threat mitigation with real-time monitoring and auditing capabilities. This integration provides holistic AI-assisted protection, enhancing cybersecurity posture." Microsoft partner EY (previously known as Ernst and Young) has also leveraged the new Purview SDK to embed Purview value into their GenAI initiatives. “We’re not just building AI tools, we are creating Agentic solutions where trust, security, and transparency are present from the start, supported by the policy controls provided through the Purview SDK. We’re seeing 25 to 30 percent time savings when we build secure features using the Purview SDK,” noted Sumanta Kar, Partner, Innovation and Emerging Tech at EY. Learn more about the Purview SDK. Microsoft Purview integrates natively with Azure AI Foundry Organizations are developing an average of 14 custom AI applications. The rapid pace of AI innovation may leave security teams unaware of potential data security and compliance risks within their environments. With the update announced today, Azure AI Foundry signals are now directly integrated with Purview Data Security Posture Management for AI, Insider Risk Management, and data compliance controls, minimizing the need for additional development work. For example, for AI applications and agents built with Azure AI Foundry models, data security teams can gain visibility into AI usage and data risks in Purview DSPM for AI, with no additional work from developers. Data security teams can also detect, investigate, and respond to both malicious and inadvertent user activities, such as a departing employee leveraging an AI agent to retrieve an anomalous amount of sensitive data, with Microsoft Purview Insider Risk Management (IRM) policies. Lastly, user prompts and AI responses in Azure AI apps and agents can now be ingested into Purview compliance tools as mentioned above. Learn more about Microsoft Purview for Azure AI Foundry. 2. Purview data protections extended to Copilot Studio agents grounded in Microsoft Dataverse data Coming to preview in June, Purview Information Protection extends auto-labeling and label inheritance coverage to Dataverse to help prevent oversharing and data leaks. Information Protection makes it easier for organizations to automatically classify and protect sensitive data at scale. A common challenge is that sensitive data often lands in Dataverse from various sources without consistent labeling or protection. The rapid adoption of agents built using Copilot Studio and grounding data from Dataverse increases the risk of data oversharing and leakage if data is not properly protected. With auto-labeling, data stored in Dataverse tables can be automatically labeled based on policies set in Microsoft Purview, regardless of its source. This reduces the need for manual labeling effort and protects sensitive information from the moment it enters Dataverse. With label inheritance, AI agent responses grounded in Dataverse data will automatically carry and honor the source data’s sensitivity label. If a response pulls from multiple tables with different labels, the most restrictive label is applied to ensure consistent protection. For example, a financial advisor building an agent in Copilot Studio might connect multiple Dataverse tables, some labeled as “General” and others as “Highly Confidential.” If a response pulls from both, it will inherit the most restrictive label, in this case, "Highly Confidential,” to prevent unauthorized access and ensure appropriate protections are applied across both maker and users of the agent. Together, auto-labeling and label inheritance in Dataverse support a more secure, automated foundation for AI. : Sensitivity labels will be automatically applied to data in Dataverse : AI-generated responses will inherit and honor the source data’s sensitivity labels Learn more about protecting Dataverse data with Microsoft Purview. 3. Purview DSPM for AI can now provide visibility into unauthenticated interactions with Copilot Studio agents As organizations increasingly use Microsoft Copilot Studio to deploy AI agents for frontline customer interactions, gaining visibility into unauthenticated user interactions and proactively mitigating risks becomes increasingly critical. Building on existing Purview and Copilot Studio integrations, we’ve extended DSPM for AI and Audit in Copilot Studio to provide visibility into unauthenticated interactions, now in preview. This gives organizations a more comprehensive view of AI-related data security risks across authenticated and unauthenticated users. For example, a healthcare provider hosting an external, customer-facing agent assistant must be able to detect and respond to attempts by unauthenticated users to access sensitive patient data. With these new capabilities in DSPM for AI, data security teams can now identify these interactions, assess potential exposure of sensitive data, and act accordingly. Additionally, integration with Purview Audit provides teams with seamless access to information needed for audit requirements. : Gain visibility into all AI interactions, including those from unauthenticated users Learn more about Purview for Copilot Studio. 4. Purview Data Loss Prevention extended to more Microsoft 365 agent scenarios To help organizations prevent data oversharing through AI, at Ignite 2024, we announced that data security admins could prevent Microsoft 365 Copilot from using certain labeled documents as grounding data to generate summaries or responses. Now in preview, this control also extends to agents published in Microsoft 365 Copilot that are grounded by Microsoft 365 data, including pre-built Microsoft 365 agents, agents built with the Agent Builder, and agents built with Copilot Studio. This helps ensure that files containing sensitive content are used appropriately by AI agents. For example, confidential legal documents with highly specific language that could lead to improper guidance if summarized by an AI agent, or "Internal only” documents that shouldn’t be used to generate content that can be shared outside of the organization. : Extend data loss prevention (DLP) policies to Microsoft 365 Copilot agents to protect sensitive data Learn more about Data Loss Prevention for Microsoft 365 Copilot and agents. The data protection capabilities we are extending to agents in Agent Builder and Copilot Studio demonstrate our continued investment in strengthening the Security and Governance pillar of the Copilot Control System (CSS). CCS provides integrated controls to help IT and security teams secure, manage, and monitor Copilot and agents across Microsoft 365, spanning governance, management, and reporting. Learn more here. Explore additional resources As developers and security teams continue to secure AI throughout its lifecycle, it’s important to stay ahead of emerging risks and ensure protection. Microsoft Security provides a range of tools and resources to help you proactively secure AI models, apps, and agents from code to runtime. Explore the following resources to deepen your understanding and strengthen your approach to AI security: Learn more about Security for AI solutions on our webpage Learn more about Microsoft Purview SDK Get started with Azure AI Foundry Get started with Microsoft Entra Get started with Microsoft Purview Get started with Microsoft Defender for Cloud Get started with Microsoft 365 Copilot Get started with Copilot Studio Sign up for a free Microsoft 365 E5 Security Trial and Microsoft Purview Trial 1 Predicts 2025: Navigating Imminent AI Turbulence for Cybersecurity, Jeremy D'Hoinne, Akif Khan, Manuel Acosta, Avivah Litan, Deepak Seth, Bart Willemsen, 10 February 2025 2 IBM. "Cost of a Data Breach 2024: Financial Industry." IBM Think, 13 Aug. 2024, https://www.ibm.com/think/insights/cost-of-a-data-breach-2024-financial-industry; Cser, Tamas. "The Cost of Finding Bugs Later in the SDLC." Functionize, 5 Jan. 2023, https://www.functionize.com/blog/the-cost-of-finding-bugs-later-in-the-sdlcHow to use DSPM for AI Data Risk Assessment to Address Internal Oversharing
Background Oversharing and data leak risks may occur with or without GenAI use. However, leaders are concerned that GenAI tools might grant faster access to content with incorrect permissions, making these files easier to locate. Oversharing occurs when an employee has access to information beyond what is necessary to do their jobs. It often happens accidentally, for example if a user saves sensitive files to a SharePoint site without realizing everyone has access to that location. It could also happen when people share files too broadly (e.g. everyone in the organization sharing a link). Or it can happen when files lack protection regardless of location. Microsoft Purview Data Security for Posture Management (DSPM) for AI’s Data Risk Assessment helps to address oversharing by allowing security teams to scan files containing sensitive data and identifying data repositories such as SharePoint sites with overly permissive user access. It provides visibility into overshared content, risk assessment, remediation actions, and detailed reports. Introduction Purview Data Security Posture Management for AI (DSPM for AI)’s Data Risk Assessment is for you if you: Are an existing Microsoft 365 Copilot customer, or someone wanting to deploy Microsoft 365 Copilot: or Want to address oversharing but have not yet deployed Microsoft 365 Copilot. Prerequisites Please refer to the prerequisites for DSPM for AI in the Microsoft Learn Docs. Log in to the Purview portal To begin, start by logging into Microsoft 365 Purview portal with your admin credentials: In the Microsoft Purview portal, go to the Home page. Find DSPM for AI under solutions. Head to Purview DSPM for AI -> Data Assessment. The Data Assessments tool identifies potential oversharing risks in your organization. It also provides fixes to limit access to sensitive data. As shown on the Data Risk Assessment landing page, there are two types of assessments: A Default Assessment. This assessment runs automatically every week. Custom Assessments. This assessment is user-triggered. This blog will focus on the Default assessment and will not cover Custom assessments. The Default assessment will run automatically weekly. Additionally, the Default assessment runs weekly and targets the top 100 SharePoint sites based on usage. Default assessment Next, click the View details button for the Default data risk assessment report on the Overview page. In the Oversharing Assessment for the week page, locate the visual reports bar. The visual reports bar provides a general overview of, Assessment details, which includes: Description. Top 100 accessed SharePoint sites by usage. Last updated, next updated, and frequency. Frequency of updates for the default assessment. Total items - a visual graph of the number of items scanned and/or not scanned for sensitive information types (SITs). Sensitivity labels on data – a visual graph that includes, The number of labeled SITs detected and not detected. The number of Not labeled SITs detected and not detected. The number of data not scanned. Items shared with – a visual graph that includes the number of links, Shared with anyone. Shared organization wide. Shared with specific people. Shared outside your organization. The following data points may indicate that oversharing has occurred in the tenant: Large amount of data not scanned. Large amount of data containing SITs but not labeled. Large amount of data shared externally. Site-specific data Next, locate the list of sites (Data source ID) and their info on the table below the visual reports bar, which includes information on: Source type Total items Total items accessed Times users accessed items Unique users accessing items Total Sensitive items Total scanned items Total unscanned items Items shared with Scroll through the list and identify potential sites that may contain oversharing based on the knowledge of whether the site is private or public, and the possible conditions below: A private site that is being shared externally based on sharing links info. A private site that has a high level of documents being shared outside of the org based on a high level of total items accessed and/or unique users accessed and/or times users accessed. A public site that has a high level of sensitive items based on total sensitive items count. A site that has a high level of total unscanned items. By clicking on the Export button, you can export the Data source IDs to an Excel, CSV, JSON, and TSV file. The rollout of the export capability has started and will be complete by end of the week (week of April 28, 2025). Secure and Govern Each Site Click into each site of interest, or sites may have potential oversharing, to review the site info in the flyout panel. Overview – provides an overview of the details for the site. Data source details – provides details of where the data comes from (i.e. SharePoint) and its corresponding URL Data coverage – displays the total items scanned in the site that are either: Labeled and SITs detected, or No SITs detected Not labeled and SITs detected, or No SITs detected *Data points that may indicate that oversharing has occurred in the tenant: 1. Lots of unscanned documents. 2. Lots of documents that contain SITs but not labeled. Identify – scans your data for sensitive information. Use Microsoft Purview On-demand classification data scan to scan for sensitive information for all content in this site. Microsoft Purview On-demand classification data scan is a feature to help discover and classify sensitive content in historical data across Microsoft 365. Protect – provides remediation actions that you can take to address internal oversharing: Limit Microsoft 365 Copilot access to this site - Restrict access or block processing of certain content in SharePoint - you can choose two methods of how Copilot accesses data in SharePoint: Restrict access by label – Block processing of content with a specific sensitivity label using Purview Data Loss Prevention (DLP) policy for Copilot Restrict all items – Restrict access to site(s) using SharePoint Advanced Management (SAM) restricted content discovery (RCD) Other labeling policies - Create sensitivity label taxonomy and publish labels to SharePoint via: Default sensitivity label for SharePoint document library Default labels – setup default labels to label all new items by default using sensitivity labels. Sensitive information auto-labeling policy - Use auto-labeling policies based on sensitive content or keywords. You can click View items to view the files with SITs. SharePoint site sensitivity label to apply a sensitivity container label to the site. Review unused files - Protect sensitive data from oversharing by deleting unused files with Purview Data Lifecycle Management (DLM) retention policies. Monitor – Ongoing access monitoring Run a site access review This section displays the number of sites: Shared with anyone. Shared organization wide. Shared with specific people. Shared externally. You can then run a SharePoint site access review using SAM Run an access review through Microsoft Entra to make sure access granted is up to date. Conclusion In this blog, we explored the concept of oversharing and its implications in collaborative environments. We discussed how Microsoft Purview DSPM for AI Data Risk Assessments can help identify and mitigate risks associated with sensitive data. Additionally, this blog provided a detailed guide on using the Data Risk Assessments tool, focusing on the Default assessment, which runs automatically every week. We covered how to interpret the visual reports and identify potential oversharing risks based on various data points. Additionally, we outlined steps to secure and govern each site, including remediation actions and access monitoring. For detailed guidance on all Purview + SAM features to address oversharing, please reference the oversharing blueprint - https://aka.ms/Copilot/Oversharing. Be sure to also check out the blog on How to deploy DSPM for AI to secure and govern all types of AI, including Microsoft Copilot experiences, Enterprise AI apps, and other AI apps! Resources Address oversharing concerns with Microsoft 365 blueprint - aka.ms/Copilot/Oversharing Public webinar on oversharing - Secure AI: Practical Steps for Addressing Oversharing Concerns 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 Downloadable whitepaper - Data Security for AI Adoption | Microsoft Public roadmap for DSPM for AI - Microsoft 365 Roadmap | Microsoft 365
The Crucial Role of Data Security Posture Management in the AI Era
In an era where artificial intelligence (AI) is rapidly transforming business operations, the importance of Data Security Posture Management (DSPM) cannot be overstated. Data Security Posture Management plays an important role in modern digital infrastructure by providing a comprehensive framework to manage and mitigate data security risks. DSPM also helps in identifying and mitigating security risks associated with AI adoption along with ensuring that organizations can leverage AI technologies safely and effectively. Key aspects of DSPM: 360-degree view approach for data at rest, in-transit, and risk associated to users. Centralized Visibility and monitoring approach into sensitive data, it's usage and access across different systems. Regular risk assessments are performed to determine any vulnerabilities within the infrastructure Direct integrations with various third-party tools and CSP's Exponential Increase in Data Threats The rise of AI has brought about an exponential increase in data threats. Here are some alarming statistics: Data Security Incidents: A staggering 83% of organizations have experienced more than one data breach throughout their existence, underscoring the prevalence of security incidents. Insider Threats: Accounting for 20% of data breaches, insider threats pose significant risks, with the average cost to resolve such threats reaching $15.4 million over a 12-month period. Generative AI Concerns: The adoption of generative AI brings its own set of challenges, with over 80% of organizations expressing concerns about the potential leakage of sensitive data during the training and implementation phases. Enhancing and securing Data Security with Microsoft Purview Microsoft Purview offers an integrated solution for securing and governing data across multi-cloud and hybrid environments. Its adaptive features continuously evaluate and adjust risk levels to prevent unauthorized data use. Here are some of the key features that play a crucial role in strengthening Data Security Posture: Data Security: Data Loss Prevention: Safeguards data throughout its lifecycle, wherever it resides. Insider Risk Management: Addresses internal threats effectively. Information Protection: Ensures sensitive information remains confidential. Data Governance: Data Discovery: Identifies and classifies data across the organization. Data Quality: Maintains the integrity and accuracy of data. Data Curation: Organizes and manages data for easy access and analysis. Data Estate Insights: Provides visibility into data usage and storage. Data Compliance: Compliance Manager: Helps meet regulatory requirements and manage risks. eDiscovery and Audit: Facilitates legal investigations and compliance checks. Communication Compliance: Monitors and controls communication channels to prevent data leaks. Data Lifecycle Management: Manages the retention and deletion of data. Records Management: Ensures proper record-keeping for compliance and governance. Conclusion The integration of AI into business processes necessitates a robust approach to data security. Data Security Posture Management, as part of an organization's cybersecurity strategy, is critical for identifying, managing, and mitigating risks associated with AI adoptionBlog Series: Charting Your Path to Cyber Resiliency
Cyber resiliency is an organization’s ability to build and manage technology systems that limit the impact of cyberattacks. It helps organizations maintain operations, securely and effectively, when cyberattacks occur. As Microsoft notes, “An organization can never have perfect security, but it can become resilient to security attacks.” In Part 1 of this series, we looked at how the concept of cyber resiliency originated, introduced 2 foundational cyber resiliency frameworks and wrapped up with a quick look at some Microsoft cyber resiliency resources from our 2022 Digital Defense Report. In Part 2, we’ll dive deeper into Microsoft’s approach to cyber resiliency, starting back in 2002 with the famous Trustworthy Computing memo from Bill Gates himself. TrustWorthy Computing In 2002, Microsoft founder and CEO Bill Gates emailed a memo to all Microsoft employees, outlining the need for a new approach to how the company provided security and resiliency to our customers, and calling for changes to Microsoft products and culture. Gates referenced September 11 and several serious malware incidents in 2001 that had caused significant business disruptions, emphasizing "how important it is to ensure the integrity and security of our critical infrastructure, whether it’s the airlines or computer systems." Gates also foresaw how increasingly connected and dependent on the Internet the world would become in the future – a concept that played a key role in the development of cyber resilience frameworks. The Trustworthy Computing initiative was not created specifically to address cyber resiliency, but like cyber resiliency it was holistic in its treatment of security, covering diverse areas such as software development and customer support, as well as Microsoft’s internal operational and business practices. A 2014 article by Forbes praised Microsoft for the impact of Trustworthy Computing on Security, not just for Microsoft products, but for the entire IT industry, noting "We’ve come a long way from the 'Wild West” era of malware—thanks in large part to the ongoing efforts of Microsoft Trustworthy Computing." Zero Trust Microsoft didn't invent Zero Trust but has been an industry leader in actively promoting and developing Zero Trust strategies for many years, as well as using Zero Trust to secure our own environments. For example, Microsoft has collaborated with NIST (the National Institute of Standards and Technology) and other vendors to develop a practice guide to help organizations design and build Zero Trust architectures. Zero Trust and cyber resiliency are not the same, but there are many similarities between them, starting with the idea that we must Assume Breach, given the speed, scale and sophistication of threat actors and the challenges every Security team faces. In addition: Both stress the importance of identifying the most critical business resources and prioritizing the protection of those resources Both are concerned with limiting the blast radius of an attack and reducing the attacker’s ability to move laterally Both are designed to protect hybrid environments across multiple pillars that include both legacy and modern technologies Both emphasize the need for the organization to continually adapt protections to keep up with threat actors Secure Future Initiative There are many similarities between the TrustWorthy Computing initiative and Microsoft’s current Secure Future Initiative (SFI). Again, it began with an internal memo to employees, this time by Microsoft Security EVP Charlie Bell, in November 2023. Like TrustWorthy Computing, SFI illustrates Microsoft’s leadership in addressing current cybersecurity challenges that now include AI advancements, increasingly sophisticated ransomware-as-a-service organizations, and nation-state activity targeting critical infrastructure. Like TrustWorthy Computing, SFI is holistic in nature. As Vice Chair and President Brad Smith emphasized in his own intro to SFI "This new initiative will bring together every part of Microsoft to advance cybersecurity protection." The Secure Future Initiative is also rooted in Microsoft’s experiences as a company dedicated to continually improving our own cyber resilience. In a May 2024 report on SFI progress, Microsoft CEO Satya Nadella noted that cyberattacks, such as the 2023 Storm-0558 attack that targeted Microsoft, 'underscore the severity of the threats facing our company and our customers, as well as our responsibility to defend against these increasingly sophisticated threat actors." Finally, like TrustWorthy Computing, SFI is clear that security – both for Microsoft and for our customers – is the company’s number one priority. Satya concluded his message with a familiar call to action for Microsoft employees: "If you’re faced with the tradeoff between security and another priority, your answer is clear: Do security." Microsoft's Key Issues Impacting Cyber Resiliency Part 1 of this series introduced Microsoft’s key issues impacting cyber resiliency. These are issues that we in MIRCAT (the Microsoft Incident Response Critical Action Team) routinely address in our incident response/compromise recovery work with clients: Insecure configuration of identity provider Insufficient privilege access and lateral movement controls No Multi-Factor Authentication Low maturity security operations Lack of information protection control Limited adoption of modern security frameworks Each of these issues is further broken down into distinct components. For example, the issue Insufficient privilege access and lateral movement controls has 5 components: No privilege isolation in Active Directory via tier model No use of Privilege Access Workstations Lack of local admin password management controls Lack of Privilege Access Management controls Excessive admin credentials found Trying to address all cyber resilience issues can be overwhelming for clients, which is why we emphasize taking a phased approach to each issue and component. For example, Lack of Privilege Access Management controls in Entra can be addressed by Microsoft Privileged Identity Management (PIM). When helping a client implement PIM, we employ a phased approach that might look something like this: Phase 1: Implement PIM to protect privileged roles in Entra, starting with Global Administrators and guest accounts. Gradually onboard additional Entra Admin roles. Phase 2: Implement PIM to protect select highly privileged roles in the most business-critical Azure subscriptions. Gradually onboard additional subscriptions. Phase 3: Extend PIM management to more complex use cases involving time-bound privileged group membership, authentication context and approval workflows. When implementing a security technology to help your organization increase cyber resiliency, your goal should be to implement it fully with no exceptions. Unfortunately, in incident response and compromise recovery engagements we often see gaps that limit our clients’ resilience to cyberattacks. For example, we regularly work with clients who tell us that they’ve implemented PIM, only to find that many privileged roles have been permanently assigned outside of PIM. In other cases, we see PIM used only for Entra roles while no privileged access controls are applied to Azure subscriptions running business-critical workloads. At the same time, when business reasons dictate that a cyber resilience control cannot be fully implemented, organizations should not adopt an all-or-nothing approach. For example, financial constraints prohibit some clients from providing privileged access workstations to all administrators or FIDO 2 compatible security keys to all users. In those cases, organizations are encouraged to start by providing those additional protections to Tier 0 administrators at a minimum, followed by Tier 1 administrators of business-critical workloads. Conclusion In Part 2 of our series, we explored how Microsoft has been an industry leader in cyber resiliency over the years, beginning with the days of TrustWorthy Computing more than 20 years ago. We also delved deeper into Microsoft’s current guidance on the key issues that we see limiting our customers’ cyber resilience. The journey to cyber resilience is a challenging and time-consuming one with a lot of Big Rocks that clients commonly struggle with: Vulnerability management Policy management Securing privileged access Adapting to the continuously changing cyber threat landscape Maturing the SecOps capability Fortunately, it’s a journey that organizations don’t have to make alone, and increasingly it’s a journey that AI can help with. And that’s what we’ll examine in the final part of this series.Enhance AI security and governance across multi-model and multi-cloud environments
Generative AI adoption is accelerating, with AI transformation happening in real-time across various industries. This rapid adoption is reshaping how organizations operate and innovate, but it also introduces new challenges that require careful attention. At Ignite last fall, we announced several new capabilities to help organizations secure their AI transformation. These capabilities were designed to address top customer priorities such as preventing data oversharing, safeguarding custom AI, and preparing for emerging AI regulations. Organizations like Cummins, KPMG, and Mia Labs have leveraged these capabilities to confidently strengthen their AI security and governance efforts. However, despite these advancements, challenges persist. One major concern is the rise of shadow AI—applications used without IT or security oversight. In fact, 78% of AI users report bringing their own AI tools, such as ChatGPT and DeepSeek, into the workplace 1 . Additionally, new threats, like indirect prompt injection attacks, are emerging, with 77% of organizations expressing concerns and 11% of organizations identifying them as a critical risk 2 . To address these challenges, we are excited to announce new features and capabilities that help customers do the following: Prevent risky access and data leakage in shadow AI with granular access controls and inline data security capabilities Manage AI security posture across multi-cloud and multi-model environments Detect and respond to new AI threats, such as indirect prompt injections and wallet abuse Secure and govern data in Microsoft 365 Copilot and beyond In this blog, we’ll explore these announcements and demonstrate how they help organizations navigate AI adoption with confidence, mitigating risks, and unlocking AI’s full potential on their transformation journey. Prevent risky access and data leakage in shadow AI With the rapid rise of generative AI, organizations are increasingly encountering unauthorized employee use of AI applications without IT or security team approval. This unsanctioned and unprotected usage has given rise to “shadow AI,” significantly heightening the risk of sensitive data exposure. Today, we are introducing a set of access and data security controls designed to support a defense-in-depth strategy, helping you mitigate risks and prevent data leakage in third-party AI applications. Real-time access controls to shadow AI The first line of defense against security risks in AI applications is controlling access. While security teams can use endpoint controls to block access for all users across the organization, this approach is often too restrictive and impractical. Instead, they need more granular controls at the user level to manage access to SaaS-based AI applications. Today we are announcing the general availability of the AI web category filter in Microsoft Entra Internet Access to help enforce access controls that govern which users and groups have access to different AI applications. Internet Access deep integration with Microsoft Entra ID extends Conditional Access to any AI application, enabling organizations to apply AI access policies with granularity. By using Conditional Access as the policy control engine, organizations can enforce policies based on user roles, locations, device compliance, user risk levels, and other conditions, ensuring secure and adaptive access to AI applications. For example, with Internet Access, organizations can allow your strategy team to experiment with all or most consumer AI apps while blocking those apps for highly privileged roles, such as accounts payable or IT infrastructure admins. For even greater security, organizations can further restrict access to all AI applications if Microsoft Entra detects elevated identity risk. Inline discovery and protection of sensitive data Once users gain access to sanctioned AI applications, security teams still need to ensure that sensitive data isn’t shared with those applications. Microsoft Purview provides data security capabilities to prevent users from sending sensitive data to AI applications. Today, we are announcing enhanced Purview data security capabilities for the browser available in preview in the coming weeks. The new inline discovery & protection controls within Microsoft Edge for Business detect and block sensitive data from being sent to AI apps in real-time, even if typed directly. This prevents sensitive data leaks as users interact with consumer AI applications, starting with ChatGPT, Google Gemini, and DeepSeek. For example, if an employee attempts to type sensitive details about an upcoming merger or acquisition into Google Gemini to generate a written summary, the new inline protection controls in Microsoft Purview will block the prompt from being submitted, effectively blocking the potential leaks of confidential data to an unsanctioned AI app. This augments existing DLP controls for Edge for Business, including protections that prevent file uploads and the pasting of sensitive content into AI applications. Since inline protection is built natively into Edge for Business, newly deployed policies automatically take effect in the browser even if endpoint DLP is not deployed to the device. : Inline DLP in Edge for Business prevents sensitive data from being submitted to consumer AI applications like Google Gemini by blocking the action. The new inline protection controls are integrated with Adaptive Protection to dynamically enforce different levels of DLP policies based on the risk level of the user interacting with the AI application. For example, admins can block low-risk users from submitting prompts containing the highest-sensitivity classifiers for their organization, such as M&A-related data or intellectual property, while blocking prompts containing any sensitive information type (SIT) for elevated-risk users. Learn more about inline discovery & protection in the Edge for Business browser in this blog. In addition to the new capabilities within Edge for Business, today we are also introducing Purview data security capabilities for the network layer available in preview starting in early May. Enabled through integrations with Netskope and iboss to start, organizations will be able to extend inline discovery of sensitive data to interactions between managed devices and untrusted AI sites. By integrating Purview DLP with their SASE solution (e.g. Netskope and iBoss), data security admins can gain visibility into the use of sensitive data on the network as users interact with AI applications. These interactions can originate from desktop applications such as the ChatGPT desktop app or Microsoft Word with a ChatGPT plugin installed, or non-Microsoft browsers such as Opera and Brave that are accessing AI sites. Using Purview Data Security Posture Management (DSPM) for AI, admins will also have visibility into how these interactions contribute to organizational risk and can take action through DSPM for AI policy recommendations. For example, if there is a high volume of prompts containing sensitive data sent to ChatGPT, DSPM for AI will detect and recommend a new DLP policy to help mitigate this risk. Learn more about inline discovery for the network, including Purview integrations with Netskope and iBoss, in this blog. Manage AI security posture across multi-cloud and multi-model environments In today’s rapidly evolving AI landscape, developers frequently leverage multiple cloud providers to optimize cost, performance, and availability. Different AI models excel at various tasks, leading developers to deploy models from various providers for different use cases. Consequently, managing security posture across multi-cloud and multi-model environments has become essential. Today, Microsoft Defender for Cloud supports deployed AI workloads across Azure OpenAI Service, Azure Machine Learning, and Amazon Bedrock. To further enhance our security coverage, we are expanding AI Security Posture Management (AI-SPM) in Defender for Cloud to improve compatibility with additional cloud service providers and models. This includes: Support for Google Vertex AI models Enhanced support for Azure AI Foundry model catalog and custom models With this expansion, AI-SPM in Defender for Cloud will now offer the discovery of the AI inventory and vulnerabilities, attack path analysis, and recommended actions to address risks in Google VertexAI workloads. Additionally, it will support all models in Azure AI Foundry model catalog, including Meta Llama, Mistral, DeepSeek, as well as custom models. This expansion ensures a consistent and unified approach to managing AI security risks across multi-model and multi-cloud environments. Support for Google Vertex AI models will be available in public preview starting May 1, while support for Azure AI Foundry model catalog and custom models is generally available today. Learn More. 2: Microsoft Defender for Cloud detects an attack path to a DeepSeek R1 workload. In addition, Defender for Cloud will also offer a new data and AI security dashboard. Security teams will have access to an intuitive overview of their datastores and AI services across their multi-cloud environment, top recommendations, and critical attack paths to prioritize and accelerate remediation. The dashboard will be generally available on May 1. The new data & AI security dashboard in Microsoft Defender for Cloud provides a comprehensive overview of your data and AI security posture. These new capabilities reflect Microsoft’s commitment to helping organizations address the most critical security challenges in managing AI security posture in their heterogeneous environments. Detect and respond to new AI threats Organizations are integrating generative AI into their workflows and facing new security risks unique to AI. Detecting and responding to these evolving threats is critical to maintaining a secure AI environment. The Open Web Application Security Project (OWASP) provides a trusted framework for identifying and mitigating such vulnerabilities, such as prompt injection and sensitive information disclosure. Today, we are announcing Threat protection for AI services, a new capability that enhances threat protection in Defender for Cloud, enabling organizations to secure custom AI applications by detecting and responding to emerging AI threats more effectively. Building on the OWASP Top 10 risks for LLM applications, this capability addresses those critical vulnerabilities highlighted on the top 10 list, such as prompt injections and sensitive information disclosure. Threat protection for AI services helps organizations identify and mitigate threats to their custom AI applications using anomaly detection and AI-powered insights. With this announcement, Defender for Cloud will now extend its threat protection for AI workloads, providing a rich suite of new and enriched detections for Azure OpenAI Service and models in the Azure AI Foundry model catalog. New detections include direct and indirect prompt injections, novel attack techniques like ASCII smuggling, malicious URL in user prompts and AI responses, wallet abuse, suspicious access to AI resources, and more. Security teams can leverage evidence-based security alerts to enhance investigation and response actions through integration with Microsoft Defender XDR. For example, in Microsoft Defender XDR, a SOC analyst can detect and respond to a wallet abuse attack, where an attacker exploits an AI system to overload resources and increase costs. The analyst gains detailed visibility into the attack, including the affected application, user-entered prompts, IP address, and other suspicious activities performed by the bad actor. With this information, the SOC analyst can take action and block the attacker from accessing the AI application, preventing further risks. This capability will be generally available on May 1. Learn More. : Security teams can investigate new detections of AI threats in Defender XDR. Secure and govern data in Microsoft 365 Copilot and beyond Data oversharing and non-compliant AI use are significant concerns when it comes to securing and governing data in Microsoft Copilots. Today, we are announcing new data security and compliance capabilities. New data oversharing insights for unclassified data available in Microsoft Purview DSPM for AI: Today, we are announcing the public preview of on-demand classification for SharePoint and OneDrive. This new capability gives data security admins visibility into unclassified data stored in SharePoint and OneDrive and enables them to classify that data on demand. This helps ensure that Microsoft 365 Copilot is indexing and referencing files in its responses that have been properly classified. Previously, unclassified and unscanned files did not appear in DSPM for AI oversharing assessments. Now admins can initiate an on-demand data classification scan, directly from the oversharing assessment, ensuring that older or previously unscanned files are identified, classified, and incorporated into the reports. This allows organizations to detect and address potential risks more comprehensively. For example, an admin can initiate a scan of legacy customer contracts stored in a specified SharePoint library to detect and classify sensitive information such as account numbers or contact information. If these newly classified documents match the classifiers included in any existing auto-labeling policies, they will be automatically labeled. This helps ensure that documents containing sensitive information remain protected when they are referenced in Microsoft 365 Copilot interactions. Learn More. Security teams can trigger on-demand classification scan results in the oversharing assessment in Purview DSPM for AI. Secure and govern data in Security Copilot and Copilot in Fabric: We are excited to announce the public preview of Purview for Security Copilot and Copilot in Fabric, starting with Copilot in Power BI, offering DSPM for AI, Insider Risk Management, and data compliance controls, including eDiscovery, Audit, Data Lifecycle Management, and Communication Compliance. These capabilities will help organizations enhance data security posture, manage compliance, and mitigate risks more effectively. For example, admins can now use DSPM for AI to discover sensitive data in user prompts and responses and detect unethical or risky AI usage. Purview’s DSPM for AI provides admins with comprehensive reports on user activities and data interactions in Copilot for Power BI, as part of the Copilot in Fabric experience, and Security Copilot. DSPM Discoverability for Communication Compliance: This new feature in Communication Compliance, which will be available in public preview starting May 1, enables organizations to quickly create policies that detect inappropriate messages that could lead to data compliance risks. The new recommendation card on the DSPM for AI page offers a one-click policy creation in Microsoft Purview Communication Compliance, simplifying the detection and mitigation of potential threats, such as regulatory violations or improperly shared sensitive information. With these enhanced capabilities for securing and governing data in Microsoft 365 Copilot and beyond, organizations can confidently embrace AI innovation while maintaining strict security and compliance standards. Explore additional resources As organizations embrace AI, securing and governing its use is more important than ever. Staying informed and equipped with the right tools is key to navigating its challenges. Explore these resources to see how Microsoft Security can help you confidently adopt AI in your organization. Learn more about Security for AI solutions on our webpage Get started with Microsoft Purview Get started with Microsoft Defender for Cloud Sign up for a free Microsoft 365 E5 Security Trial and Microsoft Purview Trial Learn more about the innovations designed to help your organization protect data, defend against cyber threats, and stay compliant. Join Microsoft leaders online at Microsoft Secure on April 9. [1] 2024 Work Trend Index Annual Report, Microsoft and LinkedIn, May 2024, N=31,000. [2] Gartner®, Gartner Peer Community Poll – If your org’s using any virtual assistants with AI capabilities, are you concerned about indirect prompt injection attacks? 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