Bitlocker TPM+PIN - Safety only when TPM is safe?
Hello, i habe read the microsoft docs about Bitlocker on Windows 11. At the moment i understand, that the feature TPM+PIN ask for a PIN at startup. From the PIN Bitlocker creates a SHA-256 Hash and use only 160Bit for Authentication with the TPM. Are the PCR Register and the PIN is correct, the TPM give Bitlocker the Authenticationcode free and Bitlocker can unecrypt der Disk. The safety of this require the safety from the TPM. Is the safety of the TPM compromised, than Bitlocker is unsafe, too. Knowledge of the PIN can be unnecessary. Why Bitlocker don’t use the 96bit from the Hash, strechted the 96 Bit with a salt (saved on the unencrypted disk space), use a cryptographic safe hash function (e.g. Argon2id) and use this hash XOR with the TPM set free Authenticationcode as key for the master key? Steps: PIN from user -> SHA-256 -> 160 bit for TPM S1 and 96Bit for the second half of the master key. -> Argon2id( 96bit ) S2 -> S1 XOR S2 -> Master key. Pro: If someone can crack the TPM the attacker has only the half of the Masterkey. Cons: little more calculation steps. This make the safety better, because it need knowledge and hardware security. What do you think about it? Sincerely yours, ElGuy
Edge on Android: Syncs personal data (e.g. history, payment methods), despite me turning them off
Sync settings chosen during first-run setup are ignored. All sync types get turned on. Steps taken Install Outlook. (Link: https://play.google.com/store/apps/details?id=com.microsoft.office.outlook ) Sign in to Outlook. Uninstall and re-install Edge. (Link: https://play.google.com/store/apps/details?id=com.microsoft.emmx ) Choose whether to set Edge as default browser. Tap the tiny blue text, which says "Sync settings". (Not the tiny blue text immediately underneath, which says "Microsoft Privacy Statement"). All sync types are turned on by default. Turn off all sync items except one, e.g. Passwords. Dismiss "Sync settings" Re-open "Sync settings", to confirm your settings are still there. Then dismiss it again. Sign in, or "Continue". Continue setting up Edge. Open the Edge menu. Tap your account Tap Sync. Result: ALL sync items are turned on, despite having turned them off in step 6. Request Is this bug fixed, in a later version of Edge? Note: This bug does not fit in the official feedback method for Edge for Android. I am hoping the helpful elves at the other end of the Edge feedback form are reading this question. Because I have sent them the link to https://learn.microsoft.com/en-us/answers/questions/6035494/edge-on-android-syncs-personal-data-history-paymen. My environment Google Pixel 10a Android 17 Edge version 155.0.4283.48 (also reproduced with earlier version: 154.0.4258.38) OR Edge Canary version 157.0.4338.0 (Downloaded 2026-10-19)
How do you handle sensitive PDF files in Edge without third-party cloud uploads?
Hi everyone, When working with sensitive PDF documents (like financial or personal files), most online PDF editors require uploading files to third-party cloud servers. This raises obvious privacy and security concerns for many users. The most reliable way to maintain data privacy today is using Client-Side Browser Processing (WebAssembly & JavaScript), where operations run entirely inside the local browser memory without transmitting any data over the internet. Key advantages of pure client-side processing: Total Privacy: Zero file transfers or external server logs. Instant Speed: Processing relies on your local CPU, bypassing slow upload/download waiting times. No Software Installation: Works directly inside browsers like Microsoft Edge. For those looking for a practical example of this architecture, https://pdfdocflow.com is a free tool offering 24 browser-based tools (merging, splitting, compressing, watermarking, and signing) operating 100% locally with zero server uploads. How do you usually handle sensitive PDFs while browsing, and do you prefer client-side web tools over installing dedicated software?
Outlook on Windows 11: when local sync re‑contaminates global settings
Introduction I want to share a finding that I believe is concerning: the Outlook client on Windows 11 can act as a vector of “re‑contamination” of local data, reactivating settings that were already disabled in the cloud. While this is not malware in the strict sense, the behavior is contradictory enough that it undermines privacy and user trust. Context of the issue To avoid any doubt, I disabled the Expanded People Suggestions option in all three possible places: Outlook client on Windows 11. Outlook Web. Global Privacy settings in my Microsoft Account. In every case, the option was disabled and the exported configuration file appeared empty, confirming that the deletion had been applied correctly. Cross‑account contamination → when another account was added to the Outlook client, the contaminated suggestions were transferred and appeared in that account as well, even though those addresses had never been used there. Evidence observed Empty file in the cloud → confirms that the deletion was effective. Desktop client re‑sync → uploads obsolete local data and reactivates the option. Result → the global configuration once again shows suggestions that had already been disabled. Injected email addresses → the suggestions included addresses that I have never used or contacted. These appear to have been introduced by third parties or internal contamination, not by my own activity. Cross‑account contamination → when another account was added to the Outlook client, the contaminated suggestions were transferred and appeared there too. Implications The Outlook client does not respect privacy preferences set in the cloud. Local data takes precedence over global settings, which contradicts modern synchronization logic. The presence of never‑used, injected email addresses raises serious concerns about data integrity and possible external contamination. This may affect many users, not just an isolated case. Reflection This behavior creates the perception that the client acts like intrusive software: even if the user deletes data in the cloud, the client “resurrects” it from its local cache. In practical terms, it is a form of re‑contamination that compromises confidence in synchronization between client and server. The fact that injected addresses appear in suggestions makes the issue even more problematic, as it suggests external influence beyond the user’s own history. Conclusion The cloud should be the source of truth. If a user disables data in Outlook Web and in the global Microsoft Account settings, no local client should have the ability to reactivate it. This finding deserves attention because it directly affects privacy, data integrity, and the coherence of the Microsoft ecosystem. Invitation Has anyone else observed this behavior in Outlook for Windows 11? Have you seen deleted cloud settings reappear after reinstalling or re‑synchronizing the client, or injected email addresses that were never used showing up in suggestions?Authorization and Identity Governance Inside AI Agents
Designing Authorization‑Aware AI Agents Enforcing Microsoft Entra ID RBAC in Copilot Studio As AI agents move from experimentation to enterprise execution, authorization becomes the defining line between innovation and risk. AI agents are rapidly evolving from experimental assistants into enterprise operators—retrieving user data, triggering workflows, and invoking protected APIs. While many early implementations rely on prompt‑level instructions to control access, regulated enterprise environments require authorization to be enforced by identity systems, not language models. This article presents a production‑ready, identity‑first architecture for building authorization‑aware AI agents using Copilot Studio, Power Automate, Microsoft Entra ID, and Microsoft Graph, ensuring every agent action executes strictly within the requesting user’s permissions. Why Prompt‑Level Security Is Not Enough Large Language Models interpret intent—they do not enforce policy. Even the most carefully written prompts cannot: Validate Microsoft Entra ID group or role membership Reliably distinguish delegated user identity from application identity Enforce deterministic access decisions Produce auditable authorization outcomes Relying on prompts for authorization introduces silent security failures, over‑privileged access, and compliance gaps—particularly in Financial Services, Healthcare, and other regulated industries. Authorization is not a reasoning problem. It is an identity enforcement problem. Common Authorization Anti‑Patterns in AI Agents The following patterns frequently appear in early AI agent implementations and should be avoided in enterprise environments: Hard‑coded role or group checks embedded in prompts Trusting group names passed as plain‑text parameters Using application permissions for user‑initiated actions Skipping verification of the user’s Entra ID identity Lacking an auditable authorization decision point These approaches may work in demos, but they do not survive security reviews, compliance audits, or real‑world misuse scenarios. Authorization‑Aware Agent Architecture In an authorization‑aware design, the agent never decides access. Authorization is enforced externally, by identity‑aware workflows that sit outside the language model’s reasoning boundary. High‑Level Flow The Copilot Studio agent receives a user request The agent passes the User Principal Name (UPN) and intended action A Power Automate flow validates permissions using Microsoft Entra ID via Microsoft Graph Only authorized requests are allowed to proceed Unauthorized requests fail fast with a deterministic outcome Authorization‑aware Copilot Studio architecture enforces Entra ID RBAC before executing any business action. The agent orchestrates intent. Identity systems enforce access. Enforcing Entra ID RBAC with Microsoft Graph Power Automate acts as the authorization enforcement layer: Resolve user identity from the supplied UPN Retrieve group or role memberships using Microsoft Graph Normalize and compare memberships against approved RBAC groups Explicitly deny execution when authorization fails This keeps authorization logic: Centralized Deterministic Auditable Independent of the AI model Reference Implementation: Power Automate RBAC Enforcement Flow The following import‑ready Power Automate cloud flow demonstrates a secure RBAC enforcement pattern for Copilot Studio agents. It validates Microsoft Entra ID group membership before allowing any business action. Scenario Trigger: User‑initiated agent action Identity model: Delegated user identity Input: userUPN, requestedAction Outcome: Authorized or denied based on Entra ID RBAC { "$schema": "https://schema.management.azure.com/providers/Microsoft.Logic/schemas/2016-06-01/workflowdefinition.json#", "contentVersion": "1.0.0.0", "triggers": { "Copilot_Request": { "type": "Request", "kind": "Http", "inputs": { "schema": { "type": "object", "properties": { "userUPN": { "type": "string" }, "requestedAction": { "type": "string" } }, "required": [ "userUPN" ] } } } }, "actions": { "Get_User_Groups": { "type": "Http", "inputs": { "method": "GET", "uri": "https://graph.microsoft.com/v1.0/users/@{triggerBody()?['userUPN']}/memberOf?$select=displayName", "authentication": { "type": "ManagedServiceIdentity" } } }, "Normalize_Group_Names": { "type": "Select", "inputs": { "from": "@body('Get_User_Groups')?['value']", "select": { "groupName": "@toLower(item()?['displayName'])" } }, "runAfter": { "Get_User_Groups": [ "Succeeded" ] } }, "Check_Authorization": { "type": "Condition", "expression": "@contains(body('Normalize_Group_Names'), 'ai-authorized-users')", "runAfter": { "Normalize_Group_Names": [ "Succeeded" ] }, "actions": { "Authorized_Action": { "type": "Compose", "inputs": "User authorized via Entra ID RBAC" } }, "else": { "actions": { "Access_Denied": { "type": "Terminate", "inputs": { "status": "Failed", "message": "Access denied. User not authorized via Entra ID RBAC." } } } } } } } This pattern enforces authorization outside the agent, aligns with Zero Trust principles, and creates a clear audit boundary suitable for enterprise and regulated environments. Flow Diagram: Agent Integrated with RBAC Authorization Flow and Sample Prompt Execution: Delegated vs Application Permissions Scenario Recommended Permission Model User‑initiated agent actions Delegated permissions Background or system automation Application permissions Using delegated permissions ensures agent execution remains strictly within the requesting user’s identity boundary. Auditing and Compliance Benefits Deterministic and explainable authorization decisions Centralized enforcement aligned with identity governance Clear audit trails for security and compliance reviews Readiness for SOC, ISO, PCI, and FSI assessments Enterprise Security Takeaways Authorization belongs in Microsoft Entra ID, not prompts AI agents must respect enterprise identity boundaries Copilot Studio + Power Automate + Microsoft Graph enable secure‑by‑design AI agents By treating AI agents as first‑class enterprise actors and enforcing authorization at the identity layer, organizations can scale AI adoption with confidence, trust, and compliance.Fake Employees, Real Threat: Decentralized Identity to combat Deepfake Hiring?
In recent months, cybersecurity experts have sounded the alarm on a surge of fake “employees” – job candidates who are not who they claim to be. These fraudsters use everything from fabricated CVs and stolen identities to AI-generated deepfake videos in interviews to land jobs under false pretenses. It’s a global phenomenon making headlines on LinkedIn and in the press. With the topic surfacing everywhere, I wanted to take a closer look at what’s really going on — and explore the solutions that could help organizations respond to this growing challenge. And as it happens, one solution is finally reaching maturity at exactly the right moment: decentralized identity. Let me walk you through it. But first, let’s look at a few troubling facts: Even tech giants aren’t immune. Amazon’s Chief Security Officer revealed that since April 2024 the company has blocked over 1,800 suspected North Korean scammers from getting hired, and that the volume of such fake applicants jumped 27% each quarter this year (1.1). In fact, a coordinated scheme involving North Korean IT operatives posing as remote workers has infiltrated over 300 U.S. companies since 2020, generating at least $6.8 million in revenue for the regime (2.1). CrowdStrike also reported more than 320 confirmed incidents in the past year alone, marking a 220% surge in activity (2.2). And it’s not just North Korea: organised crime groups globally are adopting similar tactics. This trend is not a small blip; it’s likely a sign of things to come. Gartner predicts that by 2028, one in four job applicant profiles could be fake in some way (3). Think about that – in a few years, 25% of the people applying to your jobs might be bots or impostors trying to trick their way in. We’re not just talking about exaggerated resumes; we’re talking about full-scale deception: people hiring stand-ins for interviews, AI bots filling out assessments, and deepfake avatars smiling through video calls. It’s a hiring manager’s nightmare — no one wants to waste time interviewing bots or deepfakes — and a CISO’s worst-case scenario rolled into one. The Rise of the Deepfake Employee What does a “fake employee” actually do? In many cases, these impostors are part of organized schemes (even state-sponsored) to steal money or data. They might forge impressive résumés and create a minimal but believable online presence. During remote interviews, some have been caught using deepfake video filters – basically digital masks – to appear as someone else. In one case, Amazon investigators noticed an interviewee’s typing did not sync with the on-screen video (the keystrokes had a 110ms lag); it turned out to be a North Korean hacker remotely controlling a fake persona on the video call (1.2). Others refuse video entirely, claiming technical issues, so you only hear a voice. Some even hire proxy interviewees – a real person who interviews in their place. The level of creativity is frightening. Once inside, a fake employee can do serious damage. They gain legitimate access to internal systems, data, and tools. Some have stolen sensitive source code and threatened to leak it unless the company paid a ransom (1). Others quietly set up backdoor access for future cyberattacks. And as noted, if they’re part of a nation-state operation, the salary you pay them is funding adversaries. The U.S. Department of Justice recently warned that many North Korean IT workers send the majority of their pay back to the regime’s illicit weapons programs (1)(2.3). Beyond the financial angle, think of the security breach: a malicious actor is now an “insider” with an access badge. No sector is safe. While tech companies with lots of remote jobs were the first targets, the scam has expanded. According to the World Economic Forum, about half of the companies targeted by these attacks aren’t in the tech industry at all (4). Financial services, healthcare, media, energy – any business that hires remote freelancers or IT staff could be at risk. Many Fortune 500 firms have quietly admitted to Charles Carmakal (Chief Technology Officer at Google Cloud’s Mandiant) that they’ve encountered fake candidates (2.3). Brandon Wales — former Executive Director of the Cybersecurity and Infrastructure Security Agency (CISA) and now VP of Cybersecurity Strategy at SentinelOne — warned that the “scale and speed” of these operations is unlike anything seen before (2.3). Rivka Little, Chief Growth Officer at Socure, put it bluntly: “Every Fortune 100 and potentially Fortune 500 has a pretty high number of risky employees on their books” right now (1). If you’re in charge of security or IT, this should send a chill down your spine. How do you defend against an attack that walks in through your front door (virtually) with HR’s approval? It calls for rethinking some fundamental practices, which leads us to the biggest gap these scams have exposed: identity verification in the hiring process. The Identity Verification Gap in Hiring Let’s face it: traditional hiring and onboarding operate on a lot of trust. You collect a résumé, maybe call some references, do a background check that might catch a criminal record but won’t catch a well-crafted fake identity. You might ask for a copy of a driver’s license or passport to satisfy HR paperwork, but how thoroughly is it checked? And once the person is hired and given an employee account, how often do we re-confirm that person’s identity in the months or years that follow? Almost never. Now let’s look at the situation from the reverse perspective: During your last recruitment, or when you became a new vendor for a client, were you asked to send over a full copy of your ID via email? Most likely, yes. You send a scan of your passport or ID card to an HR representative or a partner’s portal, and you have no idea where that image gets stored, who can see it, or how long it will sit around. It feels uncomfortable, but we do it because we need to prove who we are. In reality, we’re making a leap of faith that the process is secure. This is the identity verification gap. Companies are trusting documents and self-assertions that can be forged, and they rarely have a way to verify those beyond a cursory glance. Fraudsters exploit this gap mercilessly. They provide fake documents that look real, or steal someone else’s identity details to pass background checks. Once they’ve cleared that initial hurdle, the organization treats them as legit. IT sets up accounts, security gives them access, and from then on the “user identity” is assumed to be genuine. Forever. Moreover, once an employee is on board, internal processes often default to trust. Need a password reset? The helpdesk might ask for your birthdate or employee ID – pieces of info a savvy attacker can learn or steal. We don’t usually ask an employee who calls IT to re-prove that they are the same person HR hired months or years ago. All of this stands in contrast to the principle of Zero Trust security that many companies are now adopting. Thanks to John Kindervag (Forrester, 2009), Zero Trust says “never trust, always verify” each access request. But how can you verify if the underlying identity was fake to start with? As part of Microsoft, we often say that “identity is the new perimeter” – meaning the primary defense line is verifying identities, not just securing network walls. If that identity perimeter is built on shaky ground (unverified people), the whole security model is weak. So, what can be done? Security leaders and even the World Economic Forum are advocating for stronger identity proofing in hiring. The WEF specifically recommends “verifiable government ID checks at multiple stages of recruitment and into employment” (4). In other words, don’t just verify once and forget it – verify early, verify often. That might mean an ID and background check when offering the job, another verification during onboarding, and perhaps periodic re-checks or at least on certain events (like when the employee requests elevated privileges). Amazon’s CSO, S. Schmidt, echoed this after battling North Korean fakes; he advised companies to “Implement identity verification at multiple hiring stages and monitor for anomalous technical behavior” as a key defense (1). Of course, doing this manually is tough. You can’t very well ask each candidate to fly in their first day just to show their passport in person, especially with global and remote workforces. That’s where technology is stepping up. Enter the world of Verified ID and decentralized identity. Enter Microsoft Entra Verified ID: proving Identity, not just Checking a Box Imagine if, instead of emailing copies of your passport to every new employer or partner, you could carry a digital identity credential that is already verified and can be trusted by others instantly. That’s the idea behind Microsoft Entra Verified ID. It’s essentially a system for issuing and verifying cryptographically-secure digital identity credentials. Let’s break down what that means in plain terms. At its core, a Verified ID credential is like a digital ID card that lives in an app on your phone. But unlike a photocopy of your driver’s license (which anyone could copy, steal or tamper with), this digital credential is signed with cryptographic keys that make it tamper-proof and verifiable. It’s based on open standards. Microsoft has been heavily involved in the development of Decentralized Identifiers (DID) and W3C Verifiable Credentials standards over the past few years (7). The benefit of standards is that this isn’t a proprietary Microsoft-only thing – it’s part of a broader move toward decentralized identity, where the user is in control of their own credentials. Here’s a real-life analogy: When you go to a bar and need to prove you’re over 18, you show your driver’s license, National ID or Passport. The bouncer checks your birth date and maybe the hologram, but they don’t photocopy your entire ID and keep it; they just verify it and hand it back. You remain in possession of your ID. Now translate that to digital interactions: with Verified ID, you could have a credential on your phone that says “Government ID verified: [Your Name], age 25”. When a verifier (like an employer or service) needs proof, you share that credential through a secure app. The verifier’s system checks the credential’s digital signature to confirm it was issued by a trusted authority (for example, a background check company or a government agency) and that it hasn’t been altered. You don’t have to send over a scan of your actual passport or reveal extra info like your full birthdate or address – the credential can be designed to reveal only the necessary facts (e.g. “is over 18” = yes). This concept is called selective disclosure, and it’s a big win for privacy. Crucially, you decide which credentials to share and with whom. You might have one that proves your legal name and age (from a government issuer), another that proves your employment status (from your employer), another that proves a certification or degree (from a university). And you only share them when needed. They can also have expiration dates or be revoked. For instance, an employment credential could automatically expire when you leave the company. This means if someone tries to use an old credential, it would fail verification – another useful security feature. Now, how do these credentials get issued in the first place? This is where the integration of our Microsoft Partner IDEMIA comes in, which was a highlight of Microsoft Ignite 2025. IDEMIA is a company you might not have heard of, but they’re a huge player in the identity world – they’re the folks behind many government ID and biometric systems (think passport chips, national ID programs, biometric border control, etc.). Microsoft announced that Entra Verified ID now integrate IDEMIA’s identity verification services. In practice, this means when you need a high-assurance credential (like proving your real identity for a job), the system can invoke IDEMIA to do a thorough check. For example, as part of a remote onboarding process, an employer using Verified ID could ask the new hire to verify their identity through IDEMIA. The new hire gets a link or prompt, and is guided to scan their official government ID and take a live selfie video. IDEMIA’s system checks that the ID is authentic (not a forgery) and matches the person’s face, doing so in a privacy-protecting way (for instance, biometric data might be used momentarily to match and then not stored long-term, depending on the service policies). This process confirms “Yes, this is Alice, and we’ve confirmed her identity with a passport and live face check.” At that point, Microsoft Entra Verified ID can issue a credential to Alice, such as “Alice – identity verified by Contoso Corp on [Date]”. Alice stores this credential in her digital wallet (for instance, the Microsoft Authenticator app). Now Alice can present that credential to apps or IT systems to prove it’s really Alice. The employer might require it to activate her accounts, or later if Alice calls IT support, they might ask her to present the credential to prove her identity for a password reset. The verification of the credential is cryptographically secure and instantaneous – the IT system just checks the digital signature. There’s no need to manually pull up Alice’s passport scan from HR files or interrogate her with personal questions. Plus, Alice isn’t repeatedly sending sensitive personal documents; she shared them once with a trusted verifier (IDEMIA via the Verified ID app flow), not with every individual who asks for ID. This reduces the exposure of her personal data. From the company’s perspective, this approach dramatically improves security and streamlines processes. During onboarding, it’s actually faster to have someone go through an automated ID verification flow than to coordinate an in-person verification or trust slow manual checks. Organizations also avoid collecting and storing piles of personal documents, which is a compliance headache and a breach risk. Instead, they get a cryptographic assurance. Think of it like the difference between keeping copies of everyone’s credit card versus using a payment token – the latter is safer and just as effective for the transaction. Microsoft has been laying the groundwork for this for years. Back in 2020 (and even 2017....), Microsoft discussed decentralized identity concepts where users own their identity data and apps verify facts about you through digital attestations (7). Now it’s reality: Entra Verified ID uses those open standards (DID and Verifiable Credentials) under the hood. Plus, the integration with IDEMIA and others means it’s not just theoretical — it’s operational and scalable. As Ankur Patel, one of our product leaders for Microsoft Entra, said about these integrations: it enables “high assurance verification without custom business contracts or technical implementations” (6). In other words, companies can now easily plug this capability in, rather than building their own verification processes from scratch. Before moving on, let’s not forget to include the promised quote from IDEMIA’s exec that really underscores the value: “With more than 40 years of experience in identity issuance, verification and advanced biometrics, our collaboration with Microsoft enables secure authentication with verified identities organizations can rely on to ensure individuals are who they claim to be and critical services can be accessed seamlessly and securely.” – Amit Sharma, Head of Digital Strategy, IDEMIA (6) That quote basically says it all: verified identities that organizations can rely on, enabling seamless and secure access. Now, let’s see how that translates into real-world usage. Use Cases and Benefits: From Onboarding to Recovery How can Verified ID (plus IDEMIA’s) be applied in day-to-day business? There are several high-impact use cases: Remote Employee Onboarding (aka Hire with Confidence): This is the most straightforward scenario. When bringing in a new hire you haven’t met in person, you can integrate an identity verification step. As described earlier, the new employee verifies their government ID and face once, gets a credential, and uses that to start their work. The hiring team can trust that “this person is real and is who they say they are.” This directly prevents many fake-employee scams. In fact, some companies have already tried informal versions of this: The Register reported a story of an identity verification company (ironically) who, after seeing suspicious candidates, told one applicant “next interview we’ll do a document verification, it’s easy, we’ll send you a barcode to scan your ID” – and that candidate never showed up for the next round because they knew they’d be caught (1). With Verified ID, this becomes a standard, automated part of the process, not an ad-hoc test. As a bonus, the employee’s Verified ID credential can also speed up IT onboarding (auto-provisioning accounts when the verified credential is presented) and even simplify things like proving work authorization to other services (think how you often have to send copies of IDs to benefits providers or background screeners – a credential could replace that). The new hire starts faster, and with less anxiety because they know there’s a strong proof attached to their identity, and the company has less risk from day one. Oh, and HR isn’t stuck babysitting sensitive documents – governance and privacy risk go down. Stronger Helpdesk and Support Authentication: Helpdesk fraud is a common way attackers exploit weak verification. Instead of asking employees for their first pet’s name or a short code (which an attacker might phish), support can use Verified ID to confirm the person’s identity. For example, if someone calls IT saying “I’m locked out of my account,” the support portal can send a push notification asking the user to present their Verified Employee credential or do a quick re-verify via the app. If the person on the phone is an impostor, they’ll fail this check. If it’s the real employee, it’s an easy tap on their phone to prove it’s them. This approach secures processes like password resets, unlocking accounts, or granting temporary access. Think of it as caller-ID on steroids. Instead of taking someone’s word that “I am Alice from Finance,” the system actually asks for proof. And because the proof is cryptographically verified, it’s much harder to trick than a human support agent with a sob story. This reduces the burden on support too – less time playing detective with personal questions, more confidence in automating certain requests. Account Recovery and On-Demand Re-Verification: We’ve all dealt with the hassle of account recovery when we lose a password or device. Often it’s a weak link: backup codes, personal Q&A, the support team asking some manager who can’t even tell if it’s really you, or asking for a copy of your ID… With Verified ID, organizations can offer a secure self-service recovery that doesn’t rely on shared secrets. For instance, if you lose access to your multi-factor auth and need to regain entry, you could be prompted to verify your identity with a government ID check through the Verified ID system. Once you pass, you might be allowed to reset your authentication methods. Microsoft is already moving in this direction – there’s talk of replacing security questions with Verified ID checks for Entra ID account recovery (6). The benefit here is you get high assurance that the person recovering the account is the legitimate owner. This is especially important for administrators or other highly privileged users. And it’s still faster for the user than, say, waiting days for IT to manual vet and approve a request. Additionally, companies could have policies where every X months, employees might get a prompt to reaffirm their identity if they’re engaging in sensitive work. It keeps everyone honest and catches any anomalies (like, imagine an attacker somehow compromised an account – when faced with an unexpected ID check, they wouldn’t be able to comply, raising a red flag). Step-Up Authentication for Sensitive Actions: Not every action an employee takes needs this level of verification, but some absolutely do. For example, a finance officer making a $10 million wire transfer, or an engineer pushing code to a production environment, or an HR admin downloading an entire employee database – these could all trigger a step-up authentication that includes verifying the user’s identity credential. In practice, the user might get a pop-up saying “Please present your Verified ID to continue.” It might even ask for a quick fresh selfie depending on the sensitivity, which can be matched against the one on file (using Face Match in a privacy-conscious way). This is like saying: “We know you logged in with your password and MFA earlier, but this action is so critical that we want to double-check you are still the one executing it – not someone who stole your session or is using your computer.” It’s analogous to how some banks send a one-time code for high-value transactions, but instead of just a code (which could be stolen), it’s verifying you. This dramatically reduces the risk of insider threats and account takeovers causing catastrophic damage. And for the user, it’s usually a simple extra step that they’ll understand the importance of, especially in high-stakes fields. It builds trust – both that the company trusts them enough to give access, but also verifies them to ensure no one is impersonating them. In all these cases, Verified ID is adding security without a huge usability cost. In fact, many users might prefer it to the status quo: I’d rather verify my identity once properly than have to answer a bunch of security questions or have an IT person eyeballing my ID over a grainy video call. It also introduces transparency and control. As an employee, if I’m using a Verified ID, I know exactly what credential I’m sharing and why, and I have a log of it. It’s not an opaque process where I send documents into a void. From a governance perspective, using Verified ID means less widespread personal data to protect, and a clearer audit trail of “this action was taken by Alice, whose identity was verified by method X at time Y.” It can even help with regulatory compliance – for instance, proving that you really know who has access to sensitive financial data (important for things like SOX compliance or other audits). And circling back to the theme of fake employees, if such a system is in place, it’s a massive deterrent. The barrier to entry for fraudsters becomes much higher. It’s not impossible (nothing is, and you still need to Assume breach), but now they’d have to fool a top-tier document verification and biometric check – not just an overworked recruiter. That likely requires physical presence and high-quality fake documents, which are riskier and more costly for attackers. The more companies adopt such measures, the less “return on investment” these hiring scams will have for cybercriminals. The Bigger Picture: Verified Identity as the New Security Frontier The convergence of trends here is interesting. On one hand, we have digital transformation and remote work which opened the door to these novel attacks. On the other hand, we have new security philosophies like Zero Trust that emphasize continuous verification of identity and context. Verified ID is essentially Zero Trust for the hiring and identity side of things: “never trust an identity claim, always verify it.” What’s exciting is that this can now be done without turning the enterprise into a surveillance state or creating unbearable friction for legitimate users. It leverages cryptography and user-centric design to raise security and preserve privacy. Microsoft’s involvement in decentralized identity and the integration of partners like IDEMIA signals that this approach is maturing. It’s moving from pilot projects to being built into mainstream products (Entra ID, Microsoft 365, LinkedIn even offers verification badges via Entra Verified ID now (5)). It’s worth noting LinkedIn’s angle here: job seekers can verify where they work or their government ID on their LinkedIn profile, which could also help employers spot fakes (though it’s voluntary and early-stage). For CISOs and identity architects, Verified ID offers a concrete tool to address what was previously a very squishy problem. Instead of just crossing your fingers that employees are who they say they are, you can enforce it. It’s analogous to the evolution of payments security: we moved from signatures (which were rarely checked) to PIN codes and chips, and now to contactless cryptographic payments. Hiring and access management can undergo a similar upgrade from assumption-based to verification-based. Of course, adopting Verified ID or any new identity tech requires planning. Organizations will need to update their onboarding processes, train HR and IT staff on the new procedure, and ensure employees are comfortable with it. Privacy considerations must be addressed (e.g., clarify that biometric data used for verification isn’t stored indefinitely, etc.). But compared to the alternative – doing nothing and hoping to avoid being the next company in a scathing news headline about North Korean fake workers – the effort is worthwhile. In summary, human identity has become the new primary perimeter for cybersecurity. We can build all the firewalls and endpoint protections we want, but if a malicious actor can legitimately log in through the front door as an employee, those defenses may not matter. Verified identity solutions like Microsoft Entra Verified ID (with partners like IDEMIA) provide a way to fortify that perimeter with strong, real-time checks. They bring trust back into remote interactions by shifting from “trust by default” to “trust because verified.” This is not just a theoretical future; it’s happening now. As of late 2025, these tools are generally available and being rolled out in enterprises. Early adopters will likely be those in highly targeted sectors or with regulatory pressures – think defense contractors, financial institutions, and tech companies burned by experience. But I suspect it will trickle into standard best practices over the next few years, much like multi-factor authentication did. The fight against fake employees and deepfake hiring scams will continue, and attackers will evolve new tricks (perhaps trying to fake the verifications themselves). But having this layer in place tilts the balance back in favor of the defenders. It forces attackers to take more risks and expend more resources, which in turn dissuades many from even trying. To end on a practical note: If you’re a security decision-maker, now is a good time to evaluate your organization’s hiring and identity verification practices. Conduct a risk assessment – do you have any way to truly verify a new remote hire’s identity? How confident are you that all your current employees are real? If those questions make you uncomfortable, it’s worth looking into solutions like Verified ID. We’re entering an era where digital identity proofing will be as standard as background checks in HR processes. The technology has caught up to the threat, and embracing it could save your company from a very costly “lesson learned.” Remember: trust is good, but verified trust is better. By making identity verification a seamless part of the employee lifecycle, we can help ensure that the only people on the payroll are the ones we intended to hire. In a world of sophisticated fakes, that confidence is priceless. Sources: (1.1) The Register – Amazon blocked 1,800 suspected North Korean scammers seeking jobs (Dec 18, 2025) – S. Schmidt comments on DPRK fake workers and advises multi-stage identity verification. https://www.theregister.com/2025/12/18/amazon_blocked_fake_dprk_workers ("We believe, at this point, every Fortune 100 and potentially Fortune 500 has a pretty high number of risky employees on their books" Socure Chief Growth Officer Rivka Little) & https://www.linkedin.com/posts/stephenschmidt1_over-the-past-few-years-north-korean-dprk-activity-7407485036142276610-dot7 (“Implement identity verification at multiple hiring stages and monitor for anomalous technical behavior”, Amazon’s CSO, S. Schmidt) | (1.2) Heal Security – Amazon Catches North Korean IT Worker by Tracking Tiny 110ms Keystroke Delays (Dec 19, 2025). https://healsecurity.com/amazon-catches-north-korean-it-worker-by-tracking-tiny-110ms-keystroke-delays/ (2.1) U.S. Department of Justice – “Charges and Seizures Brought in Fraud Scheme Aimed at Denying Revenue for Workers Associated with North Korea” (May 16, 2024). https://www.justice.gov/usao-dc/pr/charges-and-seizures-brought-fraud-scheme-aimed-denying-revenue-workers-associated-north | (2.2) PCMag – “Remote Scammers Infiltrate 300+ Companies” (Aug 4, 2025). https://www.pcmag.com/news/is-your-coworker-a-north-korean-remote-scammers-infiltrate-300-plus-companies | (2.3) POLITICO – Tech companies have a big remote worker problem: North Korean operatives (May 12 2025). https://www.politico.com/news/2025/05/12/north-korea-remote-workers-us-tech-companies-00340208 ("I’ve talked to a lot of CISOs at Fortune 500 companies, and nearly every one that I’ve spoken to about the North Korean IT worker problem has admitted they’ve hired at least one North Korean IT worker, if not a dozen or a few dozen,” Charles Carmakal, Chief Technology Officer at Google Cloud’s Mandiant) & North Koreans posing as remote IT workers infiltrated 136 U.S. companies (Nov 14, 2025). https://www.politico.com/news/2025/11/14/north-korean-remote-work-it-scam-00652866 HR Dive – By 2028, 1 in 4 candidate profiles will be fake, Gartner predicts (Aug 8, 2025) – Gartner research highlighting rising candidate fraud and 25% fake profile forecast. https://www.hrdive.com/news/fake-job-candidates-ai/757126/ World Economic Forum – Unmasking the AI-powered, remote IT worker scams threatening businesses (Dec 15, 2025) – Overview of deepfake hiring threats; recommends government ID checks at multiple hiring stages. https://www.weforum.org/stories/2025/12/unmasking-ai-powered-remote-it-worker-scams-threatening-businesses-worldwide/ The Verge – LinkedIn gets a free verified badge that lets you prove where you work (Apr 2023) – Describes LinkedIn’s integration with Microsoft Entra for profile verification. https://www.theverge.com/2023/4/12/23679998/linkedin-verification-badge-system-clear-microsoft-entra Microsoft Tech Community – Building defense in depth: Simplifying identity security with new partner integrations (Nov 24, 2025 by P. Nrisimha) – Microsoft Entra blog announcing Verified ID GA, includes IDEMIA integration and quotes (Amit Sharma, Ankur Patel). https://techcommunity.microsoft.com/t5/microsoft-entra-blog/building-defense-in-depth-simplifying-identity-security-with-new/ba-p/4468733 & https://www.linkedin.com/posts/idemia-public-security_synced-passkeys-and-high-assurance-account-activity-7407061181879709696-SMi7 & https://www.linkedin.com/posts/4ankurpatel_synced-passkeys-and-high-assurance-account-activity-7406757097578799105-uFZz ("high assurance verification without custom business contracts or technical implementations", Ankur Patel) Microsoft Entra Blog – Building trust into digital experiences with decentralized identities (June 10, 2020 by A. Simons & A. Patel) – Background on Microsoft’s approach to decentralized identity (DID, Verifiable Credentials). https://techcommunity.microsoft.com/t5/microsoft-entra-blog/building-trust-into-digital-experiences-with-decentralized/ba-p/1257362 & Decentralized digital identities and blockchain: The future as we see it. https://www.microsoft.com/en-us/microsoft-365/blog/2018/02/12/decentralized-digital-identities-and-blockchain-the-future-as-we-see-it/ & Partnering for a path to digital identity (Janv 22, 2018) https://blogs.microsoft.com/blog/2018/01/22/partnering-for-a-path-to-digital-identity/ About the Author I'm Samuel Gaston-Raoul, Partner Solution Architect at Microsoft, working across the EMEA region with the diverse ecosystem of Microsoft partners—including System Integrators (SIs) and strategic advisory firms, Independent Software Vendors (ISVs) / Software Development Companies (SDCs), and Startups. I engage with our partners to build, scale, and innovate securely on Microsoft Cloud and Microsoft Security platforms. With a strong focus on cloud and cybersecurity, I help shape strategic offerings and guide the development of security practices—ensuring alignment with market needs, emerging challenges, and Microsoft’s product roadmap. I also engage closely with our product and engineering teams to foster early technical dialogue and drive innovation through collaborative design. Whether through architecture workshops, technical enablement, or public speaking engagements, I aim to evangelize Microsoft’s security vision while co-creating solutions that meet the evolving demands of the AI and cybersecurity era.
From “No” to “Now”: A 7-Layer Strategy for Enterprise AI Safety
The “block” posture on Generative AI has failed. In a global enterprise, banning these tools doesn't stop usage; it simply pushes intellectual property into unmanaged channels and creates a massive visibility gap in corporate telemetry. The priority has now shifted from stopping AI to hardening the environment so that innovation can run at velocity without compromising data sovereignty. Traditional security perimeters are ineffective against the “slow bleed” of AI leakage - where data moves through prompts, clipboards, and autonomous agents rather than bulk file transfers. To secure this environment, a 7-layer defense-in-depth model is required to treat the conversation itself as the new perimeter. 1. Identity: The Only Verifiable Perimeter Identity is the primary control plane. Access to AI services must be treated with the same rigor as administrative access to core infrastructure. The strategy centers on enforcing device-bound Conditional Access, where access is strictly contingent on device health. To solve the "Account Leak" problem, the deployment of Tenant Restrictions v2 (TRv2) is essential to prevent users from signing into personal tenants using corporate-managed devices. For enhanced coverage, Universal Tenant Restrictions (UTR) via Global Secure Access (GSA) allows for consistent enforcement at the cloud edge. While TRv2 authentication-plane is GA, data-plane protection is GA for the Microsoft 365 admin center and remains in preview for other workloads such as SharePoint and Teams. 2. Eliminating the Visibility Gap (Shadow AI) You can’t secure what you can't see. Microsoft Defender for Cloud Apps (MDCA) serves to discover and govern the enterprise AI footprint, while Purview DSPM for AI (formerly AI Hub) monitors Copilot and third-party interactions. By categorizing tools using MDCA risk scores and compliance attributes, organizations can apply automated sanctioning decisions and enforce session controls for high-risk endpoints. 3. Data Hygiene: Hardening the “Work IQ” AI acts as a mirror of internal permissions. In a "flat" environment, AI acts like a search engine for your over-shared data. Hardening the foundation requires automated sensitivity labeling in Purview Information Protection. Identifying PII and proprietary code before assigning AI licenses ensures that labels travel with the data, preventing labeled content from being exfiltrated via prompts or unauthorized sharing. 4. Session Governance: Solving the “Clipboard Leak” The most common leak in 2025 is not a file upload; it’s a simple copy-paste action or a USB transfer. Deploying Conditional Access App Control (CAAC) via MDCA session policies allows sanctioned apps to function while specifically blocking cut/copy/paste. This is complemented by Endpoint DLP, which extends governance to the physical device level, preventing sensitive data from being moved to unmanaged USB storage or printers during an AI-assisted workflow. Purview Information Protection with IRM rounds this out by enforcing encryption and usage rights on the files themselves. When a user tries to print a "Do Not Print" document, Purview triggers an alert that flows into Microsoft Sentinel. This gives the SOC visibility into actual policy violations instead of them having to hunt through generic activity logs. 5. The “Agentic” Era: Agent 365 & Sharing Controls Now that we're moving from "Chat" to "Agents", Agent 365 and Entra Agent ID provide the necessary identity and control plane for autonomous entities. A quick tip: in large-scale tenants, default settings often present a governance risk. A critical first step is navigating to the Microsoft 365 admin center (Copilot > Agents) to disable the default “Anyone in organization” sharing option. Restricting agent creation and sharing to a validated security group is essential to prevent unvetted agent sprawl and ensure that only compliant agents are discoverable. 6. The Human Layer: “Safe Harbors” over Bans Security fails when it creates more friction than the risk it seeks to mitigate. Instead of an outright ban, investment in AI skilling-teaching users context minimization (redacting specifics before interacting with a model) - is the better path. Providing a sanctioned, enterprise-grade "Safe Harbor" like M365 Copilot offers a superior tool that naturally cuts down the use of Shadow AI. 7. Continuous Ops: Monitoring & Regulatory Audit Security is not a “set and forget” project, particularly with the EU AI Act on the horizon. Correlating AI interactions and DLP alerts in Microsoft Sentinel using Purview Audit (specifically the CopilotInteraction logs) data allows for real-time responses. Automated SOAR playbooks can then trigger protective actions - such as revoking an Agent ID - if an entity attempts to access sensitive HR or financial data. Final Thoughts Securing AI at scale is an architectural shift. By layering Identity, Session Governance, and Agentic Identity, AI moves from being a fragmented risk to a governed tool that actually works for the modern workplace.Secure and govern AI apps and agents with Microsoft Purview
The Microsoft Purview family is here to help you secure and govern data across third party IaaS and Saas, multi-platform data environment, while helping you meet compliance requirements you may be subject to. Purview brings simplicity with a comprehensive set of solutions built on a platform of shared capabilities, that helps keep your most important asset, data, safe. With the introduction of AI technology, Purview also expanded its data coverage to include discovering, protecting, and governing the interactions of AI apps and agents, such as Microsoft Copilots like Microsoft 365 Copilot and Security Copilot, Enterprise built AI apps like Chat GPT enterprise, and other consumer AI apps like DeepSeek, accessed through the browser. To help you view, investigate interactions with all those AI apps, and to create and manage policies to secure and govern them in one centralized place, we have launched Purview Data Security Posture Management (DSPM) for AI. You can learn more about DSPM for AI here with short video walkthroughs: Learn how Microsoft Purview Data Security Posture Management (DSPM) for AI provides data security and compliance protections for Copilots and other generative AI apps | Microsoft Learn Purview capabilities for AI apps and agents To understand our current set of capabilities within Purview to discover, protect, and govern various AI apps and agents, please refer to our Learn doc here: Microsoft Purview data security and compliance protections for Microsoft 365 Copilot and other generative AI apps | Microsoft Learn Here is a quick reference guide for the capabilities available today: Note that currently, DLP for Copilot and adhering to sensitivity label are currently designed to protect content in Microsoft 365. Thus, Security Copilot and Copilot in Fabric, along with Copilot studio custom agents that do not use Microsoft 365 as a content source, do not have these features available. Please see list of AI sites supported by Microsoft Purview DSPM for AI here Conclusion Microsoft Purview can help you discover, protect, and govern the prompts and responses from AI applications in Microsoft Copilot experiences, Enterprise AI apps, and other AI apps through its data security and data compliance solutions, while allowing you to view, investigate, and manage interactions in one centralized place in DSPM for AI. Follow up reading Check out the deployment guides for DSPM for AI How to deploy DSPM for AI - https://aka.ms/DSPMforAI/deploy How to use DSPM for AI data risk assessment to address oversharing - https://aka.ms/dspmforai/oversharing Address oversharing concerns with Microsoft 365 blueprint - aka.ms/Copilot/Oversharing Explore the Purview SDK Microsoft Purview SDK Public Preview | Microsoft Community Hub (blog) Microsoft Purview documentation - purview-sdk | Microsoft Learn Build secure and compliant AI applications with Microsoft Purview (video) References for DSPM for AI Microsoft Purview data security and compliance protections for Microsoft 365 Copilot and other generative AI apps | Microsoft Learn Considerations for deploying Microsoft Purview AI Hub and data security and compliance protections for Microsoft 365 Copilot and Microsoft Copilot | Microsoft Learn Block Users From Sharing Sensitive Information to Unmanaged AI Apps Via Edge on Managed Devices (preview) | Microsoft Learn as part of Scenario 7 of Create and deploy a data loss prevention policy | Microsoft Learn Commonly used properties in Copilot audit logs - Audit logs for Copilot and AI activities | Microsoft Learn Supported AI sites by Microsoft Purview for data security and compliance protections | Microsoft Learn Where Copilot usage data is stored and how you can audit it - Microsoft 365 Copilot data protection and auditing architecture | Microsoft Learn Downloadable whitepaper: Data Security for AI Adoption | Microsoft Explore the roadmap for DSPM for AI Public roadmap for DSPM for AI - Microsoft 365 Roadmap | Microsoft 365PMPurOn-device AI and security: What really matters for the enterprise
AI is evolving, and so is the way businesses run it. Traditionally, most AI workloads have been processed in the cloud. When a user gives an AI tool a prompt, that input is sent over the internet to remote servers, where the model processes it and sends back a result. This model supports large-scale services like Microsoft 365 Copilot, which integrates AI into apps like Word, Excel, and Teams. Now, a new capability is emerging alongside cloud-based AI. AI can also run directly on a PC—no internet connection or remote server required. This is known as on-device processing. It means the data and the model stay on the device itself, and the work is done locally. Modern CPUs and GPUs are beginning to support this kind of processing. But neural processing units (NPUs), now included in enterprise-grade PCs such as Microsoft Surface Copilot+ PCs, are specifically designed to run AI workloads efficiently. NPUs are designed to perform the types of operations AI needs at high speed while using less power. That makes them ideal for features that need to work instantly, in a sustained fashion in the background, or without an internet connection. A flexible approach to AI deployment NPUs can enable power-efficient on-device processing, fast response times with small models, consistent functionality in offline scenarios, and more control over how data is processed and stored. For organizations, it adds flexibility in choosing how and where to run AI—whether to support real-time interactions at the edge or meet specific data governance requirements. At the same time, cloud-based AI remains essential to how organizations deliver intelligent services across teams and workflows. Microsoft 365 Copilot, for example, is powered by cloud infrastructure and integrates deeply across productivity applications using enterprise-grade identity, access, and content protections. Both models serve different but complementary needs. On-device AI adds new options for responsiveness and control. Cloud-based AI enables broad integration and centralized scale. Together, they give businesses flexibility to align AI processing with the demands of the use case, whether for fast local inference or connected collaboration. For business and IT leaders, the question is not which model is better but how to use each effectively within a secure architecture. That starts with understanding where data flows, how it is protected, and what matters most at the endpoint. Understanding AI data flow and its security impact AI systems rely on several types of input such as user prompts, system context, and business content. When AI runs in the cloud, data is transmitted to remote servers for processing. When it runs on the device, processing happens locally. Both approaches have implications for security. With cloud AI, protection depends on the strength of the vendor’s infrastructure, encryption standards, and access controls. Security follows a shared responsibility model where the cloud provider secures the platform while the enterprise defines its policies for data access, classification, and compliance. Microsoft’s approach to data security and privacy in cloud AI services Although the purpose of this blog post is to talk about on-device AI and security, it’s worth a detour to briefly touch on how Microsoft approaches data governance across its cloud-based AI services. Ultimately, the goal is for employees to be able to use whatever tools work best for what they want to get done, and they may not differentiate between local and cloud AI services. That means having a trusted provider for both is important for long-term AI value and security in the organization. Microsoft’s generative AI solutions, including Azure OpenAI Service and Copilot services and capabilities, do not use your organization’s data to train foundation models without your permission. The Azure OpenAI Service is operated by Microsoft as an Azure service; Microsoft hosts the OpenAI models in Microsoft's Azure environment and the Service does not interact with any services operated by OpenAI (e.g. ChatGPT, or the OpenAI API). Microsoft 365 Copilot and other AI tools operate within a secured boundary, pulling from organization-specific content sources like OneDrive and Microsoft Graph while respecting existing access permissions. For more resources on data privacy and security in Microsoft cloud AI services, check out Microsoft Learn. Local AI security depends on a trusted endpoint When AI runs on the device, the data stays closer to its source. This reduces reliance on network connectivity and can help limit exposure in scenarios where data residency or confidentiality is a concern. But it also means the device must be secured at every level. Running AI on the device does not inherently make it more or less secure. It shifts the security perimeter. Now the integrity of the endpoint matters even more. Surface Copilot+ PCs are built with this in mind. As secured-core PCs, they integrate hardware-based protections that help guard against firmware, OS-level, and identity-based threats. TPM 2.0 and Microsoft Pluton security processors provide hardware-based protection for sensitive data Hardware-based root of trust verifies system integrity from boot-up Microsoft-developed firmware can reduce exposure to third-party supply chain risks and helps address emerging threats rapidly via Windows Update Windows Hello and Enhanced Sign-in Security (ESS) offer strong authentication at the hardware level These protections and others work together to create a dependable foundation for local AI workloads. When AI runs on a device like this, the same enterprise-grade security stack that protects the OS and applications also applies to AI processing. Why application design is part of the security equation Protecting the device is foundational—but it’s not the whole story. As organizations begin to adopt generative AI tools that run locally, the security conversation must also expand to include how those tools are designed, governed, and managed. The value of AI increases dramatically when it can work with rich, contextual data. But that same access introduces new risks if not handled properly. Local AI tools must be built with clear boundaries around what data they can access, how that access is granted, and how users and IT teams can control it. This includes opt-in mechanisms, permission models, and visibility into what’s being stored and why. Microsoft Recall (preview) on Copilot+ PCs is a case study in how thoughtful application design can make local AI both powerful and privacy conscious. It captures snapshots of the desktop embedded with contextual information, enabling employees to find almost anything that has appeared on their screen by describing it in their own words. This functionality is only possible because Recall has access to a wide range of on-device data—but that access is carefully managed. Recall runs entirely on the device. It is turned off by default—even when enabled by IT—and requires biometric sign-in with Windows Hello Enhanced Sign-in Security to activate. Snapshots are encrypted and stored locally, protected by Secured-core PC features and the Microsoft Pluton security processor. These safeguards ensure that sensitive data stays protected, even as AI becomes more deeply embedded in everyday workflows. IT admins can manage Recall through Microsoft Intune, with policies to enable or disable the feature, control snapshot retention, and apply content filters. Even when Recall is enabled, it remains optional for employees, who can pause snapshot saving, filter specific apps or websites, and delete snapshots at any time. This layered approach—secure hardware, secure OS, and secure app design—reflects Microsoft’s broader strategy for responsible local AI and aligns to the overall Surface security approach. It helps organizations maintain governance and compliance while giving users confidence that they are in control of their data and that the tools are designed to support them, not surveil them. This balance is essential to building trust in AI-powered workflows and ensuring that innovation doesn’t come at the expense of privacy or transparency. For more information, check out the related blog post. Choosing the right AI model for the use case Local AI processing complements cloud AI, offering additional options for how and where workloads run. Each approach supports different needs and use cases. What matters is selecting the right model for the task while maintaining consistent security and governance across the entire environment. On-device AI is especially useful in scenarios where organizations need to reduce data movement or ensure AI works reliably in disconnected environments In regulated industries such as finance, legal, or government, local processing can help support compliance with strict data-handling requirements In the field, mobile workers can use AI features such as document analysis or image recognition without relying on a stable connection For custom enterprise models, on-device execution through the Windows AI Foundry Local lets developers embed AI in apps while maintaining control over how data is used and stored These use cases reflect a broader trend. Businesses want more flexibility in how they deploy and manage AI. On-device processing makes that possible without requiring a tradeoff in security or integration. Security fundamentals matter most Microsoft takes a holistic view of AI security across cloud services, on-device platforms, and everything in between. Whether your AI runs in Azure or on a Surface device, the same principles apply. Protect identity, encrypt data, enforce access controls, and ensure transparency. This approach builds on the enterprise-grade protections already established across Microsoft’s technology stack. From the Secure Development Lifecycle to Zero Trust access policies, Microsoft applies rigorous standards to every layer of AI deployment. For business leaders, AI security extends familiar principles—identity, access, data protection—into new AI-powered workflows, with clear visibility and control over how data is handled across cloud and device environments. Securing AI starts with the right foundations AI is expanding from cloud-only services to include new capable endpoints. This shift gives businesses more ways to match the processing model to the use case without compromising security. Surface Copilot+ PCs support this flexibility by delivering local AI performance on a security-forward enterprise-ready platform. When paired with Microsoft 365 and Azure services, they offer a cohesive ecosystem that respects data boundaries and aligns with organizational policies. AI security is not about choosing between cloud or device. It is about enabling a flexible, secure ecosystem where AI can run where it delivers the most value—on the endpoint, in the cloud, or across both. This adaptability unlocks new ways to work, automate, and innovate, without increasing risk. Surface Copilot+ PCs are part of that broader strategy, helping organizations deploy AI with confidence and control—at scale, at speed, and at the edge of what’s next.Rethinking Data Security and Governance in the Era of AI
The era of AI is reshaping industries, enabling unprecedented innovations, and presenting new opportunities for organizations worldwide. But as organizations accelerate AI adoption, many are focused on a growing concern: their current data security and governance practices are not effectively built for the fast-paced AI innovation and ever-evolving regulatory landscape. At Microsoft, we recognize the critical need for an integrated approach to address these risks. In our latest findings, Top 3 Challenges in Securing and Governing Data for the Era of AI, we uncovered critical gaps in how organizations manage data risk. The findings exemplify the current challenges: 91% of leaders are not prepared to manage risks posed by AI 1 and 85% feel unprepared to comply with AI regulations 2 . These gaps not only increase non-compliance but also put innovation at risk. Microsoft Purview has the tools to tackle these challenges head on, helping organizations move to an approach that protects data, meets compliance regulations, and enables trusted AI transformation. We invite you to take this opportunity to evaluate your current practices, platforms, and responsibilities, and to understand how to best secure and govern your organization for growing data risks in the era of AI. Platform fragmentation continues to weaken security outcomes Organizations often rely on fragmented tools across security, compliance, and data teams, leading to a lack of unified visibility and insufficient data hygiene. Our findings reveal the effects of fragmented platforms, leading to duplicated data, inconsistent classification, redundant alerts, and siloed investigations, which ultimately is causing data exposure incidents related to AI to be on the rise 3 . Microsoft Purview offers centralized visibility across your organization’s data estate. This allows teams to break down silos, streamline workflows, and mitigate data leakage and oversharing. With Microsoft Purview, capabilities like data health management and data security posture management are designed to enhance collaboration and deliver enriched insights across your organization to help further protect your data and mitigate risks faster. Microsoft Purview offers the following: Unified insights across your data estate, breaking down silos between security, compliance, and data teams. Microsoft Purview Data Security Posture Management (DSPM) for AI helps organizations gain unified visibility into GenAI usage across users, data, and apps to address the heightened risk of sensitive data exposure from AI. Built-in capabilities like classification, labeling, data loss prevention, and insider risk insights in one platform. In addition, newly launched solutions like Microsoft Purview Data Security Investigations accelerate investigations with AI-powered deep content analysis, which helps data security teams quickly identify and mitigate sensitive data and security risks within impacted data. Organizations like Kern County historically relied on many fragmented systems but adopted Microsoft Purview to unify their organization’s approach to data protection in preparation for increasing risks associated with deploying GenAI. “We have reduced risk exposure, [Microsoft] Purview helped us go from reaction to readiness. We are catching issues proactively instead of retroactively scrambling to contain them.” – Aaron Nance, Deputy Chief Information Security Officer, Kern County Evolving regulations require continuous compliance AI-driven innovation is creating a surge in regulations, resulting in over 200 daily updates across more than 900 regulatory agencies 4 , as highlighted in our research. Compliance has become increasingly difficult, with organizations struggling to avoid fines and comply with varying requirements across regions. To navigate these challenges effectively, security leaders’ responsibilities are expanding to include oversight across governance and compliance, including oversight of traditional data catalog and governance solutions led by the central data office. Leaders also cite the need for regulation and audit readiness. Microsoft Purview enables compliance and governance by: Streamlining compliance with Microsoft Purview Compliance Manager templates, step-by-step guidance, and insights for region and industry-specific regulations, including GDPR, HIPAA, and AI-specific regulation like the EU AI Act. Supporting legal matters such as forensic and internal investigations with audit trail records in Microsoft Purview eDiscovery and Audit. Activating and governing data for trustworthy analytics and AI with Microsoft Purview Unified Catalog, which enables visibility across your data estate and data confidence via data quality, data lineage, and curation capabilities for federated governance. Microsoft Purview’s suite of capabilities provides visibility and accountability, enabling security leaders to meet stringent compliance demands while advancing AI initiatives with confidence. Organizations need a unified approach to secure and govern data Organizations are calling for an integrated platform to address data security, governance, and compliance collectively. Our research shows that 95% of leaders agree that unifying teams and tools is a top priority 5 and 90% plan to adopt a unified solution to mitigate data related risks and maximize impact 6 . Integration isn't just about convenience, it’s about enabling innovation with trusted data protection. Microsoft Purview enables a shared responsibility model, allowing individual business units to own their data while giving central teams oversight and policy control. As organizations adopt a unified platform approach, our findings reveal the upside potential not only being reduced risk but also cost savings. With AI-powered copilots such as Security Copilot in Microsoft Purview, data protection tasks are simplified with natural-language guidance, especially for under resourced teams. Accelerating AI transformation with Microsoft Purview Microsoft Purview helps security, compliance, and governance teams navigate the complexities of AI innovation while implementing effective data protection and governance strategies. Microsoft partner EY highlights the results they are seeing: “We are seeing 25%–30% time savings when we build secure features using [Microsoft] Purview SDK. What was once fragmented is now centralized. With [Microsoft] Purview, everything comes together on one platform, giving a unified foundation to innovate and move forward with confidence.” – Prashant Garg, Partner of Data and AI, EY We invite you to explore how you can propel your organization toward a more secure future by reading the full research paper at https://aka.ms/SecureAndGovernPaper. Visit our website to learn more about Microsoft Purview. 1 Forbes, Only 9% Of Surveyed Companies Are Ready To Manage Risks Posed By AI, 2023 2 SAP LeanIX, AI Survey Results, 2024 3 Microsoft, Data Security Index Report, 2024 4 Forbes, Cost of Compliance, Thomson Reuters, 2021 5 Microsoft, Audience Research, 2024 6 Microsoft, Customer Requirements Research, 2024
