Google's AI is now even smarter, and more versatile.

From Donald Trump to DOGE to Chinese hackers, this year the internet's chaos caused outsized real-world harm.

Understanding Windows Settings URIs and How to Use Them in Enterprise Environments

Windows provides a powerful and flexible management framework that enables organizations to configure, restrict, or simplify the Settings experience for their users. One of the key mechanisms behind this framework is the ms-settings: URI scheme — a consistent, internal navigation system that defines how each Settings page in Windows is accessed.

If you have ever opened Windows Settings and navigated to Privacy → Camera, you were effectively visiting a page identified by a specific internal URI:

ms-settings:privacy-webcam

These URIs exist for virtually every part of the modern Settings interface — from Windows Update to Bluetooth, Accounts, and Accessibility. Administrators and automation tools can call these URIs directly to open pages, but they can also use them for more advanced purposes, such as controlling which pages are available to users through Group Policy or MDM.

What Are ms-settings URIs?

Each page within Windows Settings has an internal URI (Uniform Resource Identifier) that begins with the prefix ms-settings: followed by a descriptive identifier. For example:

• ms-settings:windowsupdate – Windows Update
• ms-settings:bluetooth – Bluetooth settings
• ms-settings:privacy-microphone – Microphone permissions
• ms-settings:network-wifi – Wi-Fi configuration

Typing any of these URIs into Win + R or a command prompt immediately opens the corresponding Settings page. To open the camera settings, for example:

The corresponding Powershell command would be:

Start-Process "ms-settings:privacy-webcam"

These same URIs are also what Group Policy and Intune use when defining visibility rules for Settings. Over time, new pages and features are added to Windows, and therefore new URIs are introduced. Most of the available URIs are documented here:

https://learn.microsoft.com/en-us/windows/apps/develop/launch/launch-settings#ms-settings-uri-scheme-reference

Having a reliable way to extract these URIs directly from Windows helps administrators maintain accurate and consistent configuration policies across versions.

Why ms-settings URIs Matter to Enterprises

In enterprise environments, Windows devices are rarely unmanaged. Organizations typically enforce baseline configurations to meet security, usability, and compliance requirements. Control over the Settings experience can be a crucial part of that strategy. Common scenarios include:

• Kiosk and shared PCs – where users should not modify system or network settings.
• Education or classroom devices – limiting what students can access or change.
• Corporate desktops – ensuring consistent, compliant configurations across all departments.
• Call center terminals or point-of-sale systems – providing only task-relevant options.
• High-security workstations – preventing changes to privacy, update, or device settings.

By controlling access to specific Settings pages, IT administrators can:

• Reduce accidental misconfiguration.
• Lower support costs.
• Improve compliance posture.
• Simplify user experience for task-focused roles.
• Prevent exposure of system areas that are centrally managed or locked down.

Managing Settings Visibility with Group Policy

Windows includes a built-in Group Policy setting that allows administrators to control which pages in the Settings app are visible to users.
Policy location:

Computer/User Configuration → Administrative Templates → Control Panel → Settings Page Visibility

This policy uses a semicolon-separated list of rules that reference Settings pages by their ms-settings identifiers. The part after the colon is what the policy recognizes. For example:

Hide selected pages

hide:privacy-webcam;bluetooth;display

Show only selected pages

showonly:windowsupdate;about

Administrators can combine these directives to tailor the Settings experience precisely to the needs of their organization. This approach is particularly useful in locked-down environments where users have a limited set of configuration options, or where privacy and security policies mandate restricted access to certain features. Find more information about managing Settings URIs here: https://learn.microsoft.com/en-us/windows/client-management/client-tools/manage-settings-app-with-group-policy

The Challenge: Keeping Visibility Rules Current

The Windows Settings app evolves continuously. With each new feature update or release, new categories, pages, and URIs may appear. For administrators maintaining long-term device configurations, that means GPO lists need to be reviewed and updated regularly.

While Microsoft provides extensive documentation for the most common pages, enterprise administrators often need a complete and current list of all URIs available on the system they are managing. This ensures that policies remain accurate and compatible, even when upgrading from one Windows build to another.

Introducing Get-MSSettingsURIs.ps1

To simplify this process, I created a small PowerShell script called Get-MSSettingsURIs.ps1.

This script scans the system’s SystemSettings.dll file — the core component behind the modern Settings interface — and extracts every ms-settings: URI it contains. Because it reads directly from the operating system, it always reflects exactly what that Windows build supports.

You can use the script to:

• Discover all current Settings URIs on any Windows device.
• Compare differences between Windows versions (e.g., 23H2 → 25H2).
• Build or update your Group Policy “Settings Page Visibility” configuration.
• Validate that newly introduced Settings pages are correctly managed.

param( [string]$Path = "C:\Windows\ImmersiveControlPanel\SystemSettings.dll", [string]$OutFile, [switch]$GpoKeysOnly ) Set-StrictMode -Version Latest $ErrorActionPreference = 'Stop' if (-not (Test-Path -LiteralPath $Path)) { throw "Datei nicht gefunden: $Path" } # --- High-performance Scanner in C# (compiled on-the-fly) --- $cs = @" using System; using System.Collections.Generic; using System.IO; using System.Text; public static class MsSettingsScanner { static readonly byte[] AsciiPrefix = Encoding.ASCII.GetBytes("ms-settings:"); static readonly byte[] Utf16Prefix = Encoding.Unicode.GetBytes("ms-settings:"); public static List<string> ExtractAll(string filePath) { byte[] data = File.ReadAllBytes(filePath); // fast read var set = new HashSet<string>(StringComparer.OrdinalIgnoreCase); foreach (var s in FindAscii(data)) set.Add(s); foreach (var s in FindUtf16(data)) set.Add(s); var list = new List<string>(set); list.Sort(StringComparer.OrdinalIgnoreCase); return list; } // ---- ASCII ---- static IEnumerable<string> FindAscii(byte[] data) { foreach (int idx in FindAll(data, AsciiPrefix)) { int i = idx + AsciiPrefix.Length; var sb = new StringBuilder("ms-settings:"); while (i < data.Length) { char c = (char)data[i]; if (!IsValidUriChar(c)) break; sb.Append(c); i++; } yield return sb.ToString(); } } // ---- UTF-16LE ---- static IEnumerable<string> FindUtf16(byte[] data) { foreach (int idx in FindAll(data, Utf16Prefix)) { int pos = idx + Utf16Prefix.Length; var sb = new StringBuilder("ms-settings:"); // 2-Byte-Steps after the prefix (LE). Accept only ASCII (hi=0). while (pos + 1 < data.Length) { byte lo = data[pos]; byte hi = data[pos + 1]; if (hi != 0) break; // only ASCII characters char c = (char)lo; if (!IsValidUriChar(c)) break; sb.Append(c); pos += 2; } yield return sb.ToString(); } } // Boyer–Moore–Horspool over Bytes (fast) static IEnumerable<int> FindAll(byte[] haystack, byte[] needle) { int n = haystack.Length, m = needle.Length; if (m == 0 || n < m) yield break; int[] skip = new int[256]; for (int i = 0; i < skip.Length; i++) skip[i] = m; for (int i = 0; i < m - 1; i++) skip[needle[i]] = m - 1 - i; int pos = 0; int last = m - 1; while (pos <= n - m) { int j = last; while (j >= 0 && haystack[pos + j] == needle[j]) j--; if (j < 0) { yield return pos; pos += m; // next possible start } else { pos += skip[haystack[pos + last]]; } } } // valid characters after "ms-settings:" static bool IsValidUriChar(char c) { if ((c >= 'a' && c <= 'z') || (c >= 'A' && c <= 'Z') || (c >= '0' && c <= '9')) return true; switch (c) { case '-': case '_': case '.': case ':': case '/': case ';': case '?': case '&': case '=': case '#': case '%': case '+': case ',': case '@': return true; default: return false; } } } "@ # Make sure to only compile once per session $loaded = [AppDomain]::CurrentDomain.GetAssemblies() | Where-Object { $_.GetTypes() -as [type] } | Where-Object { $_.GetType("MsSettingsScanner") } if (-not $loaded) { Add-Type -TypeDefinition $cs -Language CSharp -IgnoreWarnings } $uris = [MsSettingsScanner]::ExtractAll($Path) if ($GpoKeysOnly) { $uris = $uris | ForEach-Object { if ($_ -like 'ms-settings:*') { $_.Substring(12) } else { $_ } } | Where-Object { $_ } } if ($OutFile) { $uris | Set-Content -LiteralPath $OutFile -Encoding UTF8 Write-Host ("Fertig. {0} Einträge → {1}" -f $uris.Count, $OutFile) } else { $uris Write-Host ("`nTotal: {0}" -f $uris.Count) }

How the Script Works

At a high level, Get-MSSettingsURIs.ps1 reads binary data from C:\Windows\ImmersiveControlPanel\SystemSettings.dll and searches for all strings that match the ms-settings: pattern. It supports both ASCII and Unicode encodings to ensure no identifiers are missed.

It then sorts and outputs the unique list of URIs. You can optionally format the results to make them directly usable in a Group Policy setting. Because the script runs locally and reads system files, it does not require any administrative privileges beyond read access to the Windows directory.

Example Usage

To run the script with default settings:

.\Get-MSSettingsURIs.ps1

This outputs a complete list of all ms-settings: URIs found in the current Windows installation. If you want the results formatted for direct use in Group Policy (without the ms-settings: prefix):

.\Get-MSSettingsURIs.ps1 -GpoStyle

To scan a copy of SystemSettings.dll from another Windows build (for testing or preparation):

.\Get-MSSettingsURIs.ps1 -Binary "C:\Temp\SystemSettings.dll"

Example Output

Standard output might look like this:

ms-settings:privacy-webcam ms-settings:privacy-microphone ms-settings:windowsupdate ms-settings:network-proxy ms-settings:bluetooth ms-settings:display ...

When using the -GpoStyle parameter, the output is trimmed for direct use in Group Policy:

privacy-webcam privacy-microphone windowsupdate network-proxy bluetooth display ...

Integrating the Script Into IT Operations

Once you have the list of Settings URIs, you can automate several key tasks:

• Baseline validation – Ensure the same visibility configuration applies across device groups.
• Upgrade preparation – Before deploying a new Windows release, compare URI lists to identify new or renamed pages.
• Compliance auditing – Verify that restricted settings remain hidden as expected.
• Kiosk image building – Generate a minimal set of allowed pages for kiosk or shared devices.
• Automation – Integrate the PowerShell output into configuration pipelines, Intune scripts, or Group Policy templates.

Because the script runs without external dependencies, it can easily be distributed as part of enterprise configuration management or imaging workflows.

Example Workflow for Administrators:

1. Run the PowerShell script on a reference Windows build.
2. Save the resulting URI list to a text file, such as MSSettings_URIs_23H2.txt.
3. Use the -GpoStyle option to generate a GPO-ready list.
4. Configure the Settings Page Visibility policy in Group Policy or Intune.
5. Optionally rerun the script after major OS updates to check for new entries.

By incorporating this simple step into your management process, you ensure that every system in your environment reflects the intended configuration and that new Settings pages introduced by future Windows versions are quickly identified.

Conclusion

The ms-settings: URI system is one of Windows’ most useful yet under-appreciated administrative capabilities. For enterprises that depend on configuration consistency, compliance, or controlled user experiences, understanding and managing these URIs is key.
The Get-MSSettingsURIs.ps1 script gives administrators an easy way to extract, review, and apply these identifiers directly from any Windows installation. Combined with Group Policy or MDM, it provides a fast and reliable method to shape the Settings experience for users — ensuring that each system remains secure, focused, and predictable.

Disclaimer

This Sample Code is provided for the purpose of illustration only
and is not intended to be used in a production environment.  THIS
SAMPLE CODE AND ANY RELATED INFORMATION ARE PROVIDED "AS IS" WITHOUT
WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING BUT NOT
LIMITED TO THE IMPLIED WARRANTIES OF MERCHANTABILITY AND/OR FITNESS
FOR A PARTICULAR PURPOSE.  We grant You a nonexclusive, royalty-free
right to use and modify the Sample Code and to reproduce and distribute
the object code form of the Sample Code, provided that You agree:
(i) to not use Our name, logo, or trademarks to market Your software
product in which the Sample Code is embedded; (ii) to include a valid
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embedded; and (iii) to indemnify, hold harmless, and defend Us and
Our suppliers from and against any claims or lawsuits, including
attorneys' fees, that arise or result from the use or distribution
of the Sample Code.

This sample script is not supported under any Microsoft standard
support program or service. The sample script is provided AS IS
without warranty of any kind. Microsoft further disclaims all implied
warranties including, without limitation, any implied warranties of
merchantability or of fitness for a particular purpose. The entire
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Data Loss Prevention (DLP) and Data Security Posture Management (DSPM) form the enforcement layer that ensures Copilot can only operate within safe, compliant boundaries. While permissions determine what users can access, DLP and DSPM determine what users, and Copilot acting on their behalf, are allowed to do with the data. As organizations adopt generative AI, these controls are no longer optional. They become the policy engine that governs summarization, extraction, and cross-content interpretation at scale.

Copilot does not bypass DLP. It does not circumvent policies. It obeys the same data security enforcement path as every Microsoft 365 workload.

When properly configured, DLP and DSPM introduce guardrails that prevent unsafe prompts, accidental oversharing, or unauthorized extraction of sensitive content, even when the user legitimately has access to the file.

This step ensures your data security posture is mature enough to support large-scale, AI-driven workflows.

---

Understand the Role of DLP and DSPM in Copilot Security

Microsoft Purview DLP protects information by monitoring actions such as copying, printing, saving, uploading, and pasting content. With Copilot in Microsoft 365, DLP expands its relevance because:

• Copilot performs extractive actions on the user’s behalf
• Copilot can reinterpret or summarize content that the user can access
• Copilot can surface data from multiple locations if governance allows it
• Prompts may unintentionally request sensitive or regulated information

DSPM (Data Security Posture Management), now delivered through Microsoft Purview Data Security and Microsoft 365 Sensitivity Indexing, adds visibility across SharePoint, OneDrive, Exchange, and Teams by identifying:

• Misplaced sensitive data
• Data stored in risky or non-compliant locations
• Data exposures caused by oversharing or legacy access
• Sensitive files without labels or with weak protections

Together, DLP and DSPM form the policy foundation that limits AI interactions to approved contexts, prevents the movement of risky data, and ensures sensitive material is handled correctly.

---

Build a DLP Framework That Reflects AI-Driven Workflows

DLP policies must be designed for modern collaboration, not just endpoint or email scenarios. Copilot underscores the importance of this model because it interacts with data across multiple workloads simultaneously. A Copilot-ready DLP framework should cover:

• SharePoint and OneDrive (document extraction and summarization)
• Exchange Online (mail summaries and draft generation)
• Teams Chats and Channels (context-sensitive referencing)
• Endpoint DLP (local actions, copy or paste, print, screen capture)
• Third-party app access (via Graph Connectors and plugins)

Below is a table of Microsoft-supported DLP actions usable in SharePoint, OneDrive, Exchange, and Endpoint DLP policies.

Valid and Supported M365 DLP Actions for AI Governance

DLP Action (Microsoft Supported)	Description	How It Controls Copilot
Block	Prevents an activity such as print, copy, or upload	Prevents Copilot from retrieving or using the content in prohibited workflows
Block with Override	Allows user justification to proceed	Provides flexibility for legitimate business needs while still gating AI extraction
Audit Only	Logs the action but allows it	Helpful in learning how users prompt Copilot before enforcing controls
Restrict Access or Encrypt	Applies encryption or reduces permissions	Prevents Copilot from summarizing or interpreting restricted content
Block Sharing (internal or external)	Prevents risky share events	Ensures Copilot cannot surface data to users who lack access
Endpoint DLP: Block Copy or Paste	Prevents data exfiltration on devices	Stops AI-assisted workflows from moving sensitive data into unsafe endpoints
Endpoint DLP: Block Print or Screen Capture	Controls output channels	Prevents printing or screenshotting of AI-generated content that contains sensitive data

Documented Purview DLP capabilities support these actions. Copilot respects these controls because AI must follow the underlying Microsoft 365 permission and policy engine. DLP does not scan Copilot. It governs the user’s ability to perform protected actions, and Copilot executes under those permissions.

Disclaimer: Microsoft has not published Copilot-specific DLP outcomes for each action. The behaviors described above are based on the documented principle that Copilot operates entirely within the user’s allowed actions and Purview DLP enforcement pipeline. Organizations should test DLP enforcement with AI prompts to validate expected outcomes.

---

Integrate DSPM to Identify Hidden Risks Before AI Operates on Your Data

DSPM in Microsoft Purview provides a macro-level visibility layer across your tenant. It identifies where sensitive data lives, where it is overshared, and where security policies do not align with regulatory expectations. This is essential before enabling Copilot, because AI depends on the underlying health of your data security posture.

DSPM helps identify:

• Orphaned files containing sensitive data
• Sensitive files are stored in incorrect locations
• Files accessible by broad audiences, such as department-wide or organization-wide permissions
• Unlabeled sensitive data such as PII, financial information, or health data
• Shadow data repositories created through unmanaged Teams or SharePoint growth

DSPM should be used to:

• Assign priorities for what data must be protected first
• Recommend labels through auto-labeling integration
• Identify oversharing and validate the DLP Policy Set for AI
• Feed into DLP policies to define where controls must be strengthened

DSPM does not control Copilot. It provides visibility into where Copilot could interpret or summarize data that is currently under-secured.

---

Build a Comprehensive DLP Policy Set for AI

Your DLP configuration should include a minimal baseline policy set that specifically governs AI-driven behaviors. The table below lists fully supported and valid DLP rule categories you can deploy today in Microsoft 365.

Suggested DLP Rule Set for Copilot Readiness

Policy Type	Purpose	Supported Enforcement Action
Financial Data Policy (PCI, ABA, SWIFT, IBAN)	Prevent financial data leakage through Copilot	Block, Block with Override, Audit
Privacy or PII Data Policy (GDPR, CCPA, NIST)	Prevent AI summarization or the sharing of personal data	Restrict Access, Block
Health Information Policy (HIPAA Alignment)	Prevent accidental PHI exposure through prompts	Block, Restrict
Source Code Protection Policy	Stop Copilot from exposing internal IP or code artifacts	Block, Endpoint DLP Block Copy
M&A or Legal Confidential Policy	Protect legal case files and board materials	Restrict Access (Encryption)
Internal Only Business Data Policy	Prevent movement of internal files to external channels	Block External Sharing, Block Print
High Business Impact (HBI) Policy	Establish boundaries for sensitive operations	Block or Block with Override
Universal Audit Policy	Monitor all Copilot-related actions during rollout	Audit Only

These categories come from Microsoft’s built-in sensitive information types and Purview DLP policy templates.

Disclaimer: The mapping to Copilot relies on Microsoft’s documented rule that Copilot obeys user permissions and Purview DLP enforcement. Microsoft does not publish rule-by-rule matrices for Copilot, so enforcement expectations are based on the underlying Microsoft 365 security model.

---

Enforce In-App DLP Alerts and User Coaching

Successful AI adoption depends not only on policy enforcement but also on user awareness. Many data risks occur unintentionally, especially when employees prompt Copilot without understanding the sensitivity of the underlying content. In-app DLP alerts and user coaching messages serve as real-time guardrails that educate users while preventing risky actions before they occur. These prompts are embedded directly in Microsoft 365 applications, so they appear when a user attempts an action that violates or approaches a DLP boundary.

User-coaching messages can be tailored to your policies and should provide clear, actionable guidance, such as:

“This file contains confidential financial data and cannot be used in Copilot.”

“Your action would send sensitive personal data outside approved boundaries. Please review data handling requirements.”

“Extraction of regulated data is restricted by corporate policy. Contact your compliance team if this task is required.”

These alerts do more than block or warn. They reinforce the organization’s data handling expectations and help employees understand why a particular action is sensitive in the context of AI-driven workflows. Over time, user coaching reduces accidental policy violations, increases responsible AI usage, and strengthens your overall data culture. It introduces friction exactly where it is most effective: at the moment of decision, when a user is about to misuse or mishandle data, intentionally or not.

---

Validate AI Behavior Through Controlled DLP Testing

Once your DLP policies are configured, verify that they correctly govern Copilot’s behavior. Copilot operates inside the same compliance boundary as Microsoft 365, but real-world testing is the only way to confirm that policies behave as intended across AI-driven scenarios. Controlled validation ensures your enforcement logic, user prompts, override rules, and data controls function predictably when Copilot interacts with sensitive or regulated information.

A structured testing process should involve multiple personas, including standard users, power users, and, where appropriate, exempt users. Each test should be executed under a controlled identity with documented permission levels, giving you clear insight into how AI behaves under different user contexts.

Practical test scenarios include:

• Attempting to summarize a document protected by a Block policy.
  This validates that Copilot cannot extract or reinterpret content when DLP prevents data movement. Copilot should decline the action or fail silently, confirming that the block applies to AI-driven workflows as well as traditional user actions.
• Trying to use Copilot to rewrite or extract financial, PII, PHI, or regulated content.
  This ensures that sensitive information types are correctly detected and that your DLP actions prevent Copilot from generating derivative content that might inadvertently expose regulated data.
• Testing whether Copilot honors site-level encryption and sensitivity label rules.
  Copilot should not be able to summarize, extract, or infer content from files protected with encryption policies that forbid extraction. This test validates your sensitivity label design, extraction permissions, and MIP enforcement path.
• Checking endpoint DLP controls when Copilot outputs or generates sensitive content.
  This includes copy-and-paste restrictions, file-transfer blocks, print restrictions, and screen-capture controls. Test what happens when a user tries to paste AI-generated content into a noncompliant application or upload it to an unapproved service.
• Testing override workflows to determine whether Copilot stops or allows actions based on user justification.
  This confirms that business-justified overrides work as intended and that Copilot does not circumvent or bypass justification prompts. Overrides should appear consistently across workloads and enforce proper audit logging.

Beyond individual tests, you should evaluate the end-to-end auditing path, confirming that AI-related actions generate the expected entries in Purview Audit and that these logs clearly indicate whether DLP enforcement occurred. This is essential for investigations, regulatory reviews, and AI safety governance.

By performing these controlled scenarios, you gain measurable assurance that your DLP framework is not only correctly configured but also resilient under real AI workloads. These tests form a critical part of your Copilot readiness program, ensuring that AI behaves safely, consistently, and in complete alignment with your organization’s compliance requirements.

---

Closing Thoughts

Configuring DLP and DSPM for Copilot is not simply a compliance exercise. It is how you create safe and predictable boundaries around AI operations. By combining sensitive information identification, least-privilege access control, real-time enforcement, user coaching, and policy-based protection, you ensure Copilot works with your security posture rather than around it.

Organizations that implement DLP and DSPM before enabling Copilot gain three critical advantages:

• Lower risk of AI-assisted data exposure because sensitive information is identified early, protected consistently, and governed by real-time enforcement rules.
• Higher trust in AI output and behavior since Copilot operates inside a well-defined boundary rather than an uncontrolled permission landscape.
• Improved data governance maturity across the tenant as AI readiness forces organizations to eliminate oversharing, correct misconfigurations, and standardize protection policies.

These safeguards create the conditions necessary for AI adoption at scale. A secure data foundation ensures that Copilot enhances productivity while remaining aligned with regulatory requirements, internal policy, and organizational risk tolerance.

In the following article, we will build on this enforcement layer by focusing on identity-driven protections. We will explore how to strengthen security with Conditional Access and Session Controls for Copilot Access, ensuring that every AI interaction is validated through identity assurance, device health, conditional risk scoring, and session-based restrictions. These controls complete the defensive perimeter, tying together identity, data, and AI governance under a single, cohesive framework.