Risk type: Tool Risk
Microsoft Copilot security
Microsoft Copilot security is about preventing sensitive data from being exposed through prompts, plugins, and cross-app context when users work in browser-based copilots.
Quick answer
The fastest way to reduce AI risk is to control what can be typed, pasted, and uploaded in the browser. Combine governance (approved tools and data boundaries) with browser-layer enforcement. When users browse unknown destinations as part of AI workflows, isolation reduces endpoint exposure by running web content in an isolated container and streaming only rendered output; sessions are deleted after use.
When you need this
- Employees paste internal data into AI prompts to move faster.
- You need policy enforcement in the browser, not just training and documents.
- You want to allow AI productivity while preventing sensitive data loss.
Last updated
2026-01-29
Affected tools
- Microsoft Copilot
- Copilot for Microsoft 365
- Browser-based copilots
- Teams/Outlook copilots
How it usually happens in the browser
- Users paste sensitive data into Copilot prompts to summarize emails, documents, or tickets.
- Copilot can access broad organizational context depending on configuration and permissions.
- Users click links from AI outputs to untrusted sites, increasing browser exposure during guided workflows.
- Plugins and integrations expand data access paths and can create unexpected leakage routes.
- Outputs may be copied into external systems without review, spreading sensitive information.
What traditional defenses miss
- Permissions sprawl can make copilots “see” more data than users realize.
- DLP controls may not cover prompt boxes and cross-tab browsing workflows.
- Human review is inconsistent because AI outputs feel authoritative and time-saving.
- Browser-based usage can bypass app-level controls when users use alternative AI endpoints.
Mitigation checklist
- Apply least privilege and review data access boundaries for copilots; restrict what data sources are in scope.
- Define “never in prompts” categories and enforce browser-layer paste/upload controls.
- Require human confirmation for high-impact actions and encourage verification of AI-suggested links.
- Restrict unapproved extensions and enforce safe browsing defaults for risky destinations.
- Audit and log AI usage where possible; create an incident process for AI-related data exposures.
How isolation helps
- Isolation reduces endpoint exposure when users follow AI-suggested links to unknown destinations.
- It can be used to enforce safer browsing defaults for untrusted sites while users operate in AI-assisted workflows.
- Disposable sessions reduce residual state from risky browsing during AI-guided tasks.
FAQs
Is Copilot risk mainly about “bad answers”?
Bad answers matter, but data leakage and permission scope are often bigger issues—especially when copilots have broad access to internal data.
Do we need to block Copilot to be safe?
Not necessarily. Most orgs do better by tightening permissions, defining data boundaries, and enforcing browser-layer guardrails for prompts and links.
What’s the first policy to enforce?
Block secrets and regulated data from being pasted or uploaded into prompts, and restrict unapproved AI tools in the browser.
How does isolation help Copilot users?
It reduces risk when AI outputs send users to unknown sites by keeping that browsing away from the endpoint and under policy control.