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Stop Copilot Data Oversharing with Knostic & Purview

Microsoft 365 Copilot promises transformative productivity gains, but its powerful AI capabilities also introduce significant data oversharing risks.

Knostic complements Purview, delivering a focused, AI-native security layer. It rapidly identifies, prioritizes, and helps mitigate Copilot data oversharing, ensuring you can adopt Copilot safely and efficiently.

Download the Solution Brief

Access the full Microsoft Copilot Oversharing Risks: Solution Brief to understand how Knostic complements Purview to provide AI-driven visibility and protection against Copilot data oversharing risks.

Why Copilot Oversharing Is a Critical Risk

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AI Exposes Hidden Risks

LLMs don’t just retrieve data  - they infer and reconstruct hidden insights, potentially surfacing confidential information.

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Foundational Tools Have Gaps

Existing security tools like Purview struggle to adapt to real-time Copilot data oversharing risks, leaving organizations vulnerable.

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Copilot Increases Oversharing Scale

Instead of occasional data leaks, Copilot can proactively serve sensitive information to users, increasing the risk of unauthorized access.

How Knostic Complements Purview to Prevent Copilot Data Oversharing

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Purview Manages Data Access, Knostic Manages AI Exposure

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Purview handles data governance, but Knostic provides the AI-specific focus to manage how Copilot exposes data through inference and unique LLM risks.

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Faster Detection & Actionable Remediation

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Knostic delivers Copilot risk insights in days, not months, pinpointing precise permission or labeling issues for Purview to act on.

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Proactive AI Security, Not Just Policy Enforcement

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While Purview relies on predefined security rules, Knostic continuously adapts to new AI-driven data security challenges, ensuring your Copilot deployment remains secure over time.

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Latest research and news

AI Discretion: Teaching Machines the Human Concept of ...

 
Key Findings on AI Discretion AI lacks human discretion, often revealing sensitive insights across systems, not by violating permissions, but by inferring patterns users weren’t ...
AI data security

AI Data Security Risks and How to Minimize Them

 
Key Findings on AI Data Security Risks The most critical AI security risks include harmful confabulation (misleading outputs), adversarial attacks, unintentional data exposure ...

What’s next?

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