Even when DLP, RBAC, and Purview are implemented perfectly, LLMs can still infer sensitive knowledge.
Your policies look perfect on paper, but a single prompt like, “Summarise last quarter’s confidential bids” can draw from multiple sources and reveal protected data. Traditional DLP, DSPM, and RBAC tools like Purview only see direct access, not inference exposure. Without a feedback loop, you don’t know the controls have failed until it’s too late.
Knostic fires hundreds of LLM-style questions to systematically identify exposure.
We record each chat response and the hidden fragments it pulls from.
If a prompt returns data beyond a user's need-to-know, directly or through inference, we flag it as a policy violation and trace the exposure path.
One-click pushes updated labels, RBAC policies, or DLP rules straight into Purview, SharePoint, or Azure AD.
Continuously retest exposure paths to confirm issues are fixed, and to catch new gaps before they become problems.
Concrete prompt-level evidence of each policy miss.
Automatic retests keep controls aligned as content and roles drift.
Start in read-only mode; opt-in to enforcement when you’re ready.
Pre-mapped knowledge flows and policy decisions streamline review.
Works the same for Copilot, OpenAI, Anthropic, or your private LLM.
