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Connector refresh keeps indexed items aligned with source changes. This helps with up-to-date external search index instead of the required live action against a business system.

Indexed external items must carry permissions so results can be security trimmed. This helps with secure retrieval of connected external content instead of the required live action against a business system.

Missing ACL mapping can lead to unintended search exposure. The action is relevant to corrected external item authorization rather than live action against a business system.

File labels provide authoritative classification state for retrieved work content. It is used for source-document classification evidence; this scenario calls for consistent source access enforcement.

AI security telemetry can identify supported sensitive data interaction patterns. That addresses detection of sensitive prompt content, whereas the current case requires consistent source access enforcement.

DLP can govern sensitive data handling in supported interactions and endpoints. That addresses restriction of classified generated content movement, whereas the current case requires consistent source access enforcement.

Correcting excessive authorization closes both direct and Copilot discovery paths. It would support removal of internal oversharing, not the stated AI-related data exposure reduction.

Rights protection travels with the content when supported. Its purpose is persistent financial-file control; the specified need is AI-related data exposure reduction.

Data loss prevention provides incident context and prevention actions. It would support outbound sensitive-mail incident response, not the stated AI-related data exposure reduction.

Data minimization limits personal data processing for the task. This helps with least-data disclosure by an AI tool instead of the required accountable irreversible account deletion.

Responsible AI transparency avoids misleading users about the system. The action is relevant to informed AI output interpretation rather than accountable irreversible account deletion.

Purpose limitation and governance constrain sensitive processing. This helps with accountable processing of customer information instead of the required accountable irreversible account deletion.

Anonymous links may create an unintended access path beyond tenant membership. That addresses closure of public sharing exposure, whereas the current case requires observational AI usage evidence.

Access control defects are not fixed by changing a prompt alone. That addresses stopping unintended broad directory access, whereas the current case requires observational AI usage evidence.

A user cannot ground answers in inaccessible tenant files. It is used for diagnosing absent authorized source; this scenario calls for observational AI usage evidence.

Communication Compliance is designed for supported conduct and policy review of messages. Its purpose is problematic workplace messages; the specified need is framework evidence and control tracking.

Content classification discovery identifies data locations and matched types. Its purpose is locating sensitive identity data; the specified need is framework evidence and control tracking.

Insider risk focuses on configured risky behavior by trusted users. It would support suspected malicious insider activity, not the stated framework evidence and control tracking.

Compliance Manager tracks completion and corresponding assessment status. This helps with regulatory readiness progress instead of the required documented proof of a compliance control.

Assessment templates map controls to a selected framework. The action is relevant to regulation-specific control assessment rather than documented proof of a compliance control.

The assessment assigns responsibility for relevant controls. The action is relevant to responsibility partition for assessed controls rather than documented proof of a compliance control.

Activity explorer records supported label events and associated actors. It is used for activity behind an actual label downgrade; this scenario calls for discovery of stored sensitive content.

AI posture telemetry identifies sensitive-data use in AI applications. That addresses sensitive information in AI prompts, whereas the current case requires discovery of stored sensitive content.

eDiscovery search selects responsive content for a case. It is used for litigation-driven content collection; this scenario calls for discovery of stored sensitive content.

Privacy-aware insider risk limits exposed personal identity data during triage. Its purpose is privacy-protecting investigation; the specified need is suspected departing-employee exfiltration.

Policy tuning reduces known benign matches without disabling relevant risk detection. It would support fewer false-positive user-risk cases, not the stated suspected departing-employee exfiltration.

Case closure records the disposition and investigator rationale. Its purpose is auditable disposition of employee-risk alert; the specified need is suspected departing-employee exfiltration.

DLP monitoring supports accountable follow-up on repeated violations. The action is relevant to repeated data-loss incident response rather than evidence for a sensitive outbound email block.

Simulated matches allow validation before production enforcement. The action is relevant to impact testing of a new DLP rule rather than evidence for a sensitive outbound email block.

Governed exceptions avoid weakening protection for all users. This helps with narrowly authorized protected-data sharing instead of the required evidence for a sensitive outbound email block.

Review dispositions preserve a decision trail for policy violations. That addresses accountable escalation of flagged messages, whereas the current case requires conduct-related Teams message review.

Role-controlled review limits access to sensitive conversation content. It is used for protected access to communications investigations; this scenario calls for conduct-related Teams message review.

Narrower detection criteria can improve review precision. It is used for tuned employee communication policy; this scenario calls for conduct-related Teams message review.