Last Reviewed: 2026-06-24
Reviewer: ITMG® Security Advisory
BoK Reference Sheet
Reference Case study

AI and Sensitive Data Leakage

AI data leakage occurs when an insider exposes, enters, uploads, trains, retrieves, or shares sensitive information through AI systems or AI-enabled workflows without appropriate authorization or controls.

Notional composite.

Incident Case Analysis & Real-World Context

Case basis: Notional composite. A developer pasted a proprietary code snippet and internal error logs into an unmanaged AI chatbot to troubleshoot a production issue. A sales manager later uploaded customer call notes into an unapproved AI summarization tool. Neither user intended harm, but both actions created uncertainty about retention, data processing, contractual restrictions, confidentiality, and whether sensitive information had moved outside approved controls.

Why This Event Pattern Matters

AI leakage matters because prompts, uploaded files, retrieval indexes, embeddings, logs, outputs, plug-ins, and connected copilots can create new exposure paths that traditional DLP and access models may not fully see.

Common Event Scenarios & Progression Path

Use of approved or unapproved AI tools for normal work.

Sensitive data entered into prompts, uploads, plug-ins, or connected workspaces.

Over-permissioned retrieval or copilots surfacing data beyond need to know.

Unclear retention, training, logging, or cross-border processing terms.

IRCF™ Capability Alignment

Lessons from this event pattern directly map to the following canonical Insider Risk Capability Framework™ (IRCF™) components for organizational capability improvement:

GovernanceData ProtectionIAMMonitoringAnalysisOversight and ComplianceTraining and AwarenessRisk Management and Reporting

Insider Threat Matrix Alignment

Matrix mapping includes preparation through data collection or staging and infringement through AI-platform disclosure or overexposure. Avoid treating every AI mistake as malicious.

*The Insider Threat Matrix™ is an open framework maintained by Forscie Limited for computer-enabled insider threat investigations.

Controls & Safeguards to Leverage

Approved AI tool catalog and acceptable-use rules.
DLP/browser controls for AI uploads and prompt fields where feasible.
Copilot permission hygiene and retrieval-access review.
Logging and review of sensitive AI-use patterns where legally approved.
Role-based training for developers, sales, support, legal, HR, and executives.

Relevant Program Metrics & KPIs

Metric
Sensitive submissions to AI tools.
Metric
Approved versus unapproved AI usage.
Metric
Copilot oversharing findings.
Metric
AI exception approvals and aging.
Metric
AI training completion for sensitive populations.

Legal, Privacy, and Ethical Cautions

AI leakage may implicate privacy, IP, privilege, contract, employment monitoring, sector regulation, record retention, cross-border data transfer, and model governance. Review actual tool terms and data paths before making conclusions.

Source References & Investigation Fact-Verification

Notional composite. Do not describe this as a real event. Use the case label shown above.

Operationalize This Learning

Need to evaluate whether this scenario is covered in your environment? Use RiskTKO® or request a Guided Exposure Assessment to evaluate your current control coverage, capability maturity, and exposure trends.