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data protection

6 journal entries tagged data protection.

Offset ivory grid panels expose a terracotta square beneath the top layer, with a cobalt tab on a pale sage surface.

Guide9 October 20265 min read

AI DLP for spreadsheets: inspect hidden content

Test the workbook parts that a visible-cell preview can miss.

Test AI DLP spreadsheet coverage for hidden sheets, rows, formulas and cached values. Record extraction limits and verify policy outcomes before file delivery.

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An unnumbered analogue meter connects by black and grey cables to two probes beside a cobalt tile with an ivory inset.

Guide8 October 20265 min read

AI DLP secret validity checks: read the status

Ask what gets sent to an issuer and what the result establishes.

Review secret-validity checks through issuer disclosure, unknown results, exact token coverage and status provenance. Use GitHub's repository guidance as a reference.

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A cobalt ceramic token rests on a pale desk beside a navy metal drawer box with a matching blue circular inset.

Guide7 October 20265 min read

AI DLP pseudonymisation: protect the mapping

Review the alias, remaining context and authority to restore identity.

Assess AI DLP pseudonymisation through mapping access, contextual identification, alias consistency, expiry and controlled restoration using fictional test data.

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A steel magnifying glass rests over a print of abstract grey blocks beside a blank white card on a blue surface.

Guide6 October 20265 min read

AI DLP for screenshots: verify the OCR step

Check activation, readable text, classifier matches and the delivered result separately.

Evaluate screenshot DLP with OCR activation, location-specific limits, paired synthetic images and delivery checks. Keep unsupported AI paths and scan gaps visible.

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A raised steel stencil with four apertures stands over an ivory strip with four blue inserts, beside a blank ivory strip.

Guide5 October 20265 min read

Exact data matching for AI DLP: test the record

Check the first classifier, supporting evidence, formatting and dataset freshness on the actual delivery path.

Test AI DLP exact data matching with synthetic records, supporting evidence, formatting variants and dataset refreshes. Verify classification and delivery separately.

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A closed cream book with a blue fabric tab and an open blank notebook with a loose blue tag sit on a plum-coloured desk.

Guide4 October 20265 min read

Copilot sensitivity labels: verify each output

Check classification, usage rights and DLP decisions across the actual content path.

Separate Copilot label display, encryption rights, output inheritance and DLP restrictions. Build a controlled test using Microsoft's documented limits.

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