Organization· Security Management

Decide what counts as sensitive

Last reviewed
Version
1
For
Decision-maker, Security analyst

Situation

We need data loss prevention, but nobody has agreed which data actually matters or how much friction people will accept.

At a glance

Outcome

A short, owned list of sensitive data categories, the friction each one justifies, and a working exception process.

Benefits

  • Protection effort goes to the data that carries real risk. How to measure: Share of DLP matches that fall in an agreed category.
  • Fewer arguments during rollout, because the trade-offs were settled first. How to measure: Number of policy changes requested in the first 90 days.

Resources required

Who is involved
Privacy or legal lead, security lead, records manager, one operations representative.
Skills
Knowledge of the organization's regulatory obligations and main data flows.
Effort
Two or three working sessions.
Duration
Two to four weeks.

Risk of not doing it

Policies get written around what the tools detect by default rather than what the organization must protect, producing noise and gaps at the same time.

Make the decision

The decision to make

Which categories of information are sensitive enough to warrant automated controls, and how much interruption each category justifies for the people who handle it.

Options and trade-offs

  1. Start from regulation only

    Fast and defensible, but misses intellectual property and operational data that no law names.

  2. Start from a full data inventory

    Thorough, but slow; DLP waits months for a document nobody finishes.

  3. Start from a short list of high-impact categories and grow it

    Gets protection running in weeks. Needs a review cadence so the list does not stay short forever.

Recommended default

Start with three to five high-impact categories, each with a named owner and a friction level: audit only, warn with override, or block.

Owners

Decides
Privacy or legal lead, with the security lead
Operates
Security operations
Consulted
Records management, operations leads, labour relations where applicable

Policy statement

Copy and adapt this statement for your policy.

The organization protects the information categories listed in its sensitive data register. Each category has an owner and an approved level of control. Exceptions are requested through the service desk, approved by the category owner, and expire after twelve months.

What this constrains downstream

Making it scale

Sensitive info types and DLP policies are managed centrally and applied to every location by default, rather than through per-site exceptions. Narrow a policy with groups or administrative units; adaptive scopes for DLP cover SharePoint only and are in preview.

Enforced by a mechanism.

Avoiding common pitfalls

  1. Turning on every built-in sensitive info type

    Pick the types that map to your agreed categories. Each extra type adds matches someone must review.

  2. No owner per category

    Name one person who can approve exceptions and changes for each category.

  3. Exceptions that never expire

    Give every exception an end date and review them on the Maintenance cadence.

Checkpoints

  • Every sensitive category has an owner and a friction level.
  • The policy statement is approved and published.
  • The exception process is live in the service desk.

Sources

  1. Lightweight guide to mitigate data leakage (Microsoft Learn)
  2. Reduce false positives by using SITs and advanced classifiers (Microsoft Learn)
  3. Data Loss Prevention policy reference (Microsoft Learn)
  4. Reduce false positives with sensitive information types and advanced classifiers (Microsoft Learn)

Reviewed against

Changelog

Changelog (1 version)
Published versions of this playbook
VersionDateAuthorChange
1Sev DerghazarianFirst published. Placeholder text for the pilot build; replace before launch.