Guide

Authoring a Finding Rule with AND/OR Criteria

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About

About this guide

Encode one triage decision as a governed, fail-closed, fully reversible policy with nested criteria, a dry-run preview, four-eye approval, an audit log, and a safe revoke path.

This guide teaches you to build a single finding rule end to end in PMAP, from a nested AND/OR criteria tree to one committed, audit-logged action. You will compose conditions across more than 25 matchable fields using the 16-operator library, choose an action type, and set its place in priority-ordered evaluation. The result is a policy the engine applies consistently instead of a decision you repeat by hand.

Authoring a Finding Rule with AND/OR Criteria
The Rules workspace: a filterable policy grid with All and Suggested tabs, inline active toggles, and applied-count badges.

It is written for triage leads and security engineers who already make a recurring decision manually and want it governed. By the end you will be able to quantify blast radius with a dry-run preview and a live affected-findings scan, route a high-impact rule through four-eye approval, read its audit log after it fires, and reverse it with a safe or force revoke.

Inside this guide

  • Understand how the engine evaluates a rule in priority order before you author one.
  • Set the rule basics: name, scope, priority, and expiry.
  • Build a nested AND/OR criteria tree and pick the right field and operator for each condition.
  • Choose an action type and its parameters from the available set.
  • Quantify impact with a dry-run preview, an in-context test, and a live affected-findings scan.
  • Submit a high-impact rule for four-eye approval and read its audit log after activation.
  • Revoke a rule in safe or force mode and watch its metrics.

Before you start

  • A PMAP account with rule create and update permissions in your company scope, plus rule approve permission if you will sign off on gated rules.
  • A populated Findings queue from at least one scan import, so preview and the affected-findings view have real data to match against.
  • A clear, written triage decision you already make by hand, so the rule encodes one policy rather than guesswork.
  • Familiarity with your severity policy, SLA thresholds, and which automated changes your governance model considers sensitive enough to gate.
  • For a four-eye rule, a second reviewer with rule approve permission who did not author the rule, because self-approval is blocked server-side.

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