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Detection-as-Code Foundations
TheoryBeginner10 minDetection EngineeringLog Analysis

What Sigma Is & Rule Anatomy

What is it?

Sigma is a YAML format for describing a log detection independently of any SIEM. A rule has a title, a logsource (which data), a detection (selections + a condition), and metadata — then a converter translates it to Splunk, Elastic, etc.

Why it matters

Detections written in one SIEM's query language die with that tool. Sigma is portable: write the logic once, run it anywhere, and share it with the community.

Where you see it

A .yml file: `logsource: {category: process_creation, product: windows}` then `detection: {selection: {...}, condition: selection}`.

What normal looks like

A well-formed rule with a clear logsource, a focused selection, and a condition that names the selection(s) — readable and convertible.

What suspicious looks like

A rule with no logsource (it matches the wrong data), or a detection whose condition does not reference its selections — it will not convert or will match nothing.

How analysts investigate

Read a rule top-down: what data (logsource), what to match (selection), how to combine (condition). If any of the three is missing or mismatched, the rule is broken.

Common beginner mistakes

  • Omitting or mismatching logsource, so the rule runs against the wrong events.
  • Writing a condition that does not reference the selection.

Portable detection in YAML

  title: Encoded PowerShell from Office
  logsource: { category: process_creation, product: windows }
  detection:
    selection:
      ParentImage|endswith: '\WINWORD.EXE'
      CommandLine|contains: '-enc'
    condition: selection
  → converts to Splunk/Elastic; logic outlives the tool
A Sigma rule = logsource + detection (selection + condition); a converter targets any SIEM.

Quick check

What makes Sigma valuable over a SIEM-specific query?

A quick self-check — it doesn't affect your XP or progress.

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