Analytic Story Builder Skill

Overview

An analytic story groups related detections into a narrative around a threat scenario, campaign, or attacker behavior chain. While the "analytic story" concept originated in Splunk's ESCU, the principle — grouping detections by threat context — applies to every SIEM.

| SIEM | Concept | Implementation | |------|---------|---------------| | Splunk ESCU | Analytic Story | YAML story file + detection references | | Elastic Security | Detection rule group / Tag | Tags + rule grouping in Kibana | | Microsoft Sentinel | Analytics rule template | Grouping via Solution/Content Hub | | Sigma | Tags / rule collections | tags field + directory structure | | Chronicle SOAR | Playbook grouping | Playbooks referencing detection sets |

Story Structure (Splunk ESCU Format)

The canonical format. Other SIEMs can adapt this structure to their own grouping mechanism.

yaml
name: Story Name Here
id: <uuid>
version: 1
date: 'YYYY-MM-DD'
author: Your Name
description: >-
  One to three sentences describing the threat scenario. What is the attacker
  trying to do? Why should a defender care?
narrative: >-
  Three to five sentences providing deeper context. Include references to
  real-world campaigns, common attack chains, and why these detections were
  grouped together. Explain how the detections work together to provide
  coverage across the kill chain.
references:
  - https://attack.mitre.org/techniques/TXXXX/
  - https://relevant-blog-or-advisory.example.com
tags:
  analytic_story: Story Name Here
  category:
    - Malware          # or: Adversary Tactics, Abuse, Cloud Security, etc.
  product:
    - Splunk Enterprise
    - Splunk Cloud
  usecase: Security Monitoring
  mitre_attack:
    - T1059.001
    - T1547.001

Concise Format Guidance

Stories should be 17–19 lines of YAML (excluding blank lines). Keep it tight:

• description: 1–3 sentences. What is the threat?
• narrative: 3–5 sentences. Why do these detections belong together?
• references: 2–5 links. ATT&CK technique page + source blog/advisory.
• tags.mitre_attack: List every technique covered by detections in the story.

Anti-patterns to avoid:

• Narratives that just restate the description
• Stories with only 1 detection (group at least 2–3)
• Missing MITRE mappings
• Overly broad stories (e.g., "Windows Attacks") — be specific

When to Create a Story

Create a new story when:

1. New threat campaign — A new adversary campaign warrants grouped coverage (e.g., "STORM-0501 Ransomware")
2. Technique cluster — Multiple detections cover related sub-techniques (e.g., "Scheduled Task Abuse" covering T1053.002, T1053.005)
3. Kill chain segment — Detections span multiple tactics for a coherent attack path (e.g., "Initial Access via Phishing to Persistence")
4. Compliance/use case — A regulatory or operational requirement groups detections (e.g., "PCI DSS Monitoring")

Story Categories

| Category | Description | Example | |----------|-------------|---------| | Malware | Specific malware families | "IcedID", "QakBot Execution Chain" | | Adversary Tactics | Technique-focused groups | "Windows Persistence Techniques" | | Abuse | Legitimate tool abuse | "Living Off The Land Binaries" | | Cloud Security | Cloud-specific threats | "AWS IAM Privilege Escalation" | | Vulnerability | CVE-specific detection sets | "Log4Shell CVE-2021-44228" | | Compliance | Regulatory monitoring | "PCI DSS Log Monitoring" |

Building a Story: Workflow

Step 1: Identify the Grouping

Start from one of:

• A threat intel report mentioning multiple techniques
• A coverage gap analysis showing related uncovered techniques
• A PR adding multiple related detections

Step 2: Find Existing Stories

Check if a story already exists that this fits into:

search_stories("ransomware")
search_stories("persistence")

Step 3: Draft the Story

Use the YAML format above. Focus on:

• Clear threat description — What is the attacker doing?
• Narrative that connects the dots — How do these detections work together?
• Complete MITRE mappings — Every technique referenced by included detections

Step 4: Associate Detections

Each detection references its story via tags:

yaml
# In the detection YAML
tags:
  analytic_story:
    - Story Name Here

For non-Splunk SIEMs, use whatever grouping mechanism is available (tags, folders, rule groups).

Step 5: Validate

• Every detection in the story maps to at least one MITRE technique
• The story's mitre_attack list matches the union of all detection technique mappings
• The narrative explains why these detections are grouped (not just "these are all Windows detections")

Adapting to Other SIEMs

Elastic Security

Group detections using tags in the rule YAML:

yaml
tags:
  - "campaign:storm-0501"
  - "story:ransomware-encryption"

Microsoft Sentinel / KQL

Use Sentinel Solutions or Content Hub packages to group related analytics rules. Alternatively, use consistent naming prefixes: [STORM-0501] - Detection Name.

Sigma

Use directory structure and tags:

rules/
  windows/
    storm-0501/
      proc_creation_storm0501_initial_access.yml
      proc_creation_storm0501_persistence.yml

Tips

• Stories evolve. As new detections are added for a threat, update the story's narrative and technique list.
• Cross-reference stories. A detection can belong to multiple stories (e.g., a PowerShell detection might appear in both "Living Off The Land" and "STORM-0501 Ransomware").
• Use stories for reporting. Stories make excellent units for executive reporting — "We added coverage for the STORM-0501 campaign (8 new detections across 5 techniques)."