mukul975/anthropic-cybersecurity-skills

building-threat-hunt-hypothesis-framework

Build a systematic threat-hunt workflow that turns threat intelligence and ATT&CK gap analysis into testable hypotheses, then executes and validates them via EDR/SIEM queries (CrowdStrike, Defender, Splunk, Elastic, Sysmon, Velociraptor, Sigma) and documents findings in a standardized hunt report.

First seen Mar 16, 2026

Installation

$ npx skills add mukul975/anthropic-cybersecurity-skills --skill building-threat-hunt-hypothesis-framework

Summary

  • Build a systematic threat-hunt workflow that turns threat intelligence and ATT&CK gap analysis into testable hypotheses, then executes and validates them via EDR/SIEM queries (CrowdStrike, Defender, Splunk, Elastic, Sysmon, Velociraptor, Sigma) and documents findings in a standardized hunt report.
  • Use when planning or running a proactive threat hunt or scoping compromise from an intel- or anomaly-driven lead.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 32.4K
License LICENSE
Default branch main
Open issues 20
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0
LicenseApache-2.0

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,571 B
  • docs SUMMARY.md 461 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 183 installs

SKILL.md

Building Threat Hunt Hypothesis Framework

When to Use

  • When proactively hunting for indicators of building threat hunt hypothesis framework in the environment
  • After threat intelligence indicates active campaigns using these techniques
  • During incident response to scope compromise related to these techniques
  • When EDR or SIEM alerts trigger on related indicators
  • During periodic security assessments and purple team exercises

Prerequisites

  • EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne)
  • SIEM with relevant log data ingested (Splunk, Elastic, Sentinel)
  • Sysmon deployed with comprehensive configuration
  • Windows Security Event Log forwarding enabled
  • Threat intelligence feeds for IOC correlation

Workflow

  1. Formulate Hypothesis: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.
  2. Identify Data Sources: Determine which logs and telemetry are needed to validate or refute the hypothesis.
  3. Execute Queries: Run detection queries against SIEM and EDR platforms to collect relevant events.
  4. Analyze Results: Examine query results for anomalies, correlating across multiple data sources.
  5. Validate Findings: Distinguish true positives from false positives through contextual analysis.
  6. Correlate Activity: Link findings to broader attack chains and threat actor TTPs.
  7. Document and Report: Record findings, update detection rules, and recommend response actions.

Key Concepts

Concept Description
TA0001 Initial Access
TA0003 Persistence
TA0008 Lateral Movement
TA0010 Exfiltration

Tools & Systems

Tool Purpose
CrowdStrike Falcon EDR telemetry and threat detection
Microsoft Defender for Endpoint Advanced hunting with KQL
Splunk Enterprise SIEM log analysis with SPL queries
Elastic Security Detection rules and investigation timeline
Sysmon Detailed Windows event monitoring
Velociraptor Endpoint artifact collection and hunting
Sigma Rules Cross-platform detection rule format

Common Scenarios

  1. Scenario 1: Intelligence-driven hunt based on APT campaign report
  2. Scenario 2: ATT&CK coverage gap analysis driving hypothesis creation
  3. Scenario 3: Anomaly-driven hypothesis from UEBA alert investigation
  4. Scenario 4: Situational awareness hunt based on industry sector threats

Output Format

Hunt ID: TH-BUILDI-[DATE]-[SEQ]
Technique: TA0001
Host: [Hostname]
User: [Account context]
Evidence: [Log entries, process trees, network data]
Risk Level: [Critical/High/Medium/Low]
Confidence: [High/Medium/Low]
Recommended Action: [Containment, investigation, monitoring]