Building Threat Hunt Hypothesis Framework
SkillDocs & knowledgeGuides your agent through planning a threat hunt: forming hypotheses from threat intel and running EDR/SIEM queries to validate them.
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Details
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About this skill
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. U
What this skill tells your AI
The instructions your AI receives, as published by costrict-plugins-repo/mukul975-anthropic-cybersecurity-skills-cybersecurity-skills in skills/building-threat-hunt-hypothesis-framework/SKILL.md and read by ahel’s review.
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
- Formulate Hypothesis: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.
- Identify Data Sources: Determine which logs and telemetry are needed to validate or refute the hypothesis.
- Execute Queries: Run detection queries against SIEM and EDR platforms to collect relevant events.
- Analyze Results: Examine query results for anomalies, correlating across multiple data sources.
- Validate Findings: Distinguish true positives from false positives through contextual analysis.
- Correlate Activity: Link findings to broader attack chains and threat actor TTPs.
- 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
- Scenario 1: Intelligence-driven hunt based on APT campaign report
- Scenario 2: ATT&CK coverage gap analysis driving hypothesis creation
- Scenario 3: Anomaly-driven hypothesis from UEBA alert investigation
- 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]
Signals
- GitHub stars
- 73
- Forks
- 12
- Last commit
- Sep 2026
ahel recommends instead
Advanced
- Item type
- skill
- Key
building-threat-hunt-hypothesis-framework-costrict-p-09ldzsq- Source
- github.com/costrict-plugins-repo/mukul975-anthropic-cybersecurity-skills-cybersecurity-skills
github.com/costrict-plugins-repo/mukul975-anthropic-cybersecurity-skills-cybersecurity-skills
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