Building Threat Hunt Hypothesis Framework
SkillSecurityBuild a systematic threat hunt hypothesis framework that transforms threat
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Building Threat Hunt Hypothesis Framework skill
What this skill tells your AI
The instructions your AI receives, as published by adriannoes/awesome-agentic-ai in cursor-claude-codex/skills/anthropic-cybersecurity-skills/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
- 57
- Forks
- 12
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
building-threat-hunt-hypothesis-framework-adriannoes- Source
- github.com/adriannoes/awesome-agentic-ai