building-threat-hunt-hypothesis-framework
Build a systematic threat hunt hypothesis framework that transforms threat intelligence, attack patterns, and environmental data into testable hunting hypotheses.
- License 许可
- Apache-2.0
- 最近更新
- 2026-09-28
- Stars
- ★ 1
- Forks
- 0
01 前言 Front Matter
- name
- building-threat-hunt-hypothesis-framework
- tags
- [ "threat-hunting", "methodology", "hypothesis", "threat-intelligence", "hunting-framework", "proactive-detection" ]
- author
- mahipal
- domain
- cybersecurity
- license
- Apache-2.0
- version
- 1.0
- category
- building-threat-hunt-hypothesis-framework
- nist_csf
- [ "DE.CM-01", "DE.AE-02", "DE.AE-07", "ID.RA-05" ]
- subdomain
- threat-hunting
- description
- Build a systematic threat hunt hypothesis framework that transforms threat intelligence, attack patterns, and environmental data into testable hunting hypotheses.
- mitre_attack
- [ "T1071", "T1059.001", "T1055", "T1547" ]
02 资源文件 7
- 资产文件assets/template.md2.6 KB
- 许可证LICENSE11.0 KB
- 参考文档references/api-reference.md2.1 KB
- 参考文档references/standards.md1.6 KB
- 参考文档references/workflows.md3.1 KB
- 脚本scripts/agent.py6.6 KB
- 脚本scripts/process.py3.5 KB
03 SKILL.md 正文
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
- 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]
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