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mukul975
efca3ec611
Mapped every skill to NIST CSF 2.0 subcategory IDs (GV/ID/PR/DE/RS/RC functions) based on subdomain and content analysis. Restores 11 skills corrupted during prior rebase, re-enriching with ATLAS, D3FEND, NIST AI RMF, and CSF 2.0 fields. All 754 skills now carry structured mappings for all 5 security frameworks: - MITRE ATT&CK (in tags) - MITRE ATLAS v5.5 (atlas_techniques) - MITRE D3FEND v1.3 (d3fend_techniques) - NIST AI RMF 1.0 (nist_ai_rmf) - NIST CSF 2.0 (nist_csf)
92 lines
3.2 KiB
Markdown
92 lines
3.2 KiB
Markdown
---
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name: building-threat-hunt-hypothesis-framework
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description: Build a systematic threat hunt hypothesis framework that transforms threat intelligence, attack patterns, and
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environmental data into testable hunting hypotheses.
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domain: cybersecurity
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subdomain: threat-hunting
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tags:
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- threat-hunting
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- methodology
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- hypothesis
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- threat-intelligence
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- hunting-framework
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- proactive-detection
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version: '1.0'
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author: mahipal
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license: Apache-2.0
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nist_csf:
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- DE.CM-01
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- DE.AE-02
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- DE.AE-07
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- ID.RA-05
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---
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# Building Threat Hunt Hypothesis Framework
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## When to Use
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- When proactively hunting for indicators of building threat hunt hypothesis framework in the environment
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- After threat intelligence indicates active campaigns using these techniques
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- During incident response to scope compromise related to these techniques
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- When EDR or SIEM alerts trigger on related indicators
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- During periodic security assessments and purple team exercises
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## Prerequisites
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- EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne)
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- SIEM with relevant log data ingested (Splunk, Elastic, Sentinel)
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- Sysmon deployed with comprehensive configuration
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- Windows Security Event Log forwarding enabled
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- Threat intelligence feeds for IOC correlation
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## Workflow
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1. **Formulate Hypothesis**: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.
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2. **Identify Data Sources**: Determine which logs and telemetry are needed to validate or refute the hypothesis.
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3. **Execute Queries**: Run detection queries against SIEM and EDR platforms to collect relevant events.
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4. **Analyze Results**: Examine query results for anomalies, correlating across multiple data sources.
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5. **Validate Findings**: Distinguish true positives from false positives through contextual analysis.
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6. **Correlate Activity**: Link findings to broader attack chains and threat actor TTPs.
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7. **Document and Report**: Record findings, update detection rules, and recommend response actions.
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## Key Concepts
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| Concept | Description |
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|---------|-------------|
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| TA0001 | Initial Access |
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| TA0003 | Persistence |
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| TA0008 | Lateral Movement |
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| TA0010 | Exfiltration |
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## Tools & Systems
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| Tool | Purpose |
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|------|---------|
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| CrowdStrike Falcon | EDR telemetry and threat detection |
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| Microsoft Defender for Endpoint | Advanced hunting with KQL |
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| Splunk Enterprise | SIEM log analysis with SPL queries |
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| Elastic Security | Detection rules and investigation timeline |
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| Sysmon | Detailed Windows event monitoring |
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| Velociraptor | Endpoint artifact collection and hunting |
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| Sigma Rules | Cross-platform detection rule format |
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## Common Scenarios
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1. **Scenario 1**: Intelligence-driven hunt based on APT campaign report
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2. **Scenario 2**: ATT&CK coverage gap analysis driving hypothesis creation
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3. **Scenario 3**: Anomaly-driven hypothesis from UEBA alert investigation
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4. **Scenario 4**: Situational awareness hunt based on industry sector threats
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## Output Format
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```
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Hunt ID: TH-BUILDI-[DATE]-[SEQ]
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Technique: TA0001
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Host: [Hostname]
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User: [Account context]
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Evidence: [Log entries, process trees, network data]
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Risk Level: [Critical/High/Medium/Low]
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Confidence: [High/Medium/Low]
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Recommended Action: [Containment, investigation, monitoring]
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```
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