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]
---
name: building-threat-hunt-hypothesis-framework
description: Transform threat intelligence and attack patterns into testable hunting hypotheses for proactive threat detection.
license: Apache-2.0
---
# 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]
```
