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name: building-threat-hunt-hypothesis-framework description: 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. Use when planning or running a proactive threat hunt or scoping compromise from an intel- or anomaly-driven lead. domain: cybersecurity subdomain: threat-hunting tags:

• threat-hunting
• methodology
• hypothesis
• threat-intelligence
• hunting-framework
• proactive-detection version: '1.0' author: mahipal license: Apache-2.0 nist_csf:
• DE.CM-01
• DE.AE-02
• DE.AE-07
• ID.RA-05 mitre_attack:
• T1071
• T1059.001
• T1055
• T1547

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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]