building-threat-hunt-hypothesis-framework
Build a systematic threat-hunt workflow that turns threat intelligence and ATT&CK gap analysis into testable hypotheses, then executes and validates them via…
Skill by mukul975
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: documents, security, sales, productivity
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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 2
codeload.github.com· found in install commandraw.githubusercontent.com· found in code
Files it touches
~/.claude/skills/building-threat-hunt-hypothesis-framework
What's inside
- Skill 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.
- License
- Apache-2.0
- Instructions
- 70 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (8)
- LICENSE
- SKILL.md
- template.md · assets/
- api-reference.md · references/
- standards.md · references/
- workflows.md · references/
- agent.py · scripts/
- process.py · scripts/
SKILL.md (first lines)
# 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] ```
From mukul975/Anthropic-Cybersecurity-Skills, Apache-2.0.
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Signals
- Stars
- 34,941
- Forks
- 4,256
- Open issues
- 24
- Last commit (this folder)
- Aug 2, 2026 (2 months ago)
- Last release
- Jun 22, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
building-threat-hunt-hypothesis-framework skill. Agent Mart. https://agentmart.dev/skills/mukul975-building-threat-hunt-hypothesis-framework (last updated 2026-10-24)