proactive-hunt-gti-campaign

name	proactive-hunt-gti-campaign
description	Use when initiating threat hunting operations driven by GTI threat campaign intelligence.
category	hunting
version	1.0.0
type	Skill
title	Skill: Proactive Threat Hunting based on GTI Campaign/Actor
generated	{"by":"process:google-labs-jules","at":"2026-08-20T02:00:00Z"}

Proactive Threat Hunting based on GTI Campaign/Actor

Objective: Given a GTI Campaign or Threat Actor Collection ID (${GTI_COLLECTION_ID}), proactively search the local environment (SIEM) for related IOCs and TTPs (approximated by searching related entities). If any IOCs from the report are also found in the SecOps tenant (confirmed presence), perform deeper enrichment on those specific IOCs using GTI and check for related SIEM alerts or SOAR cases. Once done, summarize findings in a markdown report. Provide as much detail as possible.

Uses Tools:

• gti-mcp_get_collection_report
• gti-mcp_get_entities_related_to_a_collection (Initial IOC gathering)
• gti-mcp_get_collection_timeline_events (for TTP context)
• secops-mcp_get_ioc_matches (Initial SIEM check)
• secops-mcp_lookup_entity (SIEM check for specific IOCs)
• secops-mcp_search_security_events (SIEM check for specific IOCs)
• gti-mcp_get_domain_report / get_file_report / get_ip_address_report / get_url_report (Deeper GTI enrichment for found IOCs)
• gti-mcp_get_entities_related_to_a_domain/file/ip/url (Pivot on found IOCs)
• secops-mcp_get_security_alerts (Check related SIEM alerts for found IOCs/hosts)
• (Optional) gti-mcp_get_file_behavior_summary (For found file hashes)
• write_report (for report generation)
• secops-soar: post_case_comment (optional), list_cases
• You may ask follow up question
• Common Steps: {doc}common_steps/find_relevant_soar_case </run_books/common_steps/find_relevant_soar_case>

ADK Graph-Based Workflow Diagram

graph TD
    START(["START"]) --> extract_proactive_payload_node["1. extract_proactive_payload_node<br/><i>(Extract Campaign/Actor Scope Payload)</i>"]
    extract_proactive_payload_node --> correlate_gti_campaign_siem_node["2. correlate_gti_campaign_siem_node<br/><i>(Correlate GTI Campaign IOCs against SIEM)</i>"]
    correlate_gti_campaign_siem_node --> proactive_gti_hunt_router{"3. proactive_gti_hunt_router<br/><i>(Event.actions.route)</i>"}

    proactive_gti_hunt_router -- "CAMPAIGN_SIEM_MATCH_FOUND" --> handle_campaign_match_found_branch["4a. handle_campaign_match_found_branch<br/><i>(Escalate Active Campaign Matches to IR)</i>"]
    proactive_gti_hunt_router -- "NO_CAMPAIGN_ACTIVITY" --> handle_no_campaign_activity_branch["4b. handle_no_campaign_activity_branch<br/><i>(Document Clean Hunt Outcome)</i>"]

    handle_campaign_match_found_branch --> document_proactive_hunt_report_node["5. document_proactive_hunt_report_node<br/><i>(SOAR Comment & Report Summary)</i>"]
    handle_no_campaign_activity_branch --> document_proactive_hunt_report_node

Sequence Diagram

sequenceDiagram
    participant User
    participant AutomatedAgent as Automated Agent (MCP Client)
    participant GTI as gti-mcp
    participant SIEM as secops-mcp
    participant SOAR as secops-soar
    participant FindCase as skills/common/find-relevant-soar-case/SKILL.md

    User->>AutomatedAgent: Hunt for Campaign/Actor: `${GTI_COLLECTION_ID}`
    AutomatedAgent->>GTI: get_collection_report(id=`${GTI_COLLECTION_ID}`)
    GTI-->>AutomatedAgent: Collection Details (Name, Type, Description)
    AutomatedAgent->>GTI: get_collection_timeline_events(id=`${GTI_COLLECTION_ID}`)
    GTI-->>AutomatedAgent: Timeline Events (TTP Context)

    Note over AutomatedAgent: Identify relevant IOC relationships (files, domains, ips, urls)
    loop For each IOC Relationship R
        AutomatedAgent->>GTI: get_entities_related_to_a_collection(id=`${GTI_COLLECTION_ID}`, relationship_name=R)
        GTI-->>AutomatedAgent: List of IOCs (e.g., Hashes H1, Domains D1, IPs IP1...)
    end

    Note over AutomatedAgent: Initialize local_hunt_findings
    AutomatedAgent->>SIEM: get_ioc_matches(hours_back=72)
    SIEM-->>AutomatedAgent: Recent IOC Matches in SIEM (Matches M1, M2...)
    Note over AutomatedAgent: Identify key IOCs from GTI (I1, I2...) and SIEM matches (M1, M2...)

    Note over AutomatedAgent: Phase 1: Lookup key/prioritized IOCs
    loop For each prioritized IOC Ii (from GTI/SIEM Matches)
        AutomatedAgent->>SIEM: lookup_entity(entity_value=Ii, hours_back=72)
        SIEM-->>AutomatedAgent: SIEM Summary for Ii
        Note over AutomatedAgent: Record IOCs with confirmed presence (P1, P2...)
    end

    Note over AutomatedAgent: Phase 2: Deeper investigation for IOCs with confirmed presence (P1, P2...)
    loop For each Present IOC Pi
        Note over AutomatedAgent: Search SIEM Events
        AutomatedAgent->>SIEM: search_security_events(text="Events involving Pi", hours_back=72)
        SIEM-->>AutomatedAgent: Relevant SIEM Events for Pi (Note involved hosts Hi)
        Note over AutomatedAgent: Store significant event findings

        Note over AutomatedAgent: Deeper GTI Enrichment & Pivoting
        alt IOC Pi is Domain
            AutomatedAgent->>GTI: get_domain_report(domain=Pi)
            GTI-->>AutomatedAgent: Detailed Domain Report
            AutomatedAgent->>GTI: get_entities_related_to_a_domain(domain=Pi, relationship_name="resolutions")
            GTI-->>AutomatedAgent: Related IPs
            AutomatedAgent->>GTI: get_entities_related_to_a_domain(domain=Pi, relationship_name="communicating_files")
            GTI-->>AutomatedAgent: Related Files
        else IOC Pi is File Hash
            AutomatedAgent->>GTI: get_file_report(hash=Pi)
            GTI-->>AutomatedAgent: Detailed File Report
            AutomatedAgent->>GTI: get_entities_related_to_a_file(hash=Pi, relationship_name="contacted_domains")
            GTI-->>AutomatedAgent: Related Domains
            AutomatedAgent->>GTI: get_entities_related_to_a_file(hash=Pi, relationship_name="contacted_ips")
            GTI-->>AutomatedAgent: Related IPs
            %% Optional: AutomatedAgent->>GTI: get_file_behavior_summary(hash=Pi)
            %% GTI-->>AutomatedAgent: Behavior Summary
        else IOC Pi is IP Address
            AutomatedAgent->>GTI: get_ip_address_report(ip_address=Pi)
            GTI-->>AutomatedAgent: Detailed IP Report
            AutomatedAgent->>GTI: get_entities_related_to_an_ip_address(ip_address=Pi, relationship_name="resolutions")
            GTI-->>AutomatedAgent: Related Domains
            AutomatedAgent->>GTI: get_entities_related_to_an_ip_address(ip_address=Pi, relationship_name="communicating_files")
            GTI-->>AutomatedAgent: Related Files
        end
        Note over AutomatedAgent: Store enrichment and pivot findings

        Note over AutomatedAgent: Check Related SIEM Alerts & SOAR Cases
        AutomatedAgent->>SIEM: get_security_alerts(query="alert contains Pi or involves host Hi", hours_back=72)
        SIEM-->>AutomatedAgent: Related SIEM Alerts (Store findings)
        Note over AutomatedAgent: Prepare search terms (Pi + Hi)
        AutomatedAgent->>FindCase: Execute(Input: SEARCH_TERMS=[Pi, Hi], CASE_STATUS_FILTER="Opened")
        FindCase-->>AutomatedAgent: Results: RELATED_SOAR_CASES (Store findings)
    end

    Note over AutomatedAgent: Synthesize GTI context, IOCs, TTPs, SIEM findings, Enrichment, Related Alerts & Cases
    AutomatedAgent->>User: Confirm: "Hunt found potential activity related to `${GTI_COLLECTION_ID}`. Create/Update SOAR Case or Generate Report? (Create New Case/Update Case [ID]/Generate Report/Do Nothing)"
    User->>AutomatedAgent: Response (e.g., "Generate Report")

    alt Output Action Confirmed
        alt Create/Update Case
            Note over AutomatedAgent: Prepare summary comment for SOAR
            AutomatedAgent->>SOAR: post_case_comment(case_id=[New/Existing ID], comment="Proactive Hunt Summary for `${GTI_COLLECTION_ID}`: Found IOCs [...] in SIEM. Events [...] observed. GTI Context: [...].")
            SOAR-->>AutomatedAgent: Comment confirmation
            AutomatedAgent->>AutomatedAgent: attempt_completion(result="Proactive threat hunt for `${GTI_COLLECTION_ID}` complete. Findings summarized. SOAR case created/updated.")
        else Generate Report
            Note over AutomatedAgent: Synthesize report content
            AutomatedAgent->>AutomatedAgent: write_report(report_name="proactive_hunt_report_${GTI_COLLECTION_ID}_${timestamp}.md", report_contents=ReportContent)
            Note over AutomatedAgent: Report file created.
            AutomatedAgent->>AutomatedAgent: attempt_completion(result="Proactive threat hunt for `${GTI_COLLECTION_ID}` complete. Report generated.")
        else Do Nothing
             AutomatedAgent->>AutomatedAgent: attempt_completion(result="Proactive threat hunt for `${GTI_COLLECTION_ID}` complete. Findings summarized. No output action taken.")
        end
    end

## Rubrics

The following rubric is used to evaluate the execution of this **Threat Hunt/Analysis** runbook by an LLM agent.

### Grading Scale (0-100 Points)

| Criteria | Points | Description |
| :--- | :--- | :--- |
| **Scope & Query** | 25 | Defined a clear scope and executed effective queries (UDM, search). |
| **Data Analysis** | 30 | Analyzed results to identify patterns, anomalies, or malicious behavior. |
| **Findings** | 15 | Accurately identified and filtered findings (True Positives vs. False Positives). |
| **Documentation** | 15 | Documented the hunt methodology and results clearly. |
| **Operational Artifacts** | 15 | Produced required artifacts: Sequence diagram, execution metadata (date/cost), and summary. |

### Evaluation Criteria Details

#### 1. Scope & Query (25 Points)
- **10 pts**: Correctly defined the time range and entities/indicators for the hunt.
- **15 pts**: Constructed and executed valid, efficient queries to retrieve relevant data.

#### 2. Data Analysis (30 Points)
- **15 pts**: Effectively analyzed the returned data for the hypothesized threat.
- **15 pts**: Correlated events or indicators to strengthen the analysis.

#### 3. Findings (15 Points)
- **15 pts**: Correctly classified the findings and provided evidence for the conclusion.

#### 4. Documentation (15 Points)
- **15 pts**: Recorded the hunt process, queries used, and findings in the system of record.

#### 5. Operational Artifacts (15 Points)
- **5 pts**: **Sequence Diagram**: Produced a Mermaid sequence diagram visualizing the steps taken.
- **5 pts**: **Execution Metadata**: Recorded the date, duration, and estimated token cost.
- **5 pts**: **Summary Report**: Generated a concise summary of the actions and outcomes.