Runbook: Group Cases v2

Runbook: Group Cases v2#

Objective#

To analyze a defined set of recent SOAR cases, identify logical groupings based on shared entities or alert types, prioritize these groups by potential impact or severity, and generate a summary report of the findings. This helps in understanding related security events and focusing investigative efforts.

Scope#

This runbook covers:

  • Retrieving a list of recent SOAR cases.

  • Gathering detailed information (including alerts and key entities) for each case.

  • Analyzing case data to identify logical groupings based on specified or observed criteria.

  • Prioritizing the identified case groups.

  • Optionally performing basic enrichment of key shared entities within high-priority groups.

  • Generating a Markdown report summarizing the case groups, prioritization rationale, and key findings.

This runbook explicitly excludes:

  • Deep investigation of individual cases within the groups (this would typically follow for high-priority groups).

  • Containment or eradication actions.

  • Automated closure of grouped cases (though findings might inform manual closure decisions).

Inputs#

  • (Optional) ${NUMBER_OF_CASES}: Number of recent cases to analyze (e.g., 5, 10). Defaults to a predefined number (e.g., 10) if not specified.

  • (Optional) ${TIME_FRAME_HOURS}: Lookback period in hours for selecting cases. If not provided, NUMBER_OF_CASES will be the primary filter.

  • (Optional) ${GROUPING_CRITERIA}: Specific criteria for grouping cases (e.g., “shared_hostname”, “alert_type”, “CVE”, “malware_family”). If not provided, grouping will be based on observed similarities in entities and alert details.

  • (Derived) ${CASE_LIST}: List of SOAR case IDs selected for analysis.

  • (Derived) ${CASE_DETAILS_MAP}: A map or structure holding details (alerts, entities) for each case in ${CASE_LIST}.

  • (Derived) ${CASE_GROUPS}: Identified groups of related case IDs.

  • (Derived) ${PRIORITIZED_GROUPS}: The ${CASE_GROUPS} ordered by assessed priority.

  • (Derived) ${ENRICHMENT_DATA_SUMMARY}: (Optional) Summary of enrichment for key entities in high-priority groups.

Outputs#

  • ${REPORT_FILE_PATH}: The full path to the generated Markdown summary report.

  • ${REPORT_CONTENT}: The full Markdown content of the generated report.

  • ${GROUPING_ANALYSIS_SUMMARY}: A brief textual summary of how cases were grouped and prioritized.

Tools#

  • secops-soar: list_cases, get_case_full_details, list_alerts_by_case, get_entities_by_alert_group_identifiers

  • secops-mcp: lookup_entity

  • gti-mcp: Relevant enrichment tools (e.g., get_ip_address_report, get_domain_report)

  • write_to_file (Replaces write_report)

Workflow Steps & Diagram#

  1. List Cases: Retrieve recent cases using secops-soar.list_cases, filtered by ${NUMBER_OF_CASES} or ${TIME_FRAME_HOURS}. Store in ${CASE_LIST}.

  2. Gather Case Details: For each case ID in ${CASE_LIST}:

    • Use secops-soar.get_case_full_details to get overall case information.

    • Use secops-soar.list_alerts_by_case to get associated alerts.

    • Use secops-soar.get_entities_by_alert_group_identifiers (if applicable, or parse entities from alerts/events) to extract key entities.

    • Store all details in ${CASE_DETAILS_MAP}.

  3. Group Cases: Analyze entities and alert details across all cases in ${CASE_DETAILS_MAP}. Identify logical groups (${CASE_GROUPS}) based on ${GROUPING_CRITERIA} (if provided) or observed similarities (e.g., shared critical entities, common alert types, overlapping timeframes).

  4. Prioritize Groups: Assess the priority of each group in ${CASE_GROUPS} based on factors like combined alert severity, number of cases in the group, criticality of shared entities, or potential impact. Store as ${PRIORITIZED_GROUPS}.

  5. Enrich Key Entities (Optional): For high-priority groups in ${PRIORITIZED_GROUPS}, identify key shared entities. Perform basic enrichment on these entities using secops-mcp.lookup_entity and relevant gti-mcp tools. Store in ${ENRICHMENT_DATA_SUMMARY}.

  6. Generate Summary Report: Create a Markdown report (${REPORT_CONTENT}) summarizing the ${PRIORITIZED_GROUPS}, the rationale for grouping and prioritization, and key findings (including ${ENRICHMENT_DATA_SUMMARY} if available). Use write_to_file to save the report to ${REPORT_FILE_PATH} (e.g., ./reports/case_grouping_report_${timestamp}.md).

        sequenceDiagram
    participant Analyst/User
    participant AutomatedAgent as Automated Agent (MCP Client)
    participant SOAR as secops-soar
    participant SIEM as secops-mcp
    participant GTI as gti-mcp

    Analyst/User->>AutomatedAgent: Start Group Cases v2 Workflow\nInput: NUMBER_OF_CASES (opt), TIME_FRAME_HOURS (opt), GROUPING_CRITERIA (opt)

    %% Step 1: List Cases
    AutomatedAgent->>SOAR: list_cases(limit=NUMBER_OF_CASES, time_frame_hours=TIME_FRAME_HOURS)
    SOAR-->>AutomatedAgent: List of Cases (CASE_LIST: C1, C2...)

    %% Step 2: Gather Details
    Note over AutomatedAgent: Initialize CASE_DETAILS_MAP
    loop For each Case Ci in CASE_LIST
        AutomatedAgent->>SOAR: get_case_full_details(case_id=Ci)
        SOAR-->>AutomatedAgent: Details for Ci
        AutomatedAgent->>SOAR: list_alerts_by_case(case_id=Ci)
        SOAR-->>AutomatedAgent: Alerts for Ci
        AutomatedAgent->>SOAR: get_entities_by_alert_group_identifiers(case_id=Ci, ...)
        SOAR-->>AutomatedAgent: Entities for Ci
        Note over AutomatedAgent: Store all details in CASE_DETAILS_MAP[Ci]
    end

    %% Step 3 & 4: Group & Prioritize
    Note over AutomatedAgent: Analyze CASE_DETAILS_MAP based on GROUPING_CRITERIA or similarities.
    Note over AutomatedAgent: Form CASE_GROUPS (G1, G2...).
    Note over AutomatedAgent: Prioritize groups into PRIORITIZED_GROUPS.

    %% Step 5: Enrich (Optional)
    opt Enrich High Priority Groups
        Note over AutomatedAgent: Initialize ENRICHMENT_DATA_SUMMARY
        loop For each High Priority Group Gp in PRIORITIZED_GROUPS
            Note over AutomatedAgent: Identify key shared entities (Ep1, Ep2...)
            loop For each Entity Epi in Gp
                AutomatedAgent->>SIEM: lookup_entity(entity_value=Epi)
                SIEM-->>AutomatedAgent: SIEM Summary for Epi
                AutomatedAgent->>GTI: get_..._report(ioc=Epi) %% Appropriate GTI tool
                GTI-->>AutomatedAgent: GTI Enrichment for Epi
                Note over AutomatedAgent: Store in ENRICHMENT_DATA_SUMMARY
            end
        end
    end

    %% Step 6: Generate Report
    Note over AutomatedAgent: Synthesize findings into REPORT_CONTENT (Markdown)
    AutomatedAgent->>AutomatedAgent: write_to_file(path="./reports/case_grouping_report_${timestamp}.md", content=REPORT_CONTENT)
    Note over AutomatedAgent: Report file created (REPORT_FILE_PATH)
    Note over AutomatedAgent: Prepare GROUPING_ANALYSIS_SUMMARY

    AutomatedAgent->>Analyst/User: attempt_completion(result="Case grouping analysis complete. Report: REPORT_FILE_PATH. Summary: GROUPING_ANALYSIS_SUMMARY.")

Completion Criteria#

  • A list of recent SOAR cases (${CASE_LIST}) has been retrieved based on the specified criteria.

  • Detailed information, including alerts and key entities, has been gathered for each case in the list and stored (${CASE_DETAILS_MAP}).

  • Cases have been analyzed and grouped into logical clusters (${CASE_GROUPS}) based on defined or observed criteria.

  • The identified case groups have been prioritized (${PRIORITIZED_GROUPS}).

  • (Optional) Key shared entities within high-priority groups have undergone basic enrichment, and a summary (${ENRICHMENT_DATA_SUMMARY}) is available.

  • A comprehensive Markdown summary report (${REPORT_CONTENT}), detailing the groups, prioritization, and key findings, has been generated and saved to ${REPORT_FILE_PATH}.

  • A ${GROUPING_ANALYSIS_SUMMARY} is available.

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