| name | ip-get-secops-threat-intel |
| description | Use when querying Chronicle SecOps threat intelligence feeds for an IP address. |
| category | atomic |
| version | 1.0.0 |
| type | Skill |
| title | Skill: Atomic Runbook: Get IP Address Threat Intel via SecOps MCP |
| generated | {"by":"process:google-labs-jules","at":"2026-08-20T02:00:00Z"} |
Atomic Runbook: Get IP Address Threat Intel via SecOps MCP
ID: RB-ATOM-IP-002
Version: 1.0
Last_Updated: 2025-05-30
Purpose: To retrieve general threat intelligence about an IP address using the Chronicle secops-mcp get_threat_intel tool, often as a secondary check or when more narrative context is needed.
Parent_Runbook(s)/Protocol(s): rules-bank/indicator_handling_protocols.md#1-atomic-indicator-ip-address, rb_ip_get_gti_report.md (as potential next step)
Trigger: When an IP address requires external reputation/threat intelligence, potentially after an initial check with a more specialized tool like GTI, or if broader textual context is desired.
Inputs Required
ip_address: string - The IP address to query.
- Source Example: Alert field, output from
rb_ip_get_gti_report.md if further context is needed.
gti_confidence (optional): string - Confidence level from a preceding GTI check (e.g., "Low_Risk_GTI", "Medium_Risk_GTI_Needs_Correlation"). Used for context.
Execution Steps
- Tool Selection:
- Primary_Tool_MCP_Server:
secops-mcp
- Primary_Tool_Name:
get_threat_intel
- Parameter Mapping:
- Map
ip_address (Input) to the query for the MCP Tool. Construct a query string.
query: "Provide threat intelligence summary for IP address {ip_address}"
- Execute Tool: Call the
get_threat_intel tool with the constructed query.
- AI Agent Note: Refer to
rules-bank/mcp_tool_best_practices.md for specific guidance on get_threat_intel.
- Data Transformation/Extraction:
- The output is a textual summary. The AI agent will need to parse this text for keywords indicating risk or specific threat types if further automated decision-making is required based on this output.
Outputs Expected
secops_ti_summary: string - The textual threat intelligence summary provided by the get_threat_intel tool.
identified_keywords: list (optional) - List of keywords extracted by AI from the summary (e.g., "malware", "C2", "benign", "scanning activity").
output_status: string - ["Success", "Failure"]
output_message: string (if Failure) - Details of the issue.
Decision Logic / Next Steps (If Applicable)
- IF
output_status is "Success":
- IF
secops_ti_summary contains keywords like "known malicious", "C2 server", "high confidence threat" THEN
- Flag IP as "High_Risk_SecOpsTI".
- Consider proceeding to containment-related runbooks or escalate immediately.
- ELSE IF
secops_ti_summary contains keywords like "potentially unwanted", "suspicious activity", "mixed reputation" OR (gti_confidence was "Medium_Risk_GTI_Needs_Correlation" AND summary is not explicitly benign) THEN
- Flag IP as "Medium_Risk_SecOpsTI_Needs_Correlation".
- Proceed to further internal investigation runbooks (e.g.,
rb_ip_lookup_entity_chronicle.md).
- ELSE (summary suggests benign or no specific threat information)
- Flag IP as "Low_Risk_SecOpsTI" (or "Info_Only_SecOpsTI").
- Proceed to further internal investigation runbooks.
- ELSE (
output_status is "Failure"):
- Log error:
output_message.
- Escalate to human analyst: "Failed to retrieve SecOps threat intelligence for IP {ip_address}."
AI Agent Execution Notes
- The AI agent should be prepared to perform basic Natural Language Processing (NLP) on the
secops_ti_summary to extract identified_keywords if this output is to be used for further automated branching.
- If this runbook is triggered due to a failure or inconclusive result from
rb_ip_get_gti_report.md, that context should be logged.
Metrics Collection Points
- Log execution time for this runbook.
- Log
output_status.
- (Reference
rules-bank/ai_performance_logging_requirements.md)
References
rules-bank/mcp_tool_best_practices.md
rules-bank/indicator_handling_protocols.md
rules-bank/ai_performance_logging_requirements.md
- "Blueprint for AI Agents in Cybersecurity"
- "Measuring ROI of AI agents in security operations"