domain-get-gti-report

name	domain-get-gti-report
description	Use when fetching GTI threat reputation and WHOIS intelligence for a specific domain name.
category	atomic
version	1.0.0
type	Skill
title	Skill: Atomic Runbook: Get Domain Reputation from GTI
generated	{"by":"process:google-labs-jules","at":"2026-08-20T02:00:00Z"}

Atomic Runbook: Get Domain Reputation from GTI

ID: RB-ATOM-DOMAIN-001 Version: 1.0 Last_Updated: 2025-05-30 Purpose: To retrieve a comprehensive domain analysis report from Google Threat Intelligence (GTI) to assess its reputation, resolution history, and categorization. Parent_Runbook(s)/Protocol(s): rules-bank/indicator_handling_protocols.md#2-atomic-indicator-domain-name--fqdn Trigger: When a domain name or FQDN requires an external reputation check as part of an investigation or triage process.

---

Inputs Required

• domain_name: string - The domain name or FQDN to query.
  • Source Example: Alert field target.hostname, network.dns.question.name; IOC lists; Output from another runbook.

---

Execution Steps

1. Tool Selection:
   • Primary_Tool_MCP_Server: Google Threat Intelligence MCP
   • Primary_Tool_Name: get_domain_report
2. Parameter Mapping:
   • Map domain_name (Input) to MCP Tool parameter domain.
3. Execute Tool: Call the get_domain_report tool with the mapped domain_name.
   • AI Agent Note: Refer to rules-bank/mcp_tool_best_practices.md for specific guidance on GTI tools.
4. Data Transformation/Extraction:
   • The primary output is a JSON object. Key fields for initial assessment include data.attributes.last_analysis_stats (especially malicious), data.attributes.categories, data.attributes.whois, and data.attributes.resolutions.

---

Outputs Expected

• gti_domain_report: JSON - The full JSON report from the GTI get_domain_report tool.
• malicious_score: integer - The number of engines reporting the domain as malicious (extracted from gti_domain_report.data.attributes.last_analysis_stats.malicious).
• harmless_score: integer - The number of engines reporting the domain as harmless.
• suspicious_score: integer - The number of engines reporting the domain as suspicious.
• categories: list - List of categories assigned to the domain by GTI (e.g., "malware", "phishing", "benign").
• resolutions: list - List of IP addresses the domain has resolved to historically.
• whois_registrar: string (optional) - Registrar from WHOIS data.
• whois_creation_date: string/timestamp (optional) - Creation date from WHOIS.
• output_status: string - ["Success", "Failure"]
• output_message: string (if Failure) - Details of the issue (e.g., "API error", "Invalid domain format").

---

Decision Logic / Next Steps (If Applicable)

• IF output_status is "Success":
  • IF malicious_score > 5 OR "malware" IN categories OR "phishing" IN categories THEN
    • Flag Domain as "High_Risk_GTI".
    • For each IP in resolutions, consider initiating RB-ATOM-IP-001 (Get IP Reputation From GTI).
    • Consider proceeding to containment-related runbooks or escalate immediately.
  • ELSE IF malicious_score > 0 OR suspicious_score > 0 THEN
    • Flag Domain as "Medium_Risk_GTI_Needs_Correlation".
    • Proceed to rb_domain_lookup_entity_chronicle.md and for each IP in resolutions, consider RB-ATOM-IP-001.
  • ELSE (low malicious/suspicious score)
    • Flag Domain as "Low_Risk_GTI".
    • Proceed to rb_domain_lookup_entity_chronicle.md.
• ELSE (output_status is "Failure"):
  • Log error: output_message.
  • Consider executing rb_domain_get_secops_threat_intel.md as an alternative.
  • IF alternative also fails, escalate to human analyst: "Failed to retrieve external reputation for domain {domain_name}."

---

AI Agent Execution Notes

• Ensure the input domain_name is a valid domain/FQDN.
• The AI should parse the gti_domain_report to extract the specific output parameters.
• Pay attention to recently registered domains (whois_creation_date) combined with malicious indicators, as this can be a sign of a new threat campaign.

---

Metrics Collection Points

• Log execution time for this runbook.
• Log output_status, malicious_score, harmless_score, suspicious_score.
• (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