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Get Started Free →Build automated threat intelligence enrichment pipelines in Splunk Enterprise Security using lookup tables, modular inputs, and the Threat Intelligence Framework.
.claude/skills/building-threat-intelligence-enrichment-in-splunk/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | — | — |
| case-11 | ✗→✓ | ▲ Improved | — | — |
| case-05 | ✓→✓ | = Same ✓ | — | — |
| case-07 | ✓→✓ | = Same ✓ | — | — |
| case-17 | ✗→✗ | = Same ✗ | — | — |
Splunk's Threat Intelligence Framework in Enterprise Security enables SOC teams to automatically correlate indicators of compromise (IOCs) against security events. The framework ingests threat feeds, normalizes indicators into KV Store collections, and uses lookup-based correlation searches to flag matching events. Splunk Threat Intelligence Management centralizes collection, normalization, and enrichment from multiple sources, reducing triage time by providing analysts with immediate context.
External TI Sources (STIX/TAXII, CSV, API)
|
v
Modular Inputs (download and parse feeds)
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v
KV Store Collections (normalized IOC storage)
|-- ip_intel
|-- domain_intel
|-- file_intel
|-- url_intel
|-- email_intel
|
v
Threat Intelligence Lookups
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v
Correlation Searches (match events against IOCs)
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v
Notable Events (enriched with TI context)conf# inputs.conf - TAXII feed configuration [threatlist://taxii_feed_example] description = TAXII 2.1 Threat Feed type = taxii url = https://threatfeed.example.com/taxii2/ collection = threat-indicators-v21 polling_interval = 3600 api_key = <encrypted_api_key> disabled = false
conf# inputs.conf - CSV threat list [threatlist://custom_blocklist] description = Internal threat blocklist type = csv url = https://internal.company.com/threat-feeds/blocklist.csv polling_interval = 1800 disabled = false
python# bin/threatfeed_otx.py - OTX AlienVault feed collector import json import sys import requests from splunklib.modularinput import Script, Scheme, Argument, Event class OTXFeedInput(Script): def get_scheme(self): scheme = Scheme("OTX AlienVault Feed") scheme.description = "Collects IOCs from AlienVault OTX" scheme.use_external_validation = False scheme.streaming_mode = Scheme.streaming_mode_xml api_key_arg = Argument("api_key") api_key_arg.data_type = Argument.data_type_string api_key_arg.required_on_create = True scheme.add_argument(api_key_arg) pulse_days_arg = Argument("pulse_days") pulse_days_arg.data_type = Argument.data_type_number pulse_days_arg.required_on_create = False scheme.add_argument(pulse_days_arg) return scheme def stream_events(self, inputs, ew): for input_name, input_item in inputs.inputs.items(): api_key = input_item["api_key"] pulse_days = int(input_item.get("pulse_days", 30)) headers = {"X-OTX-API-KEY": api_key} url = f"https://otx.alienvault.com/api/v1/pulses/subscribed?modified_since={pulse_days}d" try: response = requests.get(url, headers=headers, timeout=60) response.raise_for_status() data = response.json() for pulse in data.get("results", []): for indicator in pulse.get("indicators", []): event = Event() event.stanza = input_name event.data = json.dumps({ "indicator": indicator["indicator"], "type": indicator["type"], "pulse_name": pulse["name"], "pulse_id": pulse["id"], "description": indicator.get("description", ""), "created": indicator.get("created", ""), "threat_source": "OTX", "confidence": pulse.get("adversary", "unknown"), }) ew.write_event(event) except requests.RequestException as e: ew.log("ERROR", f"OTX feed collection failed: {str(e)}") if __name__ == "__main__": sys.exit(OTXFeedInput().run(sys.argv))
conf# collections.conf [ip_threat_intel] field.ip = string field.threat_type = string field.confidence = number field.source = string field.description = string field.first_seen = time field.last_seen = time field.severity = string [domain_threat_intel] field.domain = string field.threat_type = string field.confidence = number field.source = string field.whois_registrar = string field.whois_created = string [file_hash_intel] field.file_hash = string field.hash_type = string field.malware_family = string field.confidence = number field.source = string field.detection_names = string
conf# transforms.conf [ip_threat_intel_lookup] external_type = kvstore collection = ip_threat_intel fields_list = ip, threat_type, confidence, source, description, severity [domain_threat_intel_lookup] external_type = kvstore collection = domain_threat_intel fields_list = domain, threat_type, confidence, source [file_hash_intel_lookup] external_type = kvstore collection = file_hash_intel fields_list = file_hash, hash_type, malware_family, confidence, source
spl| tstats summariesonly=true count from datamodel=Network_Traffic where All_Traffic.action=allowed by All_Traffic.src_ip, All_Traffic.dest_ip, All_Traffic.dest_port, _time span=5m | rename "All_Traffic.*" as * | lookup ip_threat_intel_lookup ip as dest_ip OUTPUT threat_type, confidence, source as ti_source, severity as ti_severity | where isnotnull(threat_type) | lookup asset_lookup ip as src_ip OUTPUT asset_name, asset_owner, asset_priority | eval urgency=case( ti_severity=="critical" AND asset_priority=="critical", "critical", ti_severity=="high" OR asset_priority=="critical", "high", ti_severity=="medium", "medium", true(), "low" ) | eval description="Connection from ".src_ip." (".asset_name.") to known malicious IP ".dest_ip." (".threat_type.") - Source: ".ti_source
splindex=dns sourcetype=stream:dns query_type=A OR query_type=AAAA | lookup domain_threat_intel_lookup domain as query OUTPUT threat_type as domain_threat, confidence as domain_confidence, source as ti_source | where isnotnull(domain_threat) AND domain_confidence > 70 | stats count dc(src_ip) as unique_sources values(src_ip) as source_ips by query, domain_threat, ti_source | eval severity=case(domain_confidence > 90, "critical", domain_confidence > 70, "high", true(), "medium") | eval description="DNS queries to malicious domain ".query." from ".unique_sources." hosts - Threat: ".domain_threat
splindex=endpoint sourcetype=sysmon EventCode=1 | lookup file_hash_intel_lookup file_hash as Hashes OUTPUT malware_family, confidence as hash_confidence, source as ti_source | where isnotnull(malware_family) | stats count values(ParentCommandLine) as parent_commands by Computer, User, Image, malware_family, ti_source | eval severity="critical" | eval description="Known malware ".malware_family." executed on ".Computer." by ".User." - Binary: ".Image
splindex=firewall sourcetype=pan:traffic action=allowed | eval indicators=mvappend(src_ip, dest_ip) | mvexpand indicators | lookup ip_threat_intel_lookup ip as indicators OUTPUT threat_type as ip_threat, confidence as ip_confidence, source as ip_ti_source | lookup geo_ip_lookup ip as indicators OUTPUT country, city, latitude, longitude | lookup whois_lookup ip as indicators OUTPUT org as ip_org, asn as ip_asn | where isnotnull(ip_threat) | stats count values(ip_threat) as threat_types values(ip_ti_source) as intel_sources values(country) as countries values(ip_org) as organizations latest(_time) as last_seen earliest(_time) as first_seen by src_ip, dest_ip, dest_port | eval enrichment_context="Threat: ".mvjoin(threat_types, ", ")." | Geo: ".mvjoin(countries, ", ")." | Org: ".mvjoin(organizations, ", ")
spl| inputlookup ip_threat_intel_lookup | stats count by source, threat_type | sort -count | head 20
spl| inputlookup ip_threat_intel_lookup | eval age_days=round((now() - strptime(last_seen, "%Y-%m-%dT%H:%M:%S")) / 86400, 0) | stats count avg(age_days) as avg_age_days max(age_days) as max_age_days by source | eval status=case(avg_age_days > 30, "STALE", avg_age_days > 7, "AGING", true(), "FRESH")
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-17 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-03 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-04 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-02 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-20 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-22 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-01 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-21 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-14 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-19 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-23 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-16 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-10 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-12 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-11 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-08 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-18 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-05 | pass→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-06 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-07 | pass→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-09 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-13 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-15 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +9 percentage points is the difference between those two pass rates over the 23 comparable cases.
The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.
Other measured skills in the registry, with their headline benchmark lift.