Building Threat Intelligence Enrichment in Splunk
Overview
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.
When to Use
- When deploying or configuring building threat intelligence enrichment in splunk capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
Prerequisites
- Splunk Enterprise Security (ES) 7.x or later
- Threat Intelligence Management add-on or Threat Intelligence Framework
- API keys for external threat intelligence feeds (MISP, OTX, VirusTotal, AbuseIPDB)
- KV Store enabled and properly configured
- Admin access for modular input configuration
Threat Intelligence Framework Architecture
External TI Sources (STIX/TAXII, CSV, API)
|
v
Modular Inputs (download and parse feeds)
|
v
KV Store Collections (normalized IOC storage)
|-- ip_intel
|-- domain_intel
|-- file_intel
|-- url_intel
|-- email_intel
|
v
Threat Intelligence Lookups
|
v
Correlation Searches (match events against IOCs)
|
v
Notable Events (enriched with TI context)
Configuring Threat Intelligence Sources
STIX/TAXII Feed Integration
# 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
CSV-Based Threat List
# 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
Custom Modular Input for API-Based Feeds
# 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))
Building Enrichment Lookups
KV Store Collection Configuration
# 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
Lookup Table Definitions
# 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
Enrichment Correlation Searches
IP-Based Threat Intelligence Correlation
| 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
Domain-Based Threat Intelligence Correlation
index=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
File Hash Correlation
index=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
Multi-Source Enrichment Pipeline
index=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, ", ")
Threat Intelligence Dashboards
IOC Coverage Statistics
| inputlookup ip_threat_intel_lookup
| stats count by source, threat_type
| sort -count
| head 20
Feed Freshness Monitoring
| 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")
References