abusing-dpapi-for-cred…
Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using…
Build automated IOC enrichment pipelines in Splunk Enterprise Security by ingesting threat feeds into KV Store collections and correlating them against security events via lookup tables, modular inputs, and the Threat Intelligence Framework. Use when wiring threat intel into
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Build automated IOC enrichment pipelines in Splunk Enterprise Security by ingesting threat feeds into KV Store collections and correlating them against security events via lookup tables, modular inputs, and the Threat Intelligence Framework. Use when wiring threat intel into
name: building-threat-intelligence-enrichment-in-splunk description: Build automated IOC enrichment pipelines in Splunk Enterprise Security by ingesting threat feeds into KV Store collections and correlating them against security events via lookup tables, modular inputs, and the Threat Intelligence Framework. Use when wiring threat intel into Splunk correlation searches to flag IOC matches and cut SOC triage time. domain: cybersecurity subdomain: soc-operations tags: - splunk - threat-intelligence - enrichment - ioc - lookup - siem - soc - enterprise-security version: '1.0' author: mahipal license: Apache-2.0 nist_csf: - DE.CM-01 - DE.AE-02 - RS.MA-01 - DE.AE-06 mitre_attack: - T1071 - T1105 - T1041
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)
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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)# 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
# 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
# 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))# 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 [f
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains · Apache 2.0
Repo: mukul975/Anthropic-Cybersecurity-Skills
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