Extract DPAPI-protected secrets such as credentials and browser data offline and online.
日本語の概要は準備中です。原文の説明を表示しています。
Build automated threat intelligence enrichment pipelines in Splunk Enterprise Security using lookup tables, modular inputs, and the Threat Intelligence Framework.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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)
|
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)
# 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
[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
# 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
| 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
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
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
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, ", ")
| inputlookup ip_threat_intel_lookup
| stats count by source, threat_type
| sort -count
| head 20
| 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")
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Extract DPAPI-protected secrets such as credentials and browser data offline and online.
日本語の概要は準備中です。原文の説明を表示しています。
Audit, detect, and remediate Shadow Credentials misconfigurations on msDS-KeyCredentialLink in Active Directory. Focuses on access-controls, monitoring Event ID 5136, and credential-management hygiene.
日本語の概要は準備中です。原文の説明を表示しています。
Prepare a defense-contractor environment for CMMC Level 2 certification: scope CUI and FCI, implement the 110 NIST SP 800-171 Rev 2 security requirements across 14 families, compute the SPRS score with the DoD Assessment Methodology, manage a compliant POA&M, and ready the organization for a C3PAO assessment. Use when an organization handles Controlled Unclassified Information (CUI) under a DoD contract, when a contract carries DFARS clause 252.204-7012/7019/7020/7021, when preparing for or responding to a CMMC assessment, when computing or improving an SPRS score, when building a System Security Plan or POA&M for 800-171, or when scoping which systems are in the CUI boundary. Keywords: CMMC, CMMC Level 2, NIST 800-171, SP 800-171 Rev 2, CUI, FCI, SPRS, DFARS 7012, C3PAO, POA&M, System Security Plan, DoD Assessment Methodology, 110 controls, defense industrial base, DIB, FedRAMP equivalency.
日本語の概要は準備中です。原文の説明を表示しています。
Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
日本語の概要は準備中です。原文の説明を表示しています。
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
日本語の概要は準備中です。原文の説明を表示しています。
Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
日本語の概要は準備中です。原文の説明を表示しています。