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implementing-soar-automation-with-phantom Implements Security Orchestration, Automation, and Response (SOAR) workflows using Splunk SOAR (formerly Phantom) to automate alert triage, IOC enrichment, containment actions, and incident response playbooks. Use when SOC teams need to reduce manual analyst work, standardize response procedures, or integrate multiple security tools into automated workflows.
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name implementing-soar-automation-with-phantom description Implements Security Orchestration, Automation, and Response (SOAR) workflows using Splunk SOAR (formerly Phantom) to automate alert triage, IOC enrichment, containment actions, and incident response playbooks. Use when SOC teams need to reduce manual analyst work, standardize response procedures, or integrate multiple security tools into automated workflows.
domain cybersecurity subdomain soc-operations tags ["soc","soar","phantom","splunk-soar","automation","playbook","orchestration","incident-response"] mitre_attack ["T1566","T1059","T1078"] version 1.0 author mahipal license Apache-2.0 nist_csf ["DE.CM-01","DE.AE-02","RS.MA-01","DE.AE-06"]
Implementing SOAR Automation with Phantom
When to Use
Use this skill when:
SOC teams need to automate repetitive triage and enrichment tasks for high-volume alerts
Manual response times exceed SLA requirements and automation can reduce MTTR
Multiple security tools (SIEM, EDR, firewall, TIP) need orchestrated response actions
Playbook standardization is required to ensure consistent analyst response across shifts
Do not use for fully autonomous containment without human approval gates — always include analyst decision points for high-impact actions like account disabling or host isolation.
Prerequisites
Splunk SOAR (Phantom) 6.x+ deployed with web interface access
App connectors configured: VirusTotal, CrowdStrike, ServiceNow, Active Directory, Splunk ES
Splunk ES integration for ingesting notable events as SOAR events
API credentials for each integrated tool stored in SOAR asset configuration
Python knowledge for custom playbook actions
Workflow
Step 1: Configure Asset Connections
Set up integrations with security tools via SOAR Apps:
VirusTotal Asset Configuration:
{
"app" : "VirusTotal v3" ,
"asset_name" : "virustotal_prod" ,
"configuration" : {
"api_key" : "YOUR_VT_API_KEY" ,
"rate_limit" : true ,
"max_requests_per_minute" : 4
} ,
"product_vendor" : "VirusTotal" ,
"product_name"
:
"VirusTotal"
}
CrowdStrike Falcon Asset:
{
"app" : "CrowdStrike Falcon" ,
"asset_name" : "crowdstrike_prod" ,
"configuration" : {
"client_id" : "CS_CLIENT_ID" ,
"client_secret" : "CS_CLIENT_SECRET" ,
"base_url" : "https://api.crowdstrike.com"
}
}
{
"app" : "Active Directory" ,
"asset_name" : "ad_prod" ,
"configuration" : {
"server" : "dc01.company.com" ,
"username" : "soar_service@company.com" ,
"password" : "SERVICE_ACCOUNT_PASSWORD" ,
"ssl" : true }
}
Step 2: Build Phishing Triage Playbook Create an automated phishing response playbook in Python (Phantom playbook format):
"""
Phishing Triage Automation Playbook
Trigger: New phishing email reported via Splunk ES notable or email ingestion
"""
import phantom.rules as phantom
import json
def on_start (container ):
artifacts = phantom.get_artifacts(container_id=container["id" ])
for artifact in artifacts:
artifact_type = artifact.get("cef" , {}).get("type" , "" )
if artifact_type == "url" :
phantom.act("url reputation" , targets=artifact,
assets=["virustotal_prod" ],
callback=url_reputation_callback,
name="url_reputation" )
elif artifact_type == "hash" :
phantom.act("file reputation" , targets=artifact,
assets=["virustotal_prod" ],
callback=hash_reputation_callback,
name="file_reputation" )
elif artifact_type == "ip" :
phantom.act("ip reputation" , targets=artifact,
assets=["virustotal_prod" ],
callback=ip_reputation_callback,
name="ip_reputation" )
def url_reputation_callback (action, success, container, results, handle ):
if not success:
phantom.comment(container, "URL reputation check failed" )
return
for result in results:
data = result.get("data" , [{}])[0 ]
malicious_count = data.get("summary" , {}).get("malicious" , 0 )
total_engines = data.get("summary" , {}).get("total_engines" , 0 )
if malicious_count > 5 :
phantom.act("block url" , targets=result,
assets=["palo_alto_prod" ],
name="block_malicious_url" )
phantom.set_severity(container, "high" )
phantom.set_status(container, "open" )
phantom.comment(container,
f"URL flagged by {malicious_count} /{total_engines} engines. "
f"Blocked on firewall. Escalating to Tier 2." )
phantom.act("create ticket" , targets=container,
assets=["servicenow_prod" ],
parameters=[{
"short_description" : f"Phishing - Malicious URL detected" ,
"urgency" : "2" ,
"impact" : "2"
}],
name="create_incident_ticket" )
elif malicious_count > 0 :
phantom.promote(container, template="Phishing Investigation" )
phantom.comment(container,
f"URL flagged by {malicious_count} /{total_engines} engines. "
f"Requires analyst review." )
else :
phantom.set_status(container, "closed" )
phantom.comment(container,
f"URL clean: 0/{total_engines} engines flagged. Auto-closed." )
def hash_reputation_callback (action, success, container, results, handle ):
if not success:
return
for result in results:
data = result.get("data" , [{}])[0 ]
positives = data.get("summary" , {}).get("positives" , 0 )
if positives > 10 :
phantom.act("quarantine device" , targets=result,
assets=["crowdstrike_prod" ],
name="isolate_endpoint" )
phantom.set_severity(container, "high" )
def ip_reputation_callback (action, success, container, results, handle ):
if not success:
return
for result in results:
data = result.get("data" , [{}])[0 ]
malicious = data.get("summary" , {}).get("malicious" , 0 )
if malicious > 3 :
phantom.act("block ip" , targets=result,
assets=["palo_alto_prod" ],
name="block_malicious_ip" )
Step 3: Build Alert Enrichment Playbook Automate enrichment for all incoming SIEM alerts:
"""
Universal Alert Enrichment Playbook
Runs on every new event to add context before analyst review
"""
import phantom.rules as phantom
def on_start (container ):
success, message, artifacts = phantom.get_artifacts(
container_id=container["id" ], full_data=True
)
ip_artifacts = [a for a in artifacts if a.get("cef" , {}).get("sourceAddress" )]
domain_artifacts = [a for a in artifacts if a.get("cef" , {}).get("destinationDnsDomain" )]
for artifact in ip_artifacts:
ip = artifact["cef" ]["sourceAddress" ]
phantom.act("ip reputation" ,
parameters=[{"ip" : ip}],
assets=["virustotal_prod" ],
callback=enrich_ip_callback,
name=f"vt_ip_{ip} " )
phantom.act("geolocate ip" ,
parameters=[{"ip" : ip}],
assets=["maxmind_prod" ],
callback=geoip_callback,
name=f"geo_{ip} " )
phantom.act("whois ip" ,
parameters=[{"ip" : ip}],
assets=["whois_prod" ],
name=f"whois_{ip} " )
for artifact in domain_artifacts:
domain = artifact["cef" ]["destinationDnsDomain" ]
phantom.act("domain reputation" ,
parameters=[{"domain" : domain}],
assets=["virustotal_prod" ],
name=f"vt_domain_{domain} " )
def enrich_ip_callback (action, success, container, results, handle ):
"""Update container with enrichment data"""
if success:
for result in results:
summary = result.get("summary" , {})
phantom.add_artifact(container, {
"cef" : {
"vt_malicious" : summary.get("malicious" , 0 ),
"vt_suspicious" : summary.get("suspicious" , 0 ),
"enrichment_source" : "VirusTotal"
},
"label" : "enrichment" ,
"name" : "VT IP Enrichment"
})
Step 4: Implement Approval Gates for High-Impact Actions Add human-in-the-loop for critical actions:
def containment_decision (action, success, container, results, handle ):
"""Present analyst with containment options"""
phantom.prompt(
container=container,
user="soc_tier2" ,
message=(
"Confirmed malicious activity detected.\n"
f"Host: {container['artifacts' ][0 ]['cef' ].get('sourceAddress' )} \n"
f"Threat: {results[0 ]['summary' ].get('threat_name' )} \n\n"
"Select containment action:"
),
respond_in_mins=15 ,
options=["Isolate Host" , "Disable Account" , "Both" , "Monitor Only" ],
callback=execute_containment
)
def execute_containment (action, success, container, results, handle ):
response = results.get("response" , "Monitor Only" )
if response in ["Isolate Host" , "Both" ]:
phantom.act("quarantine device" ,
parameters=[{"hostname" : container["artifacts" ][0 ]["cef" ]["sourceHostName" ]}],
assets=["crowdstrike_prod" ],
name="isolate_host" )
if response in ["Disable Account" , "Both" ]:
phantom.act("disable user" ,
parameters=[{"username" : container["artifacts" ][0 ]["cef" ]["sourceUserName" ]}],
assets=["ad_prod" ],
name="disable_account" )
phantom.comment(container, f"Analyst approved: {response} " )
Step 5: Configure Playbook Scheduling and Triggers Set up event triggers in SOAR:
{
"playbook_name" : "phishing_triage_automation" ,
"trigger" : {
"type" : "event_created" ,
"conditions" : {
"label" : [ "phishing" , "notable" ] ,
"severity" : [ "high" , "medium" ]
}
} ,
"active" : true ,
"run_as" : "automation_user"
}
Step 6: Monitor Playbook Performance Track automation effectiveness with SOAR metrics:
import requests
headers = {"ph-auth-token" : "YOUR_SOAR_TOKEN" }
response = requests.get(
"https://soar.company.com/rest/playbook_run" ,
headers=headers,
params={
"page_size" : 100 ,
"filter" : '{"status":"success"}' ,
"sort" : "create_time" ,
"order" : "desc"
}
)
runs = response.json()["data" ]
total_runs = len (runs)
avg_duration = sum (r["end_time" ] - r["start_time" ] for r in runs) / total_runs
auto_closed = sum (1 for r in runs if r.get("auto_resolved" ))
print (f"Total runs: {total_runs} " )
print (f"Avg duration: {avg_duration:.1 f} s" )
print (f"Auto-resolved: {auto_closed} /{total_runs} ({auto_closed/total_runs*100 :.0 f} %)" )
Key Concepts Term Definition SOAR Security Orchestration, Automation, and Response — platform integrating security tools with automated playbooks Playbook Automated workflow defining sequential and parallel actions triggered by security events Asset SOAR configuration for a connected security tool (API endpoint, credentials, connection parameters) Container SOAR event object containing artifacts (IOCs) from an ingested alert or incident Artifact Individual IOC or data point within a container (IP, hash, URL, domain, email) Approval Gate Human-in-the-loop step requiring analyst decision before executing high-impact automated actions
Tools & Systems
Splunk SOAR (Phantom) : Enterprise SOAR platform with 300+ app integrations and visual playbook editorSplunk ES : SIEM platform feeding notable events into SOAR as containers for automated triageCrowdStrike Falcon : EDR platform integrated via SOAR for automated host isolation and threat huntingServiceNow : ITSM platform integrated for automated incident ticket creation and trackingPalo Alto NGFW : Firewall integrated for automated IP/URL blocking via SOAR playbooks
Common Scenarios
Phishing Triage : Auto-extract URLs/attachments, detonate in sandbox, block malicious, create ticketMalware Alert Enrichment : Auto-enrich file hashes across VT/MalwareBazaar, isolate if confirmed maliciousBrute Force Response : Auto-check if attack succeeded, disable account if compromised, block source IPThreat Intel IOC Processing : Auto-ingest TI feed IOCs, check against internal logs, create blocks for matchesVulnerability Alert Response : Auto-query asset database for affected systems, create patching ticket with priority
Output Format SOAR PLAYBOOK EXECUTION REPORT
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Playbook: Phishing Triage Automation v2.3
Container: SOAR-2024-08921
Trigger: Notable event from Splunk ES (phishing)
Actions Executed:
[1] URL Reputation (VirusTotal) — 14/90 engines malicious [2.1s]
[2] IP Reputation (AbuseIPDB) — Confidence: 85% [1.3s]
[3] Block URL (Palo Alto) — Blocked on PA-5260 [0.8s]
[4] Block IP (Palo Alto) — Blocked on PA-5260 [0.7s]
[5] Create Ticket (ServiceNow) — INC0012345 created [1.5s]
[6] Prompt Analyst (Tier 2) — Response: "Isolate Host" [4m 12s]
[7] Quarantine Device (CrowdStrike) — WORKSTATION-042 isolated [3.2s]
Total Duration: 4m 22s (vs 35min avg manual triage)
Time Saved: ~31 minutes
Disposition: True Positive — Escalated to IR
