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building-incident-response-dashboard Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.
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4 arquivos name building-incident-response-dashboard description Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.
domain cybersecurity subdomain soc-operations tags ["soc","dashboard","incident-response","splunk","visualization","situational-awareness","metrics"] version 1.0 author mahipal license Apache-2.0
Building Incident Response Dashboard
When to Use
Use this skill when:
IR teams need real-time dashboards during active incidents for coordination and tracking
SOC leadership requires operational dashboards showing incident status and analyst workload
Post-incident reviews need visual timelines and impact assessments
Executive briefings require high-level incident metrics and trend analysis
Do not use for day-to-day SOC monitoring dashboards (use Incident Review instead) — IR dashboards are designed for active incident coordination and management reporting.
Prerequisites
SIEM platform (Splunk with Dashboard Studio, Elastic Kibana, or Grafana)
Notable event and incident data in SIEM (Splunk ES incident_review index)
Ticketing system integration (ServiceNow, Jira) for remediation tracking
Asset and identity lookup tables for context enrichment
Dashboard publishing access for SOC team and management distribution
Workflow
Step 1: Design Active Incident Dashboard Layout
Build a Splunk Dashboard Studio dashboard for active incident tracking:
<dashboard version ="2" theme ="dark" >
<label > Active Incident Response Dashboard</label >
<description > Real-time tracking for IR-2024-0450</description >
<row >
<panel >
<title > Incident Summary</title >
<single >
<search >
<query >
| makeresults
| eval incident_id="IR-2024-0450",
status="CONTAINMENT",
severity="Critical",
affected_hosts=7,
contained_hosts=5,
iocs_identified=23,
hours_elapsed=round((now()-strptime("2024-03-15 14:00","%Y-%m-%d %H:%M"))/3600,1)
| table incident_id, status, severity, affected_hosts, contained_hosts, iocs_identified, hours_elapsed
</query >
</search >
</single >
</panel >
</row >
</dashboard >
Step 2: Build Real-Time Affected Systems Panel Track affected systems and their containment status:
| inputlookup ir_affected_systems.csv
| eval status_color = case(
status="Contained", "#2ecc71",
status="Compromised", "#e74c3c",
status="Investigating", "#f39c12",
status="Recovered", "#3498db",
1=1, "#95a5a6"
)
| stats count by status
| eval order = case(status="Compromised", 1, status="Investigating", 2,
status="Contained", 3, status="Recovered", 4)
| sort order
| table status, count
--- Detailed host table
| inputlookup ir_affected_systems.csv
| lookup asset_lookup_by_cidr ip AS host_ip OUTPUT category, owner, priority
| table hostname, host_ip, category, owner, status, containment_time,
compromise_vector, analyst_assigned
| sort status, hostname
Step 3: Build IOC Tracking Panel Monitor IOC spread across the environment:
--- IOCs identified during incident
index=* (src_ip IN ("185.234.218.50", "45.77.123.45") OR
dest IN ("evil-c2.com", "malware-drop.com") OR
file_hash IN ("a1b2c3d4...", "e5f6a7b8..."))
earliest="2024-03-14"
| stats count AS hits, dc(src_ip) AS unique_sources,
dc(dest) AS unique_dests, latest(_time) AS last_seen
by sourcetype
| sort - hits
--- IOC timeline
index=* (src_ip IN ("185.234.218.50") OR dest="evil-c2.com")
earliest="2024-03-14"
| timechart span=1h count by sourcetype
--- New IOC discovery tracking
| inputlookup ir_ioc_list.csv
| stats count by ioc_type, source, discovery_time
| sort discovery_time
| table discovery_time, ioc_type, ioc_value, source, status
Step 4: Build Response Timeline Panel Create chronological incident timeline:
| inputlookup ir_timeline.csv
| sort _time
| eval phase = case(
action_type="detection", "Detection",
action_type="triage", "Triage",
action_type="containment", "Containment",
action_type="eradication", "Eradication",
action_type="recovery", "Recovery",
1=1, "Other"
)
| eval phase_color = case(
phase="Detection", "#e74c3c",
phase="Triage", "#f39c12",
phase="Containment", "#e67e22",
phase="Eradication", "#2ecc71",
phase="Recovery", "#3498db"
)
| table _time, phase, action, analyst, details
_time,action_type,action,analyst,details
2024-03-15 14:00,detection,Alert triggered - Cobalt Strike beacon detected,splunk_es,Notable event NE-2024-08921
2024-03-15 14:12,triage,Alert triaged - confirmed true positive,analyst_jdoe,VT score 52/72 on beacon hash
2024-03-15 14:23,containment,Host WORKSTATION-042 isolated,analyst_jdoe,CrowdStrike network isolation
2024-03-15 14:35,containment,C2 domain blocked on firewall,analyst_msmith,Palo Alto rule deployed
2024-03-15 15:00,eradication,Enterprise-wide IOC scan initiated,analyst_jdoe,Splunk search across all indices
2024-03-15 15:30,containment,3 additional hosts identified and isolated,analyst_msmith,Lateral movement confirmed
2024-03-15 16:00,eradication,Malware removed from all affected hosts,analyst_tier3,CrowdStrike RTR cleanup
2024-03-15 18:00,recovery,Systems restored and monitored,analyst_msmith,72-hour monitoring period started
Step 5: Build SOC Operations Dashboard Track overall SOC performance metrics:
--- Incident volume by severity (last 30 days)
index=notable earliest=-30d
| stats count by urgency
| eval order = case(urgency="critical", 1, urgency="high", 2, urgency="medium", 3,
urgency="low", 4, urgency="informational", 5)
| sort order
--- MTTD (Mean Time to Detect)
index=notable earliest=-30d status_label="Resolved*"
| eval mttd_minutes = round((time_of_first_event - orig_time) / 60, 1)
| stats avg(mttd_minutes) AS avg_mttd, median(mttd_minutes) AS med_mttd,
perc95(mttd_minutes) AS p95_mttd
--- MTTR (Mean Time to Respond/Resolve)
index=notable earliest=-30d status_label="Resolved*"
| eval mttr_hours = round((status_end - _time) / 3600, 1)
| stats avg(mttr_hours) AS avg_mttr, median(mttr_hours) AS med_mttr by urgency
--- Analyst workload distribution
index=notable earliest=-7d
| stats count by owner
| sort - count
--- Alert disposition breakdown
index=notable earliest=-30d status_label IN ("Resolved*", "Closed*")
| stats count by disposition
| eval percentage = round(count / sum(count) * 100, 1)
| sort - count
Step 6: Build Executive Briefing Dashboard Create a high-level dashboard for leadership during major incidents:
--- Executive summary panel
| makeresults
| eval metrics = "Business Impact: 1 file server offline (Finance dept), "
."Estimated Recovery: 4 hours, "
."Data Loss Risk: Low (backups verified), "
."Customer Impact: None, "
."Regulatory Notification: Not required (no PII exposure confirmed)"
--- Trend comparison (this month vs last month)
index=notable earliest=-60d
| eval period = if(_time > relative_time(now(), "-30d"), "Current Month", "Previous Month")
| stats count by period, urgency
| chart sum(count) AS incidents by period, urgency
--- Top threat categories
index=notable earliest=-30d
| top rule_name limit=10
| table rule_name, count, percent
Step 7: Automate Dashboard Updates Use Splunk scheduled searches to maintain dashboard data:
--- Scheduled search to update affected systems lookup (runs every 5 minutes)
index=* (src_ip IN [| inputlookup ir_ioc_list.csv | search ioc_type="ip"
| fields ioc_value | rename ioc_value AS src_ip])
earliest=-1h
| stats latest(_time) AS last_seen, count AS event_count,
values(sourcetype) AS data_sources by src_ip
| eval status = if(last_seen > relative_time(now(), "-15m"), "Active", "Dormant")
| outputlookup ir_affected_systems_auto.csv
Key Concepts Term Definition Situational Awareness Real-time understanding of incident scope, affected systems, and response progress MTTD Mean Time to Detect — average time from threat occurrence to SOC alert generation MTTR Mean Time to Respond — average time from alert to incident resolution or containment Containment Rate Percentage of affected systems successfully isolated relative to total compromised systems Burn-Down Chart Visual tracking of remaining open investigation tasks over time during an incident Executive Briefing Non-technical summary dashboard showing business impact, timeline, and recovery status
Tools & Systems
Splunk Dashboard Studio : Modern dashboard framework with drag-and-drop visualization and real-time dataElastic Kibana Dashboard : Visualization platform with Lens, Maps, and Canvas for security dashboardsGrafana : Open-source visualization platform supporting multiple data sources including Elasticsearch and SplunkMicrosoft Sentinel Workbooks : Azure-native dashboard framework with Kusto-based analytics visualizationTheHive : Open-source incident response platform with built-in case tracking and metrics dashboards
Common Scenarios
Active Ransomware Incident : Dashboard showing encryption spread, containment status, backup verification, recovery progressData Breach Investigation : Dashboard tracking affected data stores, exfiltration volume, notification requirementsPhishing Campaign Response : Dashboard showing recipient count, click rate, credential exposure, remediation statusMonthly SOC Report : Leadership dashboard with incident trends, MTTD/MTTR metrics, analyst performanceCompliance Audit : Dashboard demonstrating detection coverage, response SLA compliance, and incident closure metrics
Output Format INCIDENT RESPONSE DASHBOARD — IR-2024-0450
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
STATUS: CONTAINMENT PHASE (6h 30m elapsed)
Affected Systems: Containment Progress:
Compromised: 2 [==========----------] 71%
Investigating: 1 5 of 7 systems contained
Contained: 3
Recovered: 1
IOC Summary: Response Timeline:
IPs: 4 14:00 — Alert triggered
Domains: 2 14:12 — Confirmed malicious
Hashes: 3 14:23 — First host isolated
URLs: 5 15:00 — Enterprise scan started
Emails: 1 15:30 — 3 more hosts isolated
Key Metrics:
MTTD: 12 minutes
MTTC: 23 minutes (first host)
Analysts Active: 3 (Tier 2: 2, Tier 3: 1)
Business Impact: LOW — Finance file server offline, no customer-facing systems affected
