building-incident-response-dashboard▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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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.
| 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 |
| nist_csf | - DE.CM-01 - DE.AE-02 - RS.MA-01 - DE.AE-06 |
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
Example timeline data:
_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 data
- Elastic Kibana Dashboard: Visualization platform with Lens, Maps, and Canvas for security dashboards
- Grafana: Open-source visualization platform supporting multiple data sources including Elasticsearch and Splunk
- Microsoft Sentinel Workbooks: Azure-native dashboard framework with Kusto-based analytics visualization
- TheHive: 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 progress
- Data Breach Investigation: Dashboard tracking affected data stores, exfiltration volume, notification requirements
- Phishing Campaign Response: Dashboard showing recipient count, click rate, credential exposure, remediation status
- Monthly SOC Report: Leadership dashboard with incident trends, MTTD/MTTR metrics, analyst performance
- Compliance 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
How to use building-incident-response-dashboard on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add building-incident-response-dashboard
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches building-incident-response-dashboard from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate building-incident-response-dashboard. Access the skill through slash commands (e.g., /building-incident-response-dashboard) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★29 reviews- ★★★★★Amelia Tandon· Dec 28, 2024
Keeps context tight: building-incident-response-dashboard is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Luis Srinivasan· Sep 25, 2024
building-incident-response-dashboard has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Yash Thakker· Sep 5, 2024
building-incident-response-dashboard has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Carlos Agarwal· Sep 1, 2024
Solid pick for teams standardizing on skills: building-incident-response-dashboard is focused, and the summary matches what you get after install.
- ★★★★★Dhruvi Jain· Aug 24, 2024
Solid pick for teams standardizing on skills: building-incident-response-dashboard is focused, and the summary matches what you get after install.
- ★★★★★Sophia Khanna· Aug 20, 2024
building-incident-response-dashboard has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Chen Taylor· Aug 16, 2024
Solid pick for teams standardizing on skills: building-incident-response-dashboard is focused, and the summary matches what you get after install.
- ★★★★★Oshnikdeep· Jul 15, 2024
We added building-incident-response-dashboard from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Luis Mensah· Jul 11, 2024
building-incident-response-dashboard fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Zaid Chawla· Jul 7, 2024
We added building-incident-response-dashboard from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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