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Agent Skill · 研究检索

building-incident-response-dashboard(构建事件响应仪表板)

building-incident-response-dashboard 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

building-incident-response-dashboard 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 52,586。

总安装 552周安装 23GitHub Stars 5,866下载 184核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:building-incident-response-dashboard(构建事件响应仪表板)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/building-incident-response-dashboard
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill building-incident-response-dashboard
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill building-incident-response-dashboard

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于构建事件响应期间的可视化指挥看板,支持实时协调与影响评估展示。适用于活跃事件中的团队协作、分析师负载监控与高管简报需求场景。提供基于 SIEM 数据的态势感知面板设计,包含时间轴、资源分配与行动追踪模块。安装使用 GitHub 仓库,需配置 Splunk ES 或其他 SIEM 平台的 API 访问权限。

building-incident-response-dashboard 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/building-incident-response-dashboard

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skil…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

building-incident-response-dashboard 怎么安装?

在终端执行 npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill building…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

building-incident-response-dashboard 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

building-incident-response-dashboard 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

building-incident-response-dashboard 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

building-incident-response-dashboard 用的人多吗?

公开数据是累计安装 552 次,近一周安装 23 次,下载 184 次,GitHub 5,866 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

building-incident-response-dashboard 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 5,866 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
building-incident-response-dashboard

构建事件响应仪表板 · 本页

5525,866需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

TermDefinition
Situational AwarenessReal-time understanding of incident scope, affected systems, and response progress
MTTDMean Time to Detect — average time from threat occurrence to SOC alert generation
MTTRMean Time to Respond — average time from alert to incident resolution or containment
Containment RatePercentage of affected systems successfully isolated relative to total compromised systems
Burn-Down ChartVisual tracking of remaining open investigation tasks over time during an incident
Executive BriefingNon-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

平台分布

Codex

35.47%
按下载量换算65

Claude

34.53%
按下载量换算64

Cursor

18.08%
按下载量换算33

Gemini CLI

9.05%
按下载量换算17

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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