building-incident-response-dashboard

构建事件响应仪表盘

何时使用

在以下情况下使用此技能：

• IR 团队在活跃事件期间需要实时仪表盘以进行协调和跟踪
• SOC 领导层需要展示事件状态和分析师工作量的运营仪表盘
• 事件后复盘需要可视化时间线和影响评估
• 高管简报需要高层级的事件指标和趋势分析

不要用于日常 SOC 监控仪表盘（请改用 Incident Review）——IR 仪表盘专为活跃事件协调和管理层报告而设计。

前提条件

• SIEM 平台（带 Dashboard Studio 的 Splunk、Elastic Kibana 或 Grafana）
• SIEM 中的重大事件和事件数据（Splunk ES incident_review 索引）
• 工单系统集成（ServiceNow、Jira）用于修复跟踪
• 用于上下文补充的资产和身份查找表
• 仪表盘发布权限，以便向 SOC 团队和管理层分发

工作流

步骤 1：设计活跃事件仪表盘布局

为活跃事件跟踪构建 Splunk Dashboard Studio 仪表盘：

<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>

步骤 2：构建实时受影响系统面板

跟踪受影响系统及其遏制状态：

| 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

步骤 3：构建 IOC 跟踪面板

监控 IOC 在环境中的传播：

--- 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

步骤 4：构建响应时间线面板

创建按时间顺序排列的事件时间线：

| 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

时间线数据示例：

_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

步骤 5：构建 SOC 运营仪表盘

跟踪整体 SOC 性能指标：

--- 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

步骤 6：构建高管简报仪表盘

为重大事件期间的管理层创建高层级仪表盘：

--- 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

步骤 7：自动化仪表盘更新

使用 Splunk 计划搜索维护仪表盘数据：

--- 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

关键概念

术语	定义
态势感知	对事件范围、受影响系统和响应进度的实时了解
MTTD	平均检测时间——从威胁发生到 SOC 生成告警的平均时间
MTTR	平均响应时间——从告警到事件解决或遏制的平均时间
遏制率	成功隔离的受影响系统占全部受损系统的百分比
燃尽图	在事件期间随时间可视化跟踪剩余未完成的调查任务
高管简报	展示业务影响、时间线和恢复状态的非技术性摘要仪表盘

工具与系统

• Splunk Dashboard Studio：现代仪表盘框架，支持拖放式可视化和实时数据
• Elastic Kibana Dashboard：可视化平台，提供 Lens、Maps 和 Canvas 用于安全仪表盘
• Grafana：开源可视化平台，支持包括 Elasticsearch 和 Splunk 在内的多种数据源
• Microsoft Sentinel Workbooks：Azure 原生仪表盘框架，支持基于 Kusto 的分析可视化
• TheHive：开源事件响应平台，内置案件跟踪和指标仪表盘

常见场景

• 活跃勒索软件事件：仪表盘展示加密传播、遏制状态、备份验证、恢复进度
• 数据泄露调查：仪表盘跟踪受影响的数据存储、外泄量、通知要求
• 钓鱼活动响应：仪表盘展示收件人数量、点击率、凭据暴露、修复状态
• 月度 SOC 报告：面向领导层的仪表盘，包含事件趋势、MTTD/MTTR 指标、分析师绩效
• 合规审计：仪表盘展示检测覆盖率、响应 SLA 合规性和事件关闭指标

输出格式

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