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构建事件响应剧本

设计并记录结构化的应急响应剧本,提供分步骤的操作指导。

构建事件响应剧本 是什么?

该技能专注于为安全运营团队构建可重复使用的事件响应(IR)剧本,旨在提升响应效率和一致性。它通过一个清晰、结构化的六步工作流,指导用户从选择事件类型、定义剧本模板、编写决策树,到集成SOAR平台(如Cortex XSOAR、Splunk SOAR)实现自动化。该技能详细讲解了如何撰写特定工具的细化操作步骤(如通过CrowdStrike隔离端点),并强调通过桌面推演和实战演习进行测试和维护。适用于SOC 2、PCI-DSS、HIPAA等合规审计要求,以及红队、蓝队和安全架构师在成熟化IR程序或应对新型攻击场景中的工作。该技能的核心价值在于将零散的应急响应经验转化为标准化、可文档化和自动化的流程,从而缩短平均响应和恢复时间(MTTA、MTTC、MTTR)。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/building-incident-response-playbook

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文档

构建事件响应剧本 是做什么的?

使用场景

  • 从零开始建立或完善应急响应程序
  • 在遭遇新型攻击后,为新的事件类型记录操作流程
  • 在SOAR平台(Cortex XSOAR、Splunk SOAR)中自动化响应工作流
  • 准备需要已记录IR程序的合规审计(SOC 2、PCI-DSS、HIPAA)
  • 针对特定威胁场景,对现有IR能力进行差距分析

不要用于一次性的临时调查;剧本是可重复使用的程序文件,而非针对特定案例的报告。

前提条件

  • 基于可能性和影响识别出主要事件场景的组织风险评估
  • 采用NIST SP 800-61r3或SANS PICERL框架作为组织IR标准
  • 包含业务关键性评级和数据分类的资产清单
  • 定义角色(事件指挥官、SOC分析员、系统管理员、法务、沟通)的RACI矩阵
  • 现有检测能力清单(SIEM规则、EDR检测、IDS签名)
  • 如果构建自动化剧本,需有权访问SOAR平台

工作流

步骤1:选择并界定事件类型

定义剧本将处理的具体场景:

  • 基于组织风险评估和历史数据识别主要事件类型
  • 为清晰起见,每个剧本仅针对单一事件类型(不要合并无关场景)
  • 定义触发剧本的条件

常见剧本类型:

优先剧本(优先构建):
1. 勒索软件应急响应
2. 钓鱼/凭证泄露
3. 商业邮件欺诈
4. 恶意软件感染
5. 数据泄露/窃取
6. DDoS攻击
7. 内部威胁
8. 账号接管
9. Web应用程序入侵
10. 云基础设施入侵

步骤2:定义剧本结构

每个剧本应遵循一致的结构:

剧本模板
━━━━━━━━━━━━━━━━
1. 剧本元数据
   - 名称、版本、负责人、最后审查日期
   - 触发条件
   - 严重性标准

2. RACI矩阵
   - 每个步骤的负责人、问责人、咨询人、知情人

3. 检测与分类
   - 事件如何被检测
   - 初始分类检查清单
   - 严重性分类标准

4. 遏制
   - 短期遏制措施
   - 长期遏制措施
   - 证据保全要求

5. 根除
   - 根本原因识别
   - 恶意软件/威胁移除步骤
   - 验证程序

6. 恢复
   - 系统恢复步骤
   - 验证标准
   - 恢复后的监控要求

7. 事后处理
   - 经验教训会议触发条件
   - 报告模板
   - 检测改进措施

8. 沟通
   - 内部通知矩阵
   - 外部通知要求(监管机构、客户、执法部门)
   - 状态更新节奏

9. 附录
   - 特定工具的操作程序
   - 联系人列表
   - 证据收集检查清单

步骤3:编写决策树和升级标准

定义具有二元结果的清晰决策点:

检测告警触发
├── 告警是否为真阳性?
│   ├── 是 → 分类严重性
│   │   ├── P1(紧急) → 通知事件指挥官,立即开始遏制
│   │   ├── P2(高) → 通知IR负责人,在30分钟内开始调查
│   │   ├── P3(中等) → 排队等待在4小时内调查
│   │   └── P4(低) → 记录并调查在24小时内
│   └── 否 → 记录为误报,调整检测规则
└── 无法确定 → 升级至二级支持进行深入分析

升级触发条件:

  • 任何P1事件:立即升级至IR负责人和CISO
  • 确认数据窃取:通知法务顾问和隐私官
  • 涉及客户数据:激活客户通知流程
  • 涉及第三方:联系供应商安全联络人
  • 需要执法介入:总法律顾问授权后方可联系

步骤4:定义具体的技术操作程序

为每个步骤编写特定工具的详细说明(而非通用指导):

遏制 - 通过CrowdStrike隔离端点:
1. 打开Falcon控制台 > 主机 > 搜索受影响的主机名
2. 点击主机 > 主机详情
3. 点击右上角的

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

abusing-dpapi-for-credential-access

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket

abusing-shadow-credentials-for-privesc

Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target

achieving-cmmc-level-2-compliance

>-

acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.

analyzing-active-directory-acl-abuse

Detect dangerous ACL misconfigurations in Active Directory using ldap3

analyzing-android-malware-with-apktool

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

analyzing-api-gateway-access-logs

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect

analyzing-apt-group-with-mitre-navigator

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups

analyzing-azure-activity-logs-for-threats

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query

analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master

analyzing-browser-forensics-with-hindsight

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user

analyzing-campaign-attribution-evidence

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to

analyzing-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.

analyzing-cobalt-strike-beacon-configuration

Extract and analyze Cobalt Strike beacon configuration from PE files

analyzing-cobaltstrike-malleable-c2-profiles

Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

analyzing-command-and-control-communication

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom

analyzing-cyber-kill-chain

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain

analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

analyzing-dns-logs-for-exfiltration

Analyzes DNS query logs to detect data exfiltration via DNS tunneling,

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