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Agent Skill · 研究检索

conducting-cloud-incident-response(进行云事件响应)

conducting-cloud-incident-response 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。

conducting-cloud-incident-response 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,权限为接触敏感数据;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 49,494。

总安装 649周安装 26GitHub Stars 5,870下载 210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:conducting-cloud-incident-response(进行云事件响应)
来源仓库:https://github.com/mukul975/anthropic-cybersecurity-skills
仓库路径:skills/conducting-cloud-incident-response
安装命令:
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill conducting-cloud-incident-response
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 conducting-cloud-incident-response

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。

处理云环境的安全事件,包括未经授权的资源配置变更。分析 CloudTrail、Azure Activity Logs 和 GCP Audit Logs 中的可疑活动。调查访问密钥泄露和服务主体凭证 compromised 情况。安装前需确认权限范围和维护状态,注意是否涉及联网、命令执行或文件读写操作。

conducting-cloud-incident-response 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/conducting-cloud-incident-response

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

    它需要接触敏感数据,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

conducting-cloud-incident-response 怎么安装?

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

conducting-cloud-incident-response 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。

conducting-cloud-incident-response 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

conducting-cloud-incident-response 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。

conducting-cloud-incident-response 用的人多吗?

公开数据是累计安装 649 次,近一周安装 26 次,下载 210 次,GitHub 5,870 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。

conducting-cloud-incident-response 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 5,870 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
conducting-cloud-incident-response

进行云事件响应 · 本页

6495,870接触敏感数据未明确通过

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

Conducting Cloud Incident Response

When to Use

  • Cloud security posture management (CSPM) alerts on unauthorized resource changes
  • CloudTrail, Azure Activity Logs, or GCP Audit Logs show suspicious API calls
  • Cloud access keys or service principal credentials are suspected compromised
  • Unauthorized compute instances, storage buckets, or IAM changes are detected
  • A cloud-hosted application is breached and attacker activity spans cloud services

Do not use for on-premises-only incidents with no cloud component; use standard enterprise IR procedures.

Prerequisites

  • Cloud-native logging enabled and centralized: AWS CloudTrail (all regions), Azure Activity/Sign-in Logs, GCP Cloud Audit Logs
  • IR-specific cloud IAM roles pre-provisioned with read-only forensic access
  • Isolated forensic account/subscription/project for evidence preservation
  • Cloud incident response runbooks specific to each cloud provider
  • Cloud-native security tools: AWS GuardDuty, Azure Defender for Cloud, GCP Security Command Center
  • Network traffic logging: VPC Flow Logs (AWS/GCP), NSG Flow Logs (Azure)

Workflow

Step 1: Detect and Confirm the Cloud Incident

Identify the scope and nature of the compromise:

AWS Indicators:

CloudTrail suspicious events to investigate:
- ConsoleLogin from unexpected geolocation or IP
- CreateAccessKey for existing IAM user (persistence)
- RunInstances for crypto-mining (large instance types)
- PutBucketPolicy making S3 bucket public
- AssumeRole to cross-account roles
- DeleteTrail or StopLogging (defense evasion)
- CreateUser or AttachUserPolicy (privilege escalation)

Azure Indicators:

Azure Activity Log events to investigate:
- Sign-in from anonymous IP or TOR exit node
- Service principal credential added
- Role assignment changes (Owner, Contributor added)
- VM created in unusual region
- Storage account access key regenerated
- Conditional Access policy modified or deleted
- MFA disabled for user account

GCP Indicators:

GCP Audit Log events to investigate:
- SetIamPolicy changes granting broad access
- CreateServiceAccountKey for existing SA
- InsertInstance in unexpected zone
- SetBucketIamPolicy with allUsers
- DeleteLog or UpdateSink (log tampering)

Step 2: Contain Cloud Identity Compromise

Cloud containment is primarily an identity operation:

AWS Containment:

# Disable compromised IAM access keys
aws iam update-access-key --user-name compromised-user \
  --access-key-id AKIA... --status Inactive

# Attach deny-all policy to compromised user
aws iam attach-user-policy --user-name compromised-user \
  --policy-arn arn:aws:iam::aws:policy/AWSDenyAll

# Revoke all active sessions for compromised IAM role
aws iam put-role-policy --role-name compromised-role \
  --policy-name RevokeOlderSessions --policy-document '{
    "Version":"2012-10-17",
    "Statement":[{
      "Effect":"Deny",
      "Action":"*",
      "Resource":"*",
      "Condition":{"DateLessThan":
        {"aws:TokenIssueTime":"2025-11-15T15:00:00Z"}}
    }]
  }'

# Isolate compromised EC2 instance
aws ec2 modify-instance-attribute --instance-id i-0abc123 \
  --groups sg-isolate-forensic

Azure Containment:

# Disable compromised user
Set-AzureADUser -ObjectId "user@tenant.onmicrosoft.com" -AccountEnabled $false

# Revoke all sessions
Revoke-AzureADUserAllRefreshToken -ObjectId "user-object-id"

# Remove role assignments
Remove-AzRoleAssignment -ObjectId "sp-object-id" -RoleDefinitionName "Contributor"

# Isolate VM with NSG deny-all rule
$nsg = New-AzNetworkSecurityGroup -Name "isolate-nsg" -ResourceGroupName "rg" -Location "eastus"
$nsg | Add-AzNetworkSecurityRuleConfig -Name "DenyAll" -Priority 100 -Direction Inbound `
  -Access Deny -Protocol * -SourceAddressPrefix * -SourcePortRange * `
  -DestinationAddressPrefix * -DestinationPortRange *

Step 3: Preserve Cloud Evidence

Collect evidence before ephemeral resources are terminated or logs rotate:

AWS Evidence Collection:

  • Export CloudTrail events to S3 in the forensic account
  • Snapshot EBS volumes of compromised EC2 instances
  • Copy S3 access logs and object versions
  • Export VPC Flow Logs for the affected VPC
  • Capture IAM credential reports and access advisor data

Azure Evidence Collection:

  • Export Azure Activity Logs and Sign-in Logs (90-day retention by default)
  • Snapshot managed disks of compromised VMs
  • Export Azure AD audit logs
  • Capture NSG flow logs
  • Export Conditional Access sign-in details

GCP Evidence Collection:

  • Export Cloud Audit Logs to a forensic storage bucket
  • Snapshot persistent disks of compromised VMs
  • Export VPC Flow Logs
  • Capture IAM policy snapshots

Step 4: Investigate Cloud-Specific Attack Patterns

Analyze logs for common cloud attack techniques:

Common Cloud Attack Patterns:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. Credential Compromise → IAM Privilege Escalation → Resource Abuse
2. Public S3/Blob → Data Exfiltration
3. SSRF from Web App → IMDS Token Theft → Lateral Movement
4. Compromised CI/CD Pipeline → Malicious Deployment
5. Cross-Account Role Abuse → Multi-Account Pivot
6. Lambda/Function Abuse → Crypto-mining or Data Processing

IMDS Token Theft Investigation (AWS):

# Search CloudTrail for API calls using instance role credentials from external IP
aws cloudtrail lookup-events --lookup-attributes \
  AttributeKey=EventSource,AttributeValue=ec2.amazonaws.com \
  --start-time 2025-11-14 --end-time 2025-11-16 \
  | jq '.Events[] | select(.CloudTrailEvent | fromjson | .sourceIPAddress != "internal")'

Step 5: Eradicate and Recover

Remove adversary access and restore secure state:

  • Rotate all compromised credentials (access keys, passwords, service principal secrets)
  • Remove unauthorized IAM users, roles, policies, and access keys created by the attacker
  • Terminate unauthorized compute instances (crypto-miners, C2 servers)
  • Restore modified S3 bucket policies and storage access policies to pre-incident state
  • Re-enable security controls that were disabled (CloudTrail, GuardDuty, Defender for Cloud)
  • Review and restore Conditional Access policies and MFA configurations

Step 6: Post-Incident Cloud Hardening

Implement controls to prevent recurrence:

  • Enable MFA for all IAM users and require MFA for sensitive API calls
  • Implement SCPs (AWS) or Azure Policy to prevent logging disablement
  • Enable GuardDuty / Defender for Cloud / Security Command Center with auto-remediation
  • Implement least-privilege IAM policies using access analyzer data
  • Enable IMDS v2 (token-required) on all EC2 instances to prevent SSRF-based token theft
  • Configure budget alerts to detect crypto-mining cost spikes

Key Concepts

TermDefinition
IMDS (Instance Metadata Service)Cloud service providing instance credentials accessible from within a VM; SSRF attacks target IMDS to steal tokens
CloudTrailAWS service logging all API calls across the AWS account; primary evidence source for AWS incident response
Service PrincipalNon-human identity in Azure AD used by applications and services; compromise enables persistent API access
SCP (Service Control Policy)AWS Organizations policy that limits the maximum permissions available to accounts; useful for guardrails
Ephemeral InfrastructureCloud resources (containers, functions, auto-scaled instances) that may be terminated before evidence can be collected
Cross-Account Role AssumptionAWS mechanism allowing one account to temporarily access resources in another; attackers pivot through assumed roles

Tools & Systems

  • AWS CloudTrail / Azure Activity Logs / GCP Audit Logs: Cloud-native API logging services providing the primary audit trail
  • Cado Response: Cloud-native forensics platform for automated evidence capture from AWS, Azure, and GCP
  • Prowler (AWS) / ScoutSuite (multi-cloud): Open-source cloud security assessment tools for post-incident posture review
  • Steampipe: Open-source SQL-based tool for querying cloud APIs to investigate IAM configurations and resource states
  • Cartography (Lyft): Open-source tool for mapping cloud infrastructure relationships and identifying attack paths

Common Scenarios

Scenario: AWS Access Key Compromised via Public GitHub Repository

Context: AWS GuardDuty alerts on API calls from an unexpected IP address using an IAM user's access key. The key was accidentally committed to a public GitHub repository 4 hours ago.

Approach:

  1. Immediately disable the compromised access key via AWS IAM
  2. Attach AWSDenyAll policy to the affected IAM user
  3. Query CloudTrail for all API calls made with the compromised key since exposure
  4. Identify resources created or modified by the attacker (EC2 instances for crypto-mining, new IAM users for persistence)
  5. Terminate unauthorized resources and remove backdoor IAM entities
  6. Rotate all credentials the compromised user had access to
  7. Enable GitHub secret scanning to prevent future credential leaks

Pitfalls:

  • Only disabling the access key without checking for new access keys or IAM users created as persistence
  • Not checking all AWS regions for attacker-created resources (crypto-miners deployed in every region)
  • Forgetting to revoke temporary credentials from assumed roles (STS tokens remain valid until expiry)
  • Not calculating the financial impact of unauthorized resource usage for insurance claims

Output Format

CLOUD INCIDENT RESPONSE REPORT
================================
Incident:          INC-2025-1705
Cloud Provider:    AWS (Account: 123456789012)
Date Detected:     2025-11-15T14:00:00Z
Detection Source:  GuardDuty - UnauthorizedAccess:IAMUser/InstanceCredentialExfiltration

COMPROMISE SUMMARY
Initial Access:    IAM access key exposed in public GitHub repo
Affected Identity: iam-user: deploy-bot (AKIA...)
Attacker IP:       203.0.113.42 (VPN exit node, Netherlands)
Duration:          4 hours (10:00 UTC - 14:00 UTC)

ATTACKER ACTIVITY (from CloudTrail)
10:15 UTC - DescribeInstances (reconnaissance)
10:18 UTC - RunInstances x 12 (c5.4xlarge, all regions - crypto-mining)
10:22 UTC - CreateUser "backup-admin" (persistence)
10:23 UTC - CreateAccessKey for "backup-admin"
10:25 UTC - AttachUserPolicy - AdministratorAccess to "backup-admin"
10:30 UTC - PutBucketPolicy - s3://data-bucket made public (exfiltration)

CONTAINMENT ACTIONS
[x] Original access key disabled
[x] User policy set to AWSDenyAll
[x] Backdoor IAM user "backup-admin" deleted
[x] 12 crypto-mining instances terminated (all regions)
[x] S3 bucket policy restored to private

FINANCIAL IMPACT
Unauthorized EC2: $2,847 (4 hours x 12 x c5.4xlarge)
Data Transfer:    $127 (S3 public access data egress)
Total:            $2,974

POST-INCIDENT HARDENING
1. GitHub secret scanning enabled
2. Access key rotation policy implemented
3. SCP preventing CloudTrail disablement deployed
4. GuardDuty auto-remediation Lambda configured

平台分布

Codex

37.86%
按下载量换算80

Claude

29.51%
按下载量换算62

Cursor

18.99%
按下载量换算40

Gemini CLI

8.99%
按下载量换算19

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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