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

Agent Skill

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。

总安装

649

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

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通过

Snyk

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敏感数据

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