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Cloud Incident Response

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Streamline your response to cloud security incidents.

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What Cloud Incident Response does

Conducting Cloud Incident Response is a skill designed for security professionals managing incidents across major cloud platforms like AWS, Azure, and GCP. This skill provides a structured workflow for detecting, containing, and investigating security incidents that involve cloud resources. It emphasizes identity-based containment and forensic evidence acquisition, which are critical in environments where resources are ephemeral and logs may rotate quickly. By leveraging cloud-native logging and security tools, users can respond effectively to threats and breaches that span multiple cloud services.

The skill is particularly useful when cloud security posture management (CSPM) alerts indicate unauthorized changes or when suspicious API calls are detected in CloudTrail, Azure Activity Logs, or GCP Audit Logs. It guides users through a series of steps to confirm the incident, contain the compromise, preserve evidence, and investigate attack patterns specific to cloud environments. This structured approach ensures that security teams can act swiftly and effectively to mitigate risks and recover from incidents.

To utilize this skill, users must have cloud-native logging enabled and pre-provisioned IAM roles that allow for forensic access. The skill also requires a forensic account or subscription to preserve evidence and specific runbooks tailored to each cloud provider. By following the provided scripts and workflows, security teams can ensure that they are not only responding to incidents but also learning from them to improve their overall security posture.

This skill is intended for cloud security engineers, incident responders, and DevSecOps teams who need a reliable method for managing cloud incidents. It is not suitable for on-premises-only incidents, where traditional incident response procedures should be applied instead.

When to use it

Use this skill when CSPM alerts indicate unauthorized resource changes or when suspicious activity is detected in cloud logs.

When not to use it

Do not use this skill for incidents that are solely on-premises without any cloud component.

What you can build with it

Responding to Unauthorized Changes

When CSPM alerts indicate unauthorized changes to cloud resources, use this skill to quickly identify and contain the threat.

Investigating Suspicious API Calls

If logs show suspicious API calls, follow the workflow to confirm the incident and gather necessary evidence for analysis.

Managing Cloud Breaches

In the event of a breach affecting multiple cloud services, utilize this skill to coordinate response efforts and secure the environment.

How to install Cloud Incident Response

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1. Install with the skills CLI

npx skills add mukul975/anthropic-cybersecurity-skills/conducting-cloud-incident-response --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by mukul975

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

Frequently asked questions about Cloud Incident Response

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