conducting-cloud-incident-response

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/conducting-cloud-incident-response
0 commentsdiscussion
summary

Responds to security incidents in cloud environments (AWS, Azure, GCP) by performing identity-based containment, cloud-native log analysis, resource isolation, and forensic evidence acquisition adapted for ephemeral cloud infrastructure. Activates for requests involving cloud incident response, AWS security incident, Azure compromise, GCP breach, cloud forensics, or cloud identity compromise.

skill.md
name
conducting-cloud-incident-response
description
'Responds to security incidents in cloud environments (AWS, Azure, GCP) by performing identity-based containment, cloud-native log analysis, resource isolation, and forensic evidence acquisition adapted for ephemeral cloud infrastructure. Activates for requests involving cloud incident response, AWS security incident, Azure compromise, GCP breach, cloud forensics, or cloud identity compromise. '
domain
cybersecurity
subdomain
incident-response
tags
- cloud-IR - AWS-forensics - Azure-incident-response - GCP-security - identity-containment
mitre_attack
- T1078 - T1537 - T1580 - T1525
version
1.0.0
author
mahipal
license
Apache-2.0
nist_csf
- RS.MA-01 - RS.MA-02 - RS.AN-03 - RC.RP-01

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 "[email protected]" -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
how to use conducting-cloud-incident-response

How to use conducting-cloud-incident-response on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add conducting-cloud-incident-response
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/conducting-cloud-incident-response

The skills CLI fetches conducting-cloud-incident-response from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/conducting-cloud-incident-response

Reload or restart Cursor to activate conducting-cloud-incident-response. Access the skill through slash commands (e.g., /conducting-cloud-incident-response) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.766 reviews
  • Aanya Huang· Dec 28, 2024

    conducting-cloud-incident-response fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Mateo Thompson· Dec 24, 2024

    conducting-cloud-incident-response is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Shikha Mishra· Dec 20, 2024

    conducting-cloud-incident-response fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Amina Tandon· Dec 16, 2024

    We added conducting-cloud-incident-response from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Xiao Malhotra· Dec 12, 2024

    We added conducting-cloud-incident-response from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Mateo Garcia· Dec 12, 2024

    I recommend conducting-cloud-incident-response for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Daniel Reddy· Dec 12, 2024

    Useful defaults in conducting-cloud-incident-response — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Naina Ndlovu· Dec 12, 2024

    Keeps context tight: conducting-cloud-incident-response is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Min Menon· Dec 4, 2024

    conducting-cloud-incident-response is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Xiao Yang· Nov 23, 2024

    Solid pick for teams standardizing on skills: conducting-cloud-incident-response is focused, and the summary matches what you get after install.

showing 1-10 of 66

1 / 7