Cloud Penetration Testing
Systematic security assessment of cloud infrastructure evaluating misconfigurations, IAM policies, and cloud-specific attack vectors.
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Systematic security assessment of cloud infrastructure evaluating misconfigurations, IAM policies, and cloud-specific attack vectors.
# Cloud Penetration Testing
Cloud penetration testing is the systematic, authorized simulation of attacks against cloud-hosted infrastructure, services, and applications to identify exploitable weaknesses before adversaries do. It exists because cloud environments introduce a fundamentally different attack surface than on-premises systems, one dominated by identity misconfigurations, overly permissive policies, publicly exposed storage, and provider-specific APIs that traditional penetration testing methodologies do not adequately address. Organizations migrating workloads to AWS, Azure, or Google Cloud Platform often assume the provider handles security; cloud penetration testing exists to correct that assumption and surface the real risk before it materializes as a breach.
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Cloud penetration testing is the authorized, structured evaluation of cloud-hosted resources, configurations, and access controls through simulated adversarial techniques. It assesses the security posture of environments built on infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS) models. The tester operates within the constraints of the cloud shared responsibility model, targeting the layers the customer owns: identity and access management (IAM) policies, virtual network configurations, storage bucket permissions, serverless function logic, container orchestration settings, and API gateway exposures.
Cloud penetration testing is not the same as cloud security posture management (CSPM), which is a passive, continuous monitoring discipline. It is also distinct from vulnerability scanning, which identifies known CVEs in software versions without confirming exploitability. Cloud pentesting involves active exploitation attempts within an authorized scope to prove that a misconfiguration or policy error produces actual compromise, not theoretical risk.
Subtypes include: external cloud attack surface testing, which targets publicly reachable cloud resources from an unauthenticated attacker's position; assumed-breach testing, which begins with low-privilege credentials to simulate a compromised employee or stolen API key; and internal cloud segmentation testing, which evaluates whether one cloud workload can pivot to another within the same account or across accounts. Red team engagements may chain multiple cloud attack vectors across weeks to simulate advanced persistent threat (APT) behavior. Each subtype requires a distinct testing charter and provider-specific authorization before work begins.
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Cloud penetration testing follows a structured methodology, adapted from traditional penetration testing but rebuilt around cloud-native attack techniques and tooling.
Phase 1: Authorization and Scoping
Before any technical work begins, the tester must obtain written authorization from the organization and comply with the target cloud provider's penetration testing policy. AWS, Azure, and GCP each maintain acceptable use policies that permit most security testing of customer-owned resources without prior approval, with specific exceptions for activities like denial-of-service simulation or security control bypass testing against provider infrastructure. The scope document defines which accounts, regions, services, and resource types are in bounds.
Phase 2: Reconnaissance
Reconnaissance begins externally. Testers enumerate exposed cloud assets using DNS records, certificate transparency logs (via crt.sh or Censys), WHOIS data, and cloud-specific fingerprinting. S3 bucket enumeration tools probe for publicly accessible storage objects using organization name variations. GitHub and other public code repositories are searched for hardcoded API keys, access tokens, and connection strings. Cloud service endpoints registered in DNS often reveal the provider, region, and sometimes the internal naming conventions of the target environment. This phase regularly surfaces assets the organization did not know were public.
Phase 3: IAM and Configuration Analysis
IAM misconfiguration is the most consistently dangerous finding in cloud environments. Testers enumerate IAM users, roles, groups, and policies to identify excessive permissions. Common targets include: wildcard permissions (Action: \, Resource: \) in attached policies; roles with PassRole and AssumeRole capabilities that enable privilege escalation; service accounts with console access that should be API-only; and cross-account trust relationships that grant unintended external access. Tools like Pacu (AWS-specific offensive framework), ScoutSuite (multi-cloud configuration auditor), and Prowler (AWS and Azure compliance and security checks) automate enumeration and flag misconfigurations against known-bad patterns. Testers then manually confirm and attempt to chain findings into exploitable privilege escalation paths.
Phase 4: Service-Specific Testing
Each cloud service category has distinct attack vectors. Storage services (S3, Azure Blob, GCP Cloud Storage) are tested for public read and write access, improper ACLs, and bucket policy misconfigurations that allow unauthenticated data access. Compute instances are tested for metadata service exposure: the instance metadata service (IMDS) at 169.254.169.254 on AWS has historically allowed server-side request forgery (SSRF) payloads from vulnerable applications to retrieve IAM credentials, though IMDSv2 token requirements now mitigate this in properly configured environments. Serverless functions (Lambda, Azure Functions, Cloud Functions) are tested for injection vulnerabilities in event-handling code, insecure deserialization, and overly permissive execution roles. Kubernetes clusters managed through EKS, AKS, or GKE are tested for exposed API servers, misconfigured RBAC policies, and container escape paths.
Phase 5: Exploitation and Privilege Escalation
Confirmed misconfigurations are exploited to demonstrate impact. A common scenario: a developer accidentally commits an AWS IAM access key to a public GitHub repository. A tester finds it during reconnaissance, calls AWS Security Token Service to confirm the key is active, then uses the AWS CLI to enumerate attached policies. The key belongs to an IAM user with AttachUserPolicy permissions on themselves. The tester attaches the AdministratorAccess policy to the user, achieving full account takeover within minutes, without touching a single EC2 instance or triggering a network-level alert. This is not a hypothetical; it is a pattern observed repeatedly in real engagements and documented in public breach disclosures.
Phase 6: Reporting
Each finding is documented with: the resource identifier, the specific misconfiguration or vulnerability, the exploitation steps taken, the demonstrated impact, and a remediation recommendation aligned to provider-specific guidance and CIS Benchmarks. Findings are risk-rated using CVSS v3.1 or a cloud-adapted scoring model that weights blast radius (how much of the environment is exposed) alongside exploitability.
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Cloud misconfigurations are the primary attack vector in cloud breaches, not software exploits. The Verizon Data Breach Investigations Report has consistently identified misconfiguration as a leading cause of cloud-related incidents over multiple consecutive years. Unlike software vulnerabilities, misconfigurations rarely require a CVE score or a vendor patch: they are administrative errors that take minutes to fix and can take months to discover without active testing.
The consequences of untested cloud environments are concrete and severe. In 2019, Capital One suffered a breach affecting over 100 million customers when a misconfigured AWS WAF allowed a SSRF attack, enabling an attacker to access the EC2 instance metadata service and retrieve IAM role credentials. Those credentials provided access to S3 buckets containing sensitive financial data. The breach resulted in an $80 million regulatory fine and significant reputational damage. The misconfiguration was exploitable through a chain of findings: SSRF vulnerability in the application, IMDSv1 enabled on the instance, an IAM role with excessive S3 permissions. Any single cloud penetration test following standard methodology would have surfaced this chain before it was exploited.
A common misconception is that cloud providers secure the environment. The shared responsibility model explicitly places IAM configuration, network access controls, data encryption settings, and application-layer security in the customer's responsibility column. Another misconception is that automated CSPM tools replace penetration testing. CSPM tools identify configuration drift and flag known-bad states; they do not confirm exploitability, model attack chains, or simulate how an adversary with partial access would escalate and move laterally. Human-led penetration testing produces findings that automation cannot generate, specifically those that require chaining multiple low-severity issues into a high-severity attack path.
Without regular cloud penetration testing, organizations accumulate unexamined risk. Permissions sprawl grows with every new service deployment. Legacy IAM roles from deprecated workloads remain attached to active resources. Storage buckets created during a proof-of-concept project retain public access settings when promoted to production. Each of these conditions persists silently until tested or breached.
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CDA approaches cloud penetration testing through the Planetary Defense Model (PDM), operating across the Vulnerability Surface Detection (VSD) and Identity and Access Testing (IAT) domains. The governing methodology is Continuous Surface Reduction (CSR): every surface you expose is a surface we eliminate.
In practice, this means CDA does not treat cloud penetration testing as a point-in-time event. Cloud environments change continuously: new IAM roles are created, new storage buckets are provisioned, new API endpoints are exposed. A penetration test conducted six months ago does not reflect the environment as it exists today. CDA structures cloud penetration testing engagements within a continuous testing cycle, synchronized with infrastructure change management processes to ensure that newly deployed cloud resources are assessed before they can be exploited.
Within the VSD domain, CDA maps the complete external and internal attack surface of the cloud environment before any exploitation work begins. This includes cloud asset inventory validation (comparing what the client believes exists against what is actually reachable), cross-region exposure analysis (cloud resources deployed in non-primary regions are frequently under-monitored), and third-party integration points (SaaS integrations, CI/CD pipeline access, and partner account trust relationships). CDA's surface reduction work in VSD routinely finds resources the client organization had no record of.
Within the IAT domain, CDA conducts adversarial IAM analysis that goes beyond policy enumeration. CDA testers model the permission graph of the cloud account, identifying which principals can reach which resources through direct permissions, role assumption chains, and resource-based policy grants. This graph analysis surfaces privilege escalation paths that policy-by-policy review misses. CDA then validates each path through controlled exploitation, confirming that the organization's detective controls (CloudTrail alerting, GuardDuty, Azure Defender) fire appropriately during an actual attack simulation, not just during a configuration review.
CDA delivers remediation guidance that is provider-specific and implementation-ready: not "reduce IAM permissions" but "replace the AdministratorAccess policy on role X with a scoped policy permitting only the S3 GetObject and ListBucket actions on bucket Y, and enable IMDSv2 on all EC2 instances in the us-east-1 region using the following AWS CLI command." The distinction between a recommendation and an instruction is where most cloud security engagements lose client value.
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CDA Theater missions that address topics covered in this article.
Guide to AWS Security Hub for centralized finding aggregation, continuous compliance monitoring, and automated remediation across AWS organizations.
Vendor assessment guide for HashiCorp Vault.
Wireshark is the leading network protocol analyzer for traffic capture and security investigation.
Written by CDA Editorial
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