AI Pentest for Cloud Infrastructure
AI-powered penetration testing for AWS, GCP, and Azure. Automatically audit IAM, storage, networking, and serverless configurations to find the misconfigurations that lead to breaches.
Cloud Misconfigurations Cause 80% of Breaches
A single exposed S3 bucket or overly permissive IAM role can compromise your entire infrastructure. Cloud environments are complex, and AI pentest agents systematically check every configuration that humans routinely miss.
Cloud Infrastructure Pentest Checklist
Follow these 10 steps to thoroughly pentest your cloud infrastructure. Critical items represent the most commonly exploited cloud attack vectors.
Audit IAM configurations
Review all IAM roles, policies, and permissions for overly permissive access and privilege escalation paths.
Scan for open S3 buckets
Check all storage buckets for public access, misconfigured ACLs, and exposed sensitive data.
Test serverless function security
Audit Lambda, Cloud Functions, and Azure Functions for injection, excessive permissions, and insecure triggers.
Verify network segmentation
Ensure VPCs, subnets, and network policies properly isolate production, staging, and internal services.
Check for exposed metadata endpoints
Test for SSRF attacks that can reach cloud metadata services and steal instance credentials.
Audit database access controls
Verify that databases are not publicly accessible and require proper authentication and encryption.
Test container security
Scan container images for vulnerabilities, check for privileged containers, and verify pod security policies.
Verify encryption at rest and in transit
Ensure all data stores use encryption at rest and all communications use TLS with proper certificate validation.
Scan for misconfigured security groups
Check firewall rules and security groups for overly permissive inbound and outbound access.
Test cloud API permissions
Verify that cloud management APIs are properly secured and cannot be abused for lateral movement.
Benefits of AI Pentest for Cloud
Covers AWS, GCP, and Azure
HighAI pentest agents understand the security models of all major cloud providers and test provider-specific vulnerabilities.
Finds Misconfigurations Humans Miss
HighSystematically audits hundreds of configuration settings that are easy to overlook during manual review.
Tests Serverless and Container Workloads
MediumGoes beyond traditional infrastructure testing to cover Lambda, ECS, Kubernetes, and serverless architectures.
Generates Compliance-Ready Reports
MediumProduces detailed findings mapped to SOC 2, ISO 27001, and CIS Benchmarks for audit and compliance needs.
Top Cloud Misconfigurations AI Finds
Public S3/GCS Buckets
CriticalAI scans for publicly accessible storage buckets containing backups, logs, user data, and configuration files. In 2024, exposed S3 buckets caused 12% of all reported data breaches.
Overly Permissive IAM Roles
CriticalAI audits IAM policies for wildcards (*), excessive permissions, and roles that violate least-privilege principles. A single over-permissioned role can give attackers access to your entire AWS account.
Exposed Metadata Endpoints
HighAI tests whether cloud instance metadata (169.254.169.254) is accessible through SSRF in web applications. Exposed metadata can leak IAM credentials, API keys, and instance configuration.
Misconfigured Security Groups
HighAI scans for security groups with 0.0.0.0/0 ingress rules on sensitive ports (SSH, RDP, database ports). Open security groups are the #1 entry point for cloud-based attacks.
Unencrypted Data at Rest
MediumAI checks whether databases, storage buckets, and EBS volumes have encryption enabled. Unencrypted data at rest violates every major compliance framework.
Missing CloudTrail/Audit Logging
MediumAI verifies that audit logging is enabled across all services. Without logging, you can't detect or investigate security incidents.
Cloud Security by Provider
AWS
AI tests S3 bucket policies, IAM roles, security groups, Lambda function configurations, RDS public accessibility, CloudFront distributions, and API Gateway authorization. Covers the most common attack paths including privilege escalation through misconfigured AssumeRole policies.
Google Cloud
AI audits GCS bucket permissions, IAM bindings, firewall rules, Cloud Functions security, Cloud SQL public access, and service account key management. Tests for overly permissive allUsers and allAuthenticatedUsers bindings.
Azure
AI scans blob storage access policies, RBAC assignments, network security groups, Azure Functions configuration, and Cosmos DB access controls. Checks for misconfigured Managed Identity permissions.
Serverless Security Testing
Serverless architectures (AWS Lambda, Google Cloud Functions, Azure Functions, Vercel Edge Functions) introduce unique security challenges. Functions often run with overly broad IAM permissions because developers grant full access during development and never tighten it. AI pentest agents test function permissions by attempting to access resources outside the function's intended scope.
Event-driven architectures add another attack surface. AI tests whether event sources (API Gateway, S3 triggers, SQS queues) properly validate input before invoking functions. A malicious S3 object name or SQS message can inject commands into poorly written Lambda handlers. AI also tests for cold-start timing attacks and function-level DoS through concurrent invocation floods.
Related Resources
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