# Wiz Cloud Security Assessment
Wiz Cloud Security Assessment represents a comprehensive evaluation methodology for analyzing cloud infrastructure security posture through Wiz's Cloud Native Application Protection Platform (CNAPP). This assessment framework combines agentless scanning, runtime threat detection, and vulnerability management to provide organizations with actionable insights into their cloud security risks across multi-cloud environments including AWS, Azure, Google Cloud Platform, and Kubernetes deployments.
Traditional cloud security tools operate in silos, requiring organizations to deploy separate solutions for vulnerability scanning, configuration management, compliance monitoring, and threat detection. Each tool generates its own alerts, creating security teams drowning in disconnected data points while critical attack paths remain invisible. Wiz emerged to address this fragmentation by providing a unified platform that maps relationships between cloud resources, identifies attack paths, and prioritizes risks based on actual business impact rather than theoretical CVSS scores.
The platform exists because modern cloud environments present fundamentally different security challenges than traditional on-premises infrastructure. Cloud resources are ephemeral, auto-scaling, and interconnected through complex identity and access management policies. A misconfigured storage bucket might appear benign in isolation but becomes critical when combined with an overprivileged service account and a vulnerable container image. Wiz's assessment approach focuses on these contextual relationships, enabling security teams to understand how individual vulnerabilities contribute to exploitable attack chains.
This assessment methodology fits within broader cloud security programs as the intelligence layer that informs security architecture decisions, incident response priorities, and compliance reporting. Rather than replacing existing security controls, Wiz assessments provide the visibility needed to optimize security investments and focus remediation efforts on risks that actually matter to business operations.
Wiz Cloud Security Assessment operates through an agentless architecture that connects directly to cloud provider APIs to build comprehensive inventories of cloud resources without requiring software installation on target systems. The platform authenticates using read-only service accounts with minimal permissions, then systematically discovers and analyzes every resource within the cloud environment including compute instances, containers, serverless functions, databases, storage systems, and networking configurations.
The assessment process begins with resource discovery where Wiz queries cloud APIs to enumerate all assets across subscriptions, accounts, and projects. This discovery phase captures not only active resources but also dormant assets, orphaned volumes, and forgotten development environments that often escape traditional security monitoring. For each discovered resource, Wiz extracts configuration details, network connectivity patterns, identity relationships, and metadata that reveals how resources interact within the broader cloud ecosystem.
Vulnerability assessment occurs simultaneously through multiple scanning engines that analyze different asset types. Container images undergo static analysis to identify known vulnerabilities in base layers, application dependencies, and embedded secrets. Virtual machine instances are scanned for operating system vulnerabilities, installed software packages, and configuration weaknesses. Serverless functions are analyzed for vulnerable code dependencies and excessive permissions. Database systems are evaluated for configuration drift, access controls, and data exposure risks.
Configuration analysis examines each resource against security best practices, compliance frameworks, and custom policies defined by the organization. Wiz maintains rules aligned with major standards including CIS Benchmarks, SOC 2, HIPAA, PCI DSS, and cloud provider security recommendations. The platform identifies misconfigurations such as publicly accessible storage buckets, overly permissive security groups, unencrypted data stores, and weak identity policies that create attack opportunities.
Runtime threat detection supplements configuration analysis by monitoring cloud logs, API calls, and behavioral patterns to identify suspicious activities. The platform ingests CloudTrail logs, VPC flow logs, and Kubernetes audit logs to establish baseline behaviors and detect anomalies indicating potential compromise. Machine learning algorithms identify unusual data access patterns, privilege escalation attempts, and lateral movement behaviors that suggest active threats.
Graph analysis represents Wiz's core differentiator, where the platform constructs detailed relationship maps showing how vulnerabilities, misconfigurations, and identity permissions combine to create exploitable attack paths. The security graph visualizes potential attack sequences from initial access through privilege escalation to data exfiltration or system compromise. Each attack path receives a risk score based on exploitability, business impact, and exposure scope.
Real-world attack path examples include scenarios where an internet-facing web application with a remote code execution vulnerability connects to a database containing sensitive customer data through an overprivileged service account. Another common pattern involves container images with embedded AWS access keys deployed in clusters with excessive cluster-admin permissions, enabling attackers to pivot from a single compromised pod to full cluster control.
Assessment reporting provides multiple views tailored to different stakeholder needs. Executive dashboards present risk trends, compliance posture, and business impact metrics. Security team interfaces offer detailed findings with remediation guidance, code snippets, and integration with ticketing systems. Compliance reports generate evidence packages for auditors showing control implementation and continuous monitoring capabilities. Developer-focused views provide vulnerability details integrated into CI/CD pipelines with automated pull request generation for infrastructure-as-code fixes.
The platform supports assessment customization through policy frameworks that allow organizations to define custom rules, risk scoring criteria, and compliance requirements. Teams can create policies specific to their industry, technology stack, or regulatory environment while maintaining consistency across multi-cloud deployments.
Wiz Cloud Security Assessment matters because cloud security failures consistently rank among the top causes of major data breaches, regulatory violations, and business disruptions across industries. Capital One's 2019 breach, exposing 100 million customer records through a misconfigured web application firewall, demonstrates how cloud-specific vulnerabilities can bypass traditional security controls and cause massive financial and reputational damage.
The business impact extends beyond direct breach costs to encompass compliance violations, customer trust erosion, competitive disadvantage, and operational disruption. Healthcare organizations face HIPAA violations when patient data becomes exposed through misconfigured cloud storage. Financial services firms risk regulatory sanctions when trading algorithms become compromised through vulnerable container deployments. Manufacturing companies experience production shutdowns when OT networks become accessible through cloud connectivity misconfigurations.
Traditional vulnerability management approaches fail in cloud environments because they cannot understand the contextual relationships that determine actual risk. A critical vulnerability in an isolated development system poses minimal threat, while a medium-severity vulnerability in a system with access to production databases demands immediate attention. Without this context, security teams waste resources patching irrelevant vulnerabilities while critical attack paths remain unaddressed.
Speed of change in cloud environments makes manual security assessment impractical. Organizations deploy hundreds of new resources daily through automated infrastructure-as-code pipelines. Security configurations that were compliant yesterday become risky today when new resources are added or network policies change. Continuous assessment becomes essential for maintaining security posture visibility in dynamic environments.
Common misconceptions about cloud security assessment include the belief that cloud providers handle all security responsibilities. While cloud platforms secure the underlying infrastructure, customers remain responsible for securing their data, applications, configurations, and access controls. Another misconception assumes that existing network security tools provide adequate cloud visibility. Traditional tools cannot access cloud provider APIs, analyze serverless functions, or understand cloud-native identity models.
The shift toward DevOps and infrastructure-as-code requires security assessment integration into development workflows. Security cannot remain a separate function that evaluates systems after deployment. Effective cloud security assessment must provide feedback during development, automatically preventing risky configurations from reaching production while enabling developers to maintain deployment velocity.
Compliance requirements increasingly demand continuous monitoring capabilities rather than point-in-time assessments. Regulations like GDPR, CCPA, and industry standards require organizations to demonstrate ongoing security controls and rapid incident response capabilities. Automated assessment platforms provide the audit trails and evidence packages needed to satisfy regulatory requirements while reducing manual compliance overhead.
CDA approaches Wiz Cloud Security Assessment through the Preventative Defense Methodology (PDM), specifically within the Security Posture Hygiene (SPH) and Vulnerability and Signature Detection (VSD) domains. SPH owns the continuous configuration assessment and compliance monitoring functions, ensuring that cloud environments maintain secure baseline configurations through automated policy enforcement and drift detection. VSD handles vulnerability identification, attack path analysis, and threat intelligence integration that enables proactive threat hunting and incident response preparation.
The Autonomous Posture Command (APC) methodology applies directly to Wiz assessments where "Your posture adapts. Your hygiene never sleeps." represents the continuous monitoring and adaptive response capabilities required for effective cloud security. Cloud environments change rapidly through automated deployments, auto-scaling events, and configuration updates that can introduce new attack vectors within minutes. Traditional periodic assessments cannot maintain visibility into these dynamic environments.
APC implementation requires assessment platforms to automatically adapt scanning scope and risk prioritization as cloud environments evolve. New resources must be discovered and assessed immediately upon deployment. Configuration changes must trigger reassessment of affected attack paths. Threat intelligence updates must automatically adjust risk scores for existing vulnerabilities based on current exploit activity. This adaptive approach ensures that security posture visibility remains current despite constant environmental change.
CDA differs from conventional thinking by emphasizing attack path context over individual vulnerability counts. Traditional approaches focus on vulnerability scanning metrics, configuration compliance percentages, and time-to-patch statistics. While these metrics provide useful operational indicators, they fail to communicate actual business risk or guide effective resource allocation.
The PDM approach prioritizes understanding how vulnerabilities combine with misconfigurations and excessive permissions to create exploitable attack chains. A vulnerability becomes critical not based on its CVSS score but on its position within potential attack paths that lead to business-critical assets. This contextual approach enables security teams to focus remediation efforts on the small percentage of issues that actually pose meaningful risk.
CDA methodology emphasizes integration between assessment findings and defensive control implementation. Assessment platforms should not merely identify problems but should automatically trigger defensive responses through security orchestration platforms, configuration management systems, and incident response workflows. This integration transforms assessment from a passive monitoring function into an active defense capability that strengthens security posture through automated response.
The PDM approach requires assessment integration with business context including asset criticality, data classification, and operational dependencies. Technical risk scores must be adjusted based on business impact to ensure that remediation priorities align with organizational objectives rather than purely technical severity metrics.
• Cloud security assessment requires continuous, automated evaluation capabilities rather than periodic manual reviews due to the dynamic nature of cloud environments where resources are constantly created, modified, and destroyed through automated processes
• Attack path analysis provides more actionable risk insights than traditional vulnerability scoring because it reveals how individual issues combine to create exploitable chains that actually threaten business operations
• Agentless assessment architectures offer comprehensive visibility across multi-cloud environments without operational overhead, but organizations must carefully manage API permissions and ensure assessment platforms receive necessary access to provide complete coverage
• Assessment integration with development workflows and infrastructure-as-code pipelines enables shift-left security practices that prevent misconfigurations from reaching production while maintaining deployment velocity
• Contextual risk prioritization based on business impact, data sensitivity, and operational criticality ensures remediation efforts focus on issues that actually matter to organizational objectives rather than generating overwhelming lists of technical findings