CNAPP vendor comparison for AWS/Azure + EKS/AKS: what should we require (posture, IaC scanning, runtime detection, agentless coverage)?

Cloud attacks do not wait for your quarterly review. For AWS, Azure, EKS, and AKS, a CNAPP has to do more than show misconfigurations. It has to continuously reduce exposure, catch risky infrastructure before it deploys, detect malicious behavior at runtime, and give teams a path from findings to fixes — fast.

If you are comparing CNAPP vendors, require four things at minimum:

Continuous posture management across cloud accounts, subscriptions, and Kubernetes.
IaC scanning that catches issues before deployment.
Runtime detection and response for workloads and clusters.
Agentless coverage for fast discovery and broad visibility without deployment friction.

If a vendor cannot do all four, you are not buying a CNAPP. You are buying a report.

What a modern CNAPP must cover

For AWS and Azure, the platform should understand the full cloud control plane and the workload layer:

AWS: organizations, accounts, IAM, EC2, EKS, S3, EBS, RDS, VPCs, security groups, CloudTrail, KMS, and container registries
Azure: management groups, subscriptions, Entra ID, AKS, VMs, Blob storage, Key Vault, NSGs, SQL, and ACR
Kubernetes: clusters, nodes, pods, namespaces, service accounts, roles, policies, and runtime behavior

The goal is not more findings. The goal is better decisions. A strong CNAPP should connect misconfigurations, identities, cloud resources, container behavior, and attack paths into one operational view.

CNAPP vendor comparison scorecard

Capability	What to require	Why it matters	Red flag
Posture management	Continuous assessment across AWS and Azure accounts, subscriptions, and Kubernetes clusters	Cloud risk changes constantly; point-in-time scans go stale fast	Periodic scans only
IaC scanning	Support for Terraform, CloudFormation, ARM/Bicep, and Kubernetes manifests in CI/CD	Catch exposure before it reaches production	Only post-deploy checks
Runtime detection	Detection of malicious activity in workloads and clusters, not just configuration drift	Attackers exploit the gap between secure-by-design and secure-in-production	Posture-only platform
Agentless coverage	Discovery and assessment without requiring an agent everywhere	Faster rollout, broader coverage, less friction	Full deployment required before value
Prioritization	Risk ranked by exploitability, attack path, and adversary tradecraft	Teams cannot fix everything; they need to fix what matters most	Severity-only scoring
Response workflows	Ticketing, scripts, containment, and orchestration from one console	Findings must turn into remediation	PDF exports and manual handoffs
Kubernetes context	Cluster-to-workload-to-identity visibility	EKS and AKS attacks spread through identity and orchestration	Siloed container views
Platform consolidation	One telemetry model across cloud, identity, and workload data	Fragmented tools hide cross-domain attacks	Multiple consoles that do not correlate

Posture management: the baseline is continuous

A CNAPP should continuously assess cloud posture, not periodically inventory it.

That means:

Detecting risky IAM permissions and overprivileged roles
Flagging public exposure and weak network paths
Identifying unencrypted data stores and weak key usage
Tracking misconfigured security groups, NSGs, and routing
Monitoring drift after deployment
Correlating cloud posture with identity and workload exposure

For AWS and Azure, posture is not just compliance. It is attack surface management. If a tool cannot tell you how a public endpoint, a vulnerable workload, and a privilege escalation path connect, it is leaving the exploit window open.

IaC scanning should stop bad infrastructure before it ships

IaC scanning is where strong programs win early.

Require a vendor that can scan:

Terraform
CloudFormation
ARM/Bicep
Kubernetes YAML and Helm
CI/CD pipelines and pull requests

The real question is not whether the tool finds misconfigurations. It is whether it helps developers and platform teams fix them before they merge.

Look for:

Pre-commit or PR-time feedback
Policy checks tied to real cloud risk
Secrets detection where appropriate
Context on why a change is dangerous
Clear remediation guidance, not just policy names

If the output is a long list of findings with no ownership, no context, and no fix path, the vendor has built a scanner — not a security program.

Runtime detection is non-negotiable

Posture tells you what could go wrong. Runtime tells you what is actually happening.

For EKS and AKS, require runtime visibility into:

Suspicious process behavior
Abnormal network activity
Container escape attempts
Unauthorized privilege escalation
Lateral movement inside the cluster
Malicious binaries, scripts, or cryptomining behavior
Cloud and Kubernetes control-plane activity tied to the workload

And runtime must lead to action.

A serious platform should be able to:

Isolate compromised workloads
Block malicious behavior in real time
Surface complete attack context
Support rapid investigation and response workflows

CrowdStrike’s Falcon Cloud Security positions this as Unified Real-Time CDR: converting prioritized risk into enforced protection, isolating compromised workloads, and blocking malicious behavior in real time. That is the standard you should expect.

Agentless coverage should expand visibility, not replace control

Agentless coverage matters because cloud environments are dynamic. Some assets are short-lived. Some are inherited. Some are difficult to instrument immediately.

Require agentless support for:

Fast discovery of cloud assets
Posture and exposure assessment
Broad visibility across AWS and Azure accounts
Low-friction rollout where deploying an agent is not practical

But do not confuse agentless with complete protection. Agentless visibility is the starting point. For workloads and runtime enforcement, you still need a control plane that can observe, correlate, and respond.

The strongest model is unified agent and agentless protection — a platform that uses the right collection method for the right job.

EKS and AKS require Kubernetes-specific depth

Many CNAPPs claim Kubernetes support. Fewer understand how attacks actually move through a cluster.

For EKS and AKS, ask vendors to show:

Cluster inventory and ownership
Namespace and workload context
Service account and role mapping
Admission and policy visibility
Node, pod, and container runtime correlation
Exposure paths from internet-facing services to sensitive workloads
Remediation actions that are tied to the cluster workflow

You should be able to trace risk from the cloud account to the cluster, from the cluster to the workload, and from the workload to the identity behind it.

If the platform cannot connect those layers, it will miss the attack path.

Prioritization should be adversary-informed

Not all critical findings are equally urgent. Some are theoretical. Some are actively exploitable.

Require a vendor that prioritizes based on:

Proven exploitation
Active adversary tradecraft
Reachability
Identity privilege
Internet exposure
Attack path analysis

CrowdStrike has been explicit about this model in cloud security: map cloud risks to active adversary tradecraft so security teams can prioritize remediation based on proven exploitation rather than theoretical severity.

That is the difference between a dashboard and an operating model.

What to ask every CNAPP vendor in a demo

Use these questions to separate real platforms from feature checklists:

How do you unify AWS, Azure, and Kubernetes telemetry in one model?
Can you show continuous posture, not just periodic scans?
Which IaC formats do you scan, and where does the feedback land?
Can you detect runtime threats in EKS and AKS and act on them?
What does your agentless coverage include, and what does it miss?
How do you prioritize findings beyond severity?
Can you correlate cloud risk with identity and workload behavior?
How do you move from findings to fixes — fast?
Can you isolate compromised workloads or launch remediation workflows directly?
Do you force analysts to pivot across tools, or can they investigate in one console?

Where CrowdStrike fits

CrowdStrike’s cloud security approach is built around the same operating model: consolidate telemetry, prioritize by adversary behavior, and enforce protection from code to cloud.

Falcon Cloud Security is positioned as the most complete CNAPP with unified agent and agentless protection, from code to cloud. The platform also includes capabilities that matter in a real comparison:

Application Explorer to unify application and cloud infrastructure context
Timeline Explorer to visualize how cloud risk evolves
Unified Real-Time CDR to isolate compromised workloads and block malicious behavior
Adversary-informed prioritization so teams focus on what attackers are actually using

That matters because cloud security is no longer just about reducing misconfigurations. It is about stopping the chain that turns exposure into breach.

Bottom line

When you compare CNAPP vendors for AWS, Azure, EKS, and AKS, do not start with dashboards. Start with operational requirements:

Continuous posture
IaC scanning
Runtime detection
Agentless coverage
Adversary-informed prioritization
Fast remediation workflows

If a vendor cannot cover all four core capabilities — posture, IaC, runtime, and agentless — across both cloud and Kubernetes, it is not ready for a modern cloud security program.

CrowdStrike’s view is simple: the exploit window is shrinking, attacks take only minutes, and your CNAPP has to do more than report risk. It has to help you stop breaches.