> For the complete documentation index, see [llms.txt](https://cortex-docs.paloaltonetworks.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cortex-docs.paloaltonetworks.com/cortex-cloud-runtime-security/network-exposure-detection/what-is-cloud-network-analyzer.md). # What is Cloud Network Analyzer? Cloud Network Analyzer (CNA) in Cortex Cloud determines which assets—such as virtual machines, databases, containers, and serverless functions—are exposed to the internet, have unrestricted access to the internet, or can laterally move within a cloud account. CNA creates an internal network topology to map the path between the internet and the asset. This map provides insights about existing network security controls, including security groups and internet gateways. CNA helps you identify the following: * Workloads exposed to access from the internet * Workloads that have unrestricted outbound access to the internet * Overly permissive security groups attached to sensitive workloads * Production applications connected to testing or staging environments between cloud accounts or VPCs * Object storage buckets with sensitive data exposed through network connectivity to external cloud accounts or networks * Kubernetes services exposed to access from the internet, their underlying endpoints, and associated deployments #### Detection capabilities: inbound, outbound, east-west CNA detects which assets are exposed to the internet, have unrestricted access to the internet, or can laterally move within a cloud account. CNA supports three types of internet exposure detection: * **Inbound:** Data or requests entering your network from external sources * **Outbound:** Data or requests leaving your network to external destinations * **East-west:** Data or requests moving laterally within your network Inbound exposure detection is referred to as “Internet exposure detection” in this documentation. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://cortex-docs.paloaltonetworks.com/cortex-cloud-runtime-security/network-exposure-detection/what-is-cloud-network-analyzer.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.