CSPM and CNAPP focus on misconfigurations and posture especially Ingress. CloudFence focuses on behavioral detection — it learns normal patterns for every workload by looking at network and identity logs, builds baselines, and flags suspicious deviations in real time, especially in outbound traffic. It complements posture tools by catching what static config oriented checks miss.

SIEMs collect and store logs but rely on manual rules and tuning to find threats. CloudFence automatically analyzes network and identity behavior, builds per-workload baselines, and detects unusual activity without rule engineering — delivering fast, focused, actionable detections purpose-built for the cloud.

CloudFence itself focuses on detection and visibility, not inline blocking. However, it can integrate with your cloud controls (like security groups, firewalls ) to automate response actions or trigger blocking through your existing infrastructure.

CloudFence charges a flat yearly fee, based on the number of workloads with active interfaces generating traffic. This model provides cost predictability, eliminates surprises, and scales with your actual environment. Integration and hosting are fully managed, and we offer unlimited seats for your security and operations teams.

CloudFence starts analyzing communications and activities as soon as logs are connected, and deviations are detected in real time once baselines are established.In most environments, building a baseline takes from hours to a few days, depending on traffic volume and workload behavior.

In parallel, CloudFence’s built-in rule engine can detect known malicious activity immediately, using IP/DNS reputation feeds or custom Guardrails — predefined rules set by the customer to enforce their own security policies (e.g., blocking traffic to specific regions, blocking communication on unapproved ports or to unapproved geographies , or flagging sensitive services).