How to Build Real-Time Programmable Security Policies with Cloudflare One

# Cloudflare One Programmability Overview Cloudflare One combines a global network with an extensible policy engine, allowing organizations to inject custom logic directly at the edge. This approach turns security policies into dynamic code that can react to each request in milliseconds, rather than relying on static rule sets. ## Programmable Policy Engine The policy engine evaluates traffic, applies rules, and can trigger custom actions without leaving the Cloudflare network. It provides the foundation for real‑time decision making.

• Supports rule‑based matching using source, destination, and request attributes.
• Integrates with software‑defined perimeter concepts for zero‑trust enforcement.
• Allows inline execution of Cloudflare Workers as policy actions.
• Provides built‑in variables for user identity, device posture, and geo‑location.
• Exposes results to downstream analytics via webhooks or logs.

## Edge Workers Integration Workers run on Cloudflare's edge, giving developers full access to request and response data at the moment of evaluation. This eliminates the latency of external round‑trips.

• Write logic in JavaScript, TypeScript, or Rust with the standard Worker runtime.
• Access environment variables for API keys, thresholds, and feature flags.
• Schedule periodic tasks (e.g., device cleanup) using the Cron trigger.
• Combine with rate‑limiting to throttle high‑risk traffic.
• Deploy updates instantly across 330+ cities without downtime.

## Custom Action Framework Beyond the default allow/block/isolate actions, Cloudflare One lets you define managed and custom actions that execute user code or external services.

• Managed templates for common use cases such as ITSM ticket creation or compliance redirects.
• Custom actions invoke external risk APIs, enrich requests with LDAP data, or modify headers on the fly.
• All actions run within the edge sandbox, preserving performance guarantees.
• Results can be fed back into policy evaluation for adaptive controls.
• Policies can be versioned and rolled back using the same infrastructure as code pipelines.

## Real‑Time Context Enrichment Enrichment pulls additional data at request time, enabling decisions that reflect the latest user or device state.

• Query internal HR or LMS systems to verify training compliance before granting access.
• Fetch threat intelligence scores from third‑party feeds.
• Validate browser fingerprints or device posture signals.
• Cache frequent look‑ups at the edge to reduce latency.
• Log enrichment outcomes for audit and reporting purposes.