Changelog

Hostname routing ↗ is now generally available. Instead of managing static IP lists and routes, you can route traffic by hostname across multiple Cloudflare One connectors:

• Cloudflare Tunnel: route a private hostname (for example, wiki.internal.local) to a private application behind your tunnel, or a public hostname (for example, bank.example.com) to egress through a specific tunnel and anchor traffic to a dedicated exit node.
• Cloudflare Mesh: attract a private or public hostname's traffic to a Mesh node.

Alongside GA, the default IPv4 range used for initial resolved IPs (also called token IPs) is changing from a Carrier-Grade NAT (CGNAT) range to a public Cloudflare-owned range:

• IPv4: 172.64.128.0/20
• IPv6: 2606:4700:0cf1:4000::/64

This is the default range. You can configure a custom initial resolved IP range for IPv4 if it conflicts with your existing network.

Why this is changing: Starting with Chrome 142 ↗, Local Network Access (LNA) restrictions block background requests to CGNAT addresses (100.64.0.0/10), which included the previous initial resolved IP default (100.80.0.0/16). LNA is implemented at the Chromium engine level, so it affects all Chromium-based browsers (for example, Microsoft Edge, Brave, and Opera), not only Google Chrome. This could silently break hostname-based Gateway features for users of these browsers, and required Chrome Enterprise policy workarounds. The new default range is public Cloudflare address space, so it is not affected by this restriction.

What is affected: Initial resolved IPs are used by several features that associate a DNS query with the network connection that follows it:

• Private and public hostname routing for Cloudflare Tunnel
• Hostname routes for Cloudflare Mesh
• Access private applications on non-HTTPS ports
• Egress policy host selectors (Domain, Host, Application, and Content Categories)

You can check your account's current range, or configure a custom range, at any time from Zero Trust > Team & Resources > Devices > Device profiles, or using the Initial Resolved IP Subnet API.

For full instructions, refer to Configure initial resolved IPs. The IPv6 range (2606:4700:0cf1:4000::/64) is unchanged and is not affected by this restriction.

If you were relying on a Chrome Enterprise policy workaround (such as LocalNetworkAccessRestrictionsTemporaryOptOut) while your account was still on the legacy CGNAT-based range, refer to Google Chrome restricts access to private hostnames for next steps.

A new GA release for the Windows Cloudflare One Client is now available on the stable releases downloads page.

This hotfix addresses an uncommon and intermittent case on Windows devices where the device is unable to reconnect after the device is woken from sleep.

Real-time Tunnel log streaming is now available in the Cloudflare dashboard under Networking > Tunnels. This brings the same live debugging capability previously only available in the Cloudflare One dashboard, including multi-connector aggregated streaming for high-availability deployments.

In the tunnel detail view, a new Live logs tab lets you:

• Stream logs from single or multiple connectors — In highly available deployments with multiple cloudflared replicas, logs from all connectors are merged into a single stream grouped by hostname, making it easy to identify which host machine produced each log entry.
• Filter by log level, event type, and HTTP method — Narrow the stream to only the events you care about (HTTP, TCP, UDP, or cloudflared internal), at any log level.

For more information, refer to Monitor tunnels and Tunnel log streams.

Turnstile Spin is now generally available with three setup paths for creating a Turnstile widget and wiring canonical server-side siteverify into your existing backend. Start in the dashboard, with Wrangler, or from your AI coding agent. All three paths create the same widget. You can complete the integration by hand or have your agent embed the widget, wire siteverify, and validate it.

Turnstile setup has two parts: embed the widget in your frontend, then call siteverify from your backend. Without the second part, the widget appears on the page but does not protect the request.

• The skill includes insertion snippets for Next.js (App Router and Pages Router), Astro, SvelteKit, Hugo, and vanilla HTML. For other frameworks, the agent proposes a generic pattern and asks you to confirm it first.
• The Turnstile dashboard flags existing widgets with no matching siteverify traffic. Select Fix with Spin to copy a prompt that guides your agent through wiring siteverify into your backend.
• Before finishing, the agent runs a real Turnstile token through your protected endpoint, checks that it passes, then replays the token to confirm the endpoint rejects it on the second try. If a check fails, the agent stops and shows you where.

You can run Spin three ways:

• In the Turnstile dashboard, select Set up with Spin, enter your domains, then select Set up. Spin creates the widget and returns the sitekey, secret, and a prompt for your agent.
• From the Wrangler CLI, run wrangler turnstile widget create. Wrangler prints the sitekey and secret. You wire the frontend and siteverify by hand.
• From your AI coding agent, paste the Spin prompt into Claude Code, Cursor, Codex, OpenCode, or GitHub Copilot Chat. Your agent fetches the skill, creates the widget, then embeds it and wires siteverify.

To get started, refer to the Turnstile Spin documentation.

Workers AI and AI Gateway now provide a unified path for accessing models and managing inference traffic. Use the same AI binding and REST API to call models hosted on Workers AI or by supported third-party providers, with AI Gateway providing observability, logging, caching, security, and billing controls.

The AI binding supports both Workers AI and third-party models through env.AI.run(). The REST API provides shared /ai/ endpoints with Cloudflare authentication across providers.

Route a Workers AI request through AI Gateway by specifying a gateway ID. Use default to automatically create a gateway on the first authenticated request, or specify an existing gateway to separate applications and workloads:

const response = await env.AI.run(
	"@cf/zai-org/glm-5.2",
	{
		messages: [{ role: "user", content: "What is the capital of France?" }],
	},
	{
		gateway: { id: "default" },
	},
);

const response = await env.AI.run(
	"@cf/zai-org/glm-5.2",
	{
		messages: [{ role: "user", content: "What is the capital of France?" }],
	},
	{
		gateway: { id: "default" },
	},
);

Requests routed through AI Gateway can be logged and included in analytics for request volume, errors, latency, token usage, and costs. You can also configure controls such as caching, rate limiting, and request retries on the gateway.

You can now use prepaid AI Gateway credits to pay for Workers AI inference. This provides one credit balance for Workers AI and supported third-party model providers. To use credits for Workers AI, set the gateway's Workers AI billing setting to Unified billing. Workers AI requests routed through that gateway deduct from your credit balance in real time.

Prepaid credits also provide access to the following Workers AI frontier models without requiring the Workers Paid plan. Each frontier Workers AI model has a rate limit of 50 requests per minute per account, per model when billed with AI Gateway credits, compared to 20 requests per minute through standard Workers AI billing:

• @cf/moonshotai/kimi-k2.6
• @cf/moonshotai/kimi-k2.7-code
• @cf/zai-org/glm-5.2

These limits are designed for typical agentic and coding workloads, where requests to frontier models can take longer to complete.

For details, refer to Workers AI limits, Workers AI pricing, Unified Billing, and the AI Gateway model catalog.

Support for MySQL in Hyperdrive is now generally available. You can connect to any MySQL database from your Workers using Hyperdrive.

Hyperdrive makes your regional, MySQL databases fast when connecting from Cloudflare Workers. It eliminates unnecessary network roundtrips during connection setup, pools database connections globally, and can cache query results to provide the fastest possible response times.

You can connect using your existing drivers, ORMs, and query builders with Hyperdrive's secure credentials, with no code changes required. MySQL support is available at the same pricing as Postgres.

import { createConnection } from "mysql2/promise";

export default {
	async fetch(request, env, ctx) {
		const connection = await createConnection({
			host: env.HYPERDRIVE.host,
			user: env.HYPERDRIVE.user,
			password: env.HYPERDRIVE.password,
			database: env.HYPERDRIVE.database,
			port: env.HYPERDRIVE.port,
			disableEval: true, // Required for Workers compatibility
		});

		const [results, fields] = await connection.query("SHOW tables;");

		ctx.waitUntil(connection.end());

		return new Response(JSON.stringify({ results, fields }), {
			headers: {
				"Content-Type": "application/json",
				"Access-Control-Allow-Origin": "*",
			},
		});
	},
};

import { createConnection } from "mysql2/promise";

export interface Env {
	HYPERDRIVE: Hyperdrive;
}

export default {
	async fetch(request, env, ctx): Promise<Response> {
		const connection = await createConnection({
			host: env.HYPERDRIVE.host,
			user: env.HYPERDRIVE.user,
			password: env.HYPERDRIVE.password,
			database: env.HYPERDRIVE.database,
			port: env.HYPERDRIVE.port,
			disableEval: true, // Required for Workers compatibility
		});

		const [results, fields] = await connection.query("SHOW tables;");

		ctx.waitUntil(connection.end());

		return new Response(JSON.stringify({ results, fields }), {
			headers: {
				"Content-Type": "application/json",
				"Access-Control-Allow-Origin": "*",
			},
		});
	},
} satisfies ExportedHandler<Env>;

Learn more about how Hyperdrive works and get started building Workers that connect to MySQL with Hyperdrive.

Cloudflare Mesh nodes can now run as Docker containers. The cloudflare/mesh ↗ image is available on Docker Hub for Docker Compose, Kubernetes, and any OCI-compatible runtime — no host-level package installation required.

The image supports amd64 and arm64 architectures and includes built-in source NAT so return traffic routes correctly without VPC route table changes.

• Docker Compose — add a cloudflare-mesh service to your compose.yaml and connect your entire stack to a private network.
• Kubernetes StatefulSet — deploy a standalone Mesh node with persistent registration state.
• Kubernetes sidecar — add the Mesh image as a sidecar container in a Pod to connect an application to Cloudflare without application changes.
• CI/CD — pull the image in a pipeline step, join the Mesh, run integration tests against private infrastructure, and tear down. The node disappears when the container exits.

For high availability, run multiple replicas with the same Mesh node token. Cloudflare operates replicas in active-passive mode with automatic failover.

For setup steps, runtime configuration, and deployment examples, refer to Run Mesh in Docker / Kubernetes.

Radar expands its Routing section ↗ with two widgets on AS pages, such as AS13335 ↗, that describe how a network reaches the rest of the Internet: the paths it takes toward the Tier-1 ↗ networks, and the mix of direct upstreams carrying its routes. Both are derived from RouteViews ↗ RIB snapshots, unioned across selected collectors.

The AS-level connectivity graph aggregates the BGP paths an AS uses to reach the Tier-1 networks, unioned across all the prefixes it announces, as observed by selected RouteViews collectors. It reads from left to right, starting at the queried AS and ending at the Tier-1 networks, and each node is labeled with its AS number, country, and organization name. Tier-1 nodes are marked so they stand apart from the intermediate networks that lead to them.

By default, the graph shows the network's direct connections to Tier-1 networks plus the indirect paths, which keeps the view readable. A Show full paths toggle expands it to every observed path, including transit through Tier-1 networks the AS already connects to. An IP version selector switches between IPv4 and IPv6, because the paths reaching Tier-1 networks may differ between the two address families.

This is the AS-level counterpart to the Real-time connectivity graph on prefix pages, such as the one for 1.1.1.0/24 ↗. Instead of covering a single prefix, it covers the union of paths for all prefixes an AS announces, which makes it a fast way to read a network's transit hierarchy: which providers it depends on, how many hops separate it from the core, and whether its paths to the core are diverse or concentrated. For more information on the prefix-level graph, refer to BGP real-time routes.

The Upstream providers widget tracks the share of an AS's observed paths carried by each of its direct upstream networks over time, drawn as a stacked area chart. Up to 10 upstreams appear as their own series and the remaining ones are grouped into Other. Transit changes such as adding a provider, dropping one, or moving traffic between them appear as movement between bands rather than as a single aggregate number. As with the connectivity graph, an IP version selector switches between IPv4 and IPv6.

The data behind both widgets is also available through two new endpoints on the BGP API:

• /bgp/routes/paths/{asn} — Returns the ordered AS path segments an AS uses to reach the Tier-1 networks, each with its observed path count, peer count, and contributing collectors, alongside the name and country of every ASN in the response. Pass collector to scope the result to a single RouteViews collector.
• /bgp/routes/upstreams/{asn}/timeseries — Returns the share of an AS's observed paths carried by each direct upstream over time. Use limit to control how many upstreams come back as separate series before the rest are grouped into an OTHER series, and ipVersion to select the address family.

Visit the AS13335 routing page ↗ to explore both widgets, or swap in any other AS number.

Cloudflare Radar now includes Radar Researcher ↗, a beta AI-powered assistant for exploring Internet trends and traffic data in plain language. Open Researcher from the header on any Radar page to ask questions by voice or text, receive explanations, and view interactive charts based on Radar API data.

To ask about a specific chart, select Explain with AI to start a conversation with its underlying data and context.

You can explore further with suggested follow-up questions, find earlier conversations through searchable history, and share conversations through shareable links.

Alongside the user-facing Researcher experience, Radar now supports WebMCP, allowing browser-based AI agents to navigate Radar, search data, and use tools such as URL scanning and domain lookup.

To get started, visit Cloudflare Radar ↗.

Sandbox SDK 1.0 is available to preview under the npm @next tag. For existing applications, the current stable package remains published on the 0.12.x line.

Sandbox SDK first shipped to provide a rich library for running untrusted and agent-driven work on Cloudflare Containers. Since then, both Sandbox and Containers have matured. This preview is a thinner SDK built on a richer Cloudflare Containers foundation.

npm i @cloudflare/sandbox@next

yarn add @cloudflare/sandbox@next

pnpm add @cloudflare/sandbox@next

bun add @cloudflare/sandbox@next

• A single execution interface — sandbox.exec() takes an argument list, returns when the process starts, and gives you a handle for output, logs, waits, and signals. Both short commands and long-running services use the same API.
• Removed session execution — the SDK no longer maintains shell state between executions. Each launch is independent. Pass cwd and env when you need them, or put multi-step shell syntax in one explicit shell command.
• RPC as the only transport — the SDK talks to the container exclusively over RPC. Remove SANDBOX_TRANSPORT, transport on getSandbox(), and setTransport().
• Improved PTY and terminal interface — interactive PTYs use createTerminal / connect, not the older session-shaped helpers.
• Code interpreter as an extension — configure the code interpreter on your Sandbox subclass so you only ship what you need.

Start new projects on @next. Migrate existing apps when you can so you are ready when 1.0 becomes stable. Deploy the Worker package and container image from the same @next line.

Coding agents: install Cloudflare Skills ↗ (Agent setup). Use sandbox-next for @next (recommended for new projects), sandbox-stable for the current stable package, and sandbox-migrate-to-next when you are ready to port. Stable-package deprecated-API cleanup is in the 2026 deprecation guide.

The main Sandbox documentation still describes today's stable package. Preview docs:

• 1.0 preview
• Get started
• Migrate
• Processes · Terminals · Errors
• API reference

The self-deployed Sandbox bridge is not currently part of this preview. We are working on bringing it in line with the latest code. Until then, use the stable bridge with the matching stable package and container image.

Further Cloudflare Containers features will let us keep reducing the size of the Sandbox SDK. We aim to ship Sandbox SDK 1.0 once those are in. In the meantime we continue to support and maintain the 1.0 preview (@next) alongside the current stable release.

AI Search gets you from a data source to a working search endpoint quickly. This release adds what you need to put that endpoint in front of real users: your own domain, authentication, and one endpoint across several instances. It also adds crawling for sites without a complete sitemap, so your index covers everything you want it to find.

Each of the following is a new option. The previous behavior is still the default, so nothing changes until you change it.

A public endpoint is a URL that a site or app can query directly, with no authentication in front of it. By default that URL is a generated hostname on search.ai.cloudflare.com. You can now serve the same endpoint from a custom domain, a hostname in a zone that you own:

https://search.example.com/search

Once your endpoint is on your own domain, you can put Cloudflare Access in front of it. For example, you usually want to give /mcp to specific agents rather than to anyone who finds the URL. Agents authenticate with an Access service token, and people who open the endpoint in a browser sign in through your identity provider.

A namespace can expose its own public endpoint with /search, /chat/completions, and /mcp paths that fan out across the instances you choose:

curl https://ns-<NAMESPACE_ENDPOINT_ID>.search.ai.cloudflare.com/search \
  --header "Content-Type: application/json" \
  --data '{
    "messages": [{ "content": "How do I configure AI Search?", "role": "user" }],
    "ai_search_options": { "instance_ids": ["docs", "support"] }
  }'

Website data sources support a new discover parse type. It starts at the source URL and collects pages from both your sitemaps and the links it finds while crawling:

curl -X POST "https://api.cloudflare.com/client/v4/accounts/<ACCOUNT_ID>/ai-search/instances" \
  -H "Authorization: Bearer <API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{
    "id": "my-ai-search",
    "type": "web-crawler",
    "source": "example.com",
    "source_params": {
      "web_crawler": {
        "parse_type": "discover",
        "discover_options": { "source": "links", "limit": 5000, "depth": 3 }
      }
    }
  }'

To learn more, refer to the AI Search documentation.

Kitesurf is Cloudflare's new stateless, highly scalable browser that runs entirely on top of Workers and is designed for AI agents. It is available for free while in beta.

Compared to Chromium, Kitesurf uses 3–7× less CPU and memory for common agentic tasks like screenshots and HTML extraction, so you can run more sessions and scale better for bursty, AI-driven workloads.

Your existing clients already work. To opt in, add the browser=kitesurf parameter to any Browser Run CDP or Quick Action endpoint:

curl -X POST 'https://api.cloudflare.com/client/v4/accounts/<ACCOUNT_ID>/browser-run/screenshot?browser=kitesurf' \
  -H 'Authorization: Bearer <API_TOKEN>' \
  -H 'Content-Type: application/json' \
  -d '{
    "url": "https://example.com"
  }' \
  --output "screenshot.png"

You can also explore Kitesurf without writing any code in the public playground ↗.

For more information, refer to the Kitesurf documentation and the blog announcement ↗.

AI Gateway now includes User Insights, a dashboard that gives you two things at once: clear visibility into how much your organization spends on AI, and a security signal that surfaces users whose usage suddenly looks abnormal. It works on the traffic already flowing through your gateway, so there is no additional setup.

On the spend side, User Insights shows organization-wide totals for cost, requests, tokens, and adoption, and lets you drill into an individual user to see their spend, top models and providers, cache hit rate, and more. To attribute usage to individual users, add a user identifier with custom metadata or put your gateway behind Cloudflare Access.

On the security side, User Insights baselines each user's normal usage from their 95th percentile (p95) session cost over the last 30 days, then flags sessions that exceed both that baseline and an organization-level threshold. A sudden jump above a user's own pattern is often the first sign of a compromised credential or a misbehaving agent, so you can investigate before it shows up on your bill.

User Insights is available to all AI Gateway customers at no additional cost.

AI Gateway now integrates with Cloudflare Access, giving you two new capabilities:

• Protect your gateway endpoint. Put your AI Gateway behind Access so you can set policies that control who is allowed to call a specific gateway's endpoint.
• Identity-aware controls. When traffic reaches AI Gateway through an Access-protected custom domain, AI Gateway can use the authenticated user's Access identity in logs, analytics, routing, and spend controls.

With identity-aware controls, you can set spend limits by authenticated user, control which gateways different users can access, filter logs by user, and build policies without passing user IDs from the client application. AI Gateway adds the verified Access user ID to request metadata as cf.user_id.

For setup instructions, refer to Cloudflare Access.

OAuth consent screens now display a shield icon with explanatory text beneath the consent screen title. Each shield icon indicates who owns the application and whether its domain ownership is verified.

• Green filled shield: Cloudflare owns and manages the application.
• Blue outlined shield: A third-party application with verified ownership of its domain.
• Amber filled shield: A third-party application without verified ownership of a domain.

Domain verification only confirms that the application owner controls the displayed domain.

For more information, refer to Authorizing an application.

Agent tracing is now available for applications built with the Agents SDK. Traces show each agent turn alongside model calls, tool runs, approvals, token usage, and Workers runtime operations.

Turn on Workers tracing in your Wrangler configuration:

{
  "$schema": "./node_modules/wrangler/config-schema.json",
  "observability": {
    "traces": {
      "enabled": true
    }
  }
}

[observability.traces]
enabled = true

Think and Flue applications emit agent traces automatically. For direct AI SDK calls, wrap the AI SDK namespace once. wrapAISDK() supports AI SDK v6 and v7. This AI SDK v7 example also supplies the agent identity:

import * as ai from "ai";
import { wrapAISDK } from "agents/observability/ai";

const tracedAI = wrapAISDK(ai);

await tracedAI.generateText({
	model,
	prompt: "Find an available appointment",
	runtimeContext: {
		agentId: "booking-agent-production",
		conversationId: "conversation-123",
	},
	telemetry: {
		functionId: "booking-agent",
		includeRuntimeContext: {
			agentId: true,
			conversationId: true,
		},
	},
});

import * as ai from "ai";
import { wrapAISDK } from "agents/observability/ai";

const tracedAI = wrapAISDK(ai);

await tracedAI.generateText({
	model,
	prompt: "Find an available appointment",
	runtimeContext: {
		agentId: "booking-agent-production",
		conversationId: "conversation-123",
	},
	telemetry: {
		functionId: "booking-agent",
		includeRuntimeContext: {
			agentId: true,
			conversationId: true,
		},
	},
});

Message and tool payload recording is off by default. Turn it on only when the payloads are safe to store:

const tracedAI = wrapAISDK(ai, {
	storeMessages: true,
	storeTools: true,
});

const tracedAI = wrapAISDK(ai, {
	storeMessages: true,
	storeTools: true,
});

Open the Agents tab ↗ in the Cloudflare dashboard to inspect sessions, replay conversations, and view trace waterfalls. For advanced setup, privacy controls, and trace structure, refer to Agent tracing.

You can now run your CI/CD pipeline on your Artifacts repo by defining a CI Workflow with the CI SDK ↗, automatically triggered on Artifacts push events.

This allows you to:

• Automatically build and deploy application code stored in Artifacts.
• Run linting, type checking, tests, and other checks on every push.
• Reuse dependencies when the lockfile (i.e. pnpm-lock.yaml) has not changed.
• Stop deployment when a check or build fails.
• Restrict API token access to the deployment step.
• Deploy the output to a Worker or a Workers for Platforms User Worker.

Define your CI steps with @cloudflare/ci. Each ci.runner() spins up an isolated sandbox, and the cache option reuses installed dependencies across each sandboxed step in your CI job.

Point cache.inputs at your lockfile (i.e. pnpm-lock.yaml, bun.lock), and the install step only runs again when that lockfile changes:

const deps = await ci.runner({
	name: "install",
	command: "bun install --frozen-lockfile",
	cache: { inputs: ["package.json", "bun.lock"] },
});

await Promise.all([
	deps.runner({ name: "lint", command: "bun run lint" }),
	deps.runner({ name: "test", command: "bun run test" }),
	deps.runner({ name: "typecheck", command: "bun run typecheck" }),
	deps.runner({ name: "build", command: "bun run build" }),
]);

await deps.runner({ name: "deploy", command: "bun wrangler deploy" });

const deps = await ci.runner({
	name: "install",
	command: "bun install --frozen-lockfile",
	cache: { inputs: ["package.json", "bun.lock"] },
});

await Promise.all([
	deps.runner({ name: "lint", command: "bun run lint" }),
	deps.runner({ name: "test", command: "bun run test" }),
	deps.runner({ name: "typecheck", command: "bun run typecheck" }),
	deps.runner({ name: "build", command: "bun run build" }),
]);

await deps.runner({ name: "deploy", command: "bun wrangler deploy" });

To start the Workflow automatically after each push, add a cf.artifacts.repo.pushed trigger to your Wrangler configuration:

{
	"triggers": {
		"events": [
			{
				"type": "cf.artifacts.repo.pushed",
				"filter": {
					"namespace": "CI",
					"repoName": "my-repo",
				},
				"target": {
					"scriptName": "my-ci-worker",
					"workflowName": "ci-workflow",
				},
			},
		],
	},
}

[[triggers.events]]
type = "cf.artifacts.repo.pushed"

  [triggers.events.filter]
  namespace = "CI"
  repoName = "my-repo"

  [triggers.events.target]
  scriptName = "my-ci-worker"
  workflowName = "ci-workflow"

To learn more, refer to Build and deploy Artifacts repos.

You can now create standalone Free accounts directly from the Cloudflare dashboard using the new Create Account button. This feature is currently available to all users.

When creating a Free account:

• You can create up to 5 Free accounts.
• Your user account must have at least 7 days of tenure to be eligible.
• The account is created immediately and ready to use.

To create a Free account, go to the Cloudflare dashboard ↗ and select Create Account from either the account switcher in the top left (where your account name appears) or from the Accounts page.

• This feature can only be used to create a Cloudflare Free account. To create an Enterprise Account under your existing contract, please contact Cloudflare Support.
• All users can create a Cloudflare Free account, however, Enterprises wish to restrict this action to only Super Administrators. We will deliver this improvement in a future release.

After creating your Free account, you can:

• Add a payment method to enable additional Cloudflare products and services.
• Update billing information to manage payment methods, billing address, or tax IDs.
• Review how Cloudflare billing works to understand the billing lifecycle and charge types.
• Assign accounts to an Enterprise Organization to centrally manage multiple accounts from a single dashboard.

You can now store up to 20 million vectors in a single Vectorize index, doubling the previous limit of 10 million vectors. This enables larger-scale semantic search, recommendation systems, and retrieval-augmented generation (RAG) applications without splitting data across multiple indexes.

Vectorize continues to support indexes with up to 1,536 dimensions per vector at 32-bit precision. Refer to the Vectorize limits documentation for complete details.

This release introduces new rules and updates Microsoft SharePoint RCE alongside enhanced SSRF cloud protection rule actions.

Key Findings

• CVE-2026-50522: An insecure deserialization vulnerability in Microsoft SharePoint Server. This may allow an unauthenticated attacker to execute arbitrary code using crafted requests.
• CVE-2026-66066: An improper input processing vulnerability in Ruby on Rails Active Storage image variant transformations. This may allow an unauthenticated attacker to perform arbitrary file reads and achieve Remote Code Execution (RCE) using maliciously crafted payload requests.
• Generic Cloud Protections: Added improved detection logic targeting Server-Side Request Forgery (SSRF) in cloud-hosted applications.

wrangler dev and vite dev automatically capture structured OpenTelemetry traces and correlated console logs during local Worker invocations.

When the tooling detects an AI agent session, it prints a terminal hint pointing to the Local Explorer API at /cdn-cgi/explorer/api. The API serves an OpenAPI schema and exposes a read-only observability query endpoint for discovering telemetry, querying traces and logs, and inspecting binding state.

The agent can identify the exact failing operation, fix the code, rerun the request, and verify the result. This debug loop requires no deployment or temporary logs.

Humans can inspect the same traces and correlated console logs in the Local Explorer browser UI. Each trace shows spans, timing, attributes, and errors.

Automatic spans cover handler calls, outbound fetch() calls, and binding calls. Custom spans appear alongside these automatic spans.

For more details, refer to the Local Explorer documentation.

Cloudflare Access administrators can now control whether a self-hosted application preemptively sets authorization cookies across its public hostnames.

Previously, Access automatically used eager redirects for applications with five or fewer hostnames. Applications with more than five hostnames received cookies as users visited each hostname. Administrators can now choose either behavior, regardless of the number of hostnames.

The new Eager redirect cookie setting is turned on by default for new applications. After a user signs in, Access redirects the browser through each hostname and sets a CF_Authorization cookie. This supports applications that need to make requests across hostnames before the user visits each one.

For applications with many hostnames, the redirect chain can cause sign-in loops in some browsers. Turn off the setting to issue the cookie only when a user visits each hostname.

To configure the setting, refer to Authorization cookie.

We're releasing an early preview of @cloudflare/computer ↗, an open-source agent runtime that gives every agent its own computer. The runtime dynamically orchestrates between fast, efficient isolates and full Linux containers, so the agent always runs on the right compute primitive for the task at hand.

@cloudflare/computer provides a virtual filesystem backed by SQLite, which you can populate from cloud storage, source control, or any files you choose. Agents can read, write, and edit files, run shell commands, and interact with Git repositories. All operations are gated, audited, and observed.

Install the package via npm:

npm install @cloudflare/computer

Instantiate a Workspace inside any Durable Object to give your agent a filesystem and execution runtime:

import { Workspace } from "@cloudflare/computer";

export class Agent {
	workspace = new Workspace({
		storage: this.ctx.storage,
	});
}

Several execution backends are included or you can write your own:

• Isolate runtime — fast, horizontally scalable execution via just-bash and Dynamic Workers, ideal for file manipulation and data processing.
• Container runtime — full Linux environment via Cloudflare Containers, mounted through FUSE, for tasks that need native binaries, package managers, or a complete userland.

The AI SDK-compatible toolkit provides common agent tools (read, write, edit, ls, exec) and guides the model to choose the appropriate backend for each task.

For more examples, including a step-by-step tutorial, visit the @cloudflare/computer repository ↗.

Read the announcement blog post for more details: Your agent needs a computer, not a container ↗.

Billing is now enabled for Cloudflare Pipelines on non-enterprise accounts. Pipelines usage beyond the included free tier will appear on your next invoice.

Pipelines charges based on two usage dimensions. Ingress into a Pipeline stream remains free regardless of volume:

• SQL transforms: $0.04 / GB for stateless transforms (filter, reshape, unnest, cast, compute).
• Sinks (egress): $0.03 / GB for JSON output, $0.06 / GB for Parquet or Iceberg output.

Workers Paid plans include 50 GB / month for both SQL transforms and sinks. Standard R2 storage and operations charges apply for data written to R2 buckets, and R2 Data Catalog charges apply when writing to Iceberg tables.

For example, a pipeline that ingests 500 GB of event data per month, uses a SQL transform to filter and reshape it, and writes 300 GB to an R2 Data Catalog Iceberg table would be billed as follows:

For full pricing details and billing examples, refer to Pipelines pricing.