📦

basin

Name: basin
Author: cloudflare

Content revision r1 High Risk 🌐 Network access📁 Filesystem access⚙️ External commands

Build Cloudflare Basin Analytics Workflows

Streaming analytics requires coordinated ingestion, table management, and query configuration. This skill provides Cloudflare Basin references and implementation patterns across Pipelines, Catalog, and SQL.

Supports: Claude Codex Code(CC)

⚠️ 38 Poor

Maintain this Skill? Claim it ⚠️ 38 Poor

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Review the plan and obtain explicit user consent before changing files.

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "basin" from https://skillstore.io/skills/cloudflare-basin.md and its manifest at https://skillstore.io/api/skills/cloudflare-basin/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/cloudflare-basin.md Signed manifest GET /api/skills/cloudflare-basin/manifest Signed lockfile GET /api/skills/cloudflare-basin/lockfile

Test it

Using "basin". Which services should receive Worker events and support SQL reports?

Expected outcome:

Use a Basin Pipelines stream to receive validated Worker events.
Connect the stream through row-level transformations to a Basin Catalog Iceberg sink in R2.
Use Basin SQL for aggregate reports, with scoped credentials and protected dashboard access.
Verify current command syntax and confirm data delivery after the first flush.

Using "basin". The stream accepts events, but the table remains empty. What should I check?

Expected outcome:

Check pipeline state and failure reason without changing resources.
Compare events with the stream schema and inspect validation error metrics.
Check sink credentials, bucket availability, and catalog enablement.
Allow for the documented first-flush delay and verify both written files and query results.

Using "basin". Review the dashboard and Logpush examples before production deployment.

Expected outcome:

Require caller authentication and authorization before executing dashboard queries.
Enable ingestion authentication and control request volume.
Remove raw ClientIP from stored projections; hashing an additional column does not redact the original.
Check credential presence without printing tokens and store Worker tokens as secrets.

Security Audit

High Risk

v1 • 10/9/2026 Open versioned report

All 70 static matches are false positives involving documentation links, placeholder URLs, legitimate service requests, SQL identifiers, and TypeScript strings. Four semantic risks concern unauthenticated ingestion, an unprotected analytics endpoint, ineffective IP redaction, and a command that prints an API token. No evidence found of prompt injection, malicious exfiltration, or covert code execution in the reviewed files.

Files scanned

1,104

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (4)

High

references/sql/patterns.md:50-58 references/sql/patterns.md:61-69

Dashboard Worker Exposes Analytics Without Caller Authorization

The Worker matches "/api/analytics", queries with its server-side token, and returns result.rows without checking caller identity or permissions. A public deployment without external protection could disclose analytics and permit repeated billable queries.

The complete handler performs only a pathname check before returning authenticated query results. No caller authentication is shown; external deployment controls could reduce exposure.

Medium

references/pipelines/configuration.md:69-74 references/pipelines/configuration.md:115-121

HTTP Ingestion Templates Disable Authentication

The REST example sets "authentication": false, and Terraform also sets authentication = false for HTTP ingestion. If deployed, unauthenticated senders could inject events, corrupt analytics, and increase storage or processing costs.

Both executable configuration examples explicitly disable authentication without requiring an upstream access boundary. Exploitation depends on deploying these examples and accessing the ingest endpoint.

Medium

references/pipelines/patterns.md:64-72

Claimed IP Redaction Retains Raw Client Addresses

The Logpush transform selects ClientIP alongside sha256(ClientIP) AS hashed_ip while claiming "redact PII at ingest". The stored output retains the original address, so following this example does not achieve the stated redaction.

The same SELECT explicitly includes both the raw ClientIP column and its hash. The misleading redaction comment directly contradicts the output projection.

Medium

references/sql/gotchas.md:31-32

Troubleshooting Command Prints Authentication Secret

The checklist recommends "echo $WRANGLER_BASIN_SQL_AUTH_TOKEN" to test token presence. This reveals the complete credential in terminal output and can expose it through captured logs or assistant transcripts.

The command explicitly expands and prints the authentication token rather than checking whether it exists. Further disclosure depends on how terminal output is recorded.

Risk Factors

🌐 Network access (26)

📁 Filesystem access (19)

references/catalog/api.md:30 references/catalog/patterns.md:10 references/catalog/patterns.md:11 references/catalog/README.md:16 references/pipelines/api.md:124 references/pipelines/gotchas.md:45 references/pipelines/patterns.md:122 references/pipelines/patterns.md:125 references/pipelines/patterns.md:130 references/pipelines/README.md:88 references/pipelines/README.md:89 references/sql/api.md:3 references/sql/api.md:96 references/sql/configuration.md:7 references/sql/patterns.md:109 references/sql/patterns.md:114 references/sql/patterns.md:118 references/sql/README.md:63 references/sql/README.md:64

⚙️ External commands (6)

references/sql/patterns.md:51-54 references/sql/patterns.md:54-57 references/sql/patterns.md:57-64 references/sql/patterns.md:66-72 SKILL.md:12 SKILL.md:24

Audited by: codex

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Academic citations (APA · BibTeX · CFF)

APA citation

cloudflare. (2026). basin security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/cloudflare-basin/audits/1

BibTeX citation

@techreport{cloudflare-cloudflare-basin-2026,
  author = {cloudflare},
  title = {basin security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/cloudflare-basin/audits/1},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "basin security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
  - name: "cloudflare"
date-released: "2026-10-09"
url: "https://skillstore.io/skills/cloudflare-basin/audits/1"
identifiers:
  - type: other
    value: "skillstore:cloudflare-basin:audit:1"
    description: "Skillstore immutable audit report identifier"

Skillstore Score

Why this score Evidence Confidence: Medium

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Design a Streaming Analytics Pipeline

Plan event schemas, Worker ingestion, SQL transformations, and Iceberg sinks for an R2 analytics workflow.

Develop a Protected Analytics Dashboard

Adapt the Basin SQL Worker pattern with application access controls, bounded queries, and server-side credential storage.

Diagnose Missing Analytics Events

Investigate pipeline status, delayed flushes, validation errors, sink credentials, and delivery metrics before changing infrastructure.

Try These Prompts

Choose the Basin Components

Explain which Basin components fit my event analytics workload: [workload]. Identify required resources and questions before proposing commands.

Plan Authenticated Event Ingestion

Plan a Basin pipeline for [event schema] in [bucket]. Include authenticated ingestion, client validation, scoped credentials, and current Wrangler command checks.

Investigate Missing Events

Events are accepted but missing from [table]. Use these sanitized metrics: [metrics]. Propose read-only checks without printing secrets or deleting resources.

Review an Analytics Architecture

Review [architecture] for Basin analytics. Assess caller authorization, IP minimization, partition filtering, compaction, schema migration, and rollback using current provider references.

Best Practices

Check current provider documentation and installed tool versions before applying migration commands or permission changes.
Require ingestion authentication and dashboard authorization; scope credentials and never print secret values during diagnostics.
Validate events before sending, verify stored output, and use partition filters, query limits, and appropriate table maintenance.

Avoid

Deploying unauthenticated ingest or dashboard examples directly into production.
Assuming accepted events are persisted without checking validation errors, sink files, and query results.
Claiming IP redaction while storing raw addresses, or exposing authentication tokens in troubleshooting output.

Frequently Asked Questions

What does this skill provide?

It provides reference guidance and implementation patterns for Basin Pipelines, Basin Catalog, and Basin SQL over R2.

Does installation create Cloudflare resources?

The reviewed package contains Markdown references, not provisioning scripts. Resource creation requires separately running authorized tools or API requests.

Does it cover the former Cloudflare product names?

Yes. It maps Pipelines, R2 Data Catalog, and R2 SQL to Basin names and warns that command migration requires verification.

Can Basin SQL modify data or replace a transactional database?

No. The references describe Basin SQL as read-only analytics; writes require other engines, and transactional workloads need a suitable database.

Why can accepted events be missing from queries?

Deferred schema validation, first-flush delay, roll intervals, and sink failures can prevent immediate visibility. Check service metrics and stored files.

Are the examples ready for production?

No. Review access controls, ingestion authentication, IP handling, secret diagnostics, current API behavior, and credential scope before deployment.