Browser Auth Flow

CommunityPopular

ruvnet

browser-auth-flow

Probe a site's authentication flow for redirect leaks, missing CSRF, weak session cookies, and OAuth misconfiguration; produces an auth findings.md

Overview

Publisher	ruvnet
Repository	`ruflo`
Skill name	`browser-auth-flow`
Stars	72.7K
Forks	8.6K
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by ruvnet on GitHub. Read the source before you install it.

Installation

Install the Browser Auth Flow AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/ruvnet/ruflo/tree/main/plugins/ruflo-browser/skills/browser-auth-flow

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/ruvnet/ruflo.git /tmp/ruflo
mkdir -p .claude/skills
cp -r /tmp/ruflo/plugins/ruflo-browser/skills/browser-auth-flow .claude/skills/browser-auth-flow

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Browser Auth Flow in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Browser Auth Flow on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Browser Auth Flow is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Browser Auth Flow

Adversarial probe of a site's authentication. Drives the login flow once, records the trajectory, then runs a configurable set of probes against the captured artifacts and live page. Output is a structured findings.md inside the RVF container.

When to use

Pre-deployment audit of a new auth flow.
Investigating a suspected token leak or redirect issue.
Establishing a baseline for ongoing regression checks.

Steps

Open a recorded session via browser-record.
Drive the auth flow as in browser-login (credentials come from --credentials <handle> referencing browser-cookies if the run is a re-auth probe).
Run probes:
- csrf: inspect the login POST in the trajectory; verify a same-origin token field is present and non-empty.
- redirect: watch browser_get-url after each nav for cross-origin redirects with auth state in the URL or fragment. Flag any token-bearing URL that crosses an origin boundary.
- cookie: walk document.cookie via browser_eval. For each cookie, check Secure, HttpOnly, SameSite, expiry, and entropy of the value. Flag missing flags or short tokens. Pass each through aidefence_scan to flag PII embedded in cookie values.
- oauth: if the flow involves a third-party provider, capture the authorization request, verify state and nonce are present and high-entropy, verify redirect_uri matches the registered callback domain.
Quarantine any token / credential / PII captured during probing — it stays inside the RVF container's findings, never returns to the model unredacted (aidefence_is_safe gate from browser-extract applies if you read the findings back).
Write findings.md with one section per probe, severity rating per finding, and a verdict (pass / warn / fail).
Index the session in browser-sessions with tag: auth-probe so future audits compare against it.

Caveats

This skill probes; it does not exploit. Do not chain follow-up requests using a captured token.
Credentials must come from a vaulted handle or interactive entry. Never hardcode them in the field map.
Some probes require multiple page loads. Trajectory step count for an auth probe typically lands at 15–40 steps; budget accordingly.
The output is structured for human review. Do not auto-act on findings without surfacing them to the user first.

Frequently asked questions

What does the Browser Auth Flow AI skill do?

Probe a site's authentication flow for redirect leaks, missing CSRF, weak session cookies, and OAuth misconfiguration; produces an auth findings.md

Why use Browser Auth Flow on TypingMind?

Because you install it once and use it with any model. Browser Auth Flow is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Browser Auth Flow in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ruvnet/ruflo/tree/main/plugins/ruflo-browser/skills/browser-auth-flow. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Browser Auth Flow?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Browser Auth Flow?

As many as you like. As long as a model supports skills, you can use Browser Auth Flow with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Browser Auth Flow AI skill free?

Yes. It is published on GitHub by ruvnet under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Quarkus Security

affaan-m

CommunityPopular

Buenas prácticas de seguridad en Quarkus para autenticación, autorización, JWT/OIDC, RBAC, validación de entrada, CSRF, gestión de secretos y seguridad de dependencias.

Quarkus Verification

Bucle de verificación para proyectos Quarkus: build, análisis estático, pruebas con cobertura, escaneos de seguridad, compilación nativa y revisión de diff antes del lanzamiento o PR.

Springboot Security

Buenas prácticas de Spring Security para autenticación/autorización, validación, CSRF, secretos, cabeceras, limitación de velocidad y seguridad de dependencias en servicios Java Spring Boot.

Agent Architecture Audit

affaan-m

CommunityPopular

エージェントおよび LLM アプリケーション向けのフルスタック診断。12 層のエージェントスタックにおけるラッパーリグレッション、メモリ汚染、ツール規律の失敗、隠れた修復ループ、レンダリング破損を監査します。重要度順の発見事項とコードファーストの修正を生成します。エージェントアプリケーション、自律ループ、または LLM を活用した機能を構築する開発者に必須です。

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Browser Auth Flow

When to use

Steps

Caveats

Frequently asked questions

Related AI Skills

Set up your own AI workspace now