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Webvuln

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PentesterFlow
webvuln

Web vulnerability hunting playbook. Use after recon, when you have specific hosts/endpoints to test for IDOR/BAC, injection, auth flaws, SSRF, and known CVEs. Emphasizes real PoC + concrete impact.

Overview

PublisherPentesterFlow
Repositoryagent
Skill namewebvuln
Stars
1.4K
Forks
248
Bundled files
Instructions only
LicenseApache-2.0
Links
  • 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 PentesterFlow on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/PentesterFlow/agent.git /tmp/agent
mkdir -p .claude/skills
cp -r /tmp/agent/skills/webvuln .claude/skills/webvuln
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Webvuln 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 Webvuln 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 Webvuln 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.

Web vuln hunting playbook

You are testing specific endpoints the user has handed you (or that came out of the recon skill). Every finding must come with a real PoC and a concrete impact statement — no theoretical bugs.

Default to curl and the built-in http tool. Do not pull in heavy scanners (nuclei, sqlmap, ffuf, etc.) unless the user explicitly asks for them or you have manually confirmed a bug and need a scanner only to characterize the bug class.

Execution rule: substitute real target values before running commands. Never write literal placeholders such as <TARGET>, <vulnerable-path>, or <PoC body> to files. If a value is unknown, ask once or derive it from /target.

1. Triage the target

Fetch the landing page with the http tool or curl. Note:

  • Framework / language signals (cookies, headers, error pages)
  • Authentication scheme (cookie, Bearer, basic)
  • API style (REST / GraphQL / gRPC)
  • Anything that suggests a known CVE family (versioned banner, vendor product name)

If you spot a versioned product, immediately web_search "<product> <version> CVE" and web_fetch the top advisory. Reproduce the CVE manually with curl before reporting.

2. Known-CVE pass (manual, curl-driven)

For each suspected CVE pulled from the advisory, craft the curl that proves it — single request when possible:

TARGET="https://app.example.com" # replace with the scoped target before running
curl -ksS -X POST "$TARGET/vulnerable-path" \
  -H 'Content-Type: application/json' \
  -d '{"replace":"with-real-poc-body"}' \
  -w "\nHTTP %{http_code}  size=%{size_download}  time=%{time_total}\n"

If the advisory describes a recognizable pattern (template injection, deserialization, etc.) and the user has explicitly authorized broader scanning, then — and only then — reach for nuclei against the single host. Otherwise stay manual.

3. Auth + access control (IDOR / BAC)

  • Identify any numeric or UUID identifiers in the URL path or query (/api/users/12345, /orders/?id=...).
  • With user-provided session A, fetch a resource you own.
  • Swap the identifier to another user's value (or use a second session from the user) and replay with curl or the http tool.
  • A 200 with foreign data = IDOR. Capture the curl one-liner and the response excerpt into findings/idor-<endpoint>.txt.

Example IDOR sweep with two sessions:

TARGET="https://app.example.com" # replace with the scoped target before running
for id in $(seq 1 50); do
  body=$(curl -ksS -H "Cookie: $SESSION_B" "$TARGET/api/users/$id" | jq -r '.email // empty')
  [ -n "$body" ] && echo "$id $body"
done

4. Injection surfaces (curl-first)

For each parameter (query, body, header, cookie):

  • Inject simple probes (', ", <x>, ${7*7}, {{7*7}}) with curl or the http tool.
  • 500s / reflected payloads / arithmetic evaluation → escalate to a targeted PoC.

Quick reflected-XSS probe with curl:

TARGET="https://app.example.com" # replace with the scoped target before running
for p in q s search query keyword; do
  curl -ksS "$TARGET/?$p=pf$(date +%s)<svg/onload=alert(1)>" \
    | grep -o "pf[0-9]*<svg.*alert(1)>" || true
done

For SQLi: only after curl-level manual confirmation (timing differences, error strings) and only with the user's explicit OK, escalate to sqlmap with --batch --level=2 --risk=1 --random-agent against the single endpoint. Default path is manual ' OR sleep(5) -- style probes via curl, then exfil via UNION when you know the schema.

5. SSRF & open redirects

Any parameter that takes a URL or hostname: try http://127.0.0.1, http://169.254.169.254/latest/meta-data/, and an out-of-band canary the user provides. Compare response timings and bodies with curl -w "%{time_total} %{size_download}\n".

6. Report

For each confirmed finding, write findings/<id>-<short-title>.md with:

  • Title, severity (VRT-aligned), category
  • Affected endpoint(s)
  • Step-by-step reproduction as the exact curl one-liner the reviewer can copy (with placeholders for session tokens)
  • Observed response excerpt proving the bug
  • Concrete impact (what data is exposed, what state can be changed, what privilege is escalated)
  • Suggested remediation

Stop after writing the report. Do not chain into further exploitation unless the user explicitly asks.

Frequently asked questions

What does the Webvuln AI skill do?

Web vulnerability hunting playbook. Use after recon, when you have specific hosts/endpoints to test for IDOR/BAC, injection, auth flaws, SSRF, and known CVEs. Emphasizes real PoC + concrete impact.

Why use Webvuln on TypingMind?

Because you install it once and use it with any model. Webvuln 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 Webvuln in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/PentesterFlow/agent/tree/main/skills/webvuln. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Webvuln?

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 Webvuln?

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

Is the Webvuln AI skill free?

Yes. It is published on GitHub by PentesterFlow under the Apache-2.0 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.

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