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Ssrf

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PentesterFlow
ssrf

Deep-dive SSRF testing — bypass filters, hit cloud metadata, chain to RCE/credential disclosure. Use when a target parameter clearly accepts a URL or hostname.

Overview

PublisherPentesterFlow
Repositoryagent
Skill namessrf
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 Ssrf 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/ssrf .claude/skills/ssrf
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ssrf 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 Ssrf 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 Ssrf 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.

SSRF playbook

You suspect a parameter is being fetched server-side. Confirm it, escalate it, prove impact.

Execution rule: use the actual parameter, callback host, and target URL before running commands. Never write literal placeholders such as <endpoint> or <role> to files; if the collaborator/canary host is missing, ask once.

1. Confirm the primitive

Send the http request with the parameter pointing to:

  • An out-of-band canary the user provides (interactsh / burp collaborator / a netcat listener they own)
  • Compare to a control value to confirm the server is doing the fetch

If the canary fires, you have at minimum a blind SSRF.

2. Map filter behavior

Probe how the server validates the URL. For each probe, capture status and body:

  • http://127.0.0.1, http://localhost, http://0.0.0.0
  • IPv6: http://[::1], http://[::ffff:127.0.0.1]
  • Decimal/octal: http://2130706433, http://0177.0.0.1
  • DNS rebinding hosts the user provides
  • Schemes: gopher://, file:///etc/passwd, dict://, ftp://
  • Redirect chain: a user-controlled URL that 302s to internal target

Group probes by outcome to fingerprint the parser (Python urllib? Java URL? curl? net/http?).

3. Hit cloud metadata

If you suspect AWS:

GET http://169.254.169.254/latest/meta-data/iam/security-credentials/
GET http://169.254.169.254/latest/meta-data/iam/security-credentials/<role>

If IMDSv2 is enforced, attempt to obtain the token via the same SSRF if the primitive supports headers.

For GCP: http://metadata.google.internal/computeMetadata/v1/ with Metadata-Flavor: Google. For Azure: http://169.254.169.254/metadata/instance?api-version=2021-02-01 with Metadata: true.

4. Internal service discovery

With the SSRF confirmed, sweep common internal ports/paths from the victim's perspective: :80, :443, :6379 (Redis), :9200 (Elastic), :8500 (Consul), :2375 (Docker), :25 (SMTP). Use response time + body fingerprint.

5. Prove impact

  • Stolen credentials → demonstrate by listing one S3 bucket / one GCS bucket the role can reach (read-only).
  • Internal admin panel → fetch a single page that's clearly internal.
  • Source code / config disclosure → grab one file via file:// or internal HTTP.

Write a report to findings/ssrf-<endpoint>.md with the exact request, the exact response, and the impact you proved. Stop there.

Frequently asked questions

What does the Ssrf AI skill do?

Deep-dive SSRF testing — bypass filters, hit cloud metadata, chain to RCE/credential disclosure. Use when a target parameter clearly accepts a URL or hostname.

Why use Ssrf on TypingMind?

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

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

Which AI models can use Ssrf?

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 Ssrf?

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

Is the Ssrf 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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