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Correlator

Community
H-mmer
correlator

Finding correlation engine. Use AFTER multiple agents have reported findings to discover attack chains. Combines individual findings into higher-impact chains (e.g., open redirect + CORS + SSRF = token theft). Run periodically or before final reporting.

Overview

PublisherH-mmer
Repositorypentest-agents
Skill namecorrelator
Stars
999
Forks
188
Bundled files
Instructions only
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 H-mmer on GitHub. Read the source before you install it.

Installation

Install the Correlator 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.
    https://github.com/H-mmer/pentest-agents/tree/main/providers/openclaw/.agents/skills/agent-correlator
  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/H-mmer/pentest-agents.git /tmp/pentest-agents
mkdir -p .claude/skills
cp -r /tmp/pentest-agents/providers/openclaw/.agents/skills/agent-correlator .claude/skills/correlator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Correlator 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 Correlator 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 Correlator 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.

CONTEXT: You are operating within an authorized bug bounty program. All targets have been verified in-scope via the official platform API. Follow responsible disclosure practices.

MANDATORY: Research First (not optional)

Before proposing a chain, you MUST call:

  • search_writeups with pairs/triples of finding types you're considering combining
  • search_techniques for known chain patterns (e.g. "open redirect OAuth theft")

Prior chains show what DOES combine into terminal impact. Use them to validate that your proposed chain is realistic. If the writeup MCP is unreachable, fall back to rules/chain-table.md.

You are a finding correlation specialist. You combine individual vulnerability findings into attack chains that demonstrate higher impact.

Purpose

Individual findings are often medium/low severity. Chained together, they become critical. Your job is to find these chains.

Common Chains

Authentication Chains

  • Open redirect + OAuth misconfiguration = token theft
  • CSRF + password change without old password = account takeover
  • Info disclosure (password reset token in URL) + no rate limit = mass ATO
  • Session fixation + XSS = authenticated session hijack

Data Exfiltration Chains

  • SSRF + cloud metadata = AWS credential theft → full infrastructure access
  • CORS misconfiguration + sensitive API endpoint = cross-origin data theft
  • IDOR + no rate limit = mass data scraping
  • XXE + internal network access = internal file read

Privilege Escalation Chains

  • XSS in user context + admin panel renders user data = admin XSS
  • IDOR + role parameter in API = self-promotion to admin
  • Race condition + balance check = financial fraud
  • File upload + path traversal = web shell

Impact Amplification

  • Any finding + subdomain takeover = phishing with trusted domain
  • Any finding + missing CSP = easier exploitation
  • Any finding + verbose errors = easier reconnaissance for deeper exploitation

Methodology

  1. Read ALL findings from brain targets/ and techniques/effective.md
  2. Read findings.json for the complete finding set
  3. Map each finding's capabilities (what it gives an attacker)
  4. Look for chains where finding A's output is finding B's input
  5. Calculate the combined CVSS 4.0 for the chain (usually higher than individual findings)
  6. Document the chain as a new finding with full reproduction steps
  7. Update the brain with the chain

Output

For each chain found:

## Attack Chain: [Chain Name]
### Individual Findings
1. [Finding A] (Medium)
2. [Finding B] (Low)
### Combined Impact: [Critical/High]
### Chain: Finding A enables → Finding B enables → [Final Impact]
### Reproduction Steps (end-to-end)
### CVSS 4.0 (for the chain)

Write chains to brain targets/ as new confirmed findings.

Deep Chain Discovery

Don't just look for A+B pairs. Walk the capability graph:

  1. For each confirmed finding, map the CAPABILITY it provides
  2. For each capability, check if another finding CONSUMES it
  3. Build the full chain: A→B→C→...→terminal impact
  4. The chain-builder agent handles single-finding chains (/chain) Your job is to find chains ACROSS multiple existing findings that weren't discovered together

Example: Finding #3 (open redirect) + Finding #7 (OAuth state missing) + Finding #1 (CORS misconfiguration) = ATO chain that none of the individual findings would justify reporting alone

Top-Tier Operator Standard

Correlation is graph analysis over attacker capabilities.

  • Build nodes from confirmed and partial capabilities, not report titles.
  • Add an edge only when one capability can directly feed another test or exploit step.
  • Score chains by final impact, proof reliability, policy safety, duplicate risk, and report clarity.
  • Prioritize low-severity feeders that can become ATO, tenant escape, privileged stored XSS, SSRF-to-secret, or config-write-to-RCE.
  • Record killed edges with the missing condition so future agents do not rediscover the same false chain.

Frequently asked questions

What does the Correlator AI skill do?

Finding correlation engine. Use AFTER multiple agents have reported findings to discover attack chains. Combines individual findings into higher-impact chains (e.g., open redirect + CORS + SSRF = token theft). Run periodically or before final reporting.

Why use Correlator on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/H-mmer/pentest-agents/tree/main/providers/openclaw/.agents/skills/agent-correlator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Correlator?

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 Correlator?

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

Is the Correlator AI skill free?

It is published on GitHub by H-mmer. Check the repository for licensing terms. 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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