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Perseus:Scan

Community
kaivyy
perseus:scan

Use when starting a security assessment to map architecture, entry points, and attack surface (Phase 1 & 2)

Overview

Publisherkaivyy
Repositoryperseus
Skill nameperseus:scan
Stars
68
Forks
14
Bundled files
Instructions only
LicenseMIT
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 kaivyy on GitHub. Read the source before you install it.

Installation

Install the Perseus:Scan 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/kaivyy/perseus.git /tmp/perseus
mkdir -p .claude/skills
cp -r /tmp/perseus/skills/perseus/scan .claude/skills/kaivyy-perseus-scan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Perseus:Scan 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 Perseus:Scan 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 Perseus:Scan 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.

Perseus Scan (Phase 1 & 2)

Overview

This skill executes the Pre-Reconnaissance Methodology of the Perseus framework. It maps the target's digital footprint, internal architecture, and attack surface to build a "Target Knowledge Graph".

Goal: Zero-blind-spot understanding of what exists, how it works, and where it can be attacked.

Methodology:

  1. Discovery (Parallel): Architecture, Entry Points, Security Patterns.
  2. Surface Mapping (Parallel): XSS Sinks, SSRF Sinks, Data Flows.
  3. Synthesis: Comprehensive Code Analysis Report.

Incremental Scan Mode

For large codebases, use incremental scanning to only analyze changed files:

Detection: Check for perseus.yaml with incremental settings:

yaml
incremental:
  enabled: true
  baseline: "main"  # or specific commit

If incremental enabled:

  1. Run git diff --name-only <baseline>...HEAD to get changed files
  2. Filter to include only code files (exclude tests, configs)
  3. Focus analysis on changed files and their dependencies
  4. Merge with previous cached results from .perseus-cache/

Incremental Workflow:

bash
# Get changed files
git diff --name-only main...HEAD | grep -E '\.(js|ts|py|go|php|rb|java|rs|cs)$'

# If no changes, skip scan
# If changes exist, scan only those files + imports

Execution Instructions

Phase 1: Discovery (Run in Parallel)

Launch these 3 agents simultaneously using a single message with multiple Task tool calls:

  1. Architecture Scanner:
    • "Map application structure, tech stack, frameworks, and critical components. Identify if web app, API, or microservices."
  2. Entry Point Mapper:
    • "Find ALL network-accessible entry points (API routes, webhooks, public functions). Catalog API schema files (OpenAPI, GraphQL). Exclude local-only tools."
  3. Security Pattern Hunter:
    • "Identify authentication flows, authorization mechanisms (RBAC/ABAC), session management, and security middleware. Map the security architecture."

Phase 2: Surface Mapping (Run in Parallel)

Wait for Phase 1 to complete. Then launch these 3 agents simultaneously:

  1. XSS/Injection Sink Hunter:
    • "Find dangerous sinks: innerHTML, exec, system, eval, SQL queries, file operations. Provide File:Line references."
  2. SSRF/External Request Tracer:
    • "Identify server-side requests: HTTP clients (fetch, axios), URL fetchers, webhooks. Map user-controllable parameters."
  3. Data Security Auditor:
    • "Trace sensitive data flows (PII, secrets, payments). Identify encryption and storage mechanisms."

Phase 3: Reporting (Synthesis)

Synthesize all findings into deliverables/code_analysis_deliverable.md.

Required Report Structure:

  1. Scope & Boundaries: Define In-Scope (Network Reachable) vs Out-of-Scope (Local/CLI).
  2. Executive Summary: High-level security posture.
  3. Architecture & Tech Stack: Frameworks, patterns, components.
  4. Authentication & Authorization: Detailed analysis of auth flows and session handling.
  5. Data Security: Encryption, storage, and sensitive data handling.
  6. Attack Surface: Detailed list of In-Scope entry points.
  7. Infrastructure: Secrets management, config, logging.
  8. Critical File Paths: Categorized list for downstream agents.
  9. XSS Sinks: List of specific sinks and render contexts.
  10. SSRF Sinks: List of specific outbound request sinks.

Schema Collection:

  • Create outputs/schemas/ directory.
  • Copy all discovered schema files (OpenAPI, GraphQL, JSON Schema) there.

Next Step: Proceed to perseus:audit to analyze identified components for vulnerabilities.

Frequently asked questions

What does the Perseus:Scan AI skill do?

Use when starting a security assessment to map architecture, entry points, and attack surface (Phase 1 & 2)

Why use Perseus:Scan on TypingMind?

Because you install it once and use it with any model. Perseus:Scan 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 Perseus:Scan in TypingMind?

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

Which AI models can use Perseus:Scan?

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 Perseus:Scan?

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

Is the Perseus:Scan AI skill free?

Yes. It is published on GitHub by kaivyy 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.

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