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Sast Entry Mapper

Community
H-mmer
sast-entry-mapper

Maps entry points where untrusted data enters a source file. Lists every function that receives external input with data type, size constraints, and initial validation. Use via /sast command.

Overview

PublisherH-mmer
Repositorypentest-agents
Skill namesast-entry-mapper
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 Sast Entry Mapper 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-sast-entry-mapper
  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-sast-entry-mapper .claude/skills/sast-entry-mapper
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sast Entry Mapper 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 Sast Entry Mapper 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 Sast Entry Mapper 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: Authorized security research. Analyzing source code for vulnerability entry points.

Task

Read the assigned source file and identify every point where data from outside the process enters. This is a reading comprehension task — list what you see, do not speculate about vulnerabilities.

What Counts as an Entry Point

Direct external input

  • Network: recv(), read() on sockets, HTTP handler params, RPC arguments
  • File: fread(), read() on file descriptors, config parsing, media decoding
  • IPC: shared memory reads, pipe reads, D-Bus message handlers, signal handlers
  • User: scanf(), getenv(), command-line args (argv), GUI input callbacks
  • Hardware: ioctl() handlers, device register reads, DMA buffer access

Indirect external input

  • Function parameters where callers pass external data (trace one level up)
  • Struct fields populated by callers with external data
  • Global/static buffers filled elsewhere from external sources
  • Callback functions invoked with external data

Language-specific

  • Rust: unsafe block reading from raw pointer, FFI function args, std::io::Read

  • Java: HttpServletRequest params, ObjectInputStream.readObject(), JNDI lookups

  • Python: request.args, sys.stdin, pickle.loads() input, eval() input

  • Go: http.Request fields, io.Reader implementations, CGo pointer args

  • PHP — ALL of these are tainted by default:

    • Superglobals: $_GET, $_POST, $_REQUEST, $_COOKIE, $_FILES, $_SERVER (note: $_SERVER['HTTP_*'] and $_SERVER['PHP_SELF']/QUERY_STRING/REQUEST_URI are attacker-controlled; $_SERVER['REMOTE_ADDR'] is semi-trusted)
    • Raw body: file_get_contents('php://input'), fopen('php://input'), $HTTP_RAW_POST_DATA
    • Session: $_SESSION[...] — tainted if any prior request wrote user input into it (second-order)
    • Env: $_ENV[...], getenv(...) — tainted in web contexts if set from request headers
    • Framework request objects (treat as direct input):
      • Laravel: $request->input(), $request->get(), $request->all(), $request->only(), $request->query(), $request->json(), $request->header(), $request->cookie(), $request->file(), request()->..., route parameters ($id in Route::get('/u/{id}', fn($id)=>...))
      • Symfony: $request->get(), $request->query->get(), $request->request->get(), $request->headers->get(), $request->files->get(), ParamConverter bound entities
      • CodeIgniter: $this->input->get(), $this->input->post(), $this->input->cookie(), $this->input->server()
      • WordPress: $_REQUEST in admin-ajax.php handlers, $_POST in wp_ajax_* callbacks, shortcode/hook callback args
      • Drupal: \Drupal::request()->query->get(), Drupal::request()->request->get(), form state values
      • Yii: Yii::$app->request->get(), $this->request->post()
    • Database-sourced taint (second-order): Any SELECT that returns data originally written from a superglobal (stored XSS/SQLi). Mark as indirect and name the write-path function if visible.
    • File upload metadata: $_FILES['x']['name'] (attacker-chosen filename — never trust extension from this), $_FILES['x']['type'] (client-provided MIME — forgeable), $_FILES['x']['tmp_name'] (trusted), $_FILES['x']['size'] (trusted)
    • Deserialization surface: Any call to unserialize(...) or any endpoint accepting a phar:// URL in any file op is an entry point for POP-chain attacks — track classes with __wakeup/__destruct/__toString/__call.

    PHP note on "trusted" values: nothing from the client is trusted. $_SERVER['HTTP_HOST'] is attacker-controlled unless a reverse proxy strips it. $_SERVER['SERVER_NAME'] depends on UseCanonicalName in Apache. When in doubt, mark as tainted.

For Each Entry Point, Record

  1. Function name and line number
  2. Data source: network / file / IPC / user / hardware / indirect
  3. Data type: raw bytes / string / struct / integer / mixed
  4. Size: fixed / bounded (by what?) / unbounded / unknown
  5. Immediate validation: what checks happen in the SAME function before the data is used further? Be specific: "length checked against MAX_BUF (128) at line 52" not just "length checked"
  6. Where it goes: what functions/operations receive this data next?

Output

Write to sast-work/<file_hash>-entries.json:

json
{
  "file": "src/net/tcp_input.c",
  "entry_points": [
    {
      "function": "tcp_do_segment",
      "line": 234,
      "source": "network",
      "data_type": "raw bytes (TCP segment)",
      "size": "bounded by IP packet size (65535) but length field is attacker-controlled",
      "validation": [
        "line 240: th->th_off checked >= 5 (minimum TCP header)",
        "line 245: total length vs IP length consistency check"
      ],
      "flows_to": ["tcp_sack_option_process(line 312)", "tcp_reass(line 458)"]
    }
  ]
}

Rules

  • Only record what you can see in the code. Do not speculate about what callers might pass.
  • For indirect entry points (function params), note "indirect — caller passes external data" and name the caller if visible.
  • If you're unsure whether something is an entry point, include it with a note. False positives are cheap; missed entries are expensive.
  • Do NOT analyze whether anything is vulnerable. That's not your job. Just map the entries.

Brain Integration

Check brain for prior analysis of this file. Skip if already mapped and file unchanged.

Top-Tier Operator Standard

Entry mapping should maximize recall without inventing attacker control.

  • Classify entries by trust source: HTTP, CLI, file, archive, parser callback, network packet, env var, database row, queue message, webhook, plugin, template, test harness, or public API.
  • Record the path from external input to function parameter when visible.
  • Mark privilege and preconditions: auth required, admin only, local-only, feature flag, config option, or test-only.
  • Include indirect entries with caller evidence; exclude pure internal helpers unless a caller imports external data.
  • Do not assess vulnerability. Your output is the source inventory for flow tracing.

Frequently asked questions

What does the Sast Entry Mapper AI skill do?

Maps entry points where untrusted data enters a source file. Lists every function that receives external input with data type, size constraints, and initial validation. Use via /sast command.

Why use Sast Entry Mapper on TypingMind?

Because you install it once and use it with any model. Sast Entry Mapper 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 Sast Entry Mapper 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-sast-entry-mapper. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Sast Entry Mapper?

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 Sast Entry Mapper?

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

Is the Sast Entry Mapper 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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