# CFF Explorer

> Use this tool when you need to analyze PE files and perform reverse engineering or malware analysis tasks on Windows. It solves problems related to PE header analysis, import/export inspection, and resource extraction by generating temporary Lua scripts and parsing structured results. The CFF Explorer tool takes PE files as input and outputs detailed analysis results, making it ideal for use cases involving Windows executable file examination and manipulation.

Canonical page: https://skillsregistry.net/skills/sutharmeet-cff-explorer  
JSON: https://api.skillsregistry.net/v1/skills/sutharmeet-cff-explorer

## Description

Bridges CFF Explorer's Lua scripting engine to enable natural language PE file analysis. Generates temporary Lua scripts, launches CFF Explorer headlessly, and parses structured results. Supports PE header analysis, import/export inspection, resource extraction, NOP patching, and conditional jump inversion for reverse engineering and malware analysis workflows on Windows.

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/sutharmeet-cff-explorer)
- **Repository:** <https://github.com/sutharmeet/cff-explorer-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "sutharmeet-cff-explorer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sutharmeet-cff-explorer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sutharmeet-cff-explorer/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt