Red Team TL;DR

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What is Red Team TL;DR?

red-tldr is a lightweight red team command lookup tool. It helps experienced red team operators quickly find the commands, techniques, and key points they need — like a man command built for offensive security.

Starting from v0.5.0, red-tldr also ships with a built-in MCP server, so AI assistants like Claude Desktop and Cursor can query your red team knowledge base directly.

Why Red Team TL;DR?

In daily red team work, you need to memorize hundreds of commands — and usually you only remember the first few characters. Searching through documentation or search engines is slow and noisy. red-tldr gives you instant, offline, deterministic answers from a curated database you control.

Features

• Full-text search — Bleve-powered BM25 search with weighted scoring (name×5, tags×3, data×1) and fuzzy matching
• Multi-format output — text (colored terminal), json, markdown
• MCP Server — Built-in Model Context Protocol server for AI assistant integration (stdio + Streamable HTTP)
• MITRE ATT&CK mapping — Entries can be tagged with tactics and techniques
• Enhanced data model — category, platforms, mitre_attack, metadata (author/source/confidence), related entries
• Backward compatible — Works with existing YAML databases, new fields are optional
• Offline-first — No cloud dependencies, no API keys, fully deterministic
• Secure — Zip-slip vulnerability fixed, path validation on all archive operations

Quick Start

Install

macOS

$ brew install red-tldr

Arch Linux

# AUR: https://aur.archlinux.org/packages/red-tldr
$ sudo pacman -S red-tldr

From Source

$ git clone https://github.com/Rvn0xsy/red-tldr
$ cd red-tldr
$ go build

Binary

Download from Releases.

$ tar -zxvf red-tldr_latest_linux_amd64.tar.gz
$ ./red-tldr

It is recommended to add red-tldr to your PATH.

Usage

Search

# Keyword search
$ red-tldr mimikatz

# Fuzzy matching — type a few characters
$ red-tldr mi

When multiple results are found, select by number:

Output Formats

# JSON output
$ red-tldr mimikatz -f json

# Markdown output
$ red-tldr mimikatz -f markdown

Update & Upgrade

# Rebuild local index (JSON + Bleve)
$ red-tldr update

# Download latest database from GitHub
$ red-tldr upgrade

MCP Server

red-tldr includes a built-in MCP server that exposes your red team knowledge base to AI assistants.

Tools

Tool	Description
search_redteam_commands	Search commands by keyword, platform, category, tactic, or technique
get_command_details	Get full details of a specific command entry
list_techniques	List available MITRE ATT&CK techniques in the database

stdio Mode (Claude Desktop / Cursor)

$ red-tldr serve

Add to your Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "red-tldr": {
      "command": "red-tldr",
      "args": ["serve"]
    }
  }
}

Streamable HTTP Mode

$ red-tldr serve --http --addr localhost:8080 --endpoint /mcp

Configuration

Default config path: ~/.red-tldr/config.toml

[red-tldr]
  index-update = false
  github-update = false
  path = ""
  color = true

Item	Description	Type
index-update	Auto-rebuild index on search	Bool
github-update	Auto-download database from GitHub	Bool
path	Database storage path	String
color	Colored terminal output	Bool

Data Model

Each entry is a YAML file in the red-tldr-db repository. The enhanced format (v0.5.0+) supports additional fields while remaining backward compatible:

name: mimikatz-sekurlsa
tags:
  - mimikatz
  - credentials
  - lsass
data: |
  # Mimikatz Sekurlsa

privilege::debug sekurlsa::logonpasswords

category: credential-access
platforms:
- windows
mitre_attack:
tactics:
  - credential-access
techniques:
  - T1003.001
metadata:
author: Rvn0xsy
confidence: high
related:
- mimikatz-dpapi

All new fields (category, platforms, mitre_attack, metadata, related) are optional — existing YAML files work without modification.

Contributing

We welcome contributions!

• Report bugs via Issues.
• Submit bug fixes as Pull Requests to the dev branch.
• For new features, create an issue first to discuss the approach before submitting a PR.
• Documentation improvements are always welcome.
• Contact: rvn0xsy@gmail.com

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