mietos - Local-first security operator for authorized labs,

项目说明

mietos

Mietos is a local-first desktop operator for authorized cybersecurity labs, internal audits, OSINT triage, and defensi workflows.

It pairs a lightweight Rust/egui interface with a local OpenAI-compatible model endpoint and a Kali WSL command runner. The goal is not to make a large local model magically omniscient. The goal is to keep the model on a tight e loop: structured challenge intake, bounded tool execution, compact context, RAG memory, workflow lessons, and clear answer/finding cards.

Intended Use

Use mietos only for systems you own, labs you are enrolled in, internal company audits you are explicitly authorized to perform, or defensi of data you are allowed to inspect.

Do not use it to scan, exploit, brute force, persist on, disrupt, or exfiltrate from third-party systems without written authorization. The operator can run intrusi when configured by the user, so scope and consent are part of the workflow, not paperwork after the fact.

What It Does

Requirements

Quick Start

Start your model ser, then configure the endpoint in the Setup page.

Default endpoint:

Default model name:

For local llama.cpp, any OpenAI-compatible /v1/chat/completions server is fine. For Ollama, use a compatible endpoint or proxy that exposes chat completions.

Basic Flow

1. Open Setup and confirm the model endpoint, model name, and Kali distro.
2. Use Check Kali to core tools.
3. Paste the authorized target, task text, and notes in Challenge.
4. Choose a bounded workflow such as Web Assessment, SIEM In, OSINT Domain, or Smart Full Run.
5. Watch Operator for li output and model trace.
6. Open Results for answer cards, flags, findings, and e.
7. Sa lessons or documents to Memory when they should help future runs.

TryHackMe And Lab Flow

Normal personal TryHackMe accounts usually do not have an API key. Paste the room/task text manually.

When using a from Windows inside Kali WSL, use a WSL path, for example:

Use this notes pattern:

Safety Model

Mietos is dual-use software. It is designed for authorized work and local labs.

Default public documentation treats the app as an operator assistant, not a permission slip. The app can execute commands as root inside Kali WSL because many lab tools require it. That also means the user is responsible for the target scope, network impact, and legal authority.

Recommended release posture:

Memory And Data

Mietos stores memory in a local SQLite database. On Windows, the default path is under %LOCALAPPDATA%\mietos\operator_memory.sqlite3.

The repository ignores local databases, runtime state, generated e, and build outputs. Treat terminal output, flags, credentials, scan results, and customer notes as sensitive.

De

Before opening a pull request or publishing a release:

Documentation

UI Previews

These are sanitized mock screenshots for documentation only, not real target
e or captures from an assessment.

!Mock UI preview of the Setup page
!Mock UI preview of the Challenge page
!Mock UI preview of the Operator page
!Mock UI preview of the Results page
!Mock UI preview of the OSINT page

CI And Release Builds

GitHub Actions runs Rust formatting, tests, and a release build on pushes and pull requests. A separate manual Windows release workflow builds mietos.exe, zips it, and uploads the zip as a workflow artifact.

Release artifacts should contain only the built executable. Do not publish local memory databases, runtime state, scan logs, captures, credentials, flags, customer notes, or other in e.

See docs/ci.md for the workflow details and local preflight commands.

Project Name

The project name is mietos.

Suggested GitHub repository name:

Suggested tagline:

Current Status

This is early software. It is useful as a local lab and audit assistant, but it is not a replacement for a professional tester, analyst, or incident responder. Local models can miss obvious paths, hallucinate, or choose weak next steps. The app is built to make that through e, traces, bounded commands, and repeatable workflows.

License

MIT. See LICENSE.

项目信息

开发语言：Rust

Star 数：2

技术要点

该项目属于防护思路方向的开源资源，代码结构清晰，适合安全研究人员学习参考。项目围绕Local-first security operator for authorized labs, audits, OSINT, and defensive investigations.展开，提供了可运行的实现，对理解相关安全机制、工具原理与攻防技术具有较高的研究价值。

从技术实现角度看，此类项目的核心在于对底层原理的深入理解与工程化落地。开发者在研究过程中可以结合官方文档与社区讨论，梳理项目的初始化流程、核心模块职责与数据流转，逐步掌握其中的技术细节与设计思路。

使用与学习建议

1. 下载源码压缩包，解压到本地环境。

2. 根据项目类型准备对应的运行环境与依赖。

3. 按照 README 中的步骤完成配置与部署。

4. 在隔离的测试环境中运行验证，避免影响生产系统。

免责声明

本资源来源于开源社区，仅供安全研究、技术学习与合法授权范围内的攻防演练使用，请勿用于任何非法或侵害他人权益的用途。使用本项目产生的一切后果由使用者自行承担。