cyber-toolbox - Python-based cybersecurity learning toolkit for de

项目说明

🧰 Mythos Lab Cyber Toolbox

Python-based cybersecurity learning toolkit for defensi, lab practice,
and automation — now with an integrated AI Security Assistant.

Features

Password strength checker

Hash generator (MD5 / SHA1 / SHA256 / SHA512)

Teach Mode – guided explanations for each tool

Expert Mode – direct access to built-in tools with AI-powered guidance for external security tools

AI Security Assistant – explanations, tool walkthroughs,

threat analysis, tool recommendations, and an NLP chat interface
Ad AI-powered cybersecurity platform for security professionals and learners.
Integrates Claude (Anthropic) and OpenAI GPT with a comprehensi of security tools.

Features

| Module | Description |
|---|---|
| 🔐 Password Checker | Strength analysis with detailed feedback |
| #️⃣ Hash Generator | MD5, SHA-1, SHA-256, SHA-512 |
| 🌐 Network Tools | Port scanner, Nmap integration, subnet helper |
| 📡 Wireless Tools | Aircrack-ng suite, monitor mode, packet capture |
| 📱 Mobile Tools | Android APK analysis, ADB, Frida integration |
| 📋 Log Analysis | Detect brute-force, SQLi, XSS, path tra |
| 📄 Report Generator | Markdown, HTML, JSON security reports |
| 🤖 AI Assistant | Claude + OpenAI chat, teach mode, topic explainer |
| 🔮 Mythos Integration | Anthropic Claude SDK — streaming, tool-use, multi-turn chat |
| 🌐 Web Interface | Mobile-accessible browser UI (Flask) |

Quick Start

Run (interactive menu)

AI Features (command-line)

Explain a

Explain a tool's output

Step-by-step walkthrough

Recommend tools for a goal

Threat / log analysis

NLP chat interface

OpenAI Integration (optional)

To enable li responses, install the optional openai Python package
and set the OPENAI_API_KEY en .
Without the package or API key, the toolbox uses its built-in knowledge base and
works fully offline.

> Privacy note: When OPENAI_API_KEY is set, queries are sent to the OpenAI API.
> For sensitive data (e.g. log files), use the --no-openai flag to force offline analysis:
>

Tools Covered by the AI Assistant

All tools listed below ha offline explanations. When OPENAI_API_KEY is set,
any tool or can be queried even if not listed here.

| Category | Tools (built-in offline guidance) |
|---|---|
| Network | Nmap, Wireshark, Snort, Suricata |
| Wireless | airmon-ng, airodump-ng, aireplay-ng, aircrack-ng |
| Exploitation | Metasploit, SQLMap |
| Credentials | Hydra, John the Ripper, Hashcat |
| Defensive | OpenVAS, Lynis, OSSEC, iptables/ufw (via tool recommendations) |
| Forensics | , Autopsy, ClamA (via tool recommendations) |

CLI Usage

Mythos Integration (Anthropic Claude SDK)

The Mythos Integration module (modules/mythos.py) provides a dedicated interface to
Anthropic's Python SDK with cybersecurity-focused helpers:

Installation

Features

| Feature | Description |
|---|---|
| Streaming responses | Li output via stream_query() |
| Tool-use / structured output | Structured JSON findings via tool_assisted_scan() |
| Multi-turn chat | Persistent con history via multi_turn_chat() |

Quick Example

Via the Interactive Menu

AI Integration

The AI agent works with or without API keys:

With Claude / Mythos: Set ANTHROPIC_API_KEY + pip install anthropic>=0.40.0

With OpenAI: Set OPENAI_API_KEY + pip install openai

Offline: Built-in responses for common security topics

Web Interface

Start the mobile-accessible web server:

Features: password checker, hash generator, AI chat, tool tutorials.

External Tools (Optional)

Purpose

Built for cybersecurity learning and authorized security testing only.
See USAGE_GUIDE.txt for full documentation.

Disclaimer

Use this toolkit only on systems you own or are explicitly authorized to test.
Always comply with applicable laws and regulations.

项目信息

开发语言：Python

Star 数：1

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Python-based cybersecurity learning toolkit for defensive security, lab practice, and automation.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。