aapp-mart - AAPP-MART is a cybersecurity engine featuring AI-p

项目说明

AAPP-MART

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About

AAPP‑MART (AI‑Powered Autonomous Attack Path Prediction & Multi‑Agent Red Team Simulation Engine) is a cybersecurity engine for ad emulation, security , threat modeling, and risk assessment.

Unlike traditional static manual penetration testing, AAPP‑MART uses predicti, graph‑based threat modeling, and autonomous ad behavior to deli and realistic security e. Its architecture helps defenders anticipate attack strategies, execute defensi , and enhance cyber resilience through repeatable, scalable, and intelligence‑dri.

AAPP-MART is designed as an extensible cybersecurity engine rather than a traditional scanner or a collection of predefined attack playbooks, pro a foundation for proacti , red teaming, purple teaming, security research, and enterprise security operations.

Why AAPP-MART?

AAPP-MART combines AI-powered attack path prediction, multi-agent red team simulation, attack graph analysis, and risk-based security assessment in a single cybersecurity engine. Instead of treating and security findings as isolated events, AAPP-MART analyzes how weaknesses, assets, identities, network relationships, and ad techniques can combine to form realistic attack paths.

Its AAPP (AI-Powered Autonomous Attack Path Prediction) capability identifies and prioritizes potential attack paths using predicti, graph-based analysis, security-state information, and deterministic security rules. MART (Multi-Agent Red Team Simulation) then provides a controlled en for modeling ad behavior across reconnaissance, initial access, pri escalation, lateral mo, persistence, and other MITRE ATT&CK-aligned acti.

AAPP-MART provides structured, repeatable, and actionable security intelligence that helps security teams understand not only where exist, but how those could contribute to a broader attack scenario.

Use Cases

How it Works

1. AI-Powered Autonomous Attack Path Prediction (AAPP)

E assets, configurations, permissions, and to predict probable attacker paths.

2. Multi-Agent Red Team Simulation (MART)

Autonomous agents simulate realistic ad actions:

3. Core Orchestration (ENGINE)

Coordinates AAPP & MART, maintains a global knowledge graph, executes simulations, and produces structured risk reports.

Legal & Authorized Use

AAPP-MART is intended solely for offensi, ad emulation, security , threat modeling, and risk assessment within en where explicit permission has been granted.

Users are fully responsible for ensuring compliance with all applicable laws, regulations, and organizational policies when operating this system.

Unauthorized use of this system is strictly prohibited and may applicable laws and regulations.

See Ethics & Responsible Use Guidelines for details.

Who is this for

Features

For full details, refer to the Features file.

Demo

Usage

Output

> [!WARNING]
> This IP/hostname is an example target used for demonstration purposes only.

Installation

Supported Operating Systems

Requirements

Optional Components

Quick Start

Clone & Setup

After installation, the CLI:

2. Run Tests

For full details, refer to the Quick Start file.

Documentation

License

Copyright © 2026 secwexen.

This project is licensed under the Apache-2.0 License.
See the LICENSE file for full details.

Contributing

Contributions and suggestions are welcome!

Please open an issue before submitting major changes or new features.

See CONTRIBUTING for detailed contribution guidelines.

Roadmap

Planned impro include:

For the full roadmap and upcoming features, see Roadmap.

Community & Support

Security

If you discover a security , please follow our responsible disclosure process.

See SECURITY for instructions on reporting issues securely.

项目信息

开发语言：Python

Star 数：9

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AAPP-MART is a cybersecurity engine featuring AI-powered autonomous attack path prediction and multi-agent red team simulation. These features include adversary emulation, attack path analysis, threat modeling, security validation, risk assessment, and MITRE ATT&CK alignment.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。