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align=\"center\"\u003e\u003cimg src=\"docs/logo/aappmart_logo.png\" width=\"300\" alt=\"AAPP-MART Logo\"\u003e\u003c/p\u003e\n\n![Build](https://img.shields.io/github/actions/workflow/status/secwexen/aappmart/build.yml?label=Build)\n![Lint](https://img.shields.io/github/actions/workflow/status/secwexen/aappmart/lint.yml?label=Lint)\n![CodeQL](https://img.shields.io/github/actions/workflow/status/secwexen/aappmart/codeql.yml?label=CodeQL)\n![Coverage](https://img.shields.io/codecov/c/github/secwexen/aappmart)\n![Release](https://img.shields.io/github/v/release/secwexen/aappmart)\n![Python Versions](https://img.shields.io/pypi/pyversions/aappmart)\n![License](https://img.shields.io/github/license/secwexen/aappmart)\n[![Website](https://img.shields.io/website?url=https://secwexen.github.io/aappmart/)](https://secwexen.github.io/aappmart/)\n\n*An autonomous intelligence engine that thinks like an attacker to protect defenders.*\n\n### Autonomous Attack Path Prediction \u0026 Multi-Agent Red Team Engine\n\nAAPP-MART is an autonomous offensive security engine designed for security teams and researchers.\nIt predicts attack paths using artificial intelligence and simulates them with a multi-agent red team,\nhelping organizations identify and mitigate risks before they are exploited.  \n\n---\n\n## Overview\n\nModern infrastructures are too complex for traditional security testing. AAPP-MART combines predictive AI with autonomous adversarial simulation to continuously evaluate an environment’s real attack surface.\n\nThe system operates in two major components:\n\n- **AAPP (AI Attack Path Predictor)**  \n  Predicts the most likely attack paths by analyzing services, permissions, vulnerabilities, and configuration weaknesses.\n\n- **MART (Multi-Agent Red Team)**  \n  Executes autonomous red team simulations using specialized AI agents that emulate real attacker behavior.\n\nTogether, they create a fully automated offensive security engine capable of forecasting and simulating attacks end-to-end.\n\n---\n\n## Key Features\n\n### AI Attack Path Prediction (AAPP)\n- Builds attack graphs from system data  \n- Identifies multi-step exploit chains  \n- Scores risk and exploitability  \n- Predicts attacker movement before it happens  \n\n### Multi-Agent Red Team (MART)\n- Reconnaissance agent  \n- Exploitation agent  \n- Privilege escalation agent  \n- Lateral movement agent  \n- Persistence agent  \n- Reporting agent  \n\nAgents collaborate and make decisions autonomously, simulating realistic adversary behavior.\n\n### Autonomous Simulation Brain\n- Merges prediction and execution  \n- Runs attack scenarios mentally before performing them  \n- Generates detailed reports and mitigation recommendations  \n\n---\n\n## Architecture\n\n```\nAAPP (Prediction Engine)\n    ↓\nPredicted Attack Paths\n    ↓\nMART (Multi-Agent Red Team)\n    ↓\nAutonomous Simulation\n    ↓\nFinal Report \u0026 Defense Recommendations\n```\n\n---\n\n## Directory Structure\n\n```\naappmart/\n│\n├── aapp/                  # Attack Path Predictor\n├── mart/                  # Multi-Agent Red Team\n├── core/                  # Autonomous simulation brain\n├── api/                   # Optional REST API\n├── cli/                   # Command-line interface\n├── data/                  # Sample data \u0026 signatures\n├── reports/               # Generated reports\n├── docs/                  # Documentation\n├── tests/                 # Unit tests\n├── scripts/               # Helper scripts\n├── requirements.txt\n├── setup.py\n└── README.md\n```\n\n---\n\n## Installation\n\n```bash\ngit clone https://github.com/secwexen/aappmart\ncd aappmart\n\n# (Optional but recommended) Create a virtual environment\npython -m venv venv\nsource venv/bin/activate  # Linux/macOS\nvenv\\Scripts\\activate     # Windows\n\npip install -r requirements.txt\n```\n\n\u003e ⚠️ Note: Core implementation is still in progress. Some modules may not be functional yet.\n\n---\n\n## Quick Start\n\n```python\nfrom aappmart.core.orchestrator import AAPP_MART\n\nengine = AAPP_MART(target=\"192.168.1.10\")\nengine.run()\n\nreport = engine.get_report()\nprint(report)\n```\n\n\u003e ⚠️ Note: Core implementation is still in progress.  \n\u003e Some modules may not be fully functional yet.  \n\u003e This example is for demonstration purposes and to help you get started.  \n\n---\n\n## Testing\n\nRun unit tests with:\n\n```bash\npytest\n```\n\n---\n\n## Use Cases\n\n- Automated red teaming  \n- Continuous security validation  \n- Attack surface mapping  \n- Zero-day exposure modeling  \n- SOC augmentation  \n- Pre-breach risk forecasting  \n\n---\n\n## Acronym Breakdown\n\n**AAPP** → AI Attack Path Predictor  \n**MART** → Multi-Agent Red Team  \n\n**AAPP-MART** = The fusion of prediction and simulation into a single autonomous attack intelligence engine.\n\n---\n\n## License\n\nThis project is licensed under the Apache License, Version 2.0.  \nSee the `LICENSE` file for full details.  \n\n---\n\n## Contributing\n\nContributions are welcome.  \nPlease open an issue before submitting major changes or new features.  \nSee `CONTRIBUTING.md` for detailed contribution guidelines.  \n\n---\n\n## Roadmap\n\n- [ ] Graph-based attack path visualizer\n- [ ] Cloud environment support\n- [ ] Agent marketplace\n- [ ] Reinforcement learning–based decision engine\n\n---\n\n## Development Status\n\n⚠️ Early-stage open source project. Core implementation is still in progress.  \nThis repository provides the project structure and foundational components of the AAPP-MART engine.  \nAdditional advanced modules and controlled security-testing features will be added progressively.  \n\n---\n\n## Ethical Use Statement\n\nAAPP-MART is designed to help organizations understand and reduce their attack surface\nby simulating adversarial behavior in a controlled and authorized manner.\nIts primary goal is to improve defensive posture, not to facilitate real-world attacks.\n\n---\n\n## Disclaimer\n\nAAPP-MART is intended exclusively for ethical, legal, and authorized security research,\npenetration testing, and defensive security validation.\n\nThe use of this tool against systems, networks, or applications without explicit\nauthorization from the system owner is strictly prohibited and may be illegal.\n\nThe authors and contributors of this project assume no responsibility or liability\nfor any misuse, damage, or legal consequences resulting from the use of this software.\nUsers are solely responsible for ensuring compliance with all applicable laws,\nregulations, and organizational policies.\n\n---\n\n## Security\n\nFor responsible disclosure and reporting security issues, please see `SECURITY.md`.  \n\n---\n\n## Author\n\n**Secwexen**  \nGitHub: [secwexen](https://github.com/secwexen)  \n","funding_links":["https://github.com/sponsors/secwexen"],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsecwexen%2Faappmart","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsecwexen%2Faappmart","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsecwexen%2Faappmart/lists"}