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AAPP-MART

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AAPP‑MART | AI‑Autonomous Attack Path Prediction & Multi‑Agent Red Team Simulation Engine is an open‑source Python security engine designed for offensive security research, adversarial modeling, and automated risk assessment. It combines AI‑powered attack‑path prediction with autonomous multi‑agent red‑team simulation to model how real attackers navigate an environment and to reveal actionable, data‑driven security insights.

Unlike traditional static vulnerability scanners or manual penetration testing, AAPP‑MART uses predictive analytics, graph‑based threat modeling, and autonomous adversarial behavior to deliver continuous and realistic security evaluation. Its architecture helps defenders anticipate attack strategies, validate defensive controls, and understand real‑world risk through repeatable, scalable, and intelligence‑driven simulations.

The system generates structured attack-path reports, MITRE ATT&CK-mapped insights, and risk scoring outputs to support SOC operations, detection engineering, and continuous security improvement.

Overview

Modern infrastructures are too dynamic and interconnected for traditional security testing to keep pace. Static scanners and predefined BAS playbooks often fail to capture how real attackers move across complex environments.

AAPP‑MART addresses this gap by combining predictive AI, AI-driven threat modeling, cyber attack surface prediction, and autonomous adversarial simulation to evaluate an environment’s real exposure. The engine models attacker behavior, forecasts potential attack paths, and simulates multi-agent adversarial activity to provide proactive, intelligence-driven insights into organizational security posture.

What is AAPP-MART?

AAPP-MART simulates real-world cyber attacks using autonomous agents that mimic adversarial behavior across complex environments. By combining machine learning-based attack path prediction with multi-agent orchestration, the system provides deep visibility into how attackers can move laterally, escalate privileges, and compromise critical assets.

Why It Matters

Modern infrastructures are too complex for manual security validation. Traditional tools fail to model dynamic attacker behavior.

AAPP-MART enables:

• Continuous security validation
• Automated red teaming
• AI-driven threat modeling
• Proactive risk discovery

Key Use Cases

1. Red Team Automation

Simulate advanced persistent threats (APT) without manual intervention.

2. Attack Path Discovery

Identify hidden attack chains across systems, identities, and networks.

3. Security Posture Validation

Continuously evaluate how resilient your environment is against evolving threats.

4. Cyber Range & Training

Create realistic adversarial scenarios for training security teams.

How It Works

AAPP-MART operates through a multi-layer architecture:

1. Data Ingestion Layer

   • Collects system, network, and identity data

2. Attack Graph Engine

   • Builds dynamic attack paths

3. AI Prediction Engine

   • Uses ML models to predict likely attacker movements

4. Multi-Agent Simulation Layer

   • Autonomous agents simulate attacker strategies

5. Risk Scoring Engine

   • Evaluates impact and likelihood of attack paths

Core Features

• AI-based attack path prediction
• Multi-agent adversarial simulation
• MITRE ATT&CK mapping
• Risk scoring and reporting
• Modular and extensible architecture

Architecture Overview

AAPP-MART consists of the following core components:

• Orchestrator Agent
• Attacker Agents
• Defender Agents
• Prediction Engine
• Risk Engine

These components interact in a feedback loop to continuously refine attack strategies and risk assessments.

Example Output

• Ranked attack paths
• Risk scores (likelihood × impact)
• MITRE ATT&CK technique mapping
• Recommended mitigations

Quick Start

See the full setup guide:

• docs/installation.md
• docs/quickstart.md

Target Users

• CISOs, InfoSec managers, and executive stakeholders seeking actionable security intelligence
• Security, engineering, and risk teams aiming to proactively assess and improve cyber resilience
• Internal/External red, blue, and purple teams requiring realistic, repeatable adversary emulation
• Organizations subject to regulatory or compliance mandates (MITRE ATT&CK, NIST, CIS, PCI DSS, ISO 27001, etc.)

Documentation

• Research Foundations
• System Components
• API Reference
• Threat Modeling
• Risk Model
• Benchmarking

Security & Responsible Usage

AAPP-MART is intended strictly for authorized security testing and research purposes. Unauthorized use is prohibited.

Roadmap

• Enhanced agent intelligence
• Reinforcement learning integration
• Real-time attack simulation
• Cloud-native deployment

Contributing

See CONTRIBUTING.md for detailed contribution guidelines.

License

Copyright © 2026 secwexen.

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