AI Agent Attack Path Discovery — AWS architecture diagram

About This Architecture

AI-driven attack path discovery system leveraging Claude and Cursor LLM agents with AWS MCP Server integration to identify critical vulnerabilities across AWS infrastructure. The architecture connects multiple data sources—AWS Secrets Manager, GitHub repositories, and filesystem endpoints—through Model Context Protocol servers that feed attack graph data into Amazon Neptune for comprehensive threat visualization. Claude Code and Cursor agents query the attack graph via Graph API Gateway while maintaining least-privilege IAM roles and secrets.read permissions to simulate real-world privilege escalation scenarios. This pattern enables security teams to proactively discover multi-step attack chains before adversaries exploit them, combining LLM reasoning with AWS native services for continuous threat intelligence. Fork and customize this diagram on Diagrams.so to model your own AWS account topology and IAM permission boundaries.

People also ask

How can I use AI agents and graph databases to automatically discover attack paths and privilege escalation vulnerabilities in my AWS infrastructure?

This diagram shows how Claude Code and Cursor LLM agents integrate with AWS MCP Server, GitHub MCP Server, and filesystem MCP Server to feed attack surface data into Amazon Neptune. The graph database visualizes multi-step attack chains by analyzing IAM roles, secrets permissions, and repository access, enabling security teams to detect privilege escalation paths before exploitation.

AI Agent Attack Path Discovery

AWSadvancedsecuritythreat-modelingattack-path-analysisLLM-agentsNeptune
Domain: SecurityAudience: Security architects and cloud security engineers performing threat modeling and attack path analysis on AWS infrastructu
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Created by

August 14, 2026

Updated

August 16, 2026 at 2:21 AM

Type

architecture

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