Introducing AIMap: Security Testing For AI Agent Infrastructure

2026-04-30 · Source: Bishop Fox - Bishopfox.com · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy · Depth: Intermediate, medium

Summary

AIMap is an open-source security testing tool developed by Bishop Fox, designed to discover, analyze, and test exposed AI agent infrastructure across the internet. It identifies publicly accessible AI endpoints, including MCP servers, Ollama instances, vLLM/LiteLLM proxies, LangServe chains, Gradio apps, and ComfyUI nodes, by querying Shodan and probing with Nuclei templates. The tool fingerprints these systems for protocol, framework, authentication status, tools, models, and system prompts. Each endpoint receives a risk score from 0 to 10 based on factors like authentication posture, tool exposure, CORS policy, and system prompt leakage, with scores above 7 indicating exploitable combinations. AIMap also offers protocol-specific attack testing capabilities for authorized engagements, such as tool enumeration for MCP servers and model weight extraction for Ollama instances. It provides a searchable interface and a 3D globe visualization for threat hunting, executive reporting, and incident response.

Key takeaway

For MLOps Engineers or AI Architects concerned about external attack surface, you should deploy AIMap to gain critical visibility into your internet-exposed AI agent infrastructure. This tool allows you to proactively identify unauthenticated access, tool abuse, and prompt leakage, mirroring an attacker's perspective. Use its risk scoring and targeted attack testing to prioritize and remediate vulnerabilities before they are exploited, ensuring compliance and reducing your organization's real-world AI security risks.

Key insights

AIMap closes the AI agent infrastructure visibility gap, enabling organizations to discover and test their exposed systems like attackers.

Principles

• Attackers already have AI system visibility.
• AI infrastructure security tooling lags.
• Risk scores combine vulnerability factors.

Method

AIMap queries Shodan for AI/ML endpoints, probes them with Nuclei templates, fingerprints details, assigns a 0-10 risk score, and runs protocol-specific attack suites.

In practice

• Deploy AIMap locally with Docker Compose.
• Configure with a Shodan API key.
• Test MCP, Ollama, OpenAI endpoints.

Topics

• AI Security Testing
• AI Agent Infrastructure
• Attack Surface Management
• Open-Source Tools
• Prompt Injection
• Vulnerability Scoring
• Shodan API

Code references

• BishopFox/aimap

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Security Engineer, MLOps Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by Bishop Fox - Bishopfox.com.