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Open to AI security standards & enablement roles

Andrew Dannenberger

AI Security Standards & Enablement

Securing the space between AI capability and real-world action.

I help organizations adopt AI safely by translating LLM, agentic AI, MCP, and RAG risks into practical security guidance, benchmarks, tools, and enablement programs.

profile — zsh
$ whoami andrew-dannenberger $ cat profile.json { "focus": "AI Security Standards & Enablement", "standards": "Principal Co-author, CIS v8.1 MCP Guide", "specialties": ["MCP", "CIS Controls", "Agentic AI"], "based": "Chicago Area / Remote", "currently": "Building a CIS MCP Benchmark" }
Highlights
Principal Co-author CIS Controls v8.1 MCP Companion Guide
Collaborator CIS Controls v8.1 AI/LLM Companion Guide
Collaborator CIS Controls v8.1 AI Agents Companion Guide
CIS Webinar From Prompts to Protocols: The Security Blueprint for Enterprise AI
Upcoming TopCyberPro Podcast
How AI Systems Work

The AI Action Pipeline

Modern AI systems move from model inference through agentic reasoning, MCP tool calls, and data retrieval — gated by human review — before taking real-world action. Understanding this flow is the foundation of AI security.

AI System Flow
Model Context Protocol
Human control gate
MCP Protocol boundary
Action output
Note — This diagram is a simplified educational overview of how AI, agents, and MCP interact. Real deployments vary significantly.
Point of View

How I Think About AI Security

A few convictions that shape how I approach standards, tools, and enablement.

Controls beat principles

Principles tell teams what to care about; controls tell them what to configure, check, and audit. Risk only drops when guidance gets specific enough to act on — which is why I work in benchmarks and control mappings, not abstractions.

Most AI failures happen at a boundary

Prompt injection, confused-deputy access, over-scoped tools — the dangerous failures live at the seams between instruction and data, model and tool, agent and action. Securing those boundaries matters more than hardening the model alone.

Enablement is a security strategy

The fastest way to create shadow AI is to make the safe path the hard path. Giving people usable, well-governed ways to adopt AI prevents more real-world risk than a strict policy that quietly gets ignored.

Human approval is a control, not a speed bump

Human-in-the-loop is most valuable exactly when an agent can take an action it cannot take back. Designed deliberately, it is a control point worth keeping — not friction to engineer away.

Expertise

What I Work On

Bridging the gap between AI capability and responsible adoption — through standards, benchmarks, and practical enablement.

AI Security Standards

CIS Controls, CIS Benchmarks, AI Companion Guides, MCP Benchmark work, and practical control mapping for emerging AI systems.

MCP & Agentic AI Security

Tool governance, least privilege, prompt and resource exposure, approval flows, confused deputy risk, and auditability across MCP ecosystems.

Secure AI Enablement

AI Office Hours, leadership briefings, customer education, practical adoption guidance, and security-aware AI workflows for all skill levels.

Applied AI Systems

Chatbots, RAG, knowledge systems, SecureSuite Platform MCP concepts, and secure AI implementation patterns.

Published Work

Selected Work

Standards authorship, benchmarks leadership, and enablement programs.

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Published Principal Co-Author

CIS Controls v8.1 MCP Companion Guide

Center for Internet Security · April 2026

Translated MCP-specific risks — tool invocation, authorization, confused-deputy patterns, and third-party server governance — into practical CIS Controls-aligned guidance across all 18 Controls.

MCP Security CIS Controls Authorship
Ongoing Lead

CIS AI Benchmarks Community

Center for Internet Security · Ongoing

Leading community work to advance practical guidance for emerging AI technologies, including scope definition, coordination, feedback cycles, and publication strategy.

CIS Benchmarks Standards Community
Ongoing Lead

AI Office Hours & Enablement Programs

Center for Internet Security · Ongoing

Designed and leads AI enablement sessions for beginner and advanced users, turning complex AI security topics into practical workflows and adoption guidance.

Enablement Training Adoption

Open to AI security standards and enablement roles

Interested in conversations about AI security advisory, standards authorship, enablement leadership, and organizations building serious AI security programs.