Whitepaper
The CTO's Essential Guide to Securing AI MCP Servers: Four Audits That Can't Wait
Whitepaper

The CTO's Essential Guide to Securing AI MCP Servers: Four Audits That Can't Wait

A comprehensive security framework examining four critical vulnerabilities in MCP deployments with actionable audit methodologies for CTOs.

Whitepaper
The CTO's Essential Guide to Securing AI MCP Servers: Four Audits That Can't Wait
David Rivkin Ph.D., Brian Scott Glassman Ph.D.
12 minutes
November 2025
7 pages
MCP Security AI Security Enterprise AI Security Audits Model Context Protocol Cybersecurity AI Infrastructure Security Testing Vulnerability Assessment CTO Guide

Live PDF Viewer

Whitepaper
The CTO's Essential Guide to Securing AI MCP Servers: Four Audits That Can't Wait
Author: David Rivkin Ph.D., Brian Scott Glassman Ph.D.
Reading Time: 12 minutes
Published: November 2025
Pages: 7

Details for the Article

Core Take Aways

Widespread misconfiguration audit: Network scanning for NeighborJack vulnerabilities affecting hundreds of publicly accessible AI MCP servers across 15,000+ global deployments

Retrofitted security assessment: Evaluating OAuth 2.1 implementation gaps, stdio transport credential management, and third-party library dependency risks

Type safety testing: Identifying schemaless JSON vulnerabilities causing silent data corruption in financial, healthcare, and industrial systems

Attack surface analysis: Comprehensive security testing across 20+ distinct attack vectors including supply chain, prompt injection, and cross-agent contamination

Actionable audit methodologies: Penetration testing frameworks, SBOM scanning, automated security tools, and ML-based anomaly detection protocols

Operational risk mitigation: Addressing missing observability, cost attribution failures, language implementation fragmentation, and schema versioning gaps

Executive Summary

Model Context Protocol (MCP) servers represent excellent tools for enterprise AI integration, delivering major productivity gains when implemented correctly. However, CTOs enabling AI systems to access enterprise services through MCP implementations bear critical responsibility for conducting comprehensive security audits to ensure robust security postures without introducing exploitable attack vectors. The rapid adoption of MCP, with over 15,000 servers deployed worldwide, has outpaced security maturity, creating urgent need for rigorous evaluation before production deployment.

The whitepaper examines four critical security concerns demanding immediate attention. First, Widespread Misconfiguration and Exposure reveals that research analyzing over 7,000 publicly accessible MCP servers found hundreds vulnerable to the NeighborJack exploit, with approximately 70 servers exhibiting severe compound flaws enabling complete host machine compromise. Second, Security Retrofitted as an Afterthought exposes how OAuth 2.1 support was only added in March 2025 after production adoption, leaving enterprises to retrofit critical protections and cobble together third-party libraries for missing features like distributed tracing, audit trails, and rate limiting.

Third, Schemaless JSON Without Type Safety demonstrates how the absence of enforced type validation allows data type mismatches to propagate silently through systems, creating catastrophic consequences in financial services (incorrect decimal precision), healthcare (medication dosing errors), and industrial systems (sensor reading failures). Fourth, Vast Attack Surface catalogs over 20 distinct attack vectors spanning classical threats (supply chain compromises, authentication bypass, privilege escalation), advanced threats (cross-agent contamination, confused deputy problems, context poisoning), and prompt injection attacks (role-play manipulation, multilingual exploits, automated attacks).

Each section provides actionable audit methodologies CTOs can implement immediately: network scanning for NeighborJack vulnerabilities, OAuth 2.1 verification on HTTP transports, deliberate type mismatch testing, comprehensive penetration testing with OWASP ZAP and Burp Suite, SBOM scanning, container security analysis with Prisma and Trivy, and ML-based anomaly detection for unusual query patterns. The whitepaper emphasizes that security is not a one-time achievement—teams must conduct comprehensive audits prior to initial deployment and establish processes for re-evaluation after every configuration change, software update, or integration modification to harness agentic AI power while protecting infrastructure, data, and stakeholders.

Need immediate help or want a proposal for your project? Reach out to us

Research & Insights

Whitepaper
Pages: 13
15 minutes

A Framework for Managing a Company Wide AI Program

This comprehensive framework provides executives and AI practitioners with a three-layer approach covering stakeholders, AI leadership, and portfolio management to systematically guide corporations from AI use case exploration to enterprise-wide implementation.

Go to Article
Whitepaper
Pages: 6
10 minutes

20 Tips for Implementing Effective AI Workflow Automations

By 2026, 30% of enterprises will automate more than half their network activities. This whitepaper provides 20 actionable tips across four phases—from strategic selection to continuous improvement—helping organizations deploy AI workflows safely and effectively.

Go to Article
Whitepaper
Pages: 7
8 minutes

A Smarter E-Commerce Checkout using AI

This whitepaper introduces the Glassman Architecture, a transparent AI framework that transforms e-commerce checkout into a dynamic, personalized experience. By leveraging customer behavior and historical data, retailers of all sizes can deploy an auditable system that evolves with their needs while using AI to increase revenue and reduce fraud.

Go to Article
Whitepaper
Pages: 14
15 minutes

What A CTO Must Budget For AI Coding Tools

CTOs and software development leaders need a clear view of AI coding tool costs. This analysis provides detailed per-developer budget projections ($1,500-$3,000/month), model pricing trends for Claude and GPT-5, and a methodology to forecast AI coding expenses for teams of any size.

Go to Article
Industry Insight
Pages: 4
8 minutes

How AI Is Revolutionizing Product Management

This industry insight reveals how AI is transforming product management through the ACID framework (AI Context Informed Decisions + Product Management), enabling teams to compress months of research, strategy, and documentation into days while maintaining quality and enhancing strategic focus.

Go to Article
A Future Vision
Pages: 4
6 minutes

Why AI-Driven Software Development Makes Agile Obsolete

This future vision article argues that AI-driven software development has eliminated the relevance of Agile methodology entirely. After 25 years of dominance, Agile's core principles—designed for human-paced development—are being systematically broken by AI models that generate code at machine speed.

Go to Article
Industry Insight
Pages: 5
9 minutes

Governing AI in Healthcare: Six Critical Imperatives

This industry insight explores the six essential imperatives that make AI governance vital for healthcare organizations deploying artificial intelligence. Healthcare organizations face significant responsibility as AI transforms patient care—from diagnostic algorithms to predictive models—requiring comprehensive governance frameworks to ensure systems operate safely, fairly, and transparently.

Go to Article
Whitepaper
Pages: 7
12 minutes

The CTO's Essential Guide to Securing AI MCP Servers: Four Audits That Can't Wait

This whitepaper provides CTOs with essential security audit methodologies for Model Context Protocol (MCP) server deployments. With over 15,000 MCP servers deployed worldwide, the rapid adoption has outpaced security maturity, creating urgent vulnerabilities across misconfiguration, retrofitted security features, type safety failures, and vast attack surfaces requiring immediate attention.

Go to Article
Industry Insight
Pages: 8
12 minutes

Top 12 Abilities for AI-Native Software Developers: What to Look For When Hiring

AI-native software developers represent the future of technology departments. This article identifies the 12 key abilities, perspectives, and knowledge areas that make developers highly effective at using AI coding tools—essential reading for CTOs and recruiters hiring in the AI-first era.

Go to Article