Securing AI Agents, MCP Servers & LLM Apps

Agents, MCP integrations, and LLM-powered apps are entering codebases faster than security programs can track them — and their behavior isn’t defined by code alone. This guide gives AI/ML engineers, platform engineers, and AppSec teams a practical see–fix–protect framework, with the checklists and templates to start today.

What’s inside:

• The agentic AI attack surface map – five layers of agentic risk, from prompt injection to poisoned MCP tools
• 12-point misconfiguration checklist – the agent & MCP permission and config checks that catch the most risk
• Triage at AI speed – what to automate, what to keep human, and how to prioritize on real risk
• Runtime protection – guardrail architectures, prompt hardening, and policy enforcement for AI in production
• Agentic AI maturity roadmap – a self-assessment aligned to NIST AI RMF, OWASP AIMA, ISO/IEC 42001, and the EU AI Act