Knowledge paper 02Official whitepaper
AI Runtime Protection for Agentic Systems
A practical control model for prompt injection, tool abuse, output validation, and human approval in live AI workflows.
22 min read8 issue pages02 May 2026
Executive summary
Agentic systems expand risk beyond model quality. Once models can invoke tools, access MCP servers, trigger workflows, and interact with customer or operational data, the security boundary shifts to runtime.
This paper explains the minimum runtime controls required for production AI systems, especially in regulated environments where governance must be visible in operation and not only in policy documents.
Paper profile
- Audience
- AI Security Lead | Platform Engineer | Model Governance Lead | SOC Architect
- Format
- Editorial issue + PDF export
- Reading modes
- Spread reader, PDF viewer, downloadable asset
Reader
Read it as a publication, not a blog post.
Open the spread reader for the full editorial experience, or use the PDF if you want a shareable file for investor follow-up, buyers, and partners.