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14 articles from Crelis on Runtime Authorization. Most recent: “An AI Agent Security Policy: What Belongs In One”.
A practical policy separates agent proposals from permission, names approval states, tests material changes, and keeps evidence for disputed actions.
Agent security maps help only if they lead to evidence for the permission behind a consequential action.
OWASP gives teams a dated field reference for agentic AI risk, not proof that a live action was authorised.
Transparency can explain that AI was involved. It does not prove that an agent had authority to release money, delete a record, or change a credit limit.
NIST's agent standards work matters, but it does not prove that a payment release, deleted record, or changed credit limit was authorised.
MCP approval can move a workflow forward, but the specification text separates transport authorization, elicitation, and later evidence of who had authority for a particular tool call.
MCP authorization uses OAuth to govern access to a server, but it does not prove why a payment release or record deletion was allowed.
OWASP gives agentic AI teams a threat model, not proof that a payment, deletion, or credit change was authorised.
Runtime security asks whether an AI agent's activity is a threat. Runtime authorization asks whether the action was permitted — and whether you can prove who permitted it.
The era of "move fast and break things" has ended at the regulatory border. Every autonomous decision your system makes is a potential point of failure without a verifiable trail. You know that retros
Autonomous agents can make decisions that a legal team may struggle to defend. Speed is a poor substitute for security. Non-deterministic systems carry inherent risk.
An autonomous AI agent without a kill switch is not an asset. It is a systemic risk. The EU AI Act's human-oversight duty for high-risk systems now applies from 2 December 2027.
From 2 December 2027 the EU AI Act's obligations for standalone high-risk systems begin to apply. "Best effort" AI compliance is running out of road.
An autonomous agent's mandate is only as strong as the infrastructure that constrains it. Accountability for unauthorized actions is a matter of architectural integrity, not better model training.