AI Agent Threat Modeling: Finding Risk Before Delegation

Sat, 23 May 2026 00:00:00 +0000

AI agent risk is easiest to reduce before the agent is busy. Once a workflow is live, every unclear boundary becomes harder to reason about. The agent has tools, users have expectations, logs are filling, and the team may be tempted to patch each concern as it appears. Threat modeling brings the risk conversation earlier, when the system is still simple enough to change.

Threat modeling does not require fear or theatrical security language. It is a disciplined way to ask what the agent can see, what it can do, what it might misunderstand, who or what might influence it, and where a mistake would matter. For agent systems, that conversation is especially useful because the interesting risks sit between language, tools, data, permissions, and human review.

Threat Modeling on Fondsites

AI Agent Threat Modeling: Finding Risk Before Delegation