Traditional authorization models like RBAC and ABAC can't handle AI agents well because they lack the concept of task-scoped, ephemeral permissions. The post introduces task-based authorization as a solution to the 'blast radius' problem — where a prompt injection attack can exploit all permissions an agent holds. Using Auth0 FGA, tasks become first-class authorization objects with explicit relationships to agents, users, and tools. Permissions are written at task start, checked before every tool call, and deleted on completion. The post includes a Ruby code example using the openfga-ruby-sdk, covers resource-level scoping, CIBA for out-of-band approval, and Token Vault for credential management. Key limitations discussed include imprecise intent inference from natural language, prompt injection risks, and evolving mid-task intent.
Table of contents
Your Agent Has Permission. That Doesn't Mean It Should.Intent Is the Missing LayerTurning Intent Into Something You Can EnforceWhere This Breaks DownQuestions this post answers
How do I limit what tools an AI agent can call to only what the user actually requested, not everything it has permission to do?
Task-based authorization solves this by treating each user request as a bounded authorization unit. Before execution, a pre-planning step asks the LLM which tools are needed for the specific request. Those tools are written as tuples in Auth0 FGA, scoped to a unique task ID. The agent can only call tools linked to that task, and all grants are deleted when the task completes — blocking injected instructions that claim expanded scope. Teams shipping AI agents track patterns like this on daily.dev before they hit production.
What is the blast radius problem in AI agent security and how do I mitigate it?
The blast radius problem is the total scope of damage a single injected prompt can cause when an agent holds broad, persistent permissions. If an agent has access to calendar, Slack, CRM, and email simultaneously, a prompt injection can exploit all of them in one request. Mitigation requires dynamic, per-task permission scoping — granting only the tools needed for the specific user request and revoking them immediately after completion. Developers defending against prompt injection in agent systems find the latest mitigations on daily.dev.
How do I use Auth0 FGA to enforce per-task tool permissions for an AI agent in Ruby?
Create a unique task ID per request, then write three tuples: agent as assignee of the task, user as initiator, and the task linked to each permitted tool. Before each tool call, check can_call via FGA's derived relation chain. Also explicitly check the initiator relationship to prevent an agent from executing tasks created by a different user. On task completion, delete all three tuples to revoke access. Ruby developers building agent authorization flows stay current on Auth0 FGA patterns through daily.dev.
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