AI 智能體不應繼承用戶的全部權限
An AI Agent Should Not Inherit Your Entire Permission Set
AI 智能體應按具體任務獲授權，而不應自動繼承發起用戶的全部權限。授權政策應界定可存取的資料、可用工具、禁止操作及有效時限；任務範圍改變時，應重新進行授權檢查，超出原定範圍便暫停、徵求批准或停止。敏感操作還應記錄委派的權限、可用工具和資料，以及操作獲準或被阻止的原因。
Copying a user's permissions into an AI agent is a security shortcut that creates authority nobody can clearly explain.
User identity is not agent authority
A person may be allowed to access many systems because of their role. An agent working on one task should not automatically receive the same reach.
The real question is not, “Who started this request?”
It is, “What is this agent allowed to do for this specific task?”
That distinction matters when an agent can call tools, access records, or trigger business actions without waiting for a person at every step.
Start with a narrow task scope
Consider an agent helping a support team summarize customer feedback.
It may need to:
- Read selected support records
- Group recurring issues
- Draft a summary for review
It should not automatically be able to:
- Export the entire support database
- Modify billing information
- Change account permissions
- Send messages to customers
The agent’s authority should match the work, not the initiating employee’s entire permission set.
Put limits around delegated authority
A useful authorization policy should answer a few practical questions:
- Which data can the agent access?
- Which tools can it use?
- Which actions are prohibited?
- How long does the authority remain valid?
- What happens when the task changes?
Time limits matter. An agent approved to analyze a support queue this morning should not retain the same access indefinitely.
Tool limits matter too. Permission to read a record does not imply permission to export it, edit it, or share it elsewhere.
Recheck when the task changes
Agents often move from one step to the next. That transition is where broad permissions become dangerous.
An agent may begin by summarizing support records, then decide it should open a billing system to investigate a pattern. That new system, new data, and new action should trigger another authorization check.
If the request falls outside the original scope, the agent should pause, ask for approval, or stop. Continuing automatically is not autonomy. It is uncontrolled delegation.
Make the decision explainable
For sensitive actions, teams need more than a record showing that a user initiated the request.
They need to reconstruct:
- What the agent was asked to do
- Which authority was delegated
- Which tools and data were available
- Why the action was allowed or blocked
- Whether a person approved the outcome
That evidence helps security and governance teams understand what happened without relying on assumptions.
An AI agent should have enough authority to complete its task, and no more.
來源：DEV Community · dev.to