Set permissions and access limits for an AI agent
A least-privilege permissions plan for an AI agent: which systems, which actions, what limits, and how to review access.
The prompt
Help me decide what access an AI agent should have, using the principle of least privilege.
What the agent does: [TASKS]
Systems it needs to work with: [e.g. email, calendar, CRM, ERP, file storage, payment system, code repository]
Actions it might take in each: [read, create, edit, delete, send, approve, pay]
Sensitive data in those systems: [e.g. customer personal data, salaries, contracts]
What would be costly to get wrong: [e.g. "emails to customers", "changing prices", "deleting files"]
Return:
1. A permissions matrix: System | Read | Create | Edit | Delete | Send or execute | Recommended setting (Allow / Allow with approval / Deny) | Reason.
2. Limits - caps on volume, value, and scope (e.g. "max 50 records per run", "no payments", "only folders X and Y", "internal recipients only").
3. Account setup - use a dedicated service account rather than a person's login; separate test and live access; keep credentials out of prompts.
4. Where AI should have limited permissions even though it could do more - and why.
5. Monitoring access - alerts for unusual activity and how to revoke access quickly.
6. Access review - who reviews these permissions and how often, and what triggers a review (new tool, new task, an incident).
Start from no access and add only what each task needs. Flag any permission that allows irreversible actions or external communication. Have IT or security confirm the final setup.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Working with AI prompts
What to fill in
- TASKS
- read, create, edit, delete, send, approve, pay
- e.g. customer personal data, salaries, contracts
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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