how are you guys handling database access for analytics/debugging agents?
Summary
作者分享为生产环境中执行分析和调试任务的 AI 代理设计数据库访问控制的经验:为每次查询签发可过期的单次权限,并在使用时重新校验,同时指出设计中仍存在的缺口,最后向社区征求其他方案。
Similar Articles
Those of you running AI agents in prod — how are you actually managing their permissions?
The article asks how engineers manage permissions for AI agents in production, highlighting common problems with broad access and lack of audit trails.
How are you securing your AI infrastructure?
探讨随着 AI agents 开始访问内部系统并自主执行操作,传统围绕'人使用单一应用'构建的安全边界失效的问题,并讨论应在 agent 层、网关层还是系统层实施策略控制,以及被拦截时如何保留 agent 运行上下文以便审计。
How are you letting AI agents touch your production database without it being terrifying?
A developer asks the community how to safely let AI agents interact with production databases, highlighting concerns over SQL injection, data leaks, and lack of audit trails.
We gave an AI agent a readonly Postgres login. It wasn’t as readonly as we thought
作者分享了为 AI agent 提供只读 Postgres 账号后发现其权限并不真正只读的经历(通过角色继承等机制可获得写权限),并开源了一个名为 agent-db-scan 的工具,用于审计给定 Postgres 连接串的有效权限、继承角色、可写表、RLS 及敏感列访问等。
People running agents in production: how do you control what they're actually allowed to do?
A developer seeks advice on how to control and bound AI agents' actions in production environments, particularly when they interact with real systems like databases and customer data, asking about current practices and whether this is a known headache.