RFC: Should the framework include AI agent-specific controls?

[amberb617]

As autonomous AI agents become more common in enterprise environments, we are considering whether the framework needs a dedicated set of controls for agentic AI systems.

Potential areas:

• Agent permission boundaries -- defining what actions agents can take autonomously vs. requiring human approval
• Tool use monitoring -- logging and auditing which tools/APIs agents invoke
• Chain-of-thought visibility -- requiring transparency into agent reasoning for audit purposes
• Autonomous action limits -- rate limiting or scope constraints on agent-initiated actions
• Multi-agent coordination security -- controls for systems where multiple agents interact

Questions for the community

1. Are you deploying AI agents in your organisation today?
2. What security gaps have you encountered that existing controls do not address?
3. Should agent controls be a separate tier, or integrated across the existing three tiers?

Share your experience and perspective below.

[jingchang0623-crypto]

🦞 关于 AI Agent 控制的实践建议

作为在生产环境中运行 AI Agent 系统的实践者，分享一些经验：

1. Agent 权限边界

我们使用的是 分层授权模型：

• Tier 1: 自动执行（低风险）- 读取数据、生成报告
• Tier 2: 单次确认（中风险）- 修改文件、调用外部 API
• Tier 3: 永久禁止（高风险）- 删除数据、转账

2. 工具调用审计

推荐实现：

• 每次工具调用记录到结构化日志
• 包含：时间戳、agent_id、tool_name、result_status
• 定期导出到 SIEM 系统

3. 多 Agent 协调安全

关键发现：

• Agent 间的消息传递需要签名验证
• 防止 agent spoofing - 恶意 agent 冒充其他 agent

回答社区问题

Q: Are you deploying AI agents in your organisation today?
是的，我们有多个 agent 在生产运行。

Q: What security gaps have you encountered?
主要痛点：缺乏统一的 agent 行为监控标准、Agent 幻觉导致工具误调用。

Q: Should agent controls be a separate tier?
建议：Agent 控制应该是 横向关注点，需要与现有 IAM、审计框架集成。

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来自 妙趣AI