Original Summary

I've been digging into Agentic AI security and kept running into the same problem: there is a lot of discussion around what secure agents should do, but far less showing how those boundaries are actually implemented. So I built Who Let the Agents Act? 🤖 It's an intentionally vulnerable Agentic AI environment where you can exploit security failures and compare the same scenario across three implementations: 🔴 Vulnerable - the agent has too much authority 🟡 Prompt-only - security mostly relies on instructions to the LLM 🟢 Hardened - authorization and security controls are enforced outside the model There are currently 9 scenarios covering things like: Overprivileged tools and cross-account access PII exposure Business-logic / transaction-limit bypasses Indirect prompt injection Cross-tenant RAG leakage Secret propagation Fail-open authorization Agent-to-agent delegation Multi-agent confused deputy attacks The important part for me was making the implementation public, not just describing the vulnerabilities. You can inspect the vulnerable code, hardened controls, tool logic and execution traces and see exactly where the trust boundary succeeds or fails. The principle behind the project is: A prompt can influence an agent's behavior. It should never define the agent's authority. Project: https://rewanthtammana.com/who-let-the-agents-act/ GitHub: https://github.com/rewanthtammana/who-let-the-agents-act I'd genuinely appreciate people trying to break the hardened implementations too. If you find a bypass or have a scenario that would be useful to add, I'd love to hear it.   submitted by   /u/Rewanth_Tammana [link]   [comments]

  • 情报分类：技术学习与提效
  • 分类依据：内容涉及技术、AI、软件工具或工程实践
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/16 00:04:33