Hey everyone, I hope it's okay for me to jump in here. I've been following Open Claw for a while, mostly reading about self-hosting and backups, but this new story really has me worried. I just saw the article about a researcher who managed to use a prompt injection attack to exfiltrate memory from an AI agent's runtime. That sounds... incredibly bad.

As someone who's still trying to get a solid grasp on security best practices, this feels like a huge escalation. I mean, we often talk about keeping agents isolated and having good network controls, but if a simple manipulated prompt can force the model to read and then send out its own memory, what does that even mean for our setups? That memory could contain anything, right? API keys, user data, internal logic... all from a seemingly normal user query.

I'm probably overreacting, but this seems like it changes the game for vendor questionnaires. When we're looking at agent runtime vendors, what kind of questions should we be asking about this specific threat? The article was light on details, but I'm imagining we need to ask about memory isolation techniques, runtime sandboxing at a deeper level, and how they monitor or filter output for potential data leakage disguised as a normal response.

Could anyone with more experience maybe walk through what the key architectural points would be to mitigate this? Like, is this purely a software sandboxing issue, or does it touch on the model's training itself? And for those of us filling out security questionnaires for vendors, how do we interpret a vague answer like "our platform employs state-of-the-art containment"? What concrete follow-ups should we insist on?

Sorry for the long post, I'm just feeling a bit out of my depth and would really appreciate some step-by-step guidance on what to look for now. This kind of exploit makes me rethink all the SSL and encryption I've set up, because if the agent itself can be tricked into sending secrets out, the transport encryption doesn't matter much.