@TongWu_Pton Are you evaluating these models with different tool permissions as well? I’d be interested in how much the surrounding controls change attack success rates for the same model.
@mark_l_watson The combination of permissions matters too. Read-only mailbox access prevents changes to email, but if the agent can pass that content to another tool with outbound access, data can still leave.
@sec_doc The alternate-tool bypass test stood out. Blocking an HTTP request doesn’t help if the agent can make the same request through a shell. How are you keeping those restrictions consistent as new tools get added?
An agent can remember a customer ID from last week.
That does not authorize today's run to open that tenant.
Memory is context.
Permission is a separate decision at the tool boundary.
Knowing what your agent was supposed to do isn’t enough.
You need to see which tools it called, what they returned, and what happened next.
If you can’t reconstruct the run, how do you investigate a failure?
@1clawAI@LakeraAI@TheHackersNews Keeping keys in a vault is only part of it. The backend still has to verify that the caller is authorized to use that installation before issuing a token. An agent can cross a customer boundary without ever seeing the underlying secret.
Open weights let attackers test prompt injections privately, outside a hosted provider’s monitoring.
Your agent’s permissions need to hold even when the model follows a malicious instruction.
People get offboarded.
Agents often don’t.
The token still works. Role still wide. The project that created it is gone.
If it can act without a living owner, it isn’t automation. It’s orphaned access.
Last week, I had the privilege of speaking at Mind and Machine DFW's first Fort Worth, TX event at @HopFusionAle . I spoke about Cybersecurity Guardrails with AI.
If you're in Ft Worth and using AI in your business, be sure to come to the next event in October.
https://t.co/5dY244MvAz
@KbXPDude@bot I'm seeing the same thing. They should at least allow grokbot to fall back to a lower model while they are rolling out or whatever they are doing.
The best SMB automations I see aren't "AI replaces HR."
They're Sheets + Slack + a daily check, with a human still owning the weird cases.
Glue first. Judgment last.
Say when you’re done.
@RodmanAi Archify's the one that caught me. Agents that turn messy process talk into a diagram people will actually follow > pretty flowchart generators.
Agents don’t fail because the prompt was short.
They fail because nobody defined “done.”
Who can approve, and what happens when the tool lies?
Spec that first. Then automate.
Reckless AI isn't mostly a model problem.
It's a permissions problem.
If it can email, pay, or access customer data, treat it like a new hire with root access.