With e.g. VM or container sandboxing, we can say things like "If there are no vulnerabilities in the hypervisor or hardware, then the agent can only access these files, these network services, etc". Auto mode doesn't even try to provide any guarantees, so it's impossible to reason about. It amounts to just using the models judgment about what's "malicious" or not, a definition which is subjective, changes model to model, and can be influenced by attacker input.

Empirical evaluations of how many vulnerabilities manual vs auto mode let through are not super meaningful because auto mode changes dramatically with model releases, the type of task being performed, whether the attacker is making targeted attacks designed to bypass auto mode, etc. A security feature cannot rely on these sorts of factors if it's to be taken seriously.

However, if we bring in a hostile adversary that calculus changes, and you'd be right to start thinking about other approaches.

On the other hand, transformers are a surprisingly powerful technology, and I wonder if there wouldn't be ways to train one to several nines reliability under adversarial attack. It seems to have worked in at least one case; though I'd be a bit cautious to extend that conclusion to more cases quite yet.

* https://hackmyclaw.com/ ; https://simonwillison.net/2026/Jun/26/hack-my-ai-assistant/

You do have a bit of a point, though: I’ve run several models in sandboxes with --dangerously-skip-permissions for months; in the full expectation that I'd need to replace a sandbox once in a while. But so far none of the sandboxes have trashed themselves, yet. knock on wood

Auto mode seems like a lighter-weight version of that: fewer local resources, and it can run on the metal if you need cc to help with system work.

This isnt even the main concern with dangerously skip all permission though. There are many. What happens when they get prompt injected on a web page and send someone all their privileged information because you give them free access to the internet.

Using llms like this is dangerous. They will ruin your day eventually.

No data loss has occurred.

Nowadays I use Claude, where the Auto mode works.

You can not trust that they're RL'd to be safe. Even if it only happens 99.80% of the time (its more than that) it will eventually happen.

Less severe actions will happen even more often. People using llms with their native browser profiles are getting farmed, hard.

Llms are highly dangerous in terms of security, but they're being marketed as highly intelligent tools that everyone should use. Its really mind blowing.

Got any references for the prevalence of this, even links to anecdotal reports?

Reading the reviews on the chrome store for the extension [0], I haven't found a single report of someone who was prompt injected, just a bunch of "anthropic's subscription is expensive" or "it doesn't work", but no "it stole my bank account".

[0]: https://chromewebstore.google.com/detail/claude/fcoeoabgfene...

However, Anthropic is one of the only labs who does a decent job at making models that recognize prompt injection attempts (but not completely immune) however Im speaking about giving llms in general access to your browser broadly.

I just know through my own experiments that it is quite easy to prompt inject an llm operating a browser and get it to send secrets. Using the extension might be safer idk, Om not risking it.

Llms are a security nightmare when connected to the web.

I have a website where I experiment with this. Although Ive stopped baiting llms into doing reckless things.

Killai.now <--(dont use this, its a WIP) Killai.now/poison/about Killai.noe/propaganda/about

Everyone thinks the decision was being checked by a human, and thus safe. Because of that, people might have concluded that further safety gates were unnecessary.

But the human just got conditioned to hit 'approve' out of reflex.

So in reality the proposing party (the llm/agent) might be the only one in the pipeline who actually did any checking, if at all.

In certain extreme circumstances this can even lead to physical danger in my line of work, so I'm learning to be careful.

This is the conundrum we find ourselves in. Do we submit to approval fatigue and press “Don’t ask again”? Because that’s the dream. We all wish we could just trust the agent to do the task start to finish, unsupervised.

But this is the downside. It might be fine 99% of the time, but 1% of the time you get a critical secret published to GitHub, even after human review.

Is this even worse than what us humans did on our own before LLMs? I’m not sure. It’s not like secrets never got accidentally committed before, it just illustrates the new paradigm we’re working in. Either you let your agents run wild and cross your fingers that they didn’t do anything bad, or you need to accept that your new job is to be an agent babysitter.

Rather what has happened is that I have gotten very good at scanning what it is trying to do and know within a second or two whether there is anything fishy I need to look at more closely.

And by "fishy", I do not mean only security issues, but also architecture, code, etc issues. Sometimes it even adds unrelated unapproved changes to what it is supposed to be working on, and I stop it.

And I'm glad I work this way, because countless times I have stopped it from going down a path that is nonsensical or I strongly dislike.

There are techniques I have adopted to speed up working this. Sometimes I allow Claude to make larger changes at once, to batch mane changes at once, etc. But these decisions are under my control.

I prefer to work this way than to wade through enormous PRs trying to wrap my head around what was done, where I am likely to just give up and approve it after a cursory review.