I'm not claiming auto is worse than manual; I'm claiming it cannot be compared with anything security-wise because it does not aim to provide any guarantees, there's no systematic way to reason about what it will and won't allow, etc
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.
Further, percent of malicious tool calls accepted is a bad metric. It's like measuring the security of ssh in terms of what percent of unauthenticated logins succeed. The only acceptable value is zero. It's pass/fail, not a spectrum. So both auto and manual mode should fail equally here. Further, the set of malicious tool calls admitted in auto mode may not be a subset of those admitted in manual mode.
Ah, you're going for the actual adversarial case.
I think I'd trust the current approver with correctly classifying regular semi-interactive LLM behavior fairly well.
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/