Is that because auto mode is good, or because the manual approval system sucks?

The blog post has more detail, but tldr is humans make mistakes that automation can catch.

Sure, but Claude is deeply useless at making permissions hooks! Every time I've tried it it completely fails at the task, despite researching the docs and using various skills. It trivially evades its own just-created rules.

Indeed. The article only compares the status quo manual system versus the auto system — and doesn’t consider ways that the manual could be improved.

As it says:

> 5% allow any shell command outright, and another 43% have interpreter rules like Bash(python:*) or Bash(node:*) that are essentially equivalent in practice

Claude Code never should have prompted to always allow Bash(python:*) or Bash(node:*) — that’s clearly a bad idea, and Anthropic know that (given the references in the article!).

Of course, Bash(python a.py) still isn’t safe if you also allow Write(a.py), because you may as well allow Bash(python:*) at that point, and that’s often practically what people want (“I want to both make edits to the source and then run the test suite”). So maybe the whole permission system is broken to start with — and the actual answer is leaning more heavily on fine-grained sandboxing.

You also, as the article rightfully points out, run into permission fatigue and users blindly hitting allow.

I do still wish you could do more with hooks — outside of auto, I might want to allow a given command via a hook if Claude Code has read access to given file, but there’s no way to query if a given path allows/denies read/write.

Will look into exposing that in hooks.

Ultimately, the threat model here is: human has to approve a lot of commands, so gets tired and accidentally approves a command they shouldn’t have. We spent a significant amount of effort to build a richer permission system, allow configuration at multiple levels, use static analysis to detect dangerous and safe commands, monitor the model to detect and block prompt injection at the inference layer, etc. Some of these components we rewrote and red teamed dozens of times. Our conclusion was that despite all of this work, in practice the threat model is that human attention is limited and that that a different approach performs an order of magnitude better in practice.

The problem is that you didn't even attempt to build a proper box (a sandbox that prevents the AI from running bad stuff by design). It's an extraordinarily hard problem. Only OpenAI Codex is actually trying to do it, and they suck at it too. They keep breaking permissions, their own AI can't troubleshoot it, their defaults give read to the whole filesystem (go ahead, slurp my ssh keys), and their "manual approval" escape does not seem to work.

I agree actually. We built an open source agent-agnostic sandbox that we are landing improvements to, much more to come: https://github.com/anthropics/sandbox-runtime. That said the sandbox is not perfect, and any sandbox needs holes punched otherwise it is not useful in practice (at least for inference and MCPs, and almost certainly more). We will be doing much more in this area.

That’s good to hear, it’s a much better approach than expecting humans to read commands and approve them or just trust that the LLM can set the proper horizons for its world itself while working.

Making a sandbox both fully secure and fully useful are contradictory requirements. If you want the agent to do any real work, you have to leave gaps.

With SOTA agents that’s a real bind, because they’re very likely to find those gaps. Whether they exploit them, close them, or leave them alone then becomes a prompting challenge yet again.

I don't think this means don't sandbox at all. You can prevent a lot of small and medium accidents by locking down or gating access to hidden files, ssh, sudo, etc.

But your sandbox can never be the whole story.

Maybe you can include some percentage of intentionally malicious commands, but not actually run them if the user approves them. Just blare an alarm telling the user they misclassified a malicious command, and maybe pause the Claude Code session for a frustrating 5–15 seconds. Video games can elicit truly astonishing levels of performance from human brains by using this approach. I'm guessing it's probably outside your Overton window, which is too bad, because it has the potential to work a lot better than the 89% you get with "Auto mode", which is far too low if anything really significant is at risk. That's not even one single order of magnitude lower risk than just "allow everything always".

Speaking of really significant things being at risk, it's pretty infuriating that the web-chat Incognito mode can't write and test code locally, and neither the non-Incognito web-chat nor the local Claude Code client can be shielded from the knowledge of my email address and my geolocation. (Even the Incognito mode knows my geolocation.) This gives users no alternative but to put privacy-sensitive information at the disposal of Claude Code, which is far too unreliable to be entrusted with it. It's tempting to attribute this to Anthropic's corporate DNA valuing users' interests at a very low level, but conceivably it's just an oversight, and if I mention it here, it will be corrected in a month or two?

this is not a serious proposal

Not only is it a serious proposal, it's been used in practice in every airport X-ray baggage scanner for decades, where it's called Threat Image Projection (TIP): https://www.xscann.com/products-HiTipPlus.html

Yes, but you can require it in such a situation, as they're subordinates who have to follow policy or lose their jobs.

As I pointed out above, Anthropic places a lot of requirements on its users already, but if Claude Code TIP were optional, presumably savvy users would turn it on voluntarily unless they wanted to use Auto Mode.

Most of anthropic's money comes from enterprises that may want to enforce something like this at an org level.

The same scanners that let handguns et al through 93% of the time, according to internal audits and journalist review?

Maybe pick a better comparison if so?

Enterprises do the exact same thing today by sending phishing emails to their own people to figure out who needs additional training. Why would an enterprise not want this feature for Claude? It seems like an extremely serious proposal.

Did you ever test putting the auto mode classifier in front of manual approval? This is how I use it, but last I checked that option is not available out of the box.

That’s how auto works right now. It gives you a prompt.

> I do still wish you could do more with hooks I might want to allow a given command via a hook [...] given path allows/denies read/write

You can make a script for the PreToolUse hook that can do that. I use a command gate script that parses input for doing that exactly, allowing/denying actions based on tool use + paths -- it started out as a hook to prevent claude from polluting my clojure projects/filesystem with python scripts in sneaky ways. Babashka works really well here

If you have a file in your repository that is not safe to run you have bigger problems than your development system getting compromised.

A key problem when using manual approval with Claude is that too much of Claude's tool use is Bash or Python slop that is difficult to review (especially when you are getting spammed by it) and impossible to handle through rules. Example:

sed -n 1,30p src/vm/wren_vm.c && sed -n 310,350p src/vm/wren_vm.c && sed -n 560,600p src/vm/wren_vm.c && sed -n 740,775p src/vm/wren_vm.c && sed -n 40,70p src/vm/wren_common.h && cat util/wren_to_c_string.py | head -80 && ls test/random doc/site doc/site/modules doc/site/modules/random 2>/dev/null; cat projects/premake/premake5.lua | head -80; cat util/generate_projects.py

After ten or more of these, you're going to get hit by review fatigue, and then, yes, manual review becomes too error-prone to use safely.

The irony is that Claude is regularly ignoring its existing Read/Write/Edit tools that could make everything more readable.

Other models/harnesses have their own problems, but Claude Code is one of the worst for manual approval.

You can get manual approval to work reasonably well if you give the model a reasonable set of tools (I have literally written my own MCP servers to cover gaps in existing harnesses) where you can then write rules for the vast majority of safe cases.

For example, I have a stdio MCP server that allows models to inspect crates under ~/.cargo/registry/src (paired with the existing query-crates MCP server). It provides read-only operations limited to crate data, so I can pretty safely auto-approve everything in there. With the right setup, including a sandbox, you only ever have to manually approve something once in a while and usually with delimited scope, avoiding review fatigue.

Opus especially seems to like to:

1) edit a file with sed, 2) try to write it with its regular tool 3) get blocked because sed changed the file 4) read the file with tool 5) edit with sed again.

Would be nice if it felt like real people were developing Claude Code, instead of chasing after another half-baked idea Claude came up with.

Related to that, there are quite a lot of common command cases where you have the choice:

- Yes, but only one time, you will have to manually approve next time

- Enable auto mode and stop worrying

- No

Nothing to save this command or part of it to the manual approve list. So will be requested again 100x times.

I run CC as its own user on my laptop with no secrets/keys/erc available other than through a LPE exploit or perhaps installing a keylogger. Can I guarantee CC won't attempt any of those things in auto mode?

There are no hard guarantees as far as LLM output is considered.

Just 3 days opus 5.5 in auto mode deleted backups that it shouldn't have, and in the "apology" it even said, "Nothing was lost, I didn't delete your original files".

I hate this condescension by Claude. It doubles down in such a bad faith way.

Saw something similar: https://news.ycombinator.com/item?id=50412916

No its not generally safer. It depends on who is doing the approving, the task being completed etc.

Auto mode may be significantly safer in the niche case where you want the model to have free reign, in a fully unopinionated environment, where it's allowed to make any changes and make any external calls.

Many of the problems when it comes to the manual approval feel like they stem from the expectation of using auto mode in the first place. After all, what's the point of improving the manual approval and safety matching if auto mode is the end all be all, and what's the point of training the model to output commands in a manner that can be parsed by a human if auto mode is always meant to be used? It's very rare for me to not see "command could not be statically analyzed", because the model keeps outputting bash golf.

[delayed]

> That is not the niche case, that's the dominant use of models.

It would be helpful to distinguish between your own opinion on how models ought to be used, compared to how others actually use models.

> That is not the niche case, that's the dominant use of models.

And if everyone else jumped off a bridge, I mean, used raw interpolation for SQL queries, would you do it too?

Don't worry, you can just use the automated approver to escape your queries! It's so secure!

Using raw SQL string interpolation doesn't get you anything much that you can't get just as easily with a parameterized query. In contrast, properly sandboxing agents is such a pain, and such a productivity drain, that hardly anyone does it in practice, save for a vocal minority online.

Auto mode seems to have some reasonable restrictions baked in. For example if you give claude access to two k8s namespaces, seriousproject-qa and seriousproject-prod, auto-mode will grant `kubectl exec` on the qa environment while denying the same command for the production environment. Of course you should be enforcing that by restricting what kind of access tokens you give claude access to, but auto-mode does have opinions about this stuff too, even if it's not bulletproof

However I do share your desire for a better manual mode. Auto-mode is both sometimes surprisingly lax, and sometimes too restrictive. Maybe manual mode should inject a reminder "keep your commands as simple one-liners", the same way plan mode injects a reminder that you are in plan mode and don't want any code changes

"Safer" also meaning it randomly blocks stuff you explicitly tell the agent to allow because Anthropic knows better. even non-cyber related stuff.

That may be for most cases, but it wasn't safe for this password scenario, and likely others that haven't been discovered. Maybe there's a PII setting that can be enabled by default.

I completely believe this, but you could also run auto mode classification in manual mode and tell the user the result.

Or even reject anything auto mode rejects while still allowing the user to reject things auto mode accepts. If what's approved is the intersection of what the user is approving and what auto mode thinks is safe then it would be strictly safer than either mode alone.

This would also be a way for users to gain confidence in auto mode before going all in on it.