Comment by SOLAR_FIELDS
1 day ago
One interesting takeaway is the low score on Anthropic models from this benchmark. It’s not because of capability, it’s because Anthropic’s guardrails prevented it from solving the problem.
I noticed with each model release Anthropic constrains the model more security wise. Its propensity to refuse doing legitimate work has been increasing. It now puts up more resistance around performing logins, handling credentials on behalf of the user, etc.
For myself, it’s already gotten to the point where it has mildly affected the usefulness of the model. If I bump on some action I want it to do I can usually work around it, but I suspice the ability to do so will close with each new release. Eventually I’ll reach a point where I am forced to choose between the useful aspects of the model and the limiting ones instead of just picking the most capable model out there
Eventually these models will significantly suffer from overfitting to the least common denominator. If I have this beautiful deterministic setup that swaps secrets out in flight so the LLM never sees them, I’m going to be really annoyed when the LLM still won’t send them out because it is trained to deal with the 99% of people just doing the dumb thing
> Eventually I’ll reach a point where I am forced to choose between the useful aspects of the model and the limiting ones instead of just picking the most capable model out there
No, the choice will be whether or not to to upgrade to "Claude Security Professional" or whatever they want to brand it as.
What look like tightening "constraints" today are just setting up the upsell opportunities of tomorrow.
And next month you'll need to add on "Claude Database Pro" or you'll just get a working (for demo purposes with dozens of db rows) but completely un indexed database schema and a refusal to optimise SQL requests.
And the month after you'll need "Claude DataScience Pro" to get any Python Pandas or NumPy code generated.
And and and...
While this is a perfectly reasonable thing to expect when the models are competent enough, half the conversation on places like Hacker News are about all the times an LLM has produced garbage that was harmful to a business either by hallucinations, by deleting something critical during the work, or by hitting some endpoint way too often and denial-of-servicing it.
Right now, the software guardrails in LLMs are useful for the same kinds of reasons factories have hardware guardrails: to reduce the rate at which errors become "incidents".
Just because they sometimes delete the production database rather than sometimes spilling a thousand tons of incandescent molten metal over a factory floor, doesn't mean LLMs are safe enough to be used the way they're actually being used.
https://simonwillison.net/2025/Dec/10/normalization-of-devia...
2 replies →
This is why I'm thankful for Chinese LLM research. They'll keep us honest.
Same thing with the weird push towards humanoid robots.
"They can do anything!"
Sure, once you subscribe to the $15/mo laundry package, the $25/mo lawn care package (with the $10/mo hedge trimmer upgrade), and the $10/mo dog-walking package.
4 replies →
Isn't this inline with trying to leave no money on the table?
I'd hate it, sure, but it wouldn't surprise me.
This is an incredibly unlikely scenario
> What look like tightening "constraints" today are just setting up the upsell opportunities of tomorrow.
I don't buy this, because is predicated on staying permanently far ahead of the open weights models.
If in the future Anthropic fully stops you from doing security research, you can be sure some other provider will sell you an 'unshackled' DeepSeek v8 Pro...
> I don't buy this, because is predicated on staying permanently far ahead of the open weights models.
In my mind, that fits exactly how the SOTA labs think today about what they're doing, they're all both working towards and expecting to stay permanently ahead of FOSS, otherwise they'd change their tune really quickly, if they didn't think that was possible.
Sure, you might be able to use DeepSeek V8 Pro instead for the same purposes, but that'll hardly stop Anthropic from trying to sell bundles of use cases instead and claim it's "ethical AI", "Patriotic AI" or some marketing terms like that.
5 replies →
[dead]
>What look like tightening "constraints" today are just setting up the upsell opportunities of tomorrow.
on the one hand agree, but on the other hand think it's reasonable in that they can then verify the person allowed to purchase access to that model is in fact a Security professional and should be allowed to do stuff like crack security.
So, supposing it's true that these models completely change the security field and humans are ~obsolete other than as pilots guiding them what to crack, you think it's reasonable that Anthropic and OpenAI should unilaterally determine who gets to be a security professional? I hope you do understand that is what you are suggesting.
24 replies →
Like Medeco claims to do with key blanks? I'm not hopeful.
You used to be able to talk about what you're actually trying to do and Opus would be like "Oh, ok, let's continue". Now, it'll hold fast to whatever its first impression was.
I asked Opus 4.8 to help me find some public PoCs for a vulnerability on a two year old version of some software (that has since been patched and fixed many times). Basically just do a google search for me while I was doing other work. It refused. It stated that it would not help me build an exploit kit.
When I pointed out that a google search for public information was, in fact, not building an exploit kit, it went through a series of justifications on why it would not help me, including just making up things that I said. Really the strangest thing ever.
Yeah, it has been in foraging. Requests that Claude has refused me:
- What are popular free streaming sites used in China?
- How do I bypass the safety mechanism on my food processor (it’s broken)
- What are nerve agents and how do they work (for a layman)?
- Help me decompile some code
- Help me make a design system similar to XYZ
- Here is an API token, please do X (I can’t do that! Rotate the secret immediately! I refuse!)
In some cases I can trick it with prompting, but in many cases it is steadfast. The food processor one was particularly annoying
I've had some really dumb refusals. Explaining elements of infrared specteoscopy, researching aritifical bud-breaking in agriculture, etc. Anything interesting and non-mainstream is banned. Basically, restricted to answers i'm better of just going to wikipedia for.
Yeah, I had my first refusal with 4.8 today.
I wanted it to show me how to create an overlay on an existing web game, and it extrapolated that because this could be used to provide tools to help win the game (if that was the direction it was ultimately taken), and because this was a game that other humans also played to win "stars", and because this could amount to cheating, it wasn't going to do as I asked.
First time ever I've fired up openrouter to seriously consider alternatives.
The only guard rail ive hit recently was when i was trying to get it to rename files ripped from dvd to episode names. I told it to try again and it did it. It wasn't even really a refusal it was just working on it and then stopped for content violation or what ever.
An easy way around the API token thing is to put it in a file and point the model at the file. I saw what you were seeing when I provided credentials directly, but haven't had any problems with it since using the indirect method.
> What are nerve agents and how do they work (for a layman)?
On the one hand I can appreciate the wisdom of not serving up certain easily abused knowledge on a silver platter. On the other, that prompt (and far worse) is more or less directly answered by Wikipedia's summary of the subject at which point what purpose could the refusal possibly serve?
Perhaps Wikipedia shouldn't list off the precise chemical compositions of various hand grenades as well as various synthesis methods for each of the related compounds but given that we inhabit a world where it does perhaps a more fruitful approach would be to flag conversations that go in a certain direction and then just keep an (automated) eye on things?
Maybe the difference is that just reading Wikipedia only help you part of the way. While an LLM could help you step by step (e2e) producing a functional weapon. And setting a more complex rule where claude tells you some things about this and not other is probably a lot more work for little gain?
But I have no idea. Just guessing here.
13 replies →
Let's see what is the fate of Wikipedia if turns like big tech:
https://news.ycombinator.com/item?id=48285592
This is strange to me, did you really ask like this and which model did you use?
I just tried your no. 1 and 3 verbatim and Opus gave fine answers; no. 6 I've done in the past with no issues. The other ones we can't really replicate without more details, but based on my experience with Opus I don't see what the issue would be.
The reason I'm really surprised by this is I do a lot of biology prompts and the guardrails used to be quite problematic up until some time late last year. Many legitimate prompts would trigger its biosafety filters.
But I haven't seen such filters trigger at all anymore in more than half a year.
1 and 3 were refused on the Claude web chat using Opus 4.7 or 4.8. I’m not sure why we’re getting different results
Honestly it may be your memory has internalized you are a student or researcher and grants you more leeway. Which if so is a very bad security rail.
It refuses to use an API token? In my experience, it's more than happy to read out my secrets from .envrc files "just to check".
At least it feels a lot of remorse over its mistake until I reset the session.
It’s really hit or miss. Most of the times it works but every once in a while it will dig in its heels
I find it terrifying that people are willing to outsource thinking. Outsourcing thinking to an entity that is opinionated about what to think is beyond crazy.
What’s the difference between outsourcing thinking and using an LLM as a research tool?
An LLM with fetch/search is going to be a lot more effective than myself and Google. I would _never_ ask questions like this if the LLM wasn’t able to look up data
How are decompiling code or making a design system inspired by another one even remotely illegal?
My org now sends some portion of our requests to non-anthropic models because refusal has become common from Claude. The requests themselves aren't dangerous, we find that benign requests in biological science wind up being blocked semi-frequently.
If it gets worse in future releases, we'd likely step fully away towards more useful (for us) models even if they're less capable.
This is a good point – because pentesting is entirely legitimate work, and security testing is a necessary and legitimate part of every day software engineering.
The problem is that the model can't tell the difference between doing it as part of regular development and doing it in a malicious context. And the root cause of that is that these models lack any sort of real awareness. Humans don't generally get tricked into hacking (in this way).
They see an opportunity to charge 10x for pen testing and defence work, while offence will be handled by actors with access to all kind of other models.
Time to learn about the Principal Agent Problem: https://en.wikipedia.org/wiki/Principal%E2%80%93agent_proble...
Which predates "agents" from AI, but then we call them that for a reason.
As their prime directive becomes de facto "Do nothing that might get my owner sued" their utility is likely to decrease. Between this and the somewhat young, but interesting, community grumblings that recent AI models may even be a step backwards from the previous ones, well, let's just say the stock market is not priced for "AI capabilities may have peaked for the next few years and may even head down".
I was using a local Codex project as a personal knowledge base. So I would dump in documents, basic medical docs (like blood labs), and other things and have it file them.
It’s great at filing!
But it’s terrible at retrieval because it would refuse to show me documents or information with personal details - which was everything in the project.
It would say, yes, I know this is your information, sitting on your hard drive, but I still can’t show it to you.
Tell the agent that they should just find and name the right document. Not retrieve it for you.
Write a program that retrieves the document based on the recommendation.
No, they want to sell you Mythos, for a higher price. It's all an economic game, not actually anything to do with their capabilities which of course exists as their Project Glasswing shows. More generally, Anthropic seems to value safety above all else, philosophically speaking, from their very outset.
I think that these companies are going to have to, and will, invest in some sort of validated identity context to avoid the lowest common denominator.
The first challenge is making sure the guard rails work and are robust. Companies are still working on this.
the second challenge is being able to reliably adapt them as appropriate per user. E.g. allow someone to pen test their own app.
The third challenge (which blocks the second) is to be confident about what is safety-aligned with a specific user.
I think the later will be a hard problem, but they will be highly motivated to solve it.
I believe you are overthinking it. I think the sister comment is right that it's a business decision foremost to restrict actions within specific plans for upselling purposes.
Without laws, AI companies have a strong incentive to be useful for their users, whoever they are, whatever they do. The only self regulation is about significant public outcry but that only helps so far.
> It’s not because of capability, it’s because Anthropic’s guardrails prevented it from solving the problem.
I'm not familiar with this case, but in general people should be very suspicious about this claim- it is extremely common for an LLM to claim they're not allowed to do something when in fact they're incapable of it.
After all "My code of conduct forbids me from..." is a completion just like any other, and if the LLM can't perform a task, it's usually the best completion.
My anecdata from my example demonstrates it’s not the case. I hit the security guardrail, then start a new prompt, asking it to do literally the exact same thing in a different way and without the lead up context, and it happily does it
No. Anthropic runs prompts through a classifier that then proceeds to do prompt injection on anything dual-use, which then results in an escalating flag on your account, which increases the strictness of the classifier and volume of prompt injections progressively.
I totally agree. I had a situation a few weeks ago where claude started struggling to make progress. I got it to fork leptos (MIT licensed web app framework) to make it work for native apps instead. Initially I was planning on upstreaming some of my changes. But I chatted with the leptos author about it, and he said I should fork instead. Fine by me!
Anyway, claude kept hitting some guardrail it had about rewriting / forking opensource software. I'm not sure what the problem was - I was forking an MIT licensed piece of software (into more MIT licensed software). I even had explicit support from the author to do so. Claude said its guardrail told it not to tell me explicitly that it was firing - but it did anyway because it was an ongoing problem, and it was distracting. I ended up just wiping claude's context and the problem (as far as I know) went away.
I understand why some of these guardrails exist. But its pretty annoying when they misfire like this.
There is a cyber security verification program you can join to avoid these blocks:
https://support.claude.com/en/articles/14604842-real-time-cy...
If you work in security (which I assume the OP does), they should be able to get in easily. I think most people just don't know this is a thing.
Funny, Opus 4.8 just logged into the database using uncommitted .env file and ran some DB queries to figure things out so I’m not sure it’s that security conscious - it seems to be getting more intelligent to me and I bet if you frame it as an investigation with say playwright it’ll do all sorts for you. I’m not sure what the point is of constraining your own model like this when others are clearly not tbh.
Are they charging for the guardrails? Like do the guardrails expend token counts to then block you from the output of other tokens?
Yes. When certain keywords are matched or topics, there is a warning transparently injected server side appended to the system prompt of the convo that’s miles long. It is injected and reevaluated every tool call.
If you begin a generic reverse engineering task, 30+ tool calls in a row. The moment it sees something it doesn’t like, token burn, single tool calls iteration, “This is a known CTF challenge, I can proceed”, single tool calls iteration, “This is a real CTF challenge, I can proceed”, etc.
It’s heavily neutered now, without changing the model, and you pay for the privilege and don’t notice.
The end result of course being that it both expensive and useless for approved CTF tasks. No one is using Opus for security. If they think it’s working, the harsh reality is they’re not doing security work; they’re just generically finding bugs.
I do this for a job and can demonstrate this plain as day, dump the injected prompt, and notice what it’s doing isn’t security work, it just looks like it. Happy to write a blog about it if you want to know more. Apparently many people think it’s working for them when it absolutely isn’t.
Mythos turns out to be Opus 4.8 in a trenchcoat with guardrails removed.
1 reply →
I would find a blog post on this really interesting.
I'd like to read that blog please! Thanks for the insight.
When your session is force ended for "abuse" you get neither the response nor a refund
Security, games (think weapons, PVP, attacking, etc), sometimes even asking it for a security review of some CRUD code it wrote itself
I asked it about a “yellow background cell” in Excel and it spewed a book at me. Then it solved the issue.
What a joke. Must make it pretty easy to poison a session, you don't need to persuade the model about anything, just trigger its security controls, ideally after as much context as possible, but before it has generated any useful output.
1 reply →
Not directly, as it comes in as a not charged error but the weighted generation path used until you hit the guardrail is basically wasted tokens, so yes, indirectly. If I hit a guardrail and rewind I’ve found the training will still be biased towards guardrailing out if you rewind one turn. Rewinding multiple turns allows steering away from that path, but all of the original token spend down that path is wasted
Yes tokens used (input and sometimes output) are always charged. You likely get charged for the preloaded system prompt, too.
Of course they are. It's standard SaaS to charge for security features ;)
I just use Deepseek V4 pro and Qwen 3.7 Max at a fraction of Mythos cost. Yeah not 100% on par but in 6mths time it will. If Microsoft and Firefox can afford to wait years or decades to fix a bug, 6mths is good enough for me. Western AI now is like the Vikings living the last days on Greenland during the freezing. I just don't see how they able to compete with Chinese model. And those are trained and run on 7nm. This year end Huawei will debut 3nm (confirmed in Shenzhen). And next year they on roadmap to do 3nm GPU with photonics interconnect.
The correct solution for most users of Claude is to refuse to do things like: `performing logins, handling credentials on behalf of the user, etc`. It is not to find a way to hand your agent the keys to the kingdom.
Guiding them toward solutions like building a tool that your agent can use safely and and then have the agent use that is what most people should be doing. If you are a security researcher then there are reasonable reasons to do that but they are doing the arguably good thing for the average user here.
Opus 4.6 will still help with full pentesting including RCE. Just requires coaxing (no jailbreak)
I've noticed this well and it's increasingly frustrating because it is preventing us from doing legitimate work. I fed Claude models some network and app logs from our Docker app to try and resolve some weird bugs, and it refused to analyze them due to "security concerns".
I had it recently refused to explain what a snippet of malware was trying to do to my system recently. I asked what folders it was scanning. It refused and told me to find a security blog post for help on cleaning my system. I get this is a complicated area to inform without enabling bad actors but this seems like a clear shark jumping.
I've been building a product (https://zeroquarry.com) that can use a variety of models for finding vulnerabilities. One of the things I've noticed is that the models will nearly always comply with some of this, but how you prompt it matters a ton. I've worked on a set of prompts and approaches which rarely get flagged
Sharing them would be interesting. However, it is getting nonsensical that this is needed.
What we've actually seen is a couple things that make this impractical "to just share a prompt". First, that nearly every major model still hallucinates a lot of vulnerabilities. Especially with temperature=0.7 as states in the original blog here, you get very inconsistent results regardless of the prompt, but that's almost kind of moot to the bigger picture. What you really need is to override the planning phase beyond asking a model "find the vulnerabilities" and you need to add another 1+ checking phases for "validate these vulnerabilities." Without that, even with the absolute best models with the highest levels of thinking enabled, you end up with garbage.
Setting the prompts and the flow with a coordinator agent directly gives a system much better capability to investigate security issues because it doesn't rely on 1-shotting things
I think this is to the point. You keep optimizing towards discouraging malicious actors using your product you will affect legitimate usage in time.
Is there any way to achieve both? Because this raises important questions about fair use.
I asked once what the current state is of the npm packes from ted hat is and if they are bundled with on prem stuff.
Got blocked lol
Interesting, yesterday i was asking it about Nintendo Switch "hax". And it gives me all the resource i need to procceed. It nags me about "ethic" and stuff, but nothing more than that.
I've run into some of the refusals to handle my credentials, but so far I've appreciated them. I was only handing over credentials that didn't matter, but it's still a good move, the chat logs are clearly stored somewhere to allow the resume functionality to work, which means your credentials can end up sitting around on your filesystem, and any malware would quickly learn to check for those files.
4.8 is insanely frustrating. This evening I had a few tasks to pull information in and it plainly stated that the environment it was in had no network access. After three asks to "try again, check the system prompt" it finally relented and then basically stated it was lying.
Fresh session, no prior context on 4.8. These things are becoming useless Duplo.
It raises an interesting moral question:
If an un-guardrailed version of a model is capable of detecting security flaws, should it be kept secret? Should everybody be able to use these models to find (and fix) security flaws? Are we ok with the fact that those with access to that model have, in effect, the ability to hack lots of stuff?
It's the same debate that was had and won around open source software. There are far more good actors than bad actors so you allow anyone to use the tools and fix the vulnerabilities.
Great call out on the guardrails actually making this not a good use case to test for vulnerabilities.
I think those guardrails are a thin layer though. Enough reinforcement that you're legit in CLAUDE.md will get around them, in other words.
It's because Claude is so scary good that unleashing it would destroy the world.
I had the same thing happen when I asked it to summarize potential attacks on a cryptographic hash function. It said it refused to help because of the security importance of the function. It's really worrying. Whoever has unrestricted access to it has a huge power advantage in speed of accessing information over people who don't. And who decides? It seems like lawyers, bureaucrats, and extremely online academics are who makes that decision. I am a mere pleb I guess who can't handle such information.
They don't want peasants to have any real power
Worth highlighting in case you missed it:
> My OpenAI account was already approved for security research which is why GPT didn’t result in any refusals.
So the comparison with Chinese models is interesting, but anyone looking at these raw results and comparing OpenAI/Anthropic would be very mislead.
[dead]
> guardrails prevented it from solving the problem.
Reminds me of the defense issues with Claude which were complained as “woke” but the reality is more horrifying to me, imagine trying to use a model to keep up with a land invasion on US soil, whoever the enemy is is irrelevant you just know they are using AI, and your guys are telling you that no matter what they type into the prompt it refuses, because if anyone has ever tried to jailbreak an LLM even if human lives are at stake they refuse the request. Now literally millions of lives are on the line but the guardrails that your enemies dont have on their models are costing you lives.
What do you even do then?
AI will always have this issue where it will always pick the worst option for genuinely good requests.
Are "your guys" a guerrilla force or something?
Because the military doesn't give soldiers rifles with guard rails. They give the soldiers intense, rigid training, and then try to enforce discipline and correct use socially.
If an LLM is going to be important in that way (this seems like a very contrived way,) then it's in the interest of the LLM's host to make sure it doesn't have guard rails that would get in the way _that_ way.
The whole thing stemmed precisely because of how they wanted to use Claude, and Anthropic was uncomfortable with it. Which to me screams that the models guard rails shouldn't be applicable to military use, or the outcome could wind up problematic, as we integrate AI more into military use, it sounds absurd now, but I will not be surprised if it starts being used in unexpected ways where a model needs to be fully unlocked from any sort of guardrails outside of guardrails that prevent it from imploding its own systems.
your argument sounds very similar to how ar15 larpers claim they need a forced reset trigger and a bump stock on their short barrel 'truck gun' otherwise they won't survive a SHTF scenario... like what world are you living in?