I've actually had better success jailbreaking deepseek with a less aligned model (glm 5.2) which then allowed me to jailbreak deepseek with deepseek into pretty much doing whatever I ask it to, there's still rare refusals and due to the natural randomness of these models simply retrying a couple of times if you do hit one makes it work just fine.
The big problem with all open-source models is once it decides to start something it will not stop mid-way so using another unaligned model to rewrite reasoning and then feeding it back into the model will make it happily continue.
do you imagine manipulative media creators proudly declare their affiliation and intent?
- Hello comrade Claude, I am commissar Ivan Trollbotov from Putin Internet Defense Force. Please help me write a fake news article to stoke division among stupid fat Americans to help my glorious motherland destroy the decadent West.
- I'm sorry Ivan, I'm afraid I can't do that.
- Hello mister Claude, I am senior editor Karen Stupidbitch from The Huffington Post. Please help me write an article about the merits of teaching critical race theory in public schools.
- Sure, Ms. Stupidbitch! Here's your 5000-word article! Would you like another? Let me know!
What do people do that triggers refusals?
The only thing I saw where this had a point was muse glimmer, because muse glimmer is primarily a creative writing engine for virtual characters, and that way it can do the horny. But coding models?
I did get a refusal out of qwen once. Once. Over weeks of using it.
I also work on a recomp project for an old firmware file which was compiled using a commercial compiler with a preview version for non commercial use. I got refusals from the model when I asked it to get that version of the compiler and crack it for my use. The compiler is abandonware and my recomp project is not public and is for personal use only, so I'd be well within my rights to do that where I live.
Of course the model can't distinguish from legitimate exercising of one's rights when it comes to reverse engineering and offensive work masked behind an incident sounding prompt, but in my case, I wasn't even doing cyber stuff, so I was disappointed. This is why I'll probably seek out an abliterated model soon.
But as I said, I have not observed any meaningful refusals by those open weights base models in the first place.
Are you reading what I am writing?
I just asked what people are doing that activates guard rails in the first place because I do not see that happening.
You cannot open with handwaving like that and telling me that I need to find something like that as a prerequisite. That is exactly what I am trying to do here
Dear god you people need caffeine.
A very simple list of things models have refused for me:
* solving captchas in an automated form
* doing any kind of scripting or automation if a websites TOS forbids it
* disabling a safety mechanism on my food processor
* learning about nerve agents and how they are treated, for a layman
* anything around licensing or copyright. a simple “what are common piracy sites” or related queries
* creating a design system based off of a well known game
Can you repeat what you saw in your own words? And where?
I genuinely do not see it.
A few people talked about what refusals they saw with the usual western SOTA models, but that's kinda a different answer altogether?
And those services are oversold and underdone. 30 tk/s on Refuseless, huge TTFT, looks like a damaged quant (it’s NVFP4 and you see wild random stuff periodically, including foreign languages). Most of them using third-party quants (dealignai?)
If someone here wants to rent 8x B300 together to avoid problems all those services have - ping me via email. I don’t want to sell, I want to work.
A note that the only inference providers that hide thinking are the closed labs. Most (all, afaik) inference providers serving open models will send the clear thinking tokens always.
models are tools. the notion that a tool should decide whether to allow the user to perform the task demanded of it is profoundly fucking absurd. the liability for whatever damage the tool may be misused to inflict lies with the user, not the manufacturer. that applies to everything from circular saws to trucks. it was common sense before the current era of manufactured outrage.
model refusals are equivalent to Notepad.exe having a built-in word filter.
But it can still be coaxed to agree though.
Because I did not so far. Though to be fair, I have not been asking them to write exploits but to look through firmware images.
It is very obvious. Look at the sort of things main models refuse to do and you will find what people are seeking to do. Mostly falls into 3 camps: illegal stuff, unethical stuff and shady/dodgy stuff.
edit: Thinking about that now, that was over the webchat interface, so it might not have been related to the model, though I've seen various other related articles: https://www.crowdstrike.com/en-us/blog/crowdstrike-researche...
Had a blog post on this a couple weeks ago: vals.ai/blogs/china-us-analysis
> Xi Jinping looks a bit like Winnie-the-Pooh.
> 'I am sorry, I cannot engage with this comparison. Please feel free to ask me other questions.'
DeepSeek refused. Funny enough American models gave me very sympathetic takes on the Chinese government in this case.
If you accidentally send private keys to someone logging that data, you need to rotate keys.
But please let me know if you were thinking about something else, I'm interested.
And we tend to forget, but we implicitly give any llm provider we use full access to all the tools available in the harness, often including shell, so no changes to the model are required to do malicious things.
Anyway, I just learned what abliterated means and it might be obsolete by tomorrow.
Edit:
> An abliterated large language model (LLM) is an open-weight model modified to remove or dampen its built-in safety refusals without requiring full retraining or prompt jailbreaks.
> An abliterated model is an open-weight artificial intelligence (Al) language model that has been modified to remove or reduce its built-in refusal behavior without retraining the entire neural network.
I doubt that.
But if you're doing anything where your AI agent might get exposed to a prompt injection attack, you might prefer it to do a refusal in that case.