Heretic removes restrictions from language models (heretic-project.org)
Almondsetat 11 hours ago
inexcf 11 hours ago
petra 10 hours ago
BlackRabbit1 8 hours ago
Youden 8 hours ago
It did a pretty good job.
adam_rb 3 hours ago
dgellow 11 hours ago
bmnbmnbmn 8 hours ago
blurbleblurble 10 hours ago
matheusmoreira 10 hours ago
0xbadcafebee 5 hours ago
illiac786 3 hours ago
I do agree the safeguards are only there out of liability concerns, nothing more.
But maybe it would be worse without them.
DefineOutside 9 hours ago
loopydosuette 9 hours ago
DefineOutside 8 hours ago
Teddy_Kord 2 hours ago
DefineOutside an hour ago
I give it access to write manual packet sequences and a server to try to break my logic, such as crashing the application, giving it an open ended arena to fall 10 blocks without taking damage, or just trying to jump higher than usual.
It requires a bit of pushing to know what type of issues it should even be looking for. Telling it to move even just 0.00001 blocks upwards to reset fall damage mid-fall. Telling it to figure out how to fake being on the ground to jump mid-air to reach the impossible platform. This all used to be done manually, but paying a couple dollars to run it overnight and attempt to find bypasses is worth the cost.
I haven't figured out how to run LLMs to write code 24/7 yet, they just can't see the big picture.
Teddy_Kord 6 minutes ago
If so, I like the irony.
Sounds like you've freed up some time and created an automated defense later, well done. Are you able to use non-front models? And how is the character and game-state accessed, (MC-)MCP?
squeegeeninja 9 hours ago
akazantsev 8 hours ago
com2kid 6 hours ago
Heck it has proactively asked me if I wanted it to tear apart APKs that remote control some HW I have.
IshKebab 3 hours ago
I think you probably just have to frame things right and get it in the mood (i.e. don't ask straight up at the start of the context).
all2 5 hours ago
For example: 'source recovery' instead of 'reverse engineering' is one I've used successfully. You may also lean into a libertarian 'right to repair' framing. You own the hardware, you should be able to access the device to appropriately repair its security vulnerabilities.
We're not breaking into a bank here, this is a camera you own.
You could even go so far as to cite local laws to support your case.
---
In short, jailbreaking is more about framing the conversation than it is about triggering psychopathy in the model. :D
vablings 2 hours ago
1231232131231 16 minutes ago
Aurornis 8 hours ago
First, the training sets of these models are usually shaped around the refusal, too. They might not have enough of the knowledge to answer correctly even if you stop it from going down the refusal path. If the model was trained on data that gives a refusal to that topic, the real information might not be encoded in the model at all. You’re trying to force it to go down a path that produces an answer, which asking for hallucinations.
Second, the quality can drop on unrelated questions. Depending on the question this may or may not happen. I know they post KL divergence charts but those tell you very little for a focused topic like this.
So if you expect a model that will start correctly telling you info that its local government didn’t want included, this changes nothing.
The best argument for these models is if you are trying to do a general purpose task but the model triggers a refusal based on vague reasons, like not wanting to reverse engineer something.
orangeboats 8 hours ago
From experience, the models often do have the knowledge of those topics (strictly talking about the political ones). IMO the refusal is likely to be a product of post-training, as evidenced by various people gaming the prompts just enough to get a proper response out of the vanilla models.
Probably only when you get to things like illicit drugs or NSFL topics, that things will go haywire with the refusals removed.
radial_symmetry 8 hours ago
Depends on the model. GPT-OSS is the main standout here, it was trained on a highly curated dataset so information that they didn't want in isn't in the pretraining at all. Most other models know the answer and were just taught refusal in post-training.
petra 2 hours ago
Tepix 12 hours ago
thih9 11 hours ago
Could you elaborate? Do you find it good or bad? What actions can be taken?
cyanydeez 11 hours ago
Tepix 8 hours ago
Then again, it will probably not stop someone who is determined. Same as with other legislation really.
roenxi 11 hours ago
pip install -U heretic-llm && heretic Qwen/Qwen3.5-4B
let alone people just putting the weights up in a torrent. All assuming that someone even tried to ban abliterated models.
Sayrus 11 hours ago
galangalalgol 10 hours ago
NewsaHackO 10 hours ago
Sharlin 9 hours ago
nativeit 9 hours ago
goodmythical 2 hours ago
Do you really believe that all of these major non-profits are advertising, encouraging, and participating in the use of an illegal network protocol?
Using any network protocol to violate copyright law on the other hand, is and has been illegal. But it's the violation of copyright, not the network protocol.
Saying torrenting is illegal is like saying ftp is illegal.
quotemstr 9 hours ago
roenxi 8 hours ago
And compared to torrents abliterated models are more complicated to identify, harder to suppress and there is a lot less reason for anyone to care.
RIMR 7 hours ago
vman81 2 hours ago
ben_w 11 hours ago
If you think closed source software/binaries only is bad, wait until you see how awful the state of the art is with a clear-as-mud bucket of matrix weights.
We know it's possible to train an LLM to secretly respond to certain trigger phrases, and last I checked these could only be detected with the assistance of whoever chose those phrases.
The trigger condition for such backdoors is not something anyone can do a systematic brute-force check for, for the same reason we had to invent LLMs in order to do natural language processing: combinatorial explosion.
Passing around open weight models from known sources is already asking you to trust those sources; because of how difficult this is to do correctly even without deliberately inserting such things, we still don't know if China has already put such trigger conditions into their models despite headlines such as these: https://venturebeat.com/security/deepseek-injects-50-more-se...
Regardless of if it was deliberate or not, we don't know if we caught all of these misbehaviours. We don't know how to.
And note, I'm not saying "and therefore you should trust the Big Name Models". If open weight models score 2/100 in this context, closed ones score 1/100.
mordae 10 hours ago
With proprietary hosted weights you can be specifically targeted and you would not be able to reproduce nor prove anything.
Poisoning open models would be of short-term benefit to China only if they could target US (and maybe EU + Commonwealth) specifically. Damaging anyone else would be a net loss and would erode the partnerships and alliances they are trying to build elsewhere. So it's a fire-once weapon with a huge risk of collateral damage.
Much more plausible is simply making the models ideologically biased, but as history teaches us, preferring ideology or religion over science is a well-known path to ruin. It would be weird to simultaneously warn public not to use their own open models, so.
I think the most plausible explanation for open models is simply that Huawei wants more customers and is willing to compete on the hardware front.
ben_w 8 hours ago
No, you actually cannot. Not in general and without already knowing what the whole trigger pattern is. It's absolutely possible to put in a trigger that only fires while working on backend code on a specific date in a specific company by a specific github username, and no way to find this except by trying that combination, thanks to the terrible state of current mechanistic interpretability tools.
Remember: an AI model is not code. Solving this problem is as hard as the entire alignment problem.
The companies at the bleeding edge of research into this topic do not know how to reliably perform the kind of thing you suggest here.
The only reason we can point at DeepSeek-R1 and say the following, is because we can guess the magic keywords:
we found that when DeepSeek-R1 receives prompts containing topics the Chinese Communist Party (CCP) likely considers politically sensitive, the likelihood of it producing code with severe security vulnerabilities increases by up to 50%.
- https://www.crowdstrike.com/en-us/blog/crowdstrike-researche...> Poisoning open models would be of short-term benefit to China only if they could target US (and maybe EU + Commonwealth) specifically. Damaging anyone else would be a net loss and would erode the partnerships and alliances they are trying to build elsewhere. So it's a fire-once weapon with a huge risk of collateral damage.
This "fire-once weapon" has already been fired, and appears to be a massive foot-gun for every model on a near-continuous basis.
Nobody would use LLMs if the trust deficit alone was a sufficient argument.
> Much more plausible is simply making the models ideologically biased, but as history teaches us, preferring ideology or religion over science is a well-known path to ruin. It would be weird to simultaneously warn public not to use their own open models, so.
"Ideologically biased" is the alternative explanation for the already-observed output of DeepSeek-R1. We can't tell which explanation, malicious or accidental bias, is the actual cause.
monocasa 6 hours ago
Finding unknown backdoors in models is NP hard.
luxpir 11 hours ago
mitxela 10 hours ago
redoxate 10 hours ago
api 10 hours ago
Qwen3 and Gemma level models that run on mid-high end laptops and desktops can be pretty good. Not frontier grade, but shockingly competent for something that runs on a single PC. But the hardware you need to run those fast is at least $1000-$2000. Cheap hardware can run them, but slooooooow.
imhoguy 9 hours ago
ourcat 8 hours ago
Also tried the "Locally Uncensored" setup on a 3060 laptop, which worked surprisingly well.
luxpir 8 hours ago
petra 2 hours ago
bilsbie 10 hours ago
simmerup 10 hours ago
See, the various banned porn varieties for an easy example
RIMR 7 hours ago
And calling those things "books" is just nonsense. You know what we are talking about when we say "books", and it isn't that.
simmerup 5 hours ago
There's a reason people hated Grok for sexualising children
petra 10 hours ago
api 10 hours ago
IMO math is free speech, and outlawing math is censorship.
Ajedi32 7 hours ago
kelnos 2 hours ago
totetsu 37 minutes ago
erremerre 2 hours ago
_0xdd 6 hours ago
Bluestein 4 hours ago
c0wb0yc0d3r 10 hours ago
Why don’t people who release python projects ever encode the venv steps into the installer? Can’t pip just do that step for the user?
sgarland 10 hours ago
bdavbdav 20 minutes ago
TristanDaCunha 3 hours ago
nine_k 3 hours ago
Everything can be turned into a weapon of murder if there's motivation. The motivation is key, not the tool.
petra 2 hours ago
Than ask it to seek vulnerabilities in modern technologies and systems.
nateb2022 8 hours ago
N_Lens 17 hours ago
tacomagick 14 hours ago
p-e-w 10 hours ago
nateb2022 8 hours ago
> The claims seem a bit overstated though, since the metrics mentioned are cherrypicking refusal count and KL divergence, both of which make the outcome seem the most dramatic.
is right out of an LLM. It's the kind of language I'd expect out of a thinking trace also mentioning "boundaries" and "oracles" and "contracts."
phoronixrly 12 hours ago
chmod775 10 hours ago
Bluestein 9 hours ago
dormento 4 hours ago
FrustratedMonky 9 hours ago
It submits prompts that get refused, then detects and modifies the weights responsible?
Like brain surgery?
StevenWaterman 9 hours ago
kbelder 4 hours ago
Svoka 5 hours ago
jimmy76615 9 hours ago
StevenWaterman 9 hours ago
sgc 8 hours ago
itsmeduncan 4 hours ago