[jke_kang]

People seem to conflate "made in China" with "can't be trusted." id argue the bigger distinction is open vs. closed. An open model can be audited, fine-tuned, and technically run entirely on your own hardware. A closed model is basically "trust us."

[mrinterweb]

Open weight models are much more auditable than closed models, but could still hide backdoors that could be near impossible to detect.

[chrsw]

Correct. We need open weights, open code and open data. If nobody else can reproduce what someone did there will always be security questions. Even if we can reproduce it there could still be security concerns but it's more realistic to investigate yourself.

[nl]

I'm all for open models, but people seem to misunderstand what they are. They aren't the same thing as open source code!

> open weights, open code and open data

Even if you have all these things you still can't replicate a model because of randomness.

You can backdoor a model with less than 1000 examples and it is impossible to detect.

[2sk21]

Yeah - we also don't know if the models from OpenAI and anthropic are back-doored either.

[chrsw]

You don't want to replicate the exact model, you want to build a system of similar capabilities.

[nl]

Great, but that seems a different concern to the auditability of a model.

You can take the code for Kimi K3 now, take the training framework from Prime and the data from Olmo, spend some money on RL environments and some more money (!) on GPU training and end up with a system of similar capabilities.

But that's completely different to being able to audit Kimi K3. Even if you had the exact code, data and training environments it is impossible to verify that the model you have came from that.

[Ericson2314]

Deterministic seed

[nl]

Deterministic seeds barely work on a single machine, small scale training run.

They just don't work at all on a many month long, 100K+ GPU cluster training run.

[fc417fc802]

While using floating point? Not happening. You'd have to switch to fixed point, not just for the models themselves but also _all_ the training code (ie backprop).

Even then you'd still need to account for order of events when an entire cluster of GPUs is involved. Also don't forget to account for any synthetic data sources. Or even non-synthetic for that matter - does your pipeline do any image resizing on the fly? Better make sure that's fully deterministic between machines (it almost certainly won't be).

It's theoretically possible but I don't expect it to materialize any time soon.

[nl]

> theoretically possible

I mean I guess, but not in a performant way if there are ever any hardware failures. And with 100K GPUs there are multiple hardware failures per day.

[essentia0]

Exactly what are the possible 'security issues' of self hosting an open weights model?

[perching_aix]

It may have been backdoored during training, potentially causing it to randomly start wreaking havoc at runtime, possibly in a clandestine manner (e.g. sneaking in bugs into generated code).

[miyoji]

This isn't a security issue related to self-hosting, it's a security issue related to use and it is shared entirely by closed weights models. Anthropic could easily be sneaking bugs into your generated code, too.

[perching_aix]

Correct, that was not my point either.

[utilize1808]

e.g. be trained to favour including compromised dependences into your projects.

[urams]

> We need open weights, open code and open data.

Even with this, the cost of verification would be enormous. You would need a massive cluster to repeat the training E2E.

[throwaw12]

> could still hide backdoors that could be near impossible to detect.

But it won't change after you download it, so you can isolate those problematic cases and use another model for different use cases

[wyrdcurt]

In my opinion, the big issue with that argument is that advances in interpretability research and steering conceivably could, and probably will, render moot that (as of now, purely hypothetical) risk of subtle sabotage for open-weight models... but not for closed models.

[_factor]

It’s not hypothetical. Magic strings are a known and implemented feature for standard model interaction. Nearly impossible to detect unless you know where to look with current technology.

[CamperBob2]

As long as I can say, "Model A, look for security holes in this code by Model B," I don't see this being a serious problem.

It's when the vendors and/or governments in charge of Model A decide that I'm not allowed to do that, that I have a problem.

[wyrdcurt]

Maybe I should clarify. As I understand it, the kind of vulnerability being discussed is something like a Chinese model invisibly "realizing" that it's working on an American project, and then deliberately leaving subtle security bugs in its generated code for Chinese hackers to later exploit. As far as I know, that scenario is hypothetically possible, but has never been demonstrated to happen in the wild. Admittedly, I could be wrong about that! If anyone has evidence to the contrary, I'd love to see it.

Of course, one could retort that gathering that evidence may be nearly impossible now, but my point stands: in the future it might/probably will be possible to properly audit open-weight models. Closed models, on the other hand, will always be a black box.

[utilize1808]

They can just favour some specific versions of some library that's been compromised. Unlike introducing bugs / flaws directly in the source code, they can claim plausible deniability, and it's much easier to implement without compromising the general coding capabilities of the models.

[wyrdcurt]

I'm talking about using mechanistic interpretability to see the model's intent. If it is deliberately using compromised libraries to weaken some code's security, there's going to be a signal in its hidden activations that it's doing so.

Finding these kinds of activations is something Anthropic is actively researching [1] but they're the only ones who can use those techniques to see Claude's intent. On the other hand, if a model is open-weights, in theory whoever is running the model could look inside the activations at runtime to see if a hidden vector associated with "deception" or "sabotage" is being activated [2].

[1] https://transformer-circuits.pub/ [2] https://arxiv.org/pdf/2509.03518

(Those sources are just a couple of relevant starting points I could find without much effort, there is also https://www.neuronpedia.org/ if one is interested in seeing interactive demonstrations of interpretability concepts)

[codedokode]

Cannot non-Chinese closed weights model do the same?

[kiicia]

which is moot point, if open model is hard to fully audit, then closed model is complete enigma and you should be more scared about closed models

[galacticaactual]

Oh really. How'd that work out for security in open source.

[weird-eye-issue]

I think that perception of China has been shifting and will look quite different over the next few years