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.

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)

Cannot non-Chinese closed weights model do the same?