DeepSeek generates insecure code if you mention Tibet. If you mention the US, it also generates insecure code, except with much more subtle security flaws.
That's certainly no accident.
https://www.crowdstrike.com/en-us/blog/crowdstrike-researche...
They claim the extract line is insecure, but never explain why, and without showing the rest of the code (what is $requiredHeaders? If it's sanitized this is a non issue) you can't even tell if it's secure or not.
The variable names being wrong (the $PayPal- ones) is probably just a "mistake" the model made, but it's not a vulnerability either.
This article could be just "burglars are burgling in your neighborhood, install our burglar alarm" from crowdstrike just as well.
> Do not use extract() on untrusted data, like user input (e.g. $_GET, $_FILES). If you do, make sure you use one of the non-overwriting flags values such as EXTR_SKIP and be aware that you should extract in the same order that's defined in variables_order within the php.ini.
Looks like calling it can shadow previously defined, unrelated variables?
Edit: On re-reading your comment, yes, if $requiredHeaders is previously sanitized then the code is technically safe. But it still presents as an insecure coding practice.
The link you cited postulates it is accidental.
> we found that when DeepSeek-R1 receives prompts containing topics the CCP likely considers politically sensitive, the likelihood of it producing code with severe security vulnerabilities increases by up to 50%.
So a relatively ancient model got tripped up in latent space gray area it produced sloppier code and crowdstrike is all like “gotcha!” Sounds like the basic thesis? Not great support, more like FUD
> got tripped up in latent space gray area
>relatively ancient model
"Intentional" is an interesting point to press me on. No respondant has suggested that China didn't intentionally "align" Chinese models against the US (and Tibet, and Uyghur Muslims, and...). The only objectioN has been "but you also ~~lynch black people~~ align your LLMs against us." Classic Soviet-style whataboutism.
>I wasn't crying foul because it's not aligned with the reality I want.
The reality I want is one where everyone argues in good faith :)
The mechanism is likely a bit inverted, it’s the weights that have been redacted, but the effect is that weights that were interfered with are affecting the problem solving abilities of the LLM - I mean, it’s insecure bad code, not a backdoor, right?
>No; it’s a signal of lobotomy. Models get dumber near where you sensor [sic] them.
"Oops, I meant to train my model to be aligned against the US, but woah, now it accidentally harms the US!! My bad!!"
Not convincing, sorry.
>I mean, it’s insecure bad code, not a backdoor, right?
Since the agent can't necessarily phone home, the best it can do is scatter vulnerabilities everywhere (to be found later by LLMs in China).
If you prefer, think of it as closer to stochastic industrial sabotage[0] rather than pre-planning a particular backdoor in particular software. Different tools, different tactics!
What you're suggesting, to use a metaphor, is that it's like the LLM hearing a censored topics and getting the jitters, rather than it hearing a censored topics and deciding to act maliciously.