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Stealing Reasoning Traces from Proprietary LLM APIs

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Re: Stealing Reasoning Traces from Proprietary LLM APIs

#51
> For some AIME problems Opus 4.8 sometimes states the answer before deriving it. We find that the API summary does not always preserve this distinction, and can instead make the reasoning appear like a clean derivation.

No surprise here but good to have more confirmation that they just put all that in the training data. And based on the "reasoning", the models have some form of index of those problems (or they are HEAVILY trained on them).

Re: Stealing Reasoning Traces from Proprietary LLM APIs

#52

The problem with this kind of excellent work is that the response to it is always to say "Fuck the user". For example, when there was a paper that came out showing that having model logprobs makes distillation an order of magnitude easier, the closed LLM providers instantly yanked out support for getting the full logprobs at every time step. You get at most top 10 candidates now and I'm sure even that's on the choppi…

Dario is a cunning business man that won't hesitate to say whatever the fuck he needs to get the US government to exercise some regulatory capture to favor anthropic.

Re: Stealing Reasoning Traces from Proprietary LLM APIs

#53

Is this how the eastern labs "distill" SOTA models? If you can play it right, you don't even need to send suspicious prompts to the frontier models. Just use them for regular tasks, extract the encrypted COT blocks and replay it to a cheaper model to get the plain text COT. But the real question is: Is it okay to steal from a thief's hoard?

The reasoning blocks are not stolen/mined from the internet at large directly. They’re the result of a lot of research, time, money, and expertise into creating a reasoning model. To me the answer is quite clearly no, especially when the encrypted blocks demonstrate they want to protect it.

Stuff available on the internet is also the result of a lot of research, time, money, and expertise. And AI companies taught us that it’s OK to yoink whatever is not bolted to the ground, even when it is illegal to do so.

Re: Stealing Reasoning Traces from Proprietary LLM APIs

#55
post #44

Earlier quoted context omitted.

Yes, this storage would be growing exponentially making the disk space and latency problems harder (add the disaster recovery/backups). I think the choice of using client side is not too bad if you ensure that its secured properly. Also the company can excuse itself from the liability of storing sensitive data on its servers, thats a big deal in itself to be compliant for enterprise audits 1. The down side is that it…

Having thought about this a little more, it's clear that server-side storage is not compatible with Zero Data Retention (ZDR). However, in non-ZDR settings, it seems likely that the providers are capturing all that data anyway? > a per user key would have solved this issue for sure It would have helped with PII leakage, but not with plain-text trace extraction attacks, right?

Per user encryption key ties it with the user session (assuming you do authentication properly), no one else can access it. User being able to see the information is not really an attack vector in this case.

The compliance rules at times are outdated and people skirt around them by following the worded rule instead of the intent.

Re: Stealing Reasoning Traces from Proprietary LLM APIs

#56

Is this how the eastern labs "distill" SOTA models? If you can play it right, you don't even need to send suspicious prompts to the frontier models. Just use them for regular tasks, extract the encrypted COT blocks and replay it to a cheaper model to get the plain text COT. But the real question is: Is it okay to steal from a thief's hoard?

Not necessarily. There's a million ways to jailbreak any current model to show the trace and bypass all guardrails, or hijack and modify it. It's just one of them.

Re: Stealing Reasoning Traces from Proprietary LLM APIs

#58
post #51

> For some AIME problems Opus 4.8 sometimes states the answer before deriving it. We find that the API summary does not always preserve this distinction, and can instead make the reasoning appear like a clean derivation. No surprise here but good to have more confirmation that they just put all that in the training data. And based on the "reasoning", the models have some form of index of those problems (or they are H…

Didn't we see this with Fable 5 on multiple benchmarks?

Re: Stealing Reasoning Traces from Proprietary LLM APIs

#60

Is this how the eastern labs "distill" SOTA models? If you can play it right, you don't even need to send suspicious prompts to the frontier models. Just use them for regular tasks, extract the encrypted COT blocks and replay it to a cheaper model to get the plain text COT. But the real question is: Is it okay to steal from a thief's hoard?

> But the real question is: Is it okay to steal By definition it cannot be stealing since you're paying for the tokens. It may be against their ToS, depending on what you end up doing with those tokens, but it cannot be stealing. If they charge by the token, all your tokens are belong to you :) I also find it very strange that everyone sort of accepts their ToS like no big deal. Imagine MS using the same terms for th…

I love how some of the biggest advancements in llms came from the Chinese labs, yet people still jump to distillation being unreasonably effective. Distillation is very good at creating smaller models from large ones sure, but nothing to me indicates it is 'unreasonably effective' compared to all the other bells and whistles being iterated on
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