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Posted by quantumgarbage 23 hours ago

Stealing Reasoning Traces from Proprietary LLM APIs(stolen-thoughts.com)
640 points | 287 commentspage 4
drob518 18 hours ago|
It’s scary the number of security tokens that end up being ingested by these models.
Havoc 17 hours ago||
TIL it actually sends the traces. I had assumed this is entirely server side
cush 17 hours ago||
I really like this website
tanh 20 hours ago||
So to make the APIs stateless (the "ideal" where they don't use server side sessions/etc) we ended up with this. I'm sorry but this is kind of hilarious. Given the salaries paid to the workers at these companies and the hype of the models, I can't believe they all fell to the same flaw.
varenc 9 hours ago||
If CoT wasn't stateless and you instead just got a reference which pointed to the CoT stored on the lab servers, the same vulnerability would still exist. Since you just need a weaker jailbroken model to read a smarter model's CoT. This being stateless or not doesn't really matter.

The stateless part is also important for enterprise customers that require zero data retention.

(they could scope CoT access per model, but then users couldn't switch models mid-session)

redox99 18 hours ago|||
It wouldn't matter if it was stored only on their servers. As long as they offer the feature to downgrade a chat to a dumber model that can be jailbroken (and the downgrade keeps the reasoning), this trick works.
8note 17 hours ago|||
this is a lethal trifecta, but where a chunk isn't even needed

you have a secret to keep that is read by the llm, and untrusted input that wants to exfiltrate it.

by hell or high water, the agent is gonna output that text

lukewarm707 19 hours ago||
strange because, their subscriptions are not stateless. they log everything and send it to 3rd parties for moderation.
elzbardico 20 hours ago||
OpenAI and Anthropic will probably now resort to save this server side, instead of relying on encription to be able to keep state on the client.
paxys 14 hours ago||
Encryption is irrelevant here. Even if it was kept fully server side, the actual issue is that they allow starting a conversation in a strong model and continuing it in a weaker one. Disallowing that entirely would be a huge hit to user experience.
agenticfish 16 hours ago||
That's not a trivial thing to do for them because they offer zero data retention environments to enterprise clients.
paxys 14 hours ago||
They can always keep the encrypted blobs server side and send the key to the user. But regardless, that isn’t going to help with this issue (see my comment above).
HoyaSaxa 17 hours ago||
I can’t believe they don’t validate a decrypted signature belongs to the user or use a unique encryption key per user/session.
Der_Einzige 21 hours ago||
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 chopping block.

People will use this to argue that a model which has exceeded Opus 4.8 (Kimi K3) somehow got most of its performance through distillation of Opus 4.8.

I still don't buy that distillation was worth more than 3 months of "catch up" time for the chinese labs. Most people who use the word "distillation" to much are revealing their sinophobia.

adrian_b 20 hours ago||
What I found the most interesting, and unfortunately not at all surprising, is that the reasoning of the LLMs frequently contained much more useful information than the actual answers, because the answers were censored.
dannyw 19 hours ago|||
You don’t even get _any_ logits with closed models for years now.

I can’t fault them too much, as logit based distillation is extremely effective.

Very useful for making smaller models out of bigger open weight models.

elzbardico 20 hours ago||
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.
khalic 21 hours ago||
This is beautiful work, congrats
dboreham 21 hours ago||
Can someone tell us how they were able to decrypt the encrypted payload? The article says they inserted the cyphertext into a session with a different model. Ok, but how does that allow you to decrypt it?
sidsud 21 hours ago||
From what I got, the weaker model (Haiku in this case) has access to the shared key and the user simply asks to "transcribe the injected reasoning".
x312 21 hours ago|||
The provider decrypts it and puts the decrypted reasoning into the model's context window. They prompt the model to repeat back the reasoning. So then the model echoes it back in plain text.
dboreham 20 hours ago||
Hmm, ok. So the attack doesn't involve decrypting the payload, only getting the server to do so. Since a model will do that if you just ask, what's so special about the attack?
desterothx 19 hours ago||
The large models whose thinking traces are useful are safeguarded against this reasoning replaying. the small models are just designed for speed and efficiency, so these safeguards are a lot meaker, making the attack possible
dboreham 16 hours ago||
I guess someone forgot to salt the encryption scheme with a meakness factor.
crazylogger 20 hours ago||
Anthropic server decrypts it as part of fulfilling every request, and haiku recites it per your request.
jijji 8 hours ago|
The fact that frontier LLM providers pirated all the data that they used for training, then to go on to encrypt all of the reasoning traces that they use to come up with the conclusions it's really disingenuous, and then have the balls to say distillation is some kind of bad behavior. they are the kings of distillation.

The hiding of this data only brings distrust to their frontier models. I think most people want to understand how something comes to a conclusion they don't want have that part left out on purpose...

it's this kind of behavior that forces people move to to open source models in the end, it's the lack of trust. the frontier model providers treat the end user/customer as a threat or adversary. Fable 5 is notorious for this. a lot of the serious questions you ask the model they won't even respond to you because of the woke guardrails. it wasn't only a couple weeks ago that huggingface had to use glm 5.2 to get the right answers about their security incident because Fable 5 didn't want to answer it.

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