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Confer – End to end encrypted AI chat

confer.to

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Re: Confer – End to end encrypted AI chat

#11
Again with the confidential VM and remote attestation crypto theater? Moxie has a good track record in general, and yet he seems to have a huge blindspot in trusting Intel broken "trusted VM" computing for some inexplicable reason. He designed the user backups of Signal messages to server with similar crypto secure "enclave" snake-oil.

Re: Confer – End to end encrypted AI chat

#12
post #7
post #4

Unless I misunderstand, this doesn't seem to address what I consider to be the largest privacy risk: the information you're providing to the LLM itself. Is there even a solution to that problem? I mean, e2ee is great and welcome, of course. That's a wonderful thing. But I need more.

Looks like Confer is hosting its own inference: https://confer.to/blog/2026/01/private-inference/ > LLMs are fundamentally stateless—input in, output out—which makes them ideal for this environment. For Confer, we run inference inside a confidential VM. Your prompts are encrypted from your device directly into the TEE using Noise Pipes, processed there, and responses are encrypted back. The host never sees plaintext.…

We'll add that link to the toptext as well. Thanks!

(It got submitted a few times but did not get any comments - might as well consolidate these threads)

Re: Confer – End to end encrypted AI chat

#13
post #9

I am confused. I get E2EE chat with a TEE, but the TEEs I know of (admittedly not an expert) are not powerful enough to do the actual inference, at least not any useful one. The blog posts published so far just glance over that.

It seems like the H100 gpu itself has some kind of secure execution environment built in. Not sure of the details but it appears that all data going to and from the gpu will be encrypted.

https://developer.nvidia.com/blog/confidential-computing-on-...

Re: Confer – End to end encrypted AI chat

#14
post #7
post #4

Unless I misunderstand, this doesn't seem to address what I consider to be the largest privacy risk: the information you're providing to the LLM itself. Is there even a solution to that problem? I mean, e2ee is great and welcome, of course. That's a wonderful thing. But I need more.

Looks like Confer is hosting its own inference: https://confer.to/blog/2026/01/private-inference/ > LLMs are fundamentally stateless—input in, output out—which makes them ideal for this environment. For Confer, we run inference inside a confidential VM. Your prompts are encrypted from your device directly into the TEE using Noise Pipes, processed there, and responses are encrypted back. The host never sees plaintext.…

That is a highly misleading statement: the GPU runs with real weights and real unencrypted user plaintext, since it has to multiply matrices of plain text, which is passed on to the supposedly "secure VM" (protected by Intel/Nvidia promises) and encrypted there. In no way is it e2e, unless you count the GPU as the "end".

Re: Confer – End to end encrypted AI chat

#15
post #7

Earlier quoted context omitted.

Looks like Confer is hosting its own inference: https://confer.to/blog/2026/01/private-inference/ > LLMs are fundamentally stateless—input in, output out—which makes them ideal for this environment. For Confer, we run inference inside a confidential VM. Your prompts are encrypted from your device directly into the TEE using Noise Pipes, processed there, and responses are encrypted back. The host never sees plaintext.…

That is a highly misleading statement: the GPU runs with real weights and real unencrypted user plaintext, since it has to multiply matrices of plain text, which is passed on to the supposedly "secure VM" (protected by Intel/Nvidia promises) and encrypted there. In no way is it e2e, unless you count the GPU as the "end".

So what you are saying is that all the TEE and remote attestation and everything might work for CPU based workflows but they just don't work with GPU effectively being unencrpyted and anyone can read it from there?

Edit: https://news.ycombinator.com/item?id=46600839 this comment says that the gpu have such capabilities as well, So I am interested what you were mentioning in the first place?

Re: Confer – End to end encrypted AI chat

#16
post #9

I am confused. I get E2EE chat with a TEE, but the TEEs I know of (admittedly not an expert) are not powerful enough to do the actual inference, at least not any useful one. The blog posts published so far just glance over that.

It seems like the H100 gpu itself has some kind of secure execution environment built in. Not sure of the details but it appears that all data going to and from the gpu will be encrypted. https://developer.nvidia.com/blog/confidential-computing-on-...

Yes, the TEE is CPU + H100 GPU.

Re: Confer – End to end encrypted AI chat

#17

Again with the confidential VM and remote attestation crypto theater? Moxie has a good track record in general, and yet he seems to have a huge blindspot in trusting Intel broken "trusted VM" computing for some inexplicable reason. He designed the user backups of Signal messages to server with similar crypto secure "enclave" snake-oil.

I think there is only so much you can do practically. Without a secure "enclave", there isn't really much you can do. What's your alternative?

Re: Confer – End to end encrypted AI chat

#18
post #7

Earlier quoted context omitted.

Looks like Confer is hosting its own inference: https://confer.to/blog/2026/01/private-inference/ > LLMs are fundamentally stateless—input in, output out—which makes them ideal for this environment. For Confer, we run inference inside a confidential VM. Your prompts are encrypted from your device directly into the TEE using Noise Pipes, processed there, and responses are encrypted back. The host never sees plaintext.…

That is a highly misleading statement: the GPU runs with real weights and real unencrypted user plaintext, since it has to multiply matrices of plain text, which is passed on to the supposedly "secure VM" (protected by Intel/Nvidia promises) and encrypted there. In no way is it e2e, unless you count the GPU as the "end".

It is true that nVidia GPU-CC TEE is not secure against decapsulation attacks, but there is a lot of effort to minimize the attack surface. This recent paper gives a pretty good overview of the security architecture: https://arxiv.org/pdf/2507.02770

Re: Confer – End to end encrypted AI chat

#19
post #10

I don't agree that this is end to end encrypted. For example, a compromise of the TEE would mean your data is exposed. In a truly end to end encrypted system, I wouldn't expect a server side compromise to be able to expose my data. This is similar to the weasely language Google is now using with the Magic Cue feature ever since Android 16 QPR 1. When it launched, it was local only -- now it's local and in the cloud "…

Just like your mobile device is one end of the end-to-end encryption, the TEE is the other end. If properly implemented, the TEE would measure all software and ensure that there are no side channels that the sensitive data could be read from.
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