Earlier quoted context omitted.
But why low resolution porn?
So that you are able to bypass the manual reviews. It still looks like CSAM, but it isn't.
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Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
171–180 of 363 posts
Re: Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
#172This is just getting wilder and wilder by the day, how spectacularly this move has backfired. As others have commented, at this point all you need is someone willing to sell you the CSAM hashes on the darknet, and this system is transparently broken. Until that day, just send known CSAM to any person you'd like to get in trouble (make sure they have icloud sync enabled), be it your neighbour or a political figure, an…
Imagine being a parent that made pictures of their own children that bathed naked in their own backyard. I don't know about you, but my parents certainly have lots of embarassing pictures of me in their photo album. There will be so many false positives in that system, it's ridiculous. It doesn't necessarily have to be a false colliding hash, but legitimate use cases that - by definition - are impossible to train neu…
That’s not how Apple’s system works. It’s not an image classifier. Only actual images that are derivatives of known CSAM images (a database of 250k images) will match. Random images of kids will not match those at any greater frequency than any other image.
Re: Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
#173The integrity of this entire system now relies on the security of the CSAM hash database, which has just dramatically increased in value to potential attackers. All it would take now, is for one CSAM hash to be known to the public, then uploading collided iPhone wallpapers to wallpaper download sites. That many false positives will overload whatever administrative capacity there is to review reports in a matter of da…
Before they make it to human review, photos in decrypted vouchers have to pass the CSAM match against a second classifier that Apple keeps to itself.
Re: Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
#174Earlier quoted context omitted.
> A hash collision allows you to create material that matches CSAM signatures, without being CSAM. This is not correct. Hash collisions won’t match the visual derivative.
That bit you quoted seems to be actually correct. It does not mention visual derivatives at all. That said I think your statement is a bit too strong, but generally true. A hash collision is not going to inherently be visually confusing. However you claim that it is impossible for an image to be both visually confusing and a hash collision, which seems unlikely. The real question is going to be how much more effort i…
I didn’t claim it was impossible, just that hash collisions won’t match both.
Also, the information needed to create a full match simply is not available.
Re: Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
#175The integrity of this entire system now relies on the security of the CSAM hash database, which has just dramatically increased in value to potential attackers. All it would take now, is for one CSAM hash to be known to the public, then uploading collided iPhone wallpapers to wallpaper download sites. That many false positives will overload whatever administrative capacity there is to review reports in a matter of da…
No, there’s another private hash function that also has to match the known CSAM image for an image to be considered a match.
That one can’t be figured out through this technique.
Re: Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
#176Earlier quoted context omitted.
Imagine being a parent that made pictures of their own children that bathed naked in their own backyard. I don't know about you, but my parents certainly have lots of embarassing pictures of me in their photo album. There will be so many false positives in that system, it's ridiculous. It doesn't necessarily have to be a false colliding hash, but legitimate use cases that - by definition - are impossible to train neu…
That’s not how Apple’s system works. It’s not an image classifier. Only actual images that are derivatives of known CSAM images (a database of 250k images) will match. Random images of kids will not match those at any greater frequency than any other image.
Counter-question: At what point is child porn actually child porn, socially and statistically speaking?
If I share that picture of my child with my friends and loved ones on Facebook - at what "scale" is it considered to be added to that database as child porn?
1k shares? 10k? Who's the one eligible to decide that? The judicatives? I think this scenario is a constitutional crisis because there's no good solution to it in terms of law and order.
Re: Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
#177Despite that Apple scanning our images is a horrible privacy practice, I don't get why 𝚜̶𝚘̶ ̶𝚖̶𝚊̶𝚗̶𝚢̶ some people think this is an ineffective idea. Surely you can easily fabricate innocent images whose NeuralHash matches the database. But in what way are you going to send them to victims and convince them to save them to their photo library? The moment you send it via WhatsApp FB will stop you because (they th…
I believe being downvoted because this is thoroughly covered in the thread. Suggest you read it all again.
Re: Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
#178What are trying to prove here? It takes a human not noticing that a glitchy image of cat is not the same as picture of dog, 30 times. Yea collisions are technically, possible. Apple has accounted for that. What is your point? Hashes are at the core of a lot of tech, and collisions are way easier and more likely to happen in those in many cases, but suddenly this is an issue for ya'll?
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Re: Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
#179Earlier quoted context omitted.
I posted another comment that was misunderstood as well. Folks, no one is proposing to download actual CSAM images to your photo lib. You could be duped thinking you downloaded an image of a beautiful sunset which was carefully manipulated to match the hash of an actual CSAM image.
> You could be duped thinking you downloaded an image of a beautiful sunset If it was anything like the image used to demonstrate this technique on Github, it's unlikely that anyone would describe that sunset as "beautiful". They'd be more likely to describe it as "bugger, this JPEG file is corrupted."
Attacks never get worse over time.
It was quite literally less than 24h from "Oh, hey, I can collide this grey blob with a dog!" to "Hey, this thing that looks like cat hashes to the same thing as this dog!"
You really think this is going to end at this proof of concept stage?
Re: Show HN: Neural-hash-collider – Find target hash collisions for NeuralHash
#180Earlier quoted context omitted.
A hash collision allows you to create material that matches CSAM signatures, without being CSAM. This opens up a new class of attacks. Specifically, many criminal actors don't touch CSAM because it's wrong. But some of these criminal actors will happily abuse legal systems, e.g. SWATTing.
> A hash collision allows you to create material that matches CSAM signatures, without being CSAM. This is not correct. Hash collisions won’t match the visual derivative.
Sorry, this is not even wrong.
The visual derivative is just a resized, very-low-resolution version of the uploaded image. "Matching the visual derivative" is completely meaningless. The visual derivative is not matched against anything, and there is no "original" visual derivative to match against.
If enough signatures match, Apple employees can decrypt the visual derivatives, and see if these extremely low resolution images look to the naked eye like they could come from CSAM. If so, they alert the authorities.. Given a way to obtain hash collisions, generating non-CSAM images that pass the visual derivative inspection is completely trivial.