Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

A catalog of naturally occurring images whose Apple NeuralHash is identical

github.com

Post reply on HN
Print view View original

101–110 of 304 posts

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#101

Post by Lamad123 »

AnonC wrote: post #74

A very relevant point on this entire discourse about Apple’s on-device CSAM scanning: According to the U.S. law, key snippets of which are quoted on the Stratechery blog (by Ben Thompson), Apple isn’t obligated to scan for CSAM. It’s only obligated to act on CSAM if it finds them. While it’s good for Apple to scan on its systems (iCloud) like Facebook, Google and other companies do on their servers, it’s inappropriat…

They say only if they find 30 matching images, they'd act. So if they find 20 or 29 and don't report them, they are actually breaking the law!! I am wondering why they chose that magical number!

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#102

Post by mlajtos »

woofie11 wrote: post #80
StrLght wrote: post #75

I don't really get what this repository is trying to achieve and what's the point of collecting collisions. Collisions will happen, that's just how it is with hashes. It's already a public knowledge that Apple has 2 more systems (some server-side verification and a manual check later) to prevent false-positives. So what's the point of researching collisions in NeuralHash?

No. Most proper cryptographic hash systems (e.g. used for verifying files, rather than data structures) never have collisions. Try to find a SHA256 collision. Anywhere, ever, in the history of mankind. This isn't for lack of looking. A lot of very smart people have looked for them. If you find one, I bet you'll be eligible for a tenured faculty slot at a good university, if not more. A whole world of secure systems w…

If I found one collision by accident, would that be any significant?

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#103

Post by theshrike79 »

AmericanChopper wrote: post #84
xadhominemx wrote: post #48

Earlier quoted context omitted.

They don’t take any action unless you have 30 matches in the database, which will not happen by chance.

It could happen on purpose if I intentionally send you 30 colliding images. I don’t know how iMessage handles images, but WhatsApp for example will put them directly into your photo library (and from there directly into iCloud if you’ve got syncing enabled). Perhaps I could even do that without revealing my motives to you.

It would STILL just mildly inconvenience the Apple wageslave tasked with checking the notifications.

If you send actual CP, then that's a wholly different matter.

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#104

Post by fleddr »

AnonC wrote: post #74

A very relevant point on this entire discourse about Apple’s on-device CSAM scanning: According to the U.S. law, key snippets of which are quoted on the Stratechery blog (by Ben Thompson), Apple isn’t obligated to scan for CSAM. It’s only obligated to act on CSAM if it finds them. While it’s good for Apple to scan on its systems (iCloud) like Facebook, Google and other companies do on their servers, it’s inappropriat…

"While it’s good for Apple to scan on its systems (iCloud) like Facebook, Google and other companies do on their servers, it’s inappropriate to do it on individual devices"

I would even challenge the justification to do this on servers, unless the data is public. If it's behind a personal login, you might as well consider it personal property/data. I find the distinction of where data is stored not very meaningful.

Allowing things to be searched for criminal content just because it's not in your immediate physical sphere makes no sense. It doesn't work like that in the physical world either. When I send a letter, and it leaves my house, no authority has the right to check its contents without a legitimate reason. Likewise, if I put stuff in a storage box in some warehouse, no authority can search it without a warrant.

Note that I'm talking about personal storage (iCloud, Gmail), not public social networks like Facebook.

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#105

Post by theshrike79 »

teekert wrote: post #85

I still think the biggest problem is that at some point a human is going to look at a false positive, this may be picture of my naked children and this human may not have the best intentions with my picture. That said, Nextcloud is my backend and I do not upload anything to iCloud (except for MS authenticator 2fa backups), so I'm safe right?

So your threat model here is that the person at Apple tasked to check for Child Porn is an actual Paedophile and might accidentally see a false positive of your child's naked photo?

You do know that they don't see the whole photo at full megapixel resolution? They're just given "a visual derivative" of the photo for checking.

Also, you really think that the persons tasked with this process are just randos off the street and not vetted specifically?

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#106

Post by PolCPP »

ithkuil wrote: post #24
Retr0id wrote: post #12

Earlier quoted context omitted.

It doesn't really matter whether all images are uploaded, or just 1 in x (for large value of x), due to the Panopticon effect.

Let's not forget what the alternative is: this is about images that are uploaded on icloud anyway. The alternative is to upload the image in clear (or with ane encryption key that apple controls), and let apple run the CSAM filter on their servers. Apple now has the ability to encrypt the images before sending them to icloud, with a private key you own. Except that some percentage of images that match the CSAM finger…

Theres not even a need to do that, upload the encrypted image and its neuralhash.

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#107

Post by jtbayly »

mrweasel wrote: post #40
roody15 wrote: post #33

Apple has yet to make a valid reason for implementing client side CSAM scanning. According to Apple only images that will be uploaded to iCloud will be scanned. If this is the case there is zero reason to scan locally and you can just scan the uploaded image once it is on the server. Apple has not implemented E2E nor has it released a statement indicating this will be implemented in the future.

One reason for client side could be to save on datacenter compute resources. That would seem like a perfectly valid reason, if that’s their reasoning.

If that’s a valid reason to steal electricity and compute resources from your customers, then why not go the whole way and use all the Mac’s as storage and compute for iCloud?

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#108

Post by UncleMeat »

AmericanChopper wrote: post #84
xadhominemx wrote: post #48

Earlier quoted context omitted.

They don’t take any action unless you have 30 matches in the database, which will not happen by chance.

It could happen on purpose if I intentionally send you 30 colliding images. I don’t know how iMessage handles images, but WhatsApp for example will put them directly into your photo library (and from there directly into iCloud if you’ve got syncing enabled). Perhaps I could even do that without revealing my motives to you.

I mean, you could send them actual illegal content too.

And human reviewers are in the process. If you've got 30 matches and they are all pictures of bridges or whatever do you think the FBI is going to show up at your house?

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#109

Post by monkeynotes »

ajb wrote: post #97
scotty79 wrote: post #71

Why are exact collisions interesting? They are not intended to be compared exactly. This algorithm doesn't even give exact matches for the same image on different hardware. https://github.com/AsuharietYgvar/AppleNeuralHash2ONNX Note: Neural hash generated here might be a few bits off from one generated on an iOS device. This is expected since different iOS devices generate slightly different hashes anyway. The reason…

If you can get exact collisions, this can be gamed. For example, suppose there are two rival gangsters. One wants to set the police on his rival. He knows that a certain (innocuous) image is on his rival's phone. So he pays someone to generate a fake child-porn image with the same neuralhash, and ensure that it gets into the child porn DB. Then, apple reports the rival to the police, and they come and investigate him…

I think before a criminal investigation, or any investigation at all is pursued, a human verifying the images would dismiss the false positive.

I would think surreptitiously placing actual child porn on a rival's phone/computer would be much, much more effective.

Cybercriminals could likely do all this remotely. Phish for apple account login, upload images. Done.

Re: A catalog of naturally occurring images whose Apple NeuralHash is identical

#110

Post by theshrike79 »

simion314 wrote: post #35
ithkuil wrote: post #24

Earlier quoted context omitted.

Let's not forget what the alternative is: this is about images that are uploaded on icloud anyway. The alternative is to upload the image in clear (or with ane encryption key that apple controls), and let apple run the CSAM filter on their servers. Apple now has the ability to encrypt the images before sending them to icloud, with a private key you own. Except that some percentage of images that match the CSAM finger…

But if Apple really cares about children why they did not done this scans in iCloud like all the others? Did not care as much as Google or Facebook? Seems to me like Apple does not care at all and seems more like a dev with big ego wanted to add neural hashes to his CV but if you can explain how Apple cared for children all this years but only now are doing something I really want to see the explanation

Because Apple is the one company that actively tries not to know anything about you.

FB and Google will exhaustively analyse every single facet of your online presence and use your pictures to train their ML models for face detection and object detection.

Apple, on the other hand, even explicitly splits Map directions to segments so that they can't know where you left from and where you are going to.

Post reply on HN