AppleNeuralHash2ONNX
onnxjs
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AppleNeuralHash2ONNX | onnxjs | |
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107 | 3 | |
1,517 | 1,565 | |
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0.0 | 4.9 | |
over 2 years ago | over 2 years ago | |
Python | TypeScript | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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AppleNeuralHash2ONNX
- Legit app in Google Play turns malicious and sends mic recordings every 15 minutes
- Daily General Discussion - October 27, 2022
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How did apple train its cp filtering algorithm?
Perhaps you're referring to the hash collisions that were generated for the client-side NeuralHash which was reverse engineered about a year ago: https://github.com/AsuharietYgvar/AppleNeuralHash2ONNX/issues/1
- [Request] A way to remove Apple’s new NeuralHash ( iCloud CSAM scanner )
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Google AI flags parents' accounts for potential abuse over kid's photos
Except Apple’s hashes have collisions where images that are similar in content but not identical will have the same hash. Meaning their process will have the same result: benign images being flagged as CSAM. See an example here https://github.com/AsuharietYgvar/AppleNeuralHash2ONNX/issues/1
- Apple Remains Silent About Plans to Detect Known CSAM Stored in iCloud Photos
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Apple should scan iPhones for child abuse images, says scanning technology inventor
perceptual hashes are completely broken due to false positives, like making a picture of a dog having the same hash as CSAM images. They are vulnerable to collision and have no preimage resistance, the most important feature. Because of that you can DOS conversations and people by sending dog images with the same hash as a CSAM: https://github.com/AsuharietYgvar/AppleNeuralHash2ONNX/issues/1
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UK cybersecurity chiefs back plan to scan phones for child abuse images | GCHQ | The Guardian
Specifically the fact that you can have one hash on two images, for example. There are other ways to abuse the CSAM system, which is confirmed by several researchers (one, two). And Apple saying it's not a concern... only to pull back on these plans.
- Frage zur drohenden Chatkontrolle
- Apple’s CSAM troubles may be back, as EU plans a law requiring detection
onnxjs
- Alternatives to tensorflowjs
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Run WASM, a client side Python runtime
Tensorflow (and by extension Keras) offload most of the actual work to C++ or C, so having those compile to WebAssembly would (I imagine) be a herculean effort.
Instead, The TF team maintains TFJS, which can run on WebAssembly[0].
There are also tractjs[1], and onnyxjs[2], both of which allow you to run (most) ONNX models (which is an open standard for specifying ML models) using WebAssembly and WebGL(only onnyxjs supports WebGL). A bunch of frameworks (caffe, pytorch, TF) support exporting to/importing from ONNX.
[0] https://blog.tensorflow.org/2020/03/introducing-webassembly-...
[1] https://github.com/bminixhofer/tractjs
[2] https://github.com/microsoft/onnxjs
- AppleNeuralHash2ONNX: Convert Apple NeuralHash Model for CSAM Detection to ONNX
What are some alternatives?
GmsCore - Free implementation of Play Services
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
hardened_malloc - Hardened allocator designed for modern systems. It has integration into Android's Bionic libc and can be used externally with musl and glibc as a dynamic library for use on other Linux-based platforms. It will gain more portability / integration over time.
run-wasm - Run WASM based code executions in the browser easily
tractjs - Run ONNX and TensorFlow inference in the browser.
OpenWifiPass - An open source implementation of Apple's Wi-Fi Password Sharing protocol in Python.
ExpansionCards - Reference designs and documentation to create Expansion Cards for the Framework Laptop
neuralhash-collisions - A catalog of naturally occurring images whose Apple NeuralHash is identical.
neural-hash-collider - Preimage attack against NeuralHash 💣
img-cryptor - Image AES256 crypt-decrypt
nhcalc - Compute NeuralHash for the given image