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Magika: AI powered fast and efficient file type identification

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Re: Magika: AI powered fast and efficient file type identification

#101

Post by tempay »

rvnx wrote: post #94
awaythrow999 wrote: post #92

Wonder how this would handle a polyglot[0][1], that is valid as a PDF document, a ZIP archive, and a Bash script that runs a Python webserver, which hosts Kaitai Struct’s WebIDE which, allowing you to view the file’s own annotated bytes. [0]: https://www.alchemistowl.org/pocorgtfo/ [1]: https://www.alchemistowl.org/pocorgtfo/pocorgtfo16.pdf Edit: just tested, and it does only identify the zip layer

You can try it here: https://google.github.io/magika/ It's relatively limited compared to `file` (~10% coverage), it's more like a specialized classificator for basic file formats, so such cases are really out-of-scope. I guess it's more for detecting common file formats then with high recall. However, where is the actual source of the model ? Let's say I want to add a new file format myself. Apparently only the sour…

Is there anything about the performance on unknown files?

I've tried a few that aren't "basic" but are widely used enough to be well supported in libmagic and it thinks they're zip files. I know enough about the underlying formats to know they're not using zip as a container under-the-hood.

Re: Magika: AI powered fast and efficient file type identification

#102

Post by vertis »

djxfade wrote: post #81
alephnan wrote: post #78

Earlier quoted context omitted.

That sounds like a nit / premature optimization. Electricity is cheap. If this is sufficiently or actually important for your org, you should measure it yourself. There are too many variables and factors subject to your org’s hardware.

Totally disagree. Most end users are on laptops and mobile devices these days, not desktop towers. Thus power efficiency is important for battery life. Performance per watt would be an interesting comparison.

I mean if you care about that you shouldn't be running anything that isn't highly optimized. Don't open webpages that might be CPU or GPU intensive. Don't run Electron apps, or really anything that isn't built in a compiled language.

Certainly you should do an audit of all the Android and iOS apps as well, to make sure they've been made in a efficient manner.

Block ads as well, they waste power.

This file identification is SUCH a small aspect of everything that is burning power in your laptop or phone as to be laughable.

Re: Magika: AI powered fast and efficient file type identification

#103

Post by KOLANICH »

secondary_op wrote: post #100

Why is this piece of code being sold as open source, when in reality it just calls into proprietary ML blob that is tiny and useless, and actual source code of model is closed while properly useful large model is non existing ?

Not into proprietary, the blob is within an Apache-licensed repo. Though there was no code to train it, but the repo contains some info allowing to recreate the code training it. Basically a JSON-based configs containing graph architecture. Even if you didn't have them, the repo contains an ONNX model, from which one can devise the architecture.

Re: Magika: AI powered fast and efficient file type identification

#104

Post by KOLANICH »

vintermann wrote: post #87
lopkeny12ko wrote: post #51

I don't understand why this needs to exist. Isn't file type detection inherently deterministic by nature? A valid tar archive will always have the same first few magic bytes. An ELF binary has a universal ELF magic and header. If the magic is bad, then the file is corrupted and not a valid XYZ file. What's the value in throwing in "heuristics" and probabilistic inference into a process that is black and white by desi…

Consider, it's perfectly possible for a file to fit two or more file formats - polyglot files are a hobby for some people. And there are also a billion formats that are not uniquely determined by magic bytes. You don't have to go further than text files.

This tool doesn't work this way.

Re: Magika: AI powered fast and efficient file type identification

#105

Post by _puk »

vertis wrote: post #102
djxfade wrote: post #81

Earlier quoted context omitted.

Totally disagree. Most end users are on laptops and mobile devices these days, not desktop towers. Thus power efficiency is important for battery life. Performance per watt would be an interesting comparison.

I mean if you care about that you shouldn't be running anything that isn't highly optimized. Don't open webpages that might be CPU or GPU intensive. Don't run Electron apps, or really anything that isn't built in a compiled language. Certainly you should do an audit of all the Android and iOS apps as well, to make sure they've been made in a efficient manner. Block ads as well, they waste power. This file identificat…

Whilst energy usage is indeed a small aspect this early on when using bespoke models, we do have to consider that this is a model for simply identifying a file type.

What happens when we introduce more bespoke models for manipulating the data in that file?

This feels like it could slowly boil to the point of programs using magnitudes higher power, at which point it'll be hard to claw it back.

Re: Magika: AI powered fast and efficient file type identification

#106

Post by flohofwoe »

I wonder how it performs with detecting C vs C++ vs ObjC vs ObjC++ and for bonus points: the common C/C++ subset (which is an incompatible C fork), also extra bonus points for detecting language version compatibility (e.g. C89 vs C99 vs C11...).

Separating C from C++ and ObjC is where the file type detection on Github traditionally had problems with (but has been getting dramatically better over time), from an "AI-powered" solution which has been trained on the entire internet I would expect to do better right from the start.

The list here doesn't even mention any of those languages except C though:

https://github.com/google/magika/blob/main/docs/supported-co...

Re: Magika: AI powered fast and efficient file type identification

#107

Post by scq »

michaelt wrote: post #95
true_religion wrote: post #89

Earlier quoted context omitted.

What end users are working with arbitrary files that they don’t know the identification of? This entire use case seems to be one suited for servers handling user media.

Theoretically? Anyone running a virus scanner. Of course, it's arguably unlikely a virus scanner would opt for an ML-based approach, as they specifically need to be robust against adversarial inputs.

You'd be surprised what an AV scanner would do.

https://twitter.com/taviso/status/732365178872856577

Re: Magika: AI powered fast and efficient file type identification

#109

Post by 20after4 »

I just want to say thank you for the release. There are quite a lot of complaints in the comments but I think this is a useful and worthwhile contribution and I appreciate the authors for going through the effort to get it approved for open source release. It would be great if the model training data was included (or at lease documentation about how to reproduce it.) but that doesn’t preclude this being useful. Thanks!
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