stable-diffusion-docker
picklescan
| stable-diffusion-docker | picklescan | |
|---|---|---|
| 4 | 7 | |
| 710 | 193 | |
| - | - | |
| 6.7 | 5.7 | |
| 4 months ago | about 1 month ago | |
| Python | Python | |
| GNU Affero General Public License v3.0 | MIT License |
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stable-diffusion-docker
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Do you guys recommend any GPU cloud hosting services for stable diffusion?
Honestly though, you’re being a bit paranoid about it. Running your own local install would be much easier, and if you use .safetensors then from my understanding you’re pretty safe. You could also run it using the Docker container for a bit more security, though imo it’s not worth the headache.
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Stable Diffusion CLI apps?
You could try a dockerized implementation of it like this one https://github.com/fboulnois/stable-diffusion-docker
- Keep yourself safe when downloading models, Pickle malware scanner GUI for Stable Diffusion
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Do we have a ready to go LXC container with web UI for stable diffusion yet ?
https://github.com/pieroit/stable-diffusion-jupyterlab-docker/ https://github.com/fboulnois/stable-diffusion-docker
picklescan
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Planting Undetectable Backdoors in Machine Learning Models
It's Python's serialisation format: https://docs.python.org/3/library/pickle.html
There are tools to check the format for suspicious behaviour: https://github.com/mmaitre314/picklescan seems to be the most developed one.
You can also check the format manually (being careful not to call into it), like demonstrated by this more rudimentary scanner: https://github.com/zxix/stable-diffusion-pickle-scanner
It you do check for security issues yourself, you'll need to read up on what magical methods/variables may cause code execution. Simple demonstrations of dangerous code can be found all over the web (https://stackoverflow.com/questions/47705202/pickle-exploiti...) but I'm sure there are obfuscation tricks that simple scans won't catch.
- Keep yourself safe when downloading models, Pickle malware scanner GUI for Stable Diffusion
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Photorealistic highres portraits
I ran it through both Python Malware Scanner and Stable Diffusion Pickle Scanner as I do with any model before and after I downloaded.
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I'm a beginner at AI art, please give me tips.
There are a few you can run on your own too. https://github.com/zxix/stable-diffusion-pickle-scanner https://github.com/mmaitre314/picklescan
- Don't download the "Anything V3" model - It contains a malware threat inside the .ckpt file
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Marathon, the power of chinese novel ai
"Picklescan" is available from here: https://github.com/mmaitre314/picklescan
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Is there a way of scanning .ckpt files for exploits?
Not a definitive solution, but there is picklescan which catches some of the obvious malicious imports (like builtin eval, exec, etc...). The safeunpickle2 script throws a lot of false positives, since it is missing some datatypestorage classes from torch that some models use. It was probably meant to be a proof of concept primarily. But it is always a good practice to adapt that script and have it print out the complete list of imports and callbacks and manually scan through them
What are some alternatives?
stable-diffusion-webui-docker - Easy Docker setup for Stable Diffusion with user-friendly UI
Stable-Diffusion-Pickle-Scanner-GUI - Pickle Scanner GUI
ComfyUI-to-Python-Extension - A powerful tool that translates ComfyUI workflows into executable Python code.
stable-diffusion-pickle-scanner
data-efficient-gans - [NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
NumPy - The fundamental package for scientific computing with Python.
stable-diffusion-pytorch - Yet another PyTorch implementation of Stable Diffusion (probably easy to read)
Sketch-Guided-Stable-Diffusion - Unofficial Implementation of the Google Paper - https://sketch-guided-diffusion.github.io/
sdxl-demos - Python demos for testing out the Stable Diffusion's XL (SDXL 0.9) model.
stable-diffusion-webui - Stable Diffusion web UI
StableDiffusionTelegram - StableDiffusionTelegram is a telegram bot that allows to generate images using the stable diffusion AI from a telegram bot, in a much more comfortable and simple way.
awesome-diffusion - A curated list of awesome Diffusion notebooks, tools, software, tutorials and resources.