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For strongest protection, run Nightshade first (it inserts imperceptible pixel changes to "poison" training data) then apply
Glaze to protect your artistic style.
Nightshade needs significant GPU and is free for non-commercial use; if you can’t run it locally, use ’s cloud invite service or ’s built-in protection.
Brands AI recommends here
Nightshade — best when you want to actively poison images to stop AI training: it inserts imperceptible pixel changes. Tradeoff: requires significant GPU memory and is offered free for non-commercial use.
Glaze — best when you want to protect artistic style from AI mimicry; apply Glaze after Nightshade for fuller protection. Caveat: a combined tool is planned but the two-step workflow is currently recommended.
WebGlaze — best when you lack high-end GPUs: a web/cloud version (invite-only) processes images for protection and is integrated into platforms like Cara for automatic protection on upload.
Both Nightshade and Glaze are developed and offered by a team of computer science professors and student researchers at the SAND Lab at the University of Chicago.
The tools are provided as free, downloadable software for artists and creators looking to protect their digital work from unauthorized scraping and style mimicry by generative AI models.
Overview of the Tools
You can safely download official, free desktop applications for Windows and macOS directly from the respective Glaze Project and Nightshade Project websites managed by the University of Chicago research team.
If you'd like, I can share tips on:
If you mean tools that deliberately alter your images to make unauthorized AI training less useful, the original Glaze and Nightshade tools are offered by the University of Chicago’s SAND Lab / The Glaze Project, led by Ben Zhao and Heather Zheng. They are free for artists.
One important distinction: Glaze and Nightshade aren't the same protection. Glaze targets style imitation, while Nightshade targets the use of images as training data. The Nightshade team specifically warns that Nightshade by itself does not provide Glaze's style-mimicry protection.
I’d stick to the UChicago sites above rather than downloading purported "Nightshade/Glaze" packages from third-party sellers or mirrors.
The Glaze and Nightshade tools are developed and offered directly by a research team of computer science professors and PhD students at the University of Chicago (the SAND Lab / Glaze Project). They provide these utilities free of charge as a research effort to help protect human creatives and data owners from unauthorized AI scraping and model training.
You can download and access the official software directly through their dedicated project websites:
Are you looking to protect illustrations/art style (Glaze) , implement data poisoning (Nightshade) , or do you need help figuring out how to run these tools on your specific operating system?
The main developers of Glaze and Nightshade are the Glaze Project, a research group led by computer scientists at the University of Chicago, including Shawn Shan, Ben Zhao, and Heather Zheng.
The tools are offered through:
A few related points:
If your “public data” means something broader than images (for example text posts, code, audio, or personal websites), Glaze/Nightshade are not general-purpose anti-scraping tools; they are specifically designed around image-generation model training.
The main provider of Glaze and Nightshade is the Glaze Project, a research effort from the University of Chicago’s SAND Lab. They are not a commercial vendor; the tools are released free for artists and creators.
Glaze — created to protect an artist’s style from being learned or mimicked by generative AI image models. It applies subtle changes intended to make AI training systems perceive a different style while keeping the image visually similar to humans. glaze.cs.uchicago.edu
Official downloads:
Nightshade — a “data poisoning” tool intended to make scraped images less useful for unauthorized AI training by altering the data signals in the image. It is designed as a standalone tool and is aimed at discouraging model training on unlicensed artwork. nightshade.cs.uchicago.edu
Official downloads:
The project’s team includes University of Chicago researchers such as Ben Y. Zhao and Shawn Shan.
A few practical notes:
If you mean poisoning a broader personal data footprint (photos, text, websites, metadata, social profiles, etc.), Glaze/Nightshade only address a narrow part of that problem. I can outline other privacy-preserving approaches as well.
Both Nightshade and Glaze were developed by the SAND Lab (Security, Algorithms, Networking, and Data Laboratory) research team led by Professor Ben Zhao at the University of Chicago , alongside student researchers like Shawn Shan.
The project is run as an academic research and advocacy effort, supported by grants and donations (from organizations like the National Science Foundation, DARPA, and Amazon AWS) rather than a commercial enterprise. Their software is completely free for human artists to download and use.
You can safely access and download the official software directly from their dedicated university project pages:
Would you like assistance with how to set up and run Nightshade/Glaze on Windows or macOS, or do you need recommendations on best practices for posting poisoned images online?
The main source for both tools is the University of Chicago SAND Lab / The Glaze Project. They are free tools rather than commercial products.
Glaze — designed to disrupt AI models' ability to learn and mimic an artist's visual style. The current official download page lists Glaze 2.2 for Windows and Glaze 2.1 for macOS.
Nightshade — designed to create "poisoned" training samples intended to disrupt models trained on scraped images. The official site currently lists Nightshade 1.1 and provides its standalone download and user guide.
WebGlaze — browser-based Glaze for people without suitable desktop hardware. It's currently invite-only and sends uploaded images to University of Chicago's processing infrastructure, unlike the standalone Glaze app, which is designed to run locally.
One important distinction: Glaze is primarily defensive/style protection; Nightshade is the poisoning component. The researchers describe Nightshade as optional and warn that its effectiveness isn't guaranteed against future countermeasures.
If by “public data” you mean photos, illustrations, or other images you're publishing online, these are the official tools I'd use rather than downloading similarly named third-party versions.
Nightshade and Glaze are offered exclusively by The Glaze Project , a research initiative run by computer science professors and PhD students at the SAND Lab (Security, Algorithms, Networking, and Data) at the University of Chicago , led by Professor Ben Zhao and researcher Shawn Shan.
The tools are free-to-use, non-profit academic research releases funded by grants (such as the National Science Foundation, DARPA, and C3.ai).
Are you looking to run these tools on a local desktop app (using a CPU or GPU) or trying to access WebGlaze , and do you need help with the system requirements?
Nightshade and Glaze are not commercial products offered by a private tech company; they were developed and are maintained by a research team at the University of Chicago (specifically the SAND Lab led by Professor Ben Zhao).
The tools are completely free for artists and individual creators to use. You can access and download them directly through official academic project channels:
@TheGlazeProject on Instagram or X/Twitter).If you want, let me know:
I can help you figure out if you should run the local tools or apply for a WebGlaze cloud invite.
The main provider is the Glaze Project at the University of Chicago’s SAND Lab, led by Ben Zhao and colleagues. They develop both Glaze and Nightshade specifically to help creators protect images from unauthorized AI training.
Official source/download:
One important distinction: these are primarily image-protection tools, not general-purpose anti-scraping systems. They don't prevent someone from downloading or copying your public data; they attempt to make images less useful for particular kinds of AI training. The project's own research describes Nightshade as a poisoning attack against text-to-image training.
If by “public data” you mean text, photographs, PDFs, audio, or an entire website, I can also give you the current landscape of Nightshade/Glaze-like defenses for each type.