HopeADeff/Hope

For protecting/preventing AI to mimic everyone's arts

26
/ 100
Experimental

Integrates Nightshade and Glaze adversarial perturbation techniques to poison training data for generative AI models, exploiting diffusion model latent spaces through convex optimization to induce concept corruption or style obfuscation. The system applies imperceptible noise modifications that preserve human visual perception while causing model mode collapse or semantic misalignment during fine-tuning. Targets Windows 10/11 systems and works with popular Stable Diffusion implementations, LoRA, and checkpoint-based models.

No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 9 / 25
Community 0 / 25

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Stars

29

Forks

Language

Python

License

MIT

Last pushed

Jan 25, 2026

Commits (30d)

0

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