The Problem: AI Scraping

Generative AI models (like Stable Diffusion, Midjourney) are trained on billions of images scraped from the open web—often without the artist's consent. Once your style is absorbed into the model, anyone can generate endless imitations, effectively treating your life's work as free training data.

The Solution: Adversarial Perturbations

AI Shield works by injecting a mathematically computed "mist" over your image. This is known as an Adversarial Attack.

AI models "see" images by identifying patterns (edges, textures, shapes). Our shield slightly alters the pixel values to maximize the model's error rate. While a human sees "Portrait of a Lady," the AI's numerical view is chaotically disrupted, causing it to misclassify the image as "Oven" or "Noise".

Understanding Protection Levels

There is an inherent trade-off between visual purity and protection strength:

• 🛡️ Low (30%): Prioritizes aesthetics. Best for portfolio display where visual fidelity is critical. Offers resistance against weak scrapers but may be bypassed by robust models.
• 🛡️ Standard (50%): The "Goldilocks" zone. Introduces slight, film-grain-like noise that is visible upon close inspection but highly effective against standard CLIP/ResNet encoders.
• 🛡️ High (80%+): Maximum defense. Creates visible patterns/artifacts. Use this for concept art or sketches you absolutely do not want learned by AI.