Remove Stable Signature from AI Images
Invisible watermark for Stable Diffusion generated images
Drag & drop your image here
or click to browse
PNG, JPG, WebP до 20 MB
How We Remove Stable Signature
Detection
We analyze the image to detect neural patterns
Removal
Latent space manipulation
Quality
Image quality preserved with lossless processing
About Stable Signature
Stability AI
invisible
neural
Yes
AI Models Using Stable Signature
Services Using Stable Signature
Helping creators & businesses everywhere work easier
See the Difference
Drag the slider to compare before and after. AI watermarks removed, quality preserved.
Portrait Photo
Street Photography
AI Art
Digital Illustration
What is Stable Signature?
Stable Signature is a watermarking technology developed by Meta Research and deployed by Stability AI in their Stable Diffusion models. Unlike metadata-based approaches, Stable Signature embeds watermarks directly into the decoder parameters of the diffusion model — meaning every image generated inherently contains the watermark.
The technology was presented at ICCV 2023 and claimed to be robust against common image manipulations including cropping, compression, and color adjustments.
How Stable Signature Works
The watermark is "rooted" in the latent diffusion model itself:
- Decoder modification — The model's decoder is fine-tuned to embed a specific signature
- Latent space encoding — Watermark information is encoded during the image generation process
- Invisible embedding — The signature is imperceptible but statistically detectable
Stability AI claimed 90%+ detection accuracy even on images cropped to just 10% of original content.
Where is Stable Signature Used?
- Stable Diffusion XL — Official Stability AI releases
- Stable Diffusion 3.x — Latest model versions
- DreamStudio — Stability AI's web interface
- API access — Official Stability AI API
Note: Community fine-tunes and third-party implementations often don't include the watermark.
Stable Signature Vulnerabilities
Research published in 2024 demonstrated that Stable Signature is less robust than initially claimed:
- Fine-tuning attacks — The watermark can be removed by additional model training
- Latent space manipulation — Processing through modified pipelines can strip the signature
- Image-to-image workflows — Using watermarked images as references for new generations
The paper "Stable Signature is Unstable" showed effective watermark removal while maintaining image quality.
Removal Methods
Latent Space Processing
Running images through a diffusion model with low denoising strength can reconstruct content without the embedded signature.
Re-generation Approach
Using the watermarked image as a ControlNet reference or img2img input with a non-watermarked model produces clean output.
Neural Reconstruction
Specialized networks can separate the watermark signal from image content in the frequency domain.
Our Removal Service
Our tool processes Stable Diffusion images through advanced latent space manipulation to remove Stable Signature watermarks while preserving visual quality and detail.
Frequently Asked Questions
Trusted by Researchers & Platforms
Join thousands of developers, researchers, and content platforms who trust AI Detector Arena
Sarah Chen
Content Platform Manager
"Finally a reliable way to compare AI detectors! We tested 8 different services and AI Detector Arena helped us pick the most accurate one for our moderation needs."
Marcus Rodriguez
AI Researcher
"The benchmarks here are incredibly useful for my research. Real-time ELO rankings show how detection accuracy evolves. Essential resource for the AI community."
Emma Wilson
Digital Artist
"As an artist who uses AI tools, I needed to understand how detectors work. This platform gave me insights into which detectors are reliable vs unreliable."
Alex Thompson
Platform Developer
"Building an app that needs AI detection? Start here. The comparison data saved us weeks of testing different APIs. Clear winner for our use case."
Lisa Park
Academic Integrity Officer
"Our institution evaluated multiple AI detection tools using this platform. The accuracy metrics and false positive rates were exactly what we needed."