Custom Model Polish Without Provenance
A checkpoint or LoRA can produce polished work with a consistent style. Look for the original post, prompt history, project file, or creator trail before treating that polish as evidence of origin.
Stable Diffusion Image Detector
Wondering whether an image came from Stable Diffusion? Upload it online and review clear AI and human probability signals before you publish, approve, or share it.
콘텐츠
이미지를 드래그 앤 드롭하거나 업로드
JPG · JPEG · PNG · WEBP · 최대 10MB
탐지 후 삭제 · 보고서는 독립적으로 검증 가능
결과
이미지를 업로드하여 시작
왼쪽에 파일을 놓거나 아래 샘플 이미지 중 하나를 선택하세요.
샘플 이미지 사용해 보기
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Top 3
AI Image Detection Tool
500K+
Images Checked Monthly
4.9
Average User Rating
Check If an Image Was Made With Stable Diffusion
A polished fantasy scene, portrait, or product mockup can look credible at first glance. Upload the visual before publishing, licensing, or sharing it. The Stable Diffusion AI image detector returns a probability result that helps you decide whether the source needs a closer review.
Detect Stable Diffusion Images with Clear AI Scores
Stable Diffusion can produce everything from stylized artwork to photorealistic scenes. Instead of a vague warning, the scan returns clear AI and human probability signals. Use that result to decide whether to trace the original source, request workflow files, or continue reviewing the image.
Review Evidence Beyond Stable Diffusion Artifacts
Stable Diffusion outputs do not share one permanent visual fingerprint. Review the probability result alongside available metadata, provenance, watermark evidence, and the creator's source history. Use Basic Scan for a quick first check or Advanced Scan when the decision needs more context.
How to Detect Stable Diffusion Images
Step 1. Upload a Suspected Stable Diffusion Image
Upload the portrait, artwork, product visual, or social post you want to check. You do not need to know which Stable Diffusion checkpoint or workflow may have produced it.
Step 2. Run the Stable Diffusion Image Check
Click “Detect Image” to begin. Lynote reviews the uploaded visual and file signals, then estimates how strongly the image leans toward AI-generated or human-made.
Step 3. Review the AI Probability Result
Read the AI and human probability signals in the result. If the image affects publication, ownership, payment, or moderation, compare the score with its original source, metadata, creator history, and available workflow files.
Common Signs of a Stable Diffusion Image
Stable Diffusion does not leave one universal visual fingerprint. Check these patterns alongside the detector result and source history, because no single sign proves which model created an image.
Local Details That Lose Coherence
Inspect hands, jewelry, eyewear, tools, labels, and object intersections. A Stable Diffusion image can look convincing overall while nearby details conflict when viewed together.
Warped Text, Labels, and Symbols
Signs, packaging, interface labels, and decorative lettering may resemble real language while containing malformed letters or inconsistent typography. Treat this as a clue, not proof.
Repeated or Over-Smoothed Textures
Hair, skin, fabric, foliage, windows, and background patterns may repeat, merge, or look unnaturally smooth across different parts of the scene.
Img2img and Inpainting Inconsistencies
Partial edits can leave mismatched edges, texture, scale, shadow, or lighting around a replaced object. Compare the edited area with the rest of the image.
Lighting and Reflections That Disagree
Compare shadows, highlights, mirrors, glass, and reflected objects. A polished composition can still contain local lighting logic that does not hold together.
Why Choose Our Stable Diffusion Detector
Visual Pattern Review
Examine textures, lighting, repeated objects, malformed text, and backgrounds. This helps guide your review without treating any single artifact as definitive proof.
EXIF Context
Camera or software metadata adds useful context to your check. Remember that screenshots, social media platforms, and heavy compression often strip this data away.
Provenance Signals
Available content credentials, editing history, and embedded watermark evidence support your review process. However, missing provenance does not automatically prove an image is real.
Stable Diffusion-Focused Review
Review Stable Diffusion-style portraits, artwork, and edited visuals in the right context. The page explains relevant clues while the detector supplies a probability signal, without claiming an exact checkpoint or workflow.
Clear Probability Result
Get a clear probability result showing AI and human likelihood. This percentage serves as a practical review signal rather than definitive Stable Diffusion attribution.
Two Review Depths
Access two review depths tailored to your workflow. Use the basic scan for everyday screening, or apply the advanced depth for higher-stakes editorial decisions.
Common Image Formats
Upload standard JPG, JPEG, PNG, WebP, and HEIC files. This covers common generation exports, saved web graphics, and standard screenshots.
Private and Secure
Your files are processed securely during the scan. We do not store your uploaded images or use them for future model training.
Who Uses a Stable Diffusion Image Detector
Digital Art Moderators
Screen digital portfolio submissions for undisclosed Stable Diffusion generation before approving artwork into community galleries.
News Editors
Use the AI probability result as one signal when a breaking-news image looks synthetic or arrives without a reliable photographer, source, or capture history.
Stock Image Reviewers
Flag undisclosed AI assets in marketplace listings to maintain strict platform quality standards for buyers.
Social Media Managers
Pause suspicious trending images before resharing them, then compare the detector result with the earliest post, credited creator, and available source files.
Creative Directors
Check freelance design deliverables to ensure strict compliance with human-only client project briefs and contracts.
Trust and Safety Teams
Screen suspicious listing visuals before requesting original source files or escalating a platform fraud case.
What Our Users Say
Javier Castillo
Digital Art Moderator
"A concept-art portfolio looked consistent, but several pieces appeared without sketches or source files. The AI score gave me a reason to pause the submission and ask for the artist's workflow evidence."
Marcus Thorne
News Editor
"A dramatic event photo arrived without a photographer credit. We ran a check, traced the earliest upload, and requested the original file instead of publishing it based on appearance alone."
Kenji Sato
Stock Image Reviewer
"We receive polished landscape images with almost no creation history. I use the score as a first filter, then compare metadata and contributor records before deciding whether an asset needs manual review."
Tariq Al-Fayed
Social Media Manager
"A reposted product image had one object that looked locally replaced. The result showed enough uncertainty to hold the post while I tracked down the brand's original version."
Elena Rostova
Creative Director
"When a brief requires human-made artwork, I check suspiciously polished deliverables before sign-off. It helps me ask for layered files and sketches without accusing an artist based on style alone."
Chloe Bennett
Marketplace Trust and Safety Reviewer
"For listing images with unclear origins, I run a private first check before escalating. The result gives our moderation team useful context while we request source files from the seller."
Frequently Asked Questions
Still got questions about our stable diffusion image detector? Here are the answers.
A Stable Diffusion detector estimates whether an image may be AI-generated by reviewing visual and available file signals. It returns a probability result for further review, not proof that a particular Stable Diffusion model created the image.
No. While the tool calculates the probability that an image is AI-generated, it cannot determine the specific checkpoint, LoRA, or workflow used. It serves as a visual review signal rather than definitive attribution.
You can upload JPG, JPEG, PNG, WebP, and HEIC images. Select the file and click “Detect Image” to begin the scan.
Malformed text can be one clue, especially on signs, packaging, and interface labels. However, readable text does not prove an image is real, and garbled text does not prove it is AI-generated. Compare this clue with the detector result and source evidence.
Yes. The current image checker accepts supported files up to 10MB.
No. The stable diffusion detector provides a probability signal based on visual patterns, but false positives can occur. It is not absolute proof.
No. We do not store your submitted files or use them to train any AI models. Your privacy is fully protected.
Yes. Basic Scan is available free without payment details. Advanced Scan is a Pro feature for checks that need additional review signals.
No account is required for Basic Scan. Upload an image and run the Stable Diffusion image check online as a guest.
The underlying image detector estimates general AI likelihood; this page frames the result around Stable Diffusion use cases and explains relevant review clues. It still cannot attribute an image to SDXL, a checkpoint, a LoRA, or a particular workflow.
No. A high score suggests the image deserves closer review, but it does not identify the exact generator. Check the original source, project or workflow files, metadata, and creator history before making a consequential decision.
Yes, but heavy resizing, screenshots, and compression can remove useful file or visual signals. Treat the result cautiously and check the highest-quality original when it is available.
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