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Stable Diffusion 3.5 & SDXL Detector: Latent Noise Forensics
Forensic analysis of Stability AI MMDiT architectures, SDXL latent representations, and LoRA weight artifacts.
使用 Sealed Rose 驗證媒體真實性
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Stable Diffusion (including SDXL and SD 3.5 Large) is the foundation of the open-source generative AI ecosystem. Open weights allow fraudsters to fine-tune custom checkpoints and LoRAs locally on consumer GPUs to generate targeted catfish personas, fake KYC credentials, and non-consensual imagery without guardrails. Sealed Rose inspects the unique latent space noise residuals and MMDiT attention maps left by Stable Diffusion models.
關鍵警訊與破綻特徵
1Attention Map Leakage on Text and Badges
Logos, shirt typography, and background signage often display pseudo-letters or fractured glyph structures from unresolved text embeddings.
2Lobe and Ear Contour Warping
Ears frequently show fused cartilaginous ridges or uneven lobe attachment when rendered against complex hairstyles.
3LoRA Overfitting and High-Contrast Edge Halos
Locally fine-tuned LoRA models produce distinct contrast halos and repetitive grain patterns around high-frequency hair strands.
Stable Diffusion MMDiT Architecture Forensics
- MMDiT Latent Noise Verification: Identifies the characteristic rectified flow and noise scheduler signatures of SD 3.5.
- Frequency Domain Inspection: Uncovers high-frequency harmonic grid lines caused by standard VAE decoding bottlenecks.
- LoRA & Checkpoint Signature Attribution: Measures style weight distribution to differentiate base models from custom community fine-tunes.
防範措施與應對步驟
Scan Image in Sealed Rose Forensic Suite
Upload the file to inspect VAE residual anomalies and detect Stable Diffusion generative checkpoints.
常見問題
Can Sealed Rose detect images created with custom SD checkpoints or Civitai models?▼
Yes. While custom checkpoints change aesthetics, they share the underlying SDXL or SD 3.5 VAE and MMDiT noise distribution detected by Sealed Rose.
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