Identify the AI generator app that produced the content (Stable Diffusion content on Telegram)

Why this matters for Stable Diffusion content on Telegram

• Person specific LoRA adapters trained on a victim's photographs enable repeated NCII generation. LoRA file removal from hosting platforms is a critical and often overlooked lever.
• Telegram channels can carry tens of thousands of subscribers and are frequently used by NCII trading communities. Channel admins can mass forward content across linked groups in seconds.
• Stable Diffusion content distributed through Telegram typically reaches between four and twelve additional platforms within 72 hours through reposts, mirrors, and cross platform redistribution.
• Source attribution to Stable Diffusion is critical for identify source app because it establishes the AI generated nature of the content, which strengthens statutory claims under 47 USC 223a regardless of whether the depicted person ever existed in unaltered form.

How AI generator removal works

What to do, step by step

1. 01
   Preserve evidence before any other action Capture full page screenshots with the URL bar visible, save the highest resolution copy of the content available, and document the Stable Diffusion fingerprint indicators including stable diffusion outputs across versions have known visual fingerprints including characteristic noise patterns in flat regions and recognizable hand and finger artifacts. Highest resolution copy of the content available, ideally the original file before redistribution compression
2. 02
   Run a biometric scan to find every copy across platforms Stable Diffusion content distributed on Telegram rarely stays there. ScanErase indexes 2.4 billion face embeddings across 200 plus platforms and identifies every current hosting location in a single scan, including additional Stable Diffusion variations.
3. 03
   Complete the source attribution documentation Stable Diffusion outputs across versions have known visual fingerprints including characteristic noise patterns in flat regions and recognizable hand and finger artifacts. Document the matching characteristics with side by side comparison samples and forensic notes. This documentation supports authentication under Federal Rules of Evidence 901.
4. 04
   Document the Stable Diffusion source attribution Stable Diffusion outputs across versions have known visual fingerprints including characteristic noise patterns in flat regions and recognizable hand and finger artifacts. This attribution evidence is critical for the legal record and supports stronger statutory claims regardless of which specific action you pursue.
5. 05
   Coordinate with Telegram platform removal Telegram accepts abuse reports at abuse@telegram.org and through the in app report flow. Public channels are routinely actioned. Private groups require additional escalation through Apple and Google app store policy reports.
6. 06
   File the complete evidence record for the legal track Federal Rules of Evidence 901 for authentication of digital evidence provides the foundational legal basis for this action. Document every notice sent, every platform response, and every confirmation in a single evidence file. ScanErase produces this Verified Removal Package automatically as your case progresses.

Legal context

• Federal Rules of Evidence 901 for authentication of digital evidence
• Source attribution as a foundational element of civil claims under state NCII statutes
• Telegram's 950 million monthly users place it well above the TAKE IT DOWN Act covered platform threshold. The FTC has explicit enforcement authority for non compliance and the app store route adds independent commercial leverage.
• Stable Diffusion attribution: The base model is open source and beyond removal action. Action proceeds against the specific fine tune model, the LoRA adapter that enables targeted generation, and the platform that hosts and distributes the harmful adapter.