Identify the AI generator app that produced the content (Unstable Diffusion content on Mastodon)

Why this matters for Unstable Diffusion content on Mastodon

• Community structure produces continuous model improvement focused on bypassing content filters in mainstream services.
• Federated content spreads across multiple instances through reposts and replies. Removing from the originating instance does not remove from the cached copies on every instance that federated the post.
• Unstable Diffusion content distributed through Mastodon typically reaches between four and twelve additional platforms within 72 hours through reposts, mirrors, and cross platform redistribution.
• Source attribution to Unstable 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 Unstable Diffusion fingerprint indicators including unstable diffusion uses community trained models with variable rendering styles, but service generated images carry platform metadata. 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 Unstable Diffusion content distributed on Mastodon 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 Unstable Diffusion variations.
3. 03
   Complete the source attribution documentation Unstable Diffusion uses community trained models with variable rendering styles, but service generated images carry platform metadata. 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 Unstable Diffusion source attribution Unstable Diffusion uses community trained models with variable rendering styles, but service generated images carry platform metadata. 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 Mastodon platform removal Mastodon is federated across thousands of independent instances. Removal requires identifying the specific instance hosting the content and contacting that instance's admin directly.
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
• Most Mastodon instance admins comply quickly with NCII reports. The Mastodon Server Covenant explicitly prohibits NCII content, which gives leverage even with instances outside US jurisdiction.
• Unstable Diffusion attribution: Discord origin community structure complicates operator identification. Action proceeds primarily through Discord trust and safety reports against the community server and through redistribution platform notices.