Identify the AI generator app that produced the content (ClothOff content on Facebook)

Why this matters for ClothOff content on Facebook

• ClothOff has been linked to multiple school harassment cases involving minors in Spain, the United States, and the United Kingdom. The service has no age verification and outputs are routinely shared on Telegram and Discord.
• Facebook Groups can host closed NCII trading communities that escape automated moderation. Marketplace listings have been used to distribute NCII as fake product images, and Profile photos can be reverse searched.
• ClothOff content distributed through Facebook typically reaches between four and twelve additional platforms within 72 hours through reposts, mirrors, and cross platform redistribution.
• Source attribution to ClothOff 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 ClothOff fingerprint indicators including clothoff outputs typically display a soft skin gradient transition along the original clothing edge, slight asymmetry in nipple placement, and a faint moire pattern in the lower abdomen. 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 ClothOff content distributed on Facebook 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 ClothOff variations.
3. 03
   Complete the source attribution documentation ClothOff outputs typically display a soft skin gradient transition along the original clothing edge, slight asymmetry in nipple placement, and a faint moire pattern in the lower abdomen. Many outputs retain the original photograph's lighting direction but lose ambient shadow continuity. 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 ClothOff source attribution ClothOff outputs typically display a soft skin gradient transition along the original clothing edge, slight asymmetry in nipple placement, and a faint moire pattern in the lower abdomen. Many outputs retain the original photograph's lighting direction but lose ambient shadow continuity. 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 Facebook platform removal Facebook accepts NCII reports through Meta's NCII portal and through the in app report flow. Marketplace, Groups, and Profile content all share the same reporting pipeline.
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
• Meta operates the NCII Hash Database Pilot in cooperation with the Cyber Civil Rights Initiative. A successful Facebook removal often produces a hash that is propagated to Instagram and other Meta platforms automatically.
• ClothOff attribution: Direct legal action against ClothOff is constrained by its Belize registration. Effective removal proceeds against the distribution platform under 47 USC 223a and against payment processors that fund the service.