How AI leak detection works

Leaks on Telegram and tube sites are not problems you solve with a search-and-find approach. They propagate in minutes, not hours — which means the system has to stop waiting for someone to flag an intrusion.

Our detection engine runs three overlapping layers.

1. Perceptual hashing

Every piece of content entering the system is reduced to a perceptual signature — a fingerprint capturing visual structure without storing the raw image. When pirated content surfaces online, we match by similarity, not byte equality.

That means crops, recompressions, pirate watermarks, horizontal flips all still get caught. Confidence thresholds are tunable per creator profile.

2. Active sweeps

We don’t wait for a leak to rise to the top of a search. Across 247 sources — Telegram, tube sites, paste sites, dark-web markets, forums and subreddits — we run sweeps every 60 seconds looking for known patterns: handle names, branding, keyword sequences, and visual fingerprints.

When the engine hits a match with confidence > 90%, the takedown pipeline auto-triggers.

3. Human escalation

AI gets it wrong sometimes. Every borderline takedown (confidence 70–90%) is reviewed manually by an anti-piracy specialist before the DMCA notice is dispatched. No false positives on legitimate fan content.

The full loop — from detection to notice — closes in under 4 minutes at the 95th percentile. Median time-to-removal after notice is 2 hours.