Stolen Vector Databases Can Be Weaponized: vec2vec Recovers Sensitive Facts at 80% Accuracy
maier_ak · x · 2026-09-10
A paper shows stolen vector databases can be weaponized: translating embeddings into a known space with vec2vec enables zero-shot attribute inference and inversion without access to the original encoder, recovering sensitive facts with up to 80% accuracy on Enron emails. vec2vec learns translations between arbitrary text-embedding spaces — no paired sentences, no original encoder, no dictionary — via adversarial training, reconstruction, cycle-consistency, and distance-preserving losses.
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