FlipJev: Fast Black-Box Red Teaming Finds Universal Adversarial Suffixes for Typed Decision Models

Summary

Researchers red-teamed Jev, a typed decision model that answers in a single query, using a fast black-box attack that calls no attacker language model. Across 12 datasets, Jev resisted common prompt injections in 10,240 paired tests, but short universal suffixes flipped confident answers within minutes, with one suffix per dataset flipping 43% of unseen documents. Suffixes generated for one task also flipped 90-100% of samples in other tasks.

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