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This work introduces REEF, a benchmark of red-teaming executable environments with faithful verification for measuring the security vulnerabilities of web agents, and introduces ANGLER, an adaptive near-miss-guided lure evolution framework for red-teaming.
RidgeFT is proposed, a lightweight analytic update framework that does not rely on exemplar replay and achieves the best overall macro-F1 across domains, backbones, and incremental protocols, while also improving both old-class retention and new-class adaptation.
Ablations show that feedback-based refinement and audio-variant search substantially improve attack discovery.
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