Steering the Narrative: Breaking Bots by Forging Robust Adversarial CAPTCHAs With Diffusion Models

Summary

Researchers propose SteerGuard, a framework that uses diffusion models to generate adversarial CAPTCHAs designed to defeat AI-based solvers. Their approach steers the diffusion generation process to embed adversarial semantics directly into CAPTCHA samples, with the aim of reducing manual dataset curation and enabling dynamic updates. The authors report superior transferability, robustness and adaptability across attacker strategies without added runtime cost, including validation on a large-scale online platform.

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