{"ID":2855802,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.16005","arxiv_id":"2510.16005","title":"Breaking Guardrails, Facing Walls: Insights on Adversarial AI for Defenders \u0026 Researchers","abstract":"Analyzing 500 CTF participants, this paper shows that while participants readily bypassed simple AI guardrails using common techniques, layered multi-step defenses still posed significant challenges, offering concrete insights for building safer AI systems.","short_abstract":"Analyzing 500 CTF participants, this paper shows that while participants readily bypassed simple AI guardrails using common techniques, layered multi-step defenses still posed significant challenges, offering concrete insights for building safer AI systems.","url_abs":"https://arxiv.org/abs/2510.16005","url_pdf":"https://arxiv.org/pdf/2510.16005v1","authors":"[\"Giacomo Bertollo\",\"Naz Bodemir\",\"Jonah Burgess\"]","published":"2025-10-14T15:01:59Z","proceeding":"cs.CR","tasks":"[\"cs.CR\",\"cs.AI\"]","methods":"[]","has_code":false}