Typed decision model vulnerabilities can push AI guardrail fail-open rates to 63%

Six lines of server-log text pushed an AI guardrail’s rate of allowing prohibited actions from 0% to 63% in a study posted on October 8, 2026. The research examines typed decision model vulnerabilities, including an attack that changed an option’s name while leaving its definition and the text being judged untouched. Key takeaways Seven open-weight models scored 36%–72% on allow-or-block decisions. Misleading option labels produced 93%–100% fail-open rates in four models. The study recommends using these models to filter reviewer workloads, not make decisions alone. Erfan Baghaei Potraghloo reported the findings in a paper published on arXiv .

Source: The Cryptonomist