Tag
This paper proposes SEAV, a verification-centric framework for evaluating jailbreak robustness in large language models by assessing response validity and correctness, significantly reducing false-positive rates in safety assessments.
This paper evaluates indirect prompt injection risks in DeepSeek Harness using AI-Infra-Guard for controlled testing, finding notable attack success rates and recommending security controls.