Seclens: Role-specific Evaluation of LLM's for security vulnerablity detection
Existing benchmarks for LLM-based vulnerability detection compress model performance into a single metric, which fails to reflect the distinct priorities of different stakeholders. For example, a CISO may emphasize high recall of critical vulnerabilities, an engineering leader may prioritize minimizing false positives, and an AI officer may balance capability against cost. To address this limitation, we introduce SecLens-R, a multi-stakeholder evaluation framework structured around 35 shared dimensions grouped into 7 measurement categories. The framework defines five role-specific weighting profiles: CISO, Chief AI Officer, Security Researcher, Head of Engineering, and AI-as-Actor. Each p...
| Authors | Subho Halder, Siddharth Saxena, Kashinath Kadaba Shrish et al. |
|---|---|
| Primary category | cs.CR |
| Published | 2 April 2026 |
| Last updated at source | 2 April 2026 |
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