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Joanna C. S. Santos

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Open access Aug 2026

Multi-SALLM: a multilingual security assessment of generated code

Multi-SALLM, a benchmarking framework designed to systematically evaluate Large Language Models’ ability to generate secure code, reveals three key findings: functional correctness and security are closely related but not equivalent, and sampling strategy is a critical risk factor.

Mohammed Latif Siddiq, Noshin Ulfat, Nishat Raihan et al. · 0 citations
Jun 2026

An Empirical Study of Security Calibration in Large Language Models for Code

The first large-scale empirical study of security calibration in LLM-generated code is presented, showing that although architectural gating improves calibration on controlled benchmarks, calibration deteriorates in realistic repository-level settings, increasing the risk of high-confidence vulnerable outputs.

Mohammed Latif Siddiq, Md Nafiu Rahman, Joanna C. S. Santos · 0 citations