Poster: Rethinking Security in LLM Code Generation through Real-World Risk Scenarios
Large Language Models (LLMs) are widely used for code generation, yet their security behavior in realistic development workflows remains underexplored. Existing benchmarks often rely on explicitly specified security requirements, failing to capture real-world scenarios where prompts are frequently ambiguous or incomplete. In this paper, we adopt a developer-centric perspective and identify three representative risk scenarios that commonly lead to security vulnerabilities in LLM-generated code: Ambiguous Requirements, Under-Specified Operational Context, and Security--Functionality Conflict. Based on these scenarios, we construct a large-scale benchmark comprising 2,700 test cases, enablin...
| Authors | Lixun Ma, Ruolong Ma, Bei Wang et al. |
|---|---|
| Primary category | cs.CR |
| Published | 25 July 2026 |
| Last updated at source | 25 July 2026 |
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