SOURCE-LINKED INTELLIGENCE
CS-Guard: Benchmarking LLM Guardrails for Code Generation Security
Large language models (LLMs) have been ex- ploited to generate malware, but the effective- ness of guardrails for code generation secu- rity remains unclear. We introduce CS-Guard, the first benchmark to systematically evalu- ate guardrails for code generation security. It covers 1) text-to-code generation with 1000 high-quality malware-generation prompts, 7 jailbreak attacks, and a novel fictional scenario attack (FSA) that embeds malicious intent in a legitimate fictional software-development sce- nario; and 2) code-to-code generation with 331 code prompts spanning code infilling, code compl
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-09T06:50:45.000Z
First collected: 2026-09-20T19:52:05.078Z. This is not the publication date.