LLMs accelerate software development but often generate insecure code. This study proposes the Security Information Budget (SIB), a real-time metric measuring mutual information between model hidden representations and security context. Research suggests that a decrease in SIB precedes the generation of vulnerabilities. Tested on DeepSeek-Coder-33B and Qwen2.5-Coder-32B using CWE-Bench and HumanEval-Security, SIB monitoring achieved an F1 score of 0.81. It detected risks an average of 23 tokens before a vulnerability appeared, effectively complementing existing static analysis tools.
| Mualliflar | Гаипназаров , Рустам, Кузнецова , Виктория, Рахимов , Гиёс |
|---|---|
| Jurnal | Al-Farg'oniy avlodlari |
| Nashr sanasi | 2026-04-28 |
| Son | 2 |
| Betlar | 37-45 |
| Til | Rus |
large language models, code security, mutual information, information bottleneck, vulnerability detection, CWE., большие языковые модели, безопасность кода, взаимная информация, информационное узкое место, обнаружение уязвимостей, CWE., katta til modellari, kod xavfsizligi, o‘zaro axborot, axborot torayishi (information bottleneck), zaifliklarni aniqlash, CWE.
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