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LLM Security Guard for Code

Authors :
Kavian, Arya
Kallehbasti, Mohammad Mehdi Pourhashem
Kazemi, Sajjad
Firouzi, Ehsan
Ghafari, Mohammad
Publication Year :
2024

Abstract

Many developers rely on Large Language Models (LLMs) to facilitate software development. Nevertheless, these models have exhibited limited capabilities in the security domain. We introduce LLMSecGuard, a framework to offer enhanced code security through the synergy between static code analyzers and LLMs. LLMSecGuard is open source and aims to equip developers with code solutions that are more secure than the code initially generated by LLMs. This framework also has a benchmarking feature, aimed at providing insights into the evolving security attributes of these models.<br />Comment: SECUTE, EASE 2024

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2405.01103
Document Type :
Working Paper
Full Text :
https://doi.org/10.1145/3661167.3661263