Instruction Tuning for Secure Code Generation

arXiv:2402.09497v1 Announce Type: new
Abstract: Modern language models (LMs) have gained widespread acceptance in everyday and professional contexts, particularly in programming. An essential procedure enabling this adoption is instruction tuning, which substantially enhances LMs' practical utility by training them to follow user instructions and human preferences. However, existing instruction tuning schemes overlook a crucial aspect: the security of generated code. As a result, even the state-of-the-art instruction-tuned LMs frequently produce unsafe code, posing significant security risks. In this work, we …

arxiv code cs.ai cs.cr cs.lg cs.se secure code