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Ethical Considerations in the Use of LLMs for Vulnerability Detection
Abstract
Large language models (LLMs) have revolutionized various fields, including software security, by enabling sophisticated analysis and automation. However, despite their potential, the application of LLMs in software security is not without challenges. This chapter explores the limitations of LLMs in this domain, focusing on issues such as data bias, model interpretability, scalability, and the potential for adversarial attacks. The chapter also discusses the complexities of integrating LLMs into existing security frameworks and the ethical implications of their use. By understanding these challenges, researchers and practitioners can better navigate the evolving landscape of software security.
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