Assessment of the Practicality of LLMs in the Field of Cybersecurity and Detection of Malicious Code

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LLMs effectively identify malicious code and analyze software vulnerabilities, despite notable challenges in deployment.
Key findings suggest that while LLMs can detect phishing attacks, their development incurs high computational costs.
This review utilizes current literature to evaluate the real-world applicability of LLMs in cybersecurity contexts.
Understanding limitations like potential biases and adversarial attacks is crucial for responsible LLM integration.

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This review assesses the practicality of large language models in cybersecurity, highlighting their potential benefits and risks.

Illindala et al. (2025) studied this question.

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