Comparative Evaluations of Large Language Models for Biosecurity, Cybersecurity and Chemical Risks

Large language models (LLMs) offer a vast array of applicability  in various fields of human endeavors for both malicious and beneficial ends. In cybersecurity, for example, LLMs are applied in the detection of vulnerability, intrusion, phishing attacks and in malware analysis (Xu et al., 2024). LLMs can be used for the automation of the design, planning and execution of scientific experiments (Boiko et al., 2023). They can facilitate the navigation of chemical space, for example, for organic synthesis, autonomous drug discovery and materials design (Bran et al., 2023; Caramelli et al., 2021; Granda et al., 2018) and for the optimization of chemical reactions (Angello et al., n.d.). Similarly, in biology, LLMs and other AIs can facilitate tasks such as protein synthesis (Wu et al., 2109).

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