Security Vulnerabilities in GPTs: An Empirical Study

This article, sourced from ArXiv, likely presents novel research on the security weaknesses of GPT models. The empirical approach suggests a data-driven analysis, which is valuable for understanding and mitigating risks associated with these powerful language models.

• •Identifies potential security flaws in GPT models.
• •Employs an empirical, likely data-driven, methodology.
• •Provides insights relevant to developers and users of GPTs.