Published: 17 January 2024
Many organizations are exploring the use of GenAI to improve productivity and business outcomes. To adopt GenAI securely, security and risk management technical professionals must implement the controls described in this research, which will help them manage and mitigate the top threats and risks.
Organizations adopt generative artificial intelligence (GenAI) in two main ways: Some consume it via web or SaaS delivery; others build their own GenAI applications using cloud-hosted large language models (LLMs).
GenAI security is a nascent and rapidly evolving field. Security practitioners and academic researchers continue to discover new attacks on GenAI apps. Early-stage startups are trying to address GenAI security needs with GenAI trust, risk and security management (TRiSM) products.
Some GenAI security threats and risks, such as data loss and prompt injection, are especially common and require prioritized treatment by security professionals. Others, such as inference attacks and inversion
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