Top 10 Risks and Mitigations of LLM Security

Organizations are increasingly integrating generative AI, but this adoption introduces significant security, privacy, and regulatory concerns.

OWASP has identified the top ten security risks for large language models in 2025 to guide enterprises in mitigating these challenges. 

These risks range from prompt injection and sensitive information disclosure to supply chain vulnerabilities and misinformation. 

For each identified risk, the source provides a brief explanation, an illustrative example, and several high-level mitigation strategies. The goal of this information is to help businesses build secure and compliant generative AI applications. 

A follow-up series will offer more in-depth analysis and best practices for addressing these critical vulnerabilities.

Om Podcasten

Decoding AI Risk explores the critical challenges organizations face when integrating AI models, with expert insights from Fortanix. In each episode, we dive into key issues like AI security risks, data privacy, regulatory compliance, and the ethical dilemmas that arise. From mitigating vulnerabilities in large language models to navigating the complexities of AI governance, this podcast equips business leaders with the knowledge to manage AI risks and implement secure, responsible AI strategies. Tune in for actionable advice from industry experts.