, RBAC and rule of least privilege) and strong authentication mechanisms to limit unauthorized access to LLM model repositories and training environments This is particularly true for the first three common examples, which could cause this vulnerability due to insider threats, misconfiguration, and/or weak security controls about the infrastructure that houses LLM models, weights and architecture in which a malicious actor could infiltrate from insider or outside the environment Supplier management tracking, verification and dependency vulnerabilities are important focus topics to prevent exploits of supply-chain attacks Restrict the LLM's access to network resources, internal services, and APIs This is particularly true for all common examples as it covers insider risk and threats, but also ultimately controls what the LLM application "has access to" and thus could be a mechanism or prevention step to prevent side-channel attacks Regularly monitor and audit access logs and activities related to LLM model repositories to detect and respond to any suspicious or unauthorized behavior promptly Automate MLOps deployment with governance and tracking and approval workflows to tighten access and deployment controls within the infrastructure Implement controls and mitigation strategies to mitigate and|or reduce risk of prompt injection techniques causing side-channel attacks Rate Limiting of API calls where applicable and|or filters to reduce risk of data exfiltration from the LLM applications, or implement techniques to detect (E. G. , DLP) extraction activity from other monitoring systems Implement adversarial robustness training to help detect extraction queries and tighten physical security measures Implement a watermarking framework into the embedding and detection stages of an LLMs lifecyle.  OWASP. org 31 | OWASP Top 10 for LLM v1