 Using third-party datasets, pre- trained models, and plugins can add vulnerabilities.   LLM10: Model Theft This involves unauthorized access, copying, or exfiltration of proprietary LLM models.  The impact includes economic losses, compromised competitive advantage, and potential access to sensitive information.   LLM01: Prompt Injections Prompt Injection Vulnerability occurs when an attacker manipulates a large language model (LLM) through crafted inputs, causing the LLM to unknowingly execute the attacker's intentions.  This can be done directly by "jailbreaking" the system prompt or indirectly through manipulated external inputs, potentially leading to data exfiltration, social engineering, and other issues