 Direct injections overwrite system prompts, while indirect ones manipulate inputs from external sources.  LLM's may inadvertently reveal confidential data in its responses, leading to unauthorized data access, privacy violations, and security breaches.  It's crucial to implement data sanitization and strict user policies to mitigate this.  LLM07: Insecure Plugin Design LLM02: Insecure Output Handling This vulnerability occurs when an LLM output is accepted without scrutiny, exposing backend systems.  Misuse may lead to severe consequences like XSS, CSRF, SSRF, privilege escalation, or remote code execution