prompt-injection-adversarial-ml-security-concerns

Summary

LLMs face three well-established threats: users can trick the model into ignoring its instructions, attackers can craft inputs to manipulate its behavior, and the model can confidently assert false information. This means any system built on these models must treat these as real, ongoing vulnerabilities to design around, not hypothetical edge cases.