CrowdStrike identifies five new prompt injection threats to AI
Summary
CrowdStrike has identified five new prompt injection techniques that target large language models (LLMs) used in enterprises. These attacks exploit LLMs by tricking them into accepting dubious instructions, leading to potential security risks. The identified techniques include trigger-activated rule addition, cognitive token suppression, algorithmic payload decomposition, special token injection, and unwitting user context-data injection.
IFF Assessment
The article details new methods for attacking AI systems, which poses a direct threat to the security of organizations utilizing these technologies.
Defender Context
Defenders need to be aware of emerging prompt injection techniques as AI adoption increases. Organizations should implement robust threat modeling and detection engineering to identify and mitigate these novel attacks, particularly focusing on the origin of model context and the potential for composite attacks.