The article introduces the "promptware kill chain," a structured framework designed to describe sophisticated, multistage attacks against Large Language Models (LLMs). By moving beyond the limited scope of simple prompt injection, the authors outline a seven-step process—including initial access, privilege escalation, and lateral movement—that mirrors traditional malware operations like Stuxnet. This model highlights how the lack of architectural separation between code and data in LLMs creates inherent vulnerabilities that allow malicious instructions to be processed with high authority.
Real-world examples, such as AI-driven worms and malicious calendar invites, illustrate the potential for persistent infection and automated data exfiltration across interconnected platforms. The authors emphasize that because prompt injection is an architectural reality of current AI, security efforts must focus on a defense-in-depth approach. This involves breaking the kill chain at subsequent stages, such as limiting an agent's permissions, preventing persistence, and disrupting command-and-control capabilities to manage systemic risks.
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