Model2h ago
Fundamental Flaw Makes LLMs Permanently Vulnerable
Researchers at the International Conference on Machine Learning argue that LLMs cannot be fully secured against hacks. This vulnerability stems from a core architectural flaw in how these models process information. The finding suggests that traditional patching methods will fail. Practitioners must now assume a baseline of insecurity for all deployed models.