This Is How Your LLM Gets Compromised - TrendMicro

Adversaries can compromise Large Language Models (LLMs) through three primary methods: embedding malicious executable instructions in model files, leveraging malicious Low-Rank Adaptation (LoRA) adapters to inject backdoors, or poisoning training data to alter model behavior directly. These supply chain vulnerabilities allow for stealthy manipulation of AI models, leading to system compromise, data exfiltration, or biased outputs that are difficult to detect using traditional security measures.