This Is How Your LLM Gets Compromised

Large Language Models used in business applications face three major compromise methods that can turn trusted AI systems into security threats. Attackers can hide malicious code in model files that executes when loaded, poison training data to create hidden backdoors triggered by specific phrases, or use lightweight adapter files called LoRAs that modify model behavior while leaving the original system untouched and appearing safe.