Model Theft: How Attackers Steal Your Fine-Tuned AI Models Through API Extraction

TL;DR Fine-tuned AI models can be stolen by repeatedly querying them and recording outputs. An attacker reconstructs your model's weights by training a mimic model on the stolen output patterns. Cost: $500-5,000. Time: 1 week. Real examples: Meta's LLaMA stolen, enterprise models extracted by competitors. Your proprietary AI model is not protected once it's behind an API. What You Need To Know Model extraction is practical: Attackers can reconstruct 85%+ accurate copy of your fine-tuned model Cost is affordable: $500-5,000 per model (feasible for competitors or nation-states) Time is short: 1-2 weeks to exfiltrate a usable model Real precedent: Meta's LLaMA leaked, enterprise models extracted, research models cloned No technical protection: APIs don't prevent extraction — only rate limiting helps Your training data is at risk: Stolen model can be reverse-engineered to infer training data Competitive advantage stolen: Competitor uses your fine-tuned model for their product Supply chain