Model Weight Exfiltration

Model weights embody the investment and capabilities of AI development. Once stolen, they can be run anywhere, modified freely, and are effectively impossible to recall.

Exfiltration paths include:

• Insider threats: Employees or contractors copying weights.
• Infrastructure compromise: Attacks on training or serving environments.
• Supply chain access: Third parties with access to model artifacts.
• Misconfigured storage: Weights left in publicly accessible buckets.
• Model extraction: Reconstructing behavior through repeated queries.

RAND's research on securing model weights describes escalating security levels needed to protect frontier models against increasingly capable attackers, including nation-states.

Enterprises fine-tuning or hosting their own models face a smaller version of the same problem and need access controls, storage security, and monitoring for model artifacts.

How PointGuard AI Helps

PointGuard AI AI Security Posture Management detects exposed model artifacts and risky storage configurations, and AI Discovery inventories models across environments so security teams know where valuable weights live.

Learn More

• RAND: Securing AI Model Weights
• MITRE ATLAS
• NIST AI Risk Management Framework