PromptRiskDBThreat intelligence atlas
AI Risk

Model weight leak

"Model weights or access to them can be leaked when initial access is granted only to a select group of individuals, such as institutional researchers [209]. This risk can increase as more people gain access, and identifying the source of the leak becomes more difficult. The availability of leaked model weights makes various attacks on systems that use the leaked AI model easier to implement, such as finding adver...

AI Risk2. Privacy & Security2.2 > AI system security vulnerabilities and attacks2 - Post-deployment

Record summary

A quick snapshot of what this page covers.

Techniques9Attack methods connected to this risk.
Mitigations14Defenses that may help with related attacks.
Domain2. Privacy & SecurityThe broad risk area this belongs to.

Risk profile

How this risk is described and categorized.

"Model weights or access to them can be leaked when initial access is granted only to a select group of individuals, such as institutional researchers [209]. This risk can increase as more people gain access, and identifying the source of the leak becomes more difficult. The availability of leaked model weights makes various attacks on systems that use the leaked AI model easier to implement, such as finding adversarial examples, elicitation of dangerous capabilities, and extraction of confidential information present in the training data. The avail- ability of model weights might also enable the misuse of the AI system using the leaked model to produce harmful or illegal content [67]."

Domain2. Privacy & Security
Subdomain2.2 > AI system security vulnerabilities and attacks
Entity1 - Human
Intent1 - Intentional
Timing2 - Post-deployment
CategoryCybersecurity
SubcategoryModel weight leak

Suggested mitigations

Defenses that may help with related attacks.

Generative AI Guardrails

ML Model EngineeringML Model Evaluation+1 more
LifecycleML Model Engineering + 2 moreCategoryTechnical - ML

Generative AI Guidelines

ML Model EngineeringML Model Evaluation+1 more
LifecycleML Model Engineering + 2 moreCategoryTechnical - ML

AI Telemetry Logging

DeploymentMonitoring and Maintenance
LifecycleDeployment + 1 moreCategoryTechnical - Cyber

Model Hardening

Data PreparationML Model Engineering
LifecycleData Preparation + 1 moreCategoryTechnical - ML

Use Multi-Modal Sensors

Business and Data UnderstandingData Preparation+1 more
LifecycleBusiness and Data Understanding + 2 moreCategoryTechnical - Cyber

Input Restoration

Data PreparationML Model Evaluation+2 more
LifecycleData Preparation + 3 moreCategoryTechnical - ML

Deepfake Detection

DeploymentMonitoring and Maintenance+2 more
LifecycleDeployment + 3 moreCategoryTechnical - ML

Source

Research source for this risk, when available.