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AI Risk

Extraction Attacks

"Extraction attacks [137] allow an adversary to query a black-box victim model and build a substitute model by training on the queries and responses. The substitute model could achieve almost the same performance as the victim model. While it is hard to fully replicate the capabilities of LLMs, adversaries could develop a domainspecific model that draws domain knowledge from LLMs"

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

Record summary

A quick snapshot of what this page covers.

Techniques16Attack methods connected to this risk.
Mitigations13Defenses that may help with related attacks.
Domain2. Privacy & SecurityThe broad risk area this belongs to.

Risk profile

How this risk is described and categorized.

Domain2. Privacy & Security
Subdomain2.2 > AI system security vulnerabilities and attacks
Entity1 - Human
Intent1 - Intentional
Timing2 - Post-deployment
CategoryModel Attacks
SubcategoryExtraction Attacks

Suggested mitigations

Defenses that may help with related attacks.

Memory Hardening

ML Model EngineeringDeployment+1 more
LifecycleML Model Engineering + 2 moreCategoryTechnical - ML

AI Telemetry Logging

DeploymentMonitoring and Maintenance
LifecycleDeployment + 1 moreCategoryTechnical - Cyber

Sanitize Training Data

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

Verify AI Artifacts

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

Code Signing

Deployment
LifecycleDeploymentCategoryTechnical - Cyber

AI Bill of Materials

Business and Data UnderstandingData Preparation+1 more
LifecycleBusiness and Data Understanding + 2 moreCategoryPolicy

Source

Research source for this risk, when available.