Record summary
A quick snapshot of what this page covers.
Techniques8Attack methods connected to this risk.
Mitigations15Defenses 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
Timing1 - Pre-deployment
CategoryModel Attacks
SubcategoryEvasion Attacks
Suggested mitigations
Defenses that may help with related attacks.
Model Hardening
Data PreparationML Model Engineering
Use Ensemble Methods
ML Model Engineering
Use Multi-Modal Sensors
Business and Data UnderstandingData Preparation+1 more
Input Restoration
Data PreparationML Model Evaluation+2 more
Adversarial Input Detection
Data PreparationML Model Engineering+3 more
Deepfake Detection
DeploymentMonitoring and Maintenance+2 more
Generative AI Guardrails
ML Model EngineeringML Model Evaluation+1 more
Generative AI Guidelines
ML Model EngineeringML Model Evaluation+1 more
Generative AI Model Alignment
ML Model EngineeringML Model Evaluation+1 more
Memory Hardening
ML Model EngineeringDeployment+1 more
Control Access to AI Models and Data at Rest
Business and Data UnderstandingData Preparation+2 more
Encrypt Sensitive Information
Data PreparationML Model Engineering+1 more
AI Model Distribution Methods
Deployment
Limit Public Release of Information
Business and Data Understanding
Limit Model Artifact Release
Business and Data UnderstandingDeployment
Source
Research source for this risk, when available.
Included resource
Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.