APromptRiskDBThreat intelligence atlas
AI Mitigation

Sanitize Training Data - AI Mitigation

Detect and remove or remediate poisoned training data. Training data should be sanitized prior to model training and recurrently for an active learning model. Implement a filter to limit ingested training data. Establish a content policy that would remove unwanted content such as certain explicit or offensive language from being used.

AI MitigationBusiness and Data UnderstandingData PreparationMonitoring and MaintenanceTechnical - ML

Record summary

A quick snapshot of what this page covers.

Techniques4Attacks this defense is designed to help with.
Lifecycle3Where this defense applies in the AI lifecycle.
Categories1How the source groups this defense.

Control summary

What this defense is meant to help prevent.

ATLAS ID
AML.M0007
Priority score
20
Business and Data UnderstandingData PreparationMonitoring and Maintenance
Technical - ML

Covered techniques

Attacks this defense is designed to help with.

AML.T0010.002 - Data

realized

Detect and remove or remediate poisoned data to avoid adversarial model drift or backdoor attacks.

Source

Where this page information comes from.