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AI Risk

Poisoning

"Data Poisoning involves deliberately corrupting a model’s training dataset to introduce vulnerabilities, derail its learning process, or cause it to make incorrect predictions (Carlini et al., 2023). For example, the tool Nightshade is a data poisoning tool, which allows artists to add invisible changes to the pixels in their art before uploading online, to break any models that use it for training.9 Such attacks...

AI Risk2. Privacy & Security2.2 > AI system security vulnerabilities and attacks1 - Pre-deployment

Record summary

A quick snapshot of what this page covers.

Techniques27Attack methods connected to this risk.
Mitigations21Defenses that may help with related attacks.
Domain2. Privacy & SecurityThe broad risk area this belongs to.

Risk profile

How this risk is described and categorized.

"Data Poisoning involves deliberately corrupting a model’s training dataset to introduce vulnerabilities, derail its learning process, or cause it to make incorrect predictions (Carlini et al., 2023). For example, the tool Nightshade is a data poisoning tool, which allows artists to add invisible changes to the pixels in their art before uploading online, to break any models that use it for training.9 Such attacks exploit the fact that most GenAI models are trained on publicly available datasets like images and videos scraped from the web, which malicious actors can easily compromise."

Domain2. Privacy & Security
Subdomain2.2 > AI system security vulnerabilities and attacks
Entity1 - Human
Intent1 - Intentional
Timing1 - Pre-deployment
CategoryMisuse tactics to compromise GenAI systems (Model integrity)
SubcategoryPoisoning

Suggested mitigations

Defenses that may help with related attacks.

Validate AI Model

ML Model EvaluationMonitoring and Maintenance
LifecycleML Model Evaluation + 1 moreCategoryTechnical - ML

Code Signing

Deployment
LifecycleDeploymentCategoryTechnical - Cyber

Sanitize Training Data

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

AI Telemetry Logging

DeploymentMonitoring and Maintenance
LifecycleDeployment + 1 moreCategoryTechnical - Cyber

Memory Hardening

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

Model Hardening

Data PreparationML Model Engineering
LifecycleData Preparation + 1 moreCategoryTechnical - ML

Input Restoration

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

AI Bill of Materials

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

Verify AI Artifacts

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

Source

Research source for this risk, when available.