Record summary
A quick snapshot of what this page covers.
Techniques8Attack methods connected to this risk.
Mitigations11Defenses that may help with related attacks.
Domain1. Discrimination & ToxicityThe broad risk area this belongs to.
Risk profile
How this risk is described and categorized.
"If the training data includes illegal or harmful information, such as false, biased, or IPR-infringing content, or lacks diversity in its sources, the output may include harmful content like illegal, malicious, or extreme information. Training data is also at risk of being poisoned through tampering, error injection, or misleading actions by attackers. This can interfere with the model's probability distribution, reducing its accuracy and reliability."
Domain1. Discrimination & Toxicity
Subdomain1.2 > Exposure to toxic content
Entity1 - Human
Intent3 - Other
Timing1 - Pre-deployment
CategoryAI's inherent safety risks
SubcategoryRisks from data (Risks of improper content and poisoning in training data)
Suggested mitigations
Defenses that may help with related attacks.
AI Telemetry Logging
DeploymentMonitoring and Maintenance
Privileged AI Agent Permissions Configuration
Deployment
Single-User AI Agent Permissions Configuration
Deployment
AI Agent Tools Permissions Configuration
Deployment
Human In-the-Loop for AI Agent Actions
Deployment
Restrict AI Agent Tool Invocation on Untrusted Data
Deployment
Segmentation of AI Agent Components
DeploymentBusiness and Data Understanding
Input and Output Validation for AI Agent Components
Business and Data UnderstandingData Preparation+1 more
Control Access to AI Models and Data at Rest
Business and Data UnderstandingData Preparation+2 more
Validate AI Model
ML Model EvaluationMonitoring and Maintenance
Code Signing
Deployment
Source
Research source for this risk, when available.
Included resource
AI Safety Governance Framework
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.