Record summary
A quick snapshot of what this page covers.
Risk profile
How this risk is described and categorized.
"Backdoors can be inserted into GPAI models during their training or fine-tuning, to be exploited during deployment [185, 118]. Attackers inserting the backdoor can be the GPAI model provider themselves or another actor (e.g., by ma- nipulating the training data or the software infrastructure used by the model provider) [222]. Some backdoors can be exploited with minimal overhead, al- lowing attackers to control the model outputs in a targeted way with a high success rate [90]."
Suggested mitigations
Defenses that may help with related attacks.
Control Access to AI Models and Data at Rest
Sanitize Training Data
Validate AI Model
Code Signing
Maintain AI Dataset Provenance
Encrypt Sensitive Information
Source
Research source for this risk, when available.
Included resource
Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.
