Publish Poisoned AI Artifacts
Description
Adversaries may create or modify AI artifacts and publish them through public or shared distribution channels to facilitate compromise of downstream AI systems. Poisoned AI artifacts may include datasets, models, and AI agent tools containing malicious content, behaviors, code, or configurations.
Adversaries may publish novel artifacts or malicious variants of legitimate artifacts through dataset or model repositories, package registries, source code repositories, tool hubs, or remotely hosted services. Victims may subsequently acquire and integrate these artifacts through AI Supply Chain Compromise.
- ATLAS ID
- AML.T0115
- Maturity
- RealizedUsed by real adversaries against AI systems in the wild.
- Platforms
- Predictive AIGenerative AIAgentic AI
Sub-techniques
Mitigations
- AML.M0007Sanitize Training Data
Dataset repositories inspect submissions and quarantine poisoned samples, labels, annotations, or metadata before listing.
- AML.M0008Validate AI Model
Model repositories evaluate submissions for backdoors, data leakage, adversarial influence, and unexpected behavior before listing.
- AML.M0016Vulnerability Scanning
Model and agent tool registries scan uploaded artifacts for malicious content before listing.
Case studies that use it
No ATLAS case study records this technique yet. Browse all case studies.