model-poisoning
Safeguard articles tagged "model-poisoning" — guides, analysis, and best practices for software supply chain and application security.
6 articles
AIBOM in 2026: Treating AI Models as a Software Supply Chain
The AI bill of materials is graduating from optional security artifact to procurement requirement. Here is what AIBOM/ML-BOM actually tracks in 2026, how it ties to the EU AI Act, and where it still falls short.
Fine-Tuning Poisoning Detection for Supply Chains
Fine-tuning inherits every problem of the base model and adds dataset provenance as a new one. Here is how detection actually works in practice.
AI Cybersecurity Glossary: Key Machine Learning & Security Terms
A defender's glossary of AI security terms — prompt injection, model poisoning, AI-BOM, adversarial ML — with dated, real-world incidents behind each one.
Detecting Model Supply Chain Poisoning in 2026
Poisoning attacks against the model supply chain have moved from research to incident reports. What detection looks like when the attack surface includes weights.
Understanding model poisoning and backdoored model weights
A poisoned model looks like any other checkpoint file. Here's how model poisoning attacks work, real incidents on Hugging Face, and how detection and provenance checks catch them.
AI Model Poisoning: Detection Techniques for the Software Supply Chain
Poisoned AI models are a supply chain threat that traditional security tools can't detect. Here are the emerging techniques for identifying compromised models.