AI & LLM
ML Model & Supply Chain Testing
Malicious model files, unsafe deserialization and poisoned dependencies in your ML pipeline.
Scoped to your environmentFixed proposalFree retest within 6 monthsNamed operator
What is ML Model and Supply Chain Testing? ML supply chain testing evaluates how models, weights, adapters and datasets enter your environment, and whether a malicious artifact — such as a pickle-based model file — could execute code or alter model behavior.
What we test
- Model file deserialization (pickle, joblib)
- Model registry & artifact integrity
- Third-party adapters and plugins
- Training & fine-tuning data poisoning
- Inference server exposure
- Dependency and container review
What you get
- Named operator from kickoff to readout
- Kill Chain Replay™ attack paths with evidence
- Risk-rated findings and remediation guidance
- Framework mapping for your auditor
- Live readout call
- Free retest of all findings within 6 months
ML Model & Supply Chain Testing FAQ
Why is a model file a security risk?
Several common model formats can embed executable code that runs when the model is loaded. We test whether your pipeline would run it.
What do we receive at the end?
An executive summary, Kill Chain Replay™ attack paths, risk-rated findings mapped to the relevant frameworks, remediation guidance, a readout call and a free retest of every reported finding within 6 months.
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