Individual skill
ml-model-extraction
Extract a functional clone of a black-box ML model via prediction API queries, and infer whether specific records were in the training set (membership inference).
packages/decepticon/decepticon/skills/standard/analyst/ml-model-extraction/SKILL.md
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- agent Repository topic
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- llm Repository topic
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# ML Model Extraction and Membership Inference
Two closely related attacks against deployed ML prediction APIs:
- **Model extraction (stealing):** reconstruct a functionally equivalent clone of the target
model using only its input/output pairs, without access to weights, architecture, or
training data. (Tramer et al. 2016, "Stealing Machine Learning Models via Prediction APIs")
- **Membership inference:** determine whether a specific record was used to train the target
model, breaching training-data confidentiality. (Shokri et al. 2017, "Membership Inference
Attacks Against Machine Learning Models")
These are distinct from LLM prompt-extraction attacks: the target is a classical ML model
(logistic regression, decision tree, DNN) or an ML-as-a-service endpoint (AWS SageMaker,
GCP AutoML, Azure ML, custom REST API).