model-extraction-relu-logits
CommunityReverse-engineer ReLU network weights.
Software Engineering#reverse engineering#neural networks#model extraction#relu networks#weight recovery#machine learning security
AuthorZurybr
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the challenge of recovering the internal weight matrices of black-box ReLU neural networks when only input-output query access is available, crucial for understanding model behavior and security.
Core Features & Use Cases
- Weight Matrix Recovery: Extracts the first layer weight matrix (A1) of a two-layer ReLU network (
f(x) = A2 @ ReLU(A1 @ x)). - Model Extraction Attacks: Enables reverse-engineering of neural network parameters for security analysis or model understanding.
- Use Case: A security researcher wants to understand the internal structure of a deployed neural network model without access to its training data or architecture. This skill can help recover the hidden layer's weight matrix by querying the model.
Quick Start
Use the model-extraction-relu-logits skill to extract the weight matrix A1 from the provided black-box ReLU network function.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: model-extraction-relu-logits Download link: https://github.com/Zurybr/lefarma-skills/archive/main.zip#model-extraction-relu-logits Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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