Predicting code vulnerabilities using machine learning classifier models trained on internal analysis states

An example system includes a processor to receive a source code sample to be classified. The processor can execute a hybrid code analysis to generate an internal analysis state. The processor can extract features from the internal analysis state via a trained machine learning model modified using tr...

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Hauptverfasser:	Copty, Fady, Doron, Shai, Igbaria, Reda
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS
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creator	Copty, Fady Doron, Shai Igbaria, Reda
description	An example system includes a processor to receive a source code sample to be classified. The processor can execute a hybrid code analysis to generate an internal analysis state. The processor can extract features from the internal analysis state via a trained machine learning model modified using transfer learning. The processor can generate a label based on the extracted features via a machine learning classifier model trained on internal analysis states of hybrid code analyses.
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title	Predicting code vulnerabilities using machine learning classifier models trained on internal analysis states
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