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AssigneeSentinel Labs Israel Ltd.
InventorsShlomi Salem, Roy Ronen, Assaf Nativ, Amit Zohar, Gal Braun, Pavel Ferencz, Eitan Shterenbaum, Tal Maimon
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Disclosed herein are systems and methods for enabling the automatic detection of executable code from a stream of bytes. In some embodiments, the stream of bytes can be sourced from the hidden areas of files that traditional malware detection solutions ignore. In some embodiments, a machine learning model is trained to detect whether a particular stream of bytes is executable code. Other embodiments described herein disclose systems and methods for automatic feature extraction using a neural network. Given a new file, the systems and methods may preprocess the code to be inputted into a trained neural network. The neural network may be used as a “feature generator” for a malware detection model. Other embodiments herein are directed to systems and methods for identifying, flagging, and/or detecting threat actors which attempt to obtain access to library functions independently.
A system for library position independent code detection, the system comprising:
A computer implemented method for library position independent code detection, the method comprising:
Dependencies are inferred from the claim text.