subhash011 / malware-detector

Malware Detector

To run the detector use the command python3 MalwareDetection.py directory_name where directory_name is the name of the directory with test files The output will be available as output.csv in the same directory.

Test Structure

• directory_name

  • hash of folder (static)
    • string.txt
    • structure_info.txt
  • hash of json (dynamic)

  Note: Static and Dynamic can be in any order. The above structure must be followed

Libraries used:

pandas
os
csv
random
pickle
argparse
numpy
seaborn
requests
shutil
statistics
sklearn
time
ast

Dataset:

The Features directory contains datasets for both static and dynamic analysis as pickle files which stores pandas dataframes.

dynamic directory:

Contains test data(pandas dataframe), test labels(numpy array), train data for benigns(pandas dataframe), train data foor malwares(pandas dataframe)

static directory:

Contains test data(pandas dataframe), test labels(numpy array), train data for benigns(pandas dataframe), train data foor malwares(pandas dataframe)

models:

contains models built for static and dynamic analysis respectively. The models are RandomForestClassifiers from sklearn.