from gym_malware.envs.utils.pefeatures import PEFeatureExtractor
# bytez = interface.fetch_file("Backdoor.Win32.Hupigon.zay")
# features = PEFeatureExtractor().extract2(bytez)
# features2 = PEFeatureExtractor().extract(bytez)
# print(features.__len__())
# print(features2.__len__())
# bytez = interface.fetch_file("VirusShare_0b3c009aa4e461a00c0b3755976b485e")
# # print(bytez)
# features = PEFeatureExtractor().extract(bytez)
# print(features.__len__())
# print(features)
file_list = interface.get_available_sha256()
np.set_printoptions(threshold=1e6)
# run the tests
extractor = PEFeatureExtractor()
index = 0
for sha256 in file_list:
print("{}:[file]:{}".format(index + 1, sha256))
bytez = interface.fetch_file(sha256)
index = index + 1
print(extractor.extract2(bytez))
print(extractor.extract2(bytez).shape)
if index > 1:
break
except FileNotFoundError:
# if you want to use the cloud interface, you must populate your own params.json
# file. Look at params.json.in for a template, which takes the following form
__private_data = {
"url": "http://my.av.api", # route to RESTful API interface
"username": "******", # Username
"password": "******", # password
"version": "1.0", # version
"threshold": 0.90 # threshold
}
# you may also need to change get_score_remote and/or get_label_remote below
# for local model
from gym_malware.envs.utils.pefeatures import PEFeatureExtractor
from sklearn.externals import joblib
feature_extractor = PEFeatureExtractor()
local_model = joblib.load(os.path.join(module_path, 'gradient_boosting.pkl'))
local_model_threshold = 0.90
class ClassificationFailure(Exception):
pass
class FileRetrievalFailure(Exception):
pass
def fetch_file(sha256):
location = os.path.join(SAMPLE_PATH, sha256)
try: