Update test.py

Genius3/raw-feature-extractor/test.py

@@ -8,21 +8,7 @@ import random
 import shutil
 from tqdm import tqdm
 import csv
-
+import pandas as pd
-
-def func():
-    path = "D:\\hkn\\infected\\datasets\\virusshare_infected0_dot\\VirusShare_ccbfc20470b099a188bda55aa8421427.dot"
-    result = []
-    with open(path, 'r') as f:
-        for line in f:
-            if '->' in line:
-                result.append(re.findall(r'\b\d+\b', line))
-    print(result)
-
-
-def func1():
-    for f in os.listdir("D:\\hkn\\infected\\datasets\\virusshare_infected0_dot"):
-        print(f[:-4])
 
 
 def create_dir():
@@ -118,13 +104,16 @@ def delete_jsonl():
 
 
 def delete_all_local():
-    src = 'D:\\hkn\\infected\\datasets\\proprecessed_pt'
+    data_dirs = ['D:\\hkn\\infected\\datasets\\virusshare_train\\1',
-    dirs = ['train_malware', 'test_malware', 'valid_malware', 'train_benign', 'test_benign', 'valid_benign',
+                 'D:\\hkn\\infected\\datasets\\virusshare_train\\2',
-            'train_malware_backup', 'test_malware_backup', 'valid_malware_backup']
+                 'D:\\hkn\\infected\\datasets\\virusshare_train\\3',
-    for d in dirs:
+                 'D:\\hkn\\infected\\datasets\\virusshare_train\\4',
-        path = os.path.join(src, d)
+                 'D:\\hkn\\infected\\datasets\\virusshare_train\\5',
-        for f in os.listdir(path):
+                 ]
-            os.remove(os.path.join(path, f))
+    for d in data_dirs:
+        path = os.listdir(d)
+        for f in path:
+            os.remove(os.path.join(d, f))
 
 
 # 重命名pt文件使之与代码相符
@@ -140,35 +129,20 @@ def rename(mal_or_be, postfix):
             os.rename(os.path.join(data_dir, f), os.path.join(data_dir, '{}_{}.pt'.format(mal_or_be, index)))
 
 
-def split_samples(flag):
+def split_data_by_label():
-    postfix = ''
+    all = 'D:\\hkn\\infected\\datasets\\virusshare_train\\all_pt'
-    if flag == 'one_family':
+    dest = 'D:\\hkn\\infected\\datasets\\virusshare_train'
-        path = 'D:\\hkn\\infected\\datasets\\proprecessed_pt\\one_family_malware'
+    csv_path = 'F:\\kkk\\dataset\\virusshare_AllLabel.csv'
-        tag = 'malware'
+    with open(csv_path, 'r') as label:
-    elif flag == 'standard':
+        label.readline()
-        path = 'D:\\hkn\\infected\\datasets\\proprecessed_pt\\all'
+        labels = label.readlines()
-        postfix = '_backup'
+        for lines in labels:
-        tag = 'malware'
+            name, cls = lines.strip().split(',')
-    elif flag == 'benign':
+            fpath = os.path.join(all, name + '.pt')
-        path = 'D:\\hkn\\infected\\datasets\\proprecessed_pt\\all_benign'
+            if os.path.exists(fpath):
-        tag = 'benign'
+                shutil.move(fpath, os.path.join(dest, cls))
-    else:
+            else:
-        return
+                print(fpath, 'file not exist.')
-
-    out = 'D:\\hkn\\infected\\datasets\\proprecessed_pt'
-    os_list = os.listdir(path)
-    random.shuffle(os_list)
-    # 8/1/1 分数据
-    train_len = int(len(os_list) * 0.8)
-    test_len = int(train_len / 8)
-    for index, f in enumerate(os_list):
-        if index < train_len:
-            shutil.copy(os.path.join(path, f), os.path.join(out, 'train_{}'.format(tag) + postfix))
-        elif train_len <= index < train_len + test_len:
-            shutil.copy(os.path.join(path, f), os.path.join(out, 'test_{}'.format(tag) + postfix))
-        else:
-            shutil.copy(os.path.join(path, f), os.path.join(out, 'valid_{}'.format(tag) + postfix))
-    rename(tag, postfix)
 
 
 def half_divide():
@@ -277,8 +251,107 @@ def generate_benign_csv():
             writer.writerow({fieldnames[0]: f, fieldnames[1]: '5'})
 
 
+def process_csv():
+    csv_path = 'F:\\kkk\\dataset\\virusshare_AllLabel.csv'
+    files = os.listdir('D:\\hkn\\infected\\datasets\\virusshare_train\\pe')
+    print(files.__len__())
+    df = df[df['Id'].isin(files)]
+    df = df.drop_duplicates('Id')
+    df['Id'] = 'VirusShare_' + df['Id']
+    df.to_csv(csv_path, index=False)
+
+
+def generate_virusshare_csv():
+    index = {'wacatac': 1, 'ulpm': 2, 'fugrafa': 3, 'redcap': 4}
+    fieldnames = ['Id', 'Class']
+    pe_dir = 'D:\\hkn\\infected\\datasets\\virusshare_train\\pe'
+    family_dir = 'D:\\hkn\\infected\\datasets\\virusshare_family'
+    csv_out = 'D:\\hkn\\infected\\datasets\\virusshare_family.csv'
+    with open(csv_out, "wb") as output_file:
+        writer = csv.DictWriter(output_file, fieldnames=fieldnames)
+        writer.writeheader()
+        for f in tqdm(os.listdir(family_dir)):
+            with open(os.path.join(family_dir, f), 'r') as family:
+                lines = family.readlines()
+                for line in lines:
+                    md5, label = line.strip().split('\t')
+                    if label in index:
+                        if os.path.exists(os.path.join(pe_dir, 'VirusShare_' + md5)):
+                            writer.writerow({fieldnames[0]: 'VirusShare_' + md5, fieldnames[1]: index[label]})
+
+
+def findlostone():
+    pe_dir = 'D:\\hkn\\infected\\datasets\\virusshare_train\\pe'
+    asm_dir = 'D:\\hkn\\infected\\datasets\\virusshare_train\\asm'
+    for f in os.listdir(pe_dir):
+        if not os.path.exists(os.path.join(asm_dir, f + '.asm')):
+            print(f)
+
+
+def find_pe_in_original_set():
+    for workflow in range(0, 69):
+        data_dir = 'D:\\hkn\\infected\\datasets\\virusshare_infected{}_json'.format(workflow)
+        for f in os.listdir(data_dir):
+            if f[:-6] == 'VirusShare_0f07b29873cf503a0fb69fa064ce76a3':
+                print(workflow)
+                return
+
+
+def select_jsonl():
+    csv_paths = 'F:\\kkk\\dataset\\virusshare_family.csv'
+    jsonl_dir = 'D:\\hkn\\infected\\datasets\\virusshare_train\\malware_jsonl'
+
+    with open(csv_paths, 'r') as csv_path:
+        labels = csv.reader(csv_path, delimiter=',')
+        data = list(labels)
+        for workflow in range(0, 69):
+            data_dir = 'D:\\hkn\\infected\\datasets\\virusshare_infected{}_json'.format(workflow)
+            for f in os.listdir(data_dir):
+                for line in data:
+                    if f[:-6] in line:
+                        shutil.copy(os.path.join(data_dir, f), jsonl_dir)
+                        break
+
+
+def generate_csv():
+    pe_dir = 'D:\\hkn\\infected\\datasets\\virusshare_train\\5\\pe'
+    csv_path = 'D:\\hkn\\infected\\datasets\\virusshare_train\\5\\virusshare_5.csv'
+    fieldnames = ['Id', 'Class']
+    with open(csv_path, "wb") as output_file:
+        writer = csv.DictWriter(output_file, fieldnames=fieldnames)
+        writer.writeheader()
+        for pe in os.listdir(pe_dir):
+            writer.writerow({fieldnames[0]: pe, fieldnames[1]: 5})
+
+
+def merge_csvs(cs, out):
+    for i, c in enumerate(cs):
+        if i == 0:
+            merged = pd.read_csv(c)
+        else:
+            merged = pd.merge(pd.read_csv(c), merged, on='Id')
+            # merged = pd.concat([merged, pd.read_csv(c)])
+
+    # if 'Class' in merged:
+    #     merged['Class'] = merged['Class'] - 1
+    merged.to_csv(out, index=False)
+
 if __name__ == '__main__':
-    generate_benign_csv()
+    # find_pe_in_original_set()
+    # split_data_by_label()
+    # select_jsonl()
+    # findlostone()
+    # generate_csv()
+    # generate_virusshare_csv()
+    # merge_csvs([
+    #     'D:\\hkn\\infected\\datasets\\virusshare_train\\virusshare_1_compliment.csv',
+    #     'D:\\hkn\\infected\\datasets\\virusshare_family.csv',
+    #     'D:\\hkn\\infected\\datasets\\virusshare_train\\virusshare_5.csv',
+    # ],
+    #     'D:\\hkn\\infected\\datasets\\virusshare_family.csv'
+    # )
+    process_csv()
+    # generate_benign_csv()
     # create_pixel_intensity()
     # create_dir()
     # change_max_item_lines()
@@ -294,7 +367,7 @@ if __name__ == '__main__':
 
     # 指定 'standard' or 'benign' or 'one_family'
     # standard表示处理所有恶意样本
-    # split_samples('standard')
+    # split_samples()
     # one_family表示仅处理一个家族，仅用于测试原模型的二分类
     # split_samples('one_family')
     # benign表示处理良性样本