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PYAS.py

@@ -70,7 +70,7 @@ class MainWindow_Controller(QMainWindow): # 初始化主程式
 
     def init_config_vars(self): # 初始化變數
         self.pyae_version = "AI Engine"
-        self.pyas_version = "3.2.9"
+        self.pyas_version = "3.3.0"
         self.mbr_value = None
         self.track_proc = None
         self.first_startup = 1
@@ -78,6 +78,7 @@ class MainWindow_Controller(QMainWindow): # 初始化主程式
         self.gc_collect = 0
         self.block_window = 0
         self.total_scan = 0
+        self.scan_time = 0
         self.virus_lock = {}
         self.virus_list_ui = []
         self.Process_quantity = 0
@@ -1194,6 +1195,7 @@ class MainWindow_Controller(QMainWindow): # 初始化主程式
                 pass
             self.scan_file = True
             self.total_scan = 0
+            self.scan_time = time.time()
             self.virus_lock = {}
             self.virus_list_ui = []
             self.ui.Virus_Scan_Solve_Button.hide()
@@ -1270,17 +1272,19 @@ class MainWindow_Controller(QMainWindow): # 初始化主程式
         try:
             QMetaObject.invokeMethod(self.ui.Virus_Scan_title, "setText",
             Qt.QueuedConnection, Q_ARG(str, self.trans("病毒掃描")))
-            if self.virus_lock:
+            if self.virus_list_ui:
                 self.ui.Virus_Scan_Solve_Button.show()
                 self.ui.Virus_Scan_Break_Button.hide()
                 self.ui.Virus_Scan_choose_Button.show()
-                text = self.trans(f"當前發現 {len(self.virus_lock)} 個病毒，共掃描 {self.total_scan} 個檔案")
+                text = self.trans(f"當前發現 {len(self.virus_list_ui)} 個病毒")
             else:
                 self.virus_scan_break()
                 text = self.trans("當前未發現病毒")
+            takes_time = int(time.time() - self.scan_time) + 1
+            text_end = self.trans(f"，耗時 {takes_time} 秒，共掃描 {self.total_scan} 個檔案")
             QMetaObject.invokeMethod(self.ui.Virus_Scan_text, "setText",
-            Qt.QueuedConnection, Q_ARG(str, text))
-            self.send_notify(text)
+            Qt.QueuedConnection, Q_ARG(str, text+text_end))
+            self.send_notify(text+text_end)
         except Exception as e:
             print(e)
 
@@ -1363,21 +1367,21 @@ class MainWindow_Controller(QMainWindow): # 初始化主程式
 
     def start_scan(self, file): # 調用掃描引擎
         try:
-            match_data = self.model.get_type(file)
-            for section, data in match_data.items():
-                label, level = self.model.dl_scan(data)
-                if label and label in self.model.detect:
-                    if self.config_json["sensitivity"]:
-                        return f"{label}.{level}"
-                    elif level >= self.model.values:
-                        return f"{label}.{level}"
+            label, level = self.model.dl_scan(file)
+            if label and self.config_json["sensitivity"]:
+                return f"{label}.{level}"
+            elif label and level >= self.model.values:
+                return f"{label}.{level}"
+        except Exception as e:
+            print(e)
+        try:
             if self.config_json["extend_mode"]:
                 label, level = self.rules.yr_scan(file)
                 if label and isinstance(level, str):
                     return f"{label}.{level}"
-            return False
-        except:
-            return False
+        except Exception as e:
+            print(e)
+        return False
 
     def repair_system(self): # 修復系統
         try:

PYAS_Engine.py

@@ -1,5 +1,5 @@
-import os, sys, time, json, yara
-import numpy, pefile, onnxruntime
+import os, sys, time, json, yara, numpy
+import chardet, pefile, onnxruntime
 from PIL import Image
 
 class YRScan:
@@ -38,19 +38,27 @@ class YRScan:
 class DLScan:
     def __init__(self):
         self.models = {}
-        self.valid_interpolations = {"none": Image.Resampling.NEAREST,
-        "box": Image.Resampling.BOX, "bilinear": Image.Resampling.BILINEAR,
-        "hamming": Image.Resampling.HAMMING, "bicubic": Image.Resampling.BICUBIC,
-        "lanczos": Image.Resampling.LANCZOS, "nearest": Image.Resampling.NEAREST}
-        self.shells = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '!o',
-        'cry', 'test', 'ace', 'yg', 'obr', 'tvm', 'dec', 'enc', 'b1_', 'base',
-        'bss', 'clr_uef', 'cursors', 'trs_age', 'engine', 'enigma', 'protect',
-        'nep', 'no_bbt', 'wpp_sf', 'retpol', 'rt', 'rwexec', 'rygs', 'poolmi',
-        's:@', 'pgae', 'proxy', 'wisevec', 'segm', 'transit', 'vmp', 'extjmp',
-        'upx', 'tracesup', 'res', 'lzma', 'malloc_h', 'miniex', 'ndr64', 'be',
-        'mssmixer', 'wow', 'press', 'fio', 'pad', 'hexpthk', 'h~;', 'icapsec',
-        'sanontcp', 'secur', 'asmstub', 'nsys_wr', 'orpc', 'pack', 'wow64svc',
-        'uedbg', 'viahw', 'data', 'zk', 'fothk', 'qihoo']#"""
+        self.valid_interpolations = {
+        "box": Image.Resampling.BOX,
+        "none": Image.Resampling.NEAREST,
+        "bilinear": Image.Resampling.BILINEAR,
+        "hamming": Image.Resampling.HAMMING,
+        "bicubic": Image.Resampling.BICUBIC,
+        "lanczos": Image.Resampling.LANCZOS,
+        "nearest": Image.Resampling.NEAREST}
+
+        shell_section = ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", 
+        "cry", "tvm", "dec", "enc", "vmp", "upx", "aes", "lzma", "press", 
+        "pack", "enigma", "protect", "secur"]
+        unknown_section = ["asmstub", "base", "bss", "clr_uef", "cursors", 
+        "engine", "fio", "fothk", "h~;", "icapsec", "malloc_h", "miniex", 
+        "mssmixer", "ndr64", "nsys_wr", "obr", "wow", "wow64svc", "wpp_sf",
+        "pad", "pgae", "poolmi", "proxy", "qihoo", "res", "retpol", "uedbg",
+        "rwexec", "rygs", "s:@", "sanontcp", "segm", "test", "tracesup",
+        "transit", "trs_age", "wisevec"]
+        unimportant_section = ["viahwaes", "orpc", "nep", "ace", "extjmp", 
+        "no_bbt", "data", "page", "hexpthk"]
+        self.shells = shell_section + unimportant_section + unknown_section
 
     def load_model(self, file_path):
         try:
@@ -68,38 +76,63 @@ class DLScan:
         except Exception as e:
             pass
 
-    def dl_scan(self, file_data):
+    def dl_scan(self, file_path):
         try:
-            label_similarities = {label: [] for label in self.labels}
-            image_data = self.preprocess_image(file_data, tuple(self.resize))
-            image_array = numpy.asarray(image_data).astype('float32') / 255.0
-            image_expand = numpy.expand_dims(image_array, axis=(0, -1))
+            batch_images = []
+            for section, file_data in self.get_type(file_path).items():
+                image_data = self.preprocess_image(file_data, tuple(self.resize))
+                image_array = numpy.asarray(image_data).astype('float32') / 255.0
+                if len(image_array.shape) == 2:
+                    image_array = numpy.expand_dims(image_array, axis=-1)
+                batch_images.append(image_array)
+            batch_results = [{label: [] for label in self.labels} for _ in range(len(batch_images))]
+            batch_images = numpy.stack(batch_images, axis=0)
             for model_name, model in self.models.items():
                 input_name = model.get_inputs()[0].name
-                pre_answers = model.run(None, {input_name: image_expand})[0][0]
-                for k, score in enumerate(pre_answers):
-                    label_similarities[self.labels[k].strip()].append(score)
-            label_percentage = {label: (sum(similarities) / len(self.models)) * 100
-            for label, similarities in label_similarities.items()}
-            label, level = max(label_percentage.items(), key=lambda x: x[1])
-            return label, int(level)
+                predictions = model.run(None, {input_name: batch_images})[0]
+                for i, pre_answers in enumerate(predictions):
+                    for k, score in enumerate(pre_answers):
+                        batch_results[i][self.labels[k].strip()].append(score)
+            final_results = []
+            for result in batch_results:
+                label_percentage = {label: (sum(scores) / len(scores)) * 100
+                for label, scores in result.items()}
+                best_label, best_confidence = max(label_percentage.items(), key=lambda x: x[1])
+                final_results.append((best_label, int(best_confidence)))
+                if best_label in self.detect:
+                    return best_label, int(best_confidence)
+            return False, False
         except Exception as e:
             return False, False
 
     def preprocess_image(self, file_data, target_size):
         width, height, channels, interpolation = target_size
-        wah = int(numpy.ceil(numpy.sqrt(len(file_data))))
-        file_data = numpy.frombuffer(file_data, dtype=numpy.uint8)
-        image_array = numpy.zeros((wah * wah,), dtype=numpy.uint8)
-        image_array[:len(file_data)] = file_data
+        wah = int(numpy.ceil(numpy.sqrt(len(file_data) / channels)))
+        array_data = numpy.frombuffer(file_data, dtype=numpy.uint8)
+        expected_size = wah * wah * channels
+        image_array = numpy.zeros((expected_size,), dtype=numpy.uint8)
+        image_array[:len(file_data)] = array_data
         if channels == 1:
-            image = Image.fromarray(image_array.reshape((wah, wah)), 'L')
+            reshape = image_array.reshape((wah, wah))
+            image = Image.fromarray(reshape, 'L')
         elif channels == 3:
-            image = Image.fromarray(image_array.reshape((wah, wah)), 'RGB')
+            reshape = image_array.reshape((wah, wah, 3))
+            image = Image.fromarray(reshape, 'RGB')
         if width == 0 and height == 0:
             return image
-        interpolations = self.valid_interpolations[interpolation.lower()]
-        return image.resize((width, height), interpolations)
+        i = self.valid_interpolations.get(interpolation.lower(), Image.BILINEAR)
+        return image.resize((width, height), i)
+
+    def is_text_file(self, content, sample_size):
+        try:
+            raw_data = content[:sample_size]
+            encoding = chardet.detect(raw_data)["encoding"]
+            if encoding in ["ascii", "utf-8", "utf-8-sig"]:
+                if raw_data.decode(encoding):
+                    return True
+            return False
+        except:
+            return False
 
     def get_type(self, file_path):
         match_data = {}
@@ -108,13 +141,14 @@ class DLScan:
             try:
                 with pefile.PE(file_path, fast_load=True) as pe:
                     for section in pe.sections:
-                        section_name = section.Name.rstrip(b'\x00').decode('latin1')
+                        name = section.Name.rstrip(b'\x00').decode('latin1')
                         if (section.Characteristics & 0x00000020 and not
-                        any(shell in section_name.lower() for shell in self.shells)):
-                            match_data[section_name] = section.get_data()
+                        any(s in name.lower() for s in self.shells)):
+                            print(name)
+                            match_data[name] = section.get_data()
             except:
-                if ftype in [".bat", ".cmd", ".ps1", ".vbs", ".wsf", ".html", 
-                ".js", ".txt", ".htm", ".hta", ".php", ".css", ".xml", ".json"]:
-                    with open(file_path, 'rb') as file:
-                        match_data[ftype] = file.read()
+                with open(file_path, 'rb') as f:
+                    file_content = f.read()
+                if self.is_text_file(file_content, 1024):
+                    match_data[ftype] = file_content
         return match_data

PYAS_Interface.py

@@ -1112,7 +1112,7 @@ class Ui_MainWindow(object):
         self.Window_title.setGeometry(QtCore.QRect(10, 0, 661, 41))
         font = QtGui.QFont()
         font.setFamily("Microsoft YaHei")
-        font.setPointSize(15)
+        font.setPointSize(13)
         font.setBold(False)
         font.setWeight(50)
         self.Window_title.setFont(font)

PYAS_Language.py

@@ -62,4 +62,5 @@ translate_dict = {
               "指定":"Specify ","清空":"Empty ","資源回收桶":"Recycle Bin ",
               "與":"With ","當":"When ","功能":"Function ","異常":"Abnormal ",
               "重置":"Reset ","窗口":"Window ","暫存":"Temp ","自訂":"Custom ",
-              "不支持":"Not Support ","共":"Total ","時":"","  ":" "}}
+              "不支持":"Not Support ","共":"Total ","秒":"Seconds ","耗時":"Takes ",
+              "時":"","  ":" "}}

PYAS_Version.py

@@ -2,7 +2,7 @@ import pyinstaller_versionfile
 
 pyinstaller_versionfile.create_versionfile(
 output_file="versionfile.txt",
-version='3.2.9',
+version='3.3.0',
 company_name="PYAS Security",
 file_description="Python Antivirus Software",
 internal_name="PYAS",

README.md

@@ -1,6 +1,6 @@
 # PYAS (Python Antivirus Software)
 
-![PYAS](https://github.com/user-attachments/assets/39c273b9-c467-480a-a8b3-31714a6df3ef)
+![PYAS_UI](https://github.com/user-attachments/assets/68765836-7272-482f-b8cd-d8ba728d88ab)
 
 ## Readme Language
 
@@ -11,13 +11,15 @@
 ## Requirements
 
 ```
-pip install pefile==2023.2.7
-pip install pyperclip==1.8.2
-pip install PyQt5==5.15.9
-pip install yara-python==4.5.1
-pip install numpy==2.1.1
+pip install chardet==5.2.0
+pip install numpy==1.26.3
 pip install onnxruntime==1.18.1
+pip install pefile==2023.2.7
 pip install pillow==10.4.0
+pip install pyperclip==1.8.2
+pip install PyQt5==5.15.11
+pip install requests==2.32.3
+pip install yara-python==4.5.1
 ```
 
 ## File Information

README_zh_CN.md

@@ -1,17 +1,19 @@
 # PYAS (Python 杀毒软件)
 
-![PYAS](https://github.com/user-attachments/assets/39c273b9-c467-480a-a8b3-31714a6df3ef)
+![PYAS_UI](https://github.com/user-attachments/assets/68765836-7272-482f-b8cd-d8ba728d88ab)
 
 ## 安装要求
 
 ```
-pip install pefile==2023.2.7
-pip install pyperclip==1.8.2
-pip install PyQt5==5.15.9
-pip install yara-python==4.5.1
-pip install numpy==2.1.1
+pip install chardet==5.2.0
+pip install numpy==1.26.3
 pip install onnxruntime==1.18.1
+pip install pefile==2023.2.7
 pip install pillow==10.4.0
+pip install pyperclip==1.8.2
+pip install PyQt5==5.15.11
+pip install requests==2.32.3
+pip install yara-python==4.5.1
 ```
 
 ## 文件信息

README_zh_TW.md

@@ -1,17 +1,19 @@
 # PYAS (Python 防毒軟體)
 
-![PYAS](https://github.com/user-attachments/assets/39c273b9-c467-480a-a8b3-31714a6df3ef)
+![PYAS_UI](https://github.com/user-attachments/assets/68765836-7272-482f-b8cd-d8ba728d88ab)
 
 ## 安裝要求
 
 ```
-pip install pefile==2023.2.7
-pip install pyperclip==1.8.2
-pip install PyQt5==5.15.9
-pip install yara-python==4.5.1
-pip install numpy==2.1.1
+pip install chardet==5.2.0
+pip install numpy==1.26.3
 pip install onnxruntime==1.18.1
+pip install pefile==2023.2.7
 pip install pillow==10.4.0
+pip install pyperclip==1.8.2
+pip install PyQt5==5.15.11
+pip install requests==2.32.3
+pip install yara-python==4.5.1
 ```
 
 ## 檔案資訊