Add files via upload

Embed/Dockerfile

@@ -1,16 +0,0 @@
-FROM python:3.10-slim
-
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    libfuzzy-dev \
-    git \
-    && rm -rf /var/lib/apt/lists/*
-
-WORKDIR /app
-
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
-
-COPY . .
-
-CMD ["python", "-u", "predict_onnx_linux.py"]

Embed/PYAS_Analyze_API.py

@@ -1,211 +0,0 @@
-import os, time, uuid, logging, requests, hashlib
-
-from pathlib import Path
-from typing import Optional, List, Dict, Any
-
-####################################################################################################
-
-class PYAS_Client:
-    def __init__(self, api_key: str, host: str, timeout: int = 30):
-        self.base_url = host.rstrip('/')
-        self.timeout = timeout
-        self.logger = logging.getLogger("PYAS_API")
-        self.session = requests.Session()
-        self.session.headers.update({"X-API-Key": api_key, "User-Agent": "PYAS-API/1.1"})
-        self.logger.info(f"Initialized PYAS API Client targeting {self.base_url}")
-
-    def _request(self, method: str, endpoint: str, **kwargs) -> Optional[requests.Response]:
-        self.logger.debug(f"Request: {method} {endpoint}")
-        try:
-            r = self.session.request(method, f"{self.base_url}{endpoint}", timeout=self.timeout, **kwargs)
-            if r.status_code == 200:
-                return r
-
-            error_map = {401: "API Key invalid", 402: "Insufficient points", 404: "Not found", 500: "Server Error"}
-            self.logger.error(f"[{endpoint}] Failed: {error_map.get(r.status_code, f'HTTP {r.status_code}')}")
-
-        except Exception as e:
-            self.logger.error(f"Connection error: {e}")
-        return None
-
-####################################################################################################
-
-    def _calculate_sha256(self, path: Path) -> str:
-        self.logger.debug(f"Calculating SHA256 for {path}")
-        sha256_hash = hashlib.sha256()
-
-        with open(path, "rb") as f:
-            for byte_block in iter(lambda: f.read(1048576), b""):
-                sha256_hash.update(byte_block)
-
-        return sha256_hash.hexdigest()
-
-    def upload_file(self, file_path: str, chunk_size: int = 5242880) -> Optional[str]:
-        path = Path(file_path)
-        if not path.exists():
-            self.logger.error(f"File not found: {file_path}")
-            return None
-        
-        file_size = path.stat().st_size
-        self.logger.info(f"Initiating upload for {path.name} ({file_size} bytes)")
-
-        if file_size > 536870912:
-            self.logger.error(f"File size exceeds 512MB limit: {file_size} bytes")
-            return None
-
-        local_sha256 = self._calculate_sha256(path)
-        status_req = self._request("GET", f"/api/processing_status/{local_sha256}")
-        
-        if status_req and status_req.json().get('status') in ['done', 'processing', 'queued']:
-            self.logger.info(f"File already exists or processing on server: {local_sha256}")
-            return local_sha256
-
-        if file_size > chunk_size:
-            return self._upload_chunked(path, chunk_size, file_size)
-        return self._upload_standard(path)
-
-####################################################################################################
-
-    def _upload_standard(self, path: Path, max_retries: int = 3) -> Optional[str]:
-        self.logger.info(f"Starting standard upload for {path.name}")
-        with open(path, 'rb') as f:
-            file_data = f.read()
-
-        for attempt in range(max_retries):
-            r = self._request("POST", "/api/upload", files={'file': (path.name, file_data)})
-            if r and 'url' in r.json():
-                sha256 = r.json().get('url', '').split('/')[-1]
-                self.logger.info(f"Standard upload successful: {sha256}")
-                return sha256
-
-            self.logger.warning(f"Standard upload retry {attempt + 1}/{max_retries}")
-            time.sleep(1)
-        
-        self.logger.error("Standard upload failed after retries")
-        return None
-
-    def _upload_chunked(self, path: Path, chunk_size: int, file_size: int, max_retries: int = 3) -> Optional[str]:
-        total_chunks = (file_size + chunk_size - 1) // chunk_size
-        upload_id = uuid.uuid4().hex
-        self.logger.info(f"Starting chunked upload for {path.name} (Chunks: {total_chunks}, ID: {upload_id})")
-        
-        with open(path, 'rb') as f:
-            for i in range(total_chunks):
-                chunk_data = f.read(chunk_size)
-                headers = {"X-Chunk-Index": str(i), "X-Total-Chunks": str(total_chunks), "X-Upload-ID": upload_id}
-                
-                chunk_success = False
-                for attempt in range(max_retries):
-                    r = self._request("POST", "/api/upload", files={'file': (path.name, chunk_data)}, headers=headers)
-                    if r:
-                        chunk_success = True
-                        self.logger.debug(f"Uploaded chunk {i + 1}/{total_chunks}")
-
-                        if i == total_chunks - 1 and 'url' in r.json():
-                            sha256 = r.json().get('url', '').split('/')[-1]
-                            self.logger.info(f"Chunked upload successful: {sha256}")
-                            return sha256
-
-                        break
-
-                    self.logger.warning(f"Chunk upload retry {attempt + 1}/{max_retries} for chunk {i}")
-                    time.sleep(1)
-                
-                if not chunk_success:
-                    self.logger.error(f"Failed to upload chunk {i + 1}/{total_chunks}")
-                    return None
-        return None
-
-####################################################################################################
-
-    def wait_for_analysis(self, sha256: str, interval: int = 5, max_retries: int = 10) -> bool:
-        self.logger.info(f"Waiting for analysis completion: {sha256}")
-        for attempt in range(max_retries):
-            r = self._request("GET", f"/api/processing_status/{sha256}")
-            if r:
-                status = r.json().get('status')
-                self.logger.debug(f"Analysis status: {status}")
-
-                if status == 'done':
-                    self.logger.info(f"Analysis completed: {sha256}")
-                    return True
-
-                if status in ['missing', 'error', 'failed']:
-                    self.logger.error(f"Analysis failed with status: {status}")
-                    return False
-
-            time.sleep(interval)
-        
-        self.logger.error(f"Analysis polling timed out for {sha256}")
-        return False
-
-    def get_report(self, sha256: str) -> Optional[Dict[str, Any]]:
-        self.logger.info(f"Fetching report for {sha256}")
-        r = self._request("GET", f"/api/report/{sha256}")
-        if r:
-            return r.json()
-
-        self.logger.error(f"Failed to fetch report for {sha256}")
-        return None
-
-####################################################################################################
-
-    def rescan(self, sha256: str) -> bool:
-        self.logger.info(f"Triggering rescan for {sha256}")
-        r = self._request("POST", f"/api/rescan/{sha256}")
-
-        success = bool(r and r.json().get('status') == 'success')
-        if success:
-            self.logger.info(f"Rescan triggered successfully for {sha256}")
-        else:
-            self.logger.error(f"Rescan failed for {sha256}")
-        return success
-
-    def search_files(self, query: str, limit: int = 50, page: int = 0, snapshot: Optional[str] = None) -> List[Dict[str, Any]]:
-        self.logger.info(f"Searching files (Query: '{query}', Limit: {limit}, Page: {page})")
-        payload = {'query': query, 'page': page}
-        if snapshot:
-            payload['snapshot'] = snapshot
-
-        r = self._request("POST", "/api/search_more", data=payload)
-        results = r.json().get('results', [])[:limit] if r else []
-        self.logger.info(f"Search returned {len(results)} results")
-        return results
-
-    def download_sample(self, sha256: str, save_dir: str = "downloads") -> Optional[str]:
-        self.logger.info(f"Downloading sample {sha256}")
-        os.makedirs(save_dir, exist_ok=True)
-        path = os.path.join(save_dir, f"{sha256}.zip")
-
-        r = self._request("GET", f"/api/download/{sha256}", stream=True)
-        if r:
-            with open(path, 'wb') as f:
-                for chunk in r.iter_content(8192):
-                    if chunk:
-                        f.write(chunk)
-            self.logger.info(f"Sample downloaded successfully to {path}")
-            return path
-
-        self.logger.error(f"Failed to download sample {sha256}")
-        return None
-
-####################################################################################################
-
-if __name__ == "__main__":
-    logging.basicConfig(level=logging.DEBUG, format='[%(asctime)s] %(levelname)s [%(name)s] - %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
-    
-    API_KEY = ""
-    HOST = "https://pyas-security.com/" 
-    
-    client = PYAS_Client(API_KEY, HOST)
-    target_file = r"test.exe"
-    
-    sha = client.upload_file(target_file)
-    if sha and client.wait_for_analysis(sha):
-        report = client.get_report(sha)
-        if report:
-            meta = report.get('data', {}).get('metadata', {})
-            logging.info(f"Result: {meta.get('label')} ({meta.get('score')}%)")
-            
-    for item in client.search_files('date>=2020; ext=exe | dll', limit=3):
-        client.download_sample(item['sha256'])

Embed/features.json

@@ -1 +0,0 @@
-["FileEntropy", "SectionMeanEntropy", "IsExe", "IsDll", "IsDriver", "Is64Bit", "Machine", "Magic", "CheckSum", "ImageBase", "SizeOfImage", "SizeOfHeaders", "Characteristics", "DllCharacteristics", "Subsystem", "LoaderFlags", "MajorLinkerVersion", "MinorLinkerVersion", "SizeOfCode", "SizeOfInitializedData", "SizeOfUninitializedData", "AddressOfEntryPoint", "BaseOfCode", "SectionAlignment", "FileAlignment", "MajorOperatingSystemVersion", "MinorOperatingSystemVersion", "MajorImageVersion", "MinorImageVersion", "MajorSubsystemVersion", "MinorSubsystemVersion", "SizeOfStackReserve", "SizeOfStackCommit", "SizeOfHeapReserve", "SizeOfHeapCommit", "NumberOfSections", "NumberOfRvaAndSizes", "PointerToSymbolTable", "NumberOfSymbols", "SizeOfOptionalHeader", "TextSectionMaxEntropy", "TextSectionMeanEntropy", "TextSizeRatio", "DataSectionMaxEntropy", "DataSectionMeanEntropy", "DataSizeRatio", "RsrcSectionMaxEntropy", "RsrcSectionMeanEntropy", "RsrcSizeRatio", "SectionCount", "ExecutableSections", "WritableSections", "ReadableSections", "SectionException", "Char_00000020_Count", "Char_00000020_MeanEntropy", "Char_00000040_Count", "Char_00000040_MeanEntropy", "Char_00000080_Count", "Char_00000080_MeanEntropy", "Char_02000000_Count", "Char_02000000_MeanEntropy", "Char_20000000_Count", "Char_20000000_MeanEntropy", "Char_40000000_Count", "Char_40000000_MeanEntropy", "Char_80000000_Count", "Char_80000000_MeanEntropy", "IconCount", "ApiCount", "ExportCount", "DebugCount", "ExceptionCount", "ImportCount", "ImportFunctionCount", "FileDescriptionLength", "FileVersionLength", "ProductNameLength", "ProductVersionLength", "CompanyNameLength", "LegalCopyrightLength", "CommentsLength", "InternalNameLength", "LegalTrademarksLength", "SpecialBuildLength", "PrivateBuildLength", "TrustSigned", "IsDebug", "IsPatched", "IsPrivateBuild", "IsPreRelease", "IsSpecialBuild", "IsAdmin", "IsInstall", "HasTlsCallbacks", "HasInvalidTimestamp", "HasRelocationDirectory", "HasPacked", "FileTimeException", "Cat_AntiDebug", "Cat_Audio", "Cat_COM", "Cat_Camera", "Cat_Clipboard", "Cat_DataObfuscation", "Cat_DotNet", "Cat_Encryption", "Cat_FileIO", "Cat_Graphics", "Cat_Injection", "Cat_Input", "Cat_Keylogging", "Cat_Memory", "Cat_MultiThreading", "Cat_Native", "Cat_Network", "Cat_Privileges", "Cat_ProcessControl", "Cat_Registry", "Cat_Resource", "Cat_ScreenCapture", "Cat_Services", "Cat_Synchronization", "Cat_WindowControl", "Dll_advapi32_dll", "Dll_bcrypt_dll", "Dll_comctl32_dll", "Dll_crypt32_dll", "Dll_dbghelp_dll", "Dll_gdi32_dll", "Dll_hal_dll", "Dll_imagehlp_dll", "Dll_iphlpapi_dll", "Dll_kernel32_dll", "Dll_mscoree_dll", "Dll_netapi32_dll", "Dll_ntdll_dll", "Dll_ole32_dll", "Dll_oleaut32_dll", "Dll_psapi_dll", "Dll_shell32_dll", "Dll_shlwapi_dll", "Dll_urlmon_dll", "Dll_user32_dll", "Dll_vbscript_dll", "Dll_version_dll", "Dll_winhttp_dll", "Dll_wininet_dll", "Dll_winmm_dll", "Dll_ws2_32_dll", "Dll_wsock32_dll", "Dll_wtsapi32_dll", "Api_AdjustTokenPrivileges", "Api_Base64Decode", "Api_BitBlt", "Api_CallNextHookEx", "Api_CallWindowProcA", "Api_CapCreateCaptureWindowA", "Api_CapCreateCaptureWindowW", "Api_CharLowerA", "Api_CharUpperA", "Api_CheckRemoteDebuggerPresent", "Api_CloseClipboard", "Api_CloseHandle", "Api_CoCreateInstance", "Api_CoInitialize", "Api_CoUninitialize", "Api_CompareStringA", "Api_ConnectNamedPipe", "Api_ControlService", "Api_CopyFileA", "Api_CopyFileW", "Api_CreateCompatibleBitmap", "Api_CreateCompatibleDC", "Api_CreateDCA", "Api_CreateDCW", "Api_CreateEventA", "Api_CreateEventW", "Api_CreateFileA", "Api_CreateFileMappingA", "Api_CreateFileMappingW", "Api_CreateFileW", "Api_CreateMutexA", "Api_CreateMutexW", "Api_CreateProcessA", "Api_CreateProcessW", "Api_CreateRemoteThread", "Api_CreateServiceA", "Api_CreateServiceW", "Api_CreateThread", "Api_CreateThreadpoolWork", "Api_CreateWindowExA", "Api_CryptAcquireContextA", "Api_CryptAcquireContextW", "Api_CryptCreateHash", "Api_CryptDecodeObject", "Api_CryptDecrypt", "Api_CryptDeriveKey", "Api_CryptDestroyHash", "Api_CryptDestroyKey", "Api_CryptEncrypt", "Api_CryptExportKey", "Api_CryptGenKey", "Api_CryptHashData", "Api_CryptImportKey", "Api_CryptReleaseContext", "Api_D3D11CreateDevice", "Api_DecodePointer", "Api_DefWindowProcA", "Api_DeleteCriticalSection", "Api_DeleteDC", "Api_DeleteFileA", "Api_DeleteFileW", "Api_DeleteObject", "Api_DeleteService", "Api_DestroyWindow", "Api_DeviceIoControl", "Api_Direct3DCreate9", "Api_DispatchMessageA", "Api_DnsQuery_A", "Api_DnsQuery_W", "Api_EncodePointer", "Api_EnterCriticalSection", "Api_EnumChildWindows", "Api_EnumWindows", "Api_ExitProcess", "Api_ExitThread", "Api_FindClose", "Api_FindFirstFileA", "Api_FindNextFileA", "Api_FindResourceA", "Api_FindWindowA", "Api_FindWindowW", "Api_FlushFileBuffers", "Api_FreeEnvironmentStringsW", "Api_FreeLibrary", "Api_FreeResource", "Api_GdipSaveImageToFile", "Api_GetACP", "Api_GetActiveWindow", "Api_GetAsyncKeyState", "Api_GetCapture", "Api_GetClientRect", "Api_GetClipboardData", "Api_GetCommandLineA", "Api_Line truncated

Embed/predict_onnx_linux.py

@@ -1,611 +0,0 @@
-import os, sys, time, re, math, pefile, json, datetime, mmap
-import numpy as np
-import onnxruntime as ort
-from signify.authenticode.signed_file.pe import SignedPEFile
-from signify.authenticode.verification_result import AuthenticodeVerificationResult
-
-####################################################################################################
-
-MODEL_FILE = "model.onnx"
-FEATURE_FILE = "features.json"
-MAX_FILE_SIZE = 4 * 1024 * 1024 * 1024
-
-####################################################################################################
-
-class WinTrust:
-    @staticmethod
-    def verify(file_path):
-        if not file_path or not os.path.exists(file_path) or os.path.getsize(file_path) == 0:
-            return 0
-        try:
-            with open(file_path, 'rb') as f:
-                with mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ) as mm:
-                    pe = SignedPEFile(mm)
-                    if not pe.signatures:
-                        return 0
-
-                    status, _ = pe.explain_verify()
-                    if status == AuthenticodeVerificationResult.OK:
-                        return 1
-        except Exception:
-            pass
-        return 0
-
-####################################################################################################
-
-class FeatureExtractor:
-    API_CAT_MAPPING = {
-        'ProcessControl': {
-            'CreateProcessA', 'CreateProcessW', 'WinExec', 'ShellExecuteA', 'ShellExecuteW',
-            'ShellExecuteExW', 'ExitProcess', 'TerminateProcess', 'OpenProcess', 'GetExitCodeProcess',
-            'SetThreadPriority', 'GetThreadPriority', 'GetCurrentProcess', 'GetCurrentProcessId',
-            'GetModuleFileNameA', 'GetCommandLineA', 'GetModuleFileNameW', 'GetStartupInfoW'
-        },
-        'Injection': {
-            'VirtualAlloc', 'VirtualAllocEx', 'VirtualProtect', 'VirtualProtectEx', 'WriteProcessMemory', 
-            'ReadProcessMemory', 'CreateRemoteThread', 'QueueUserAPC', 'SetThreadContext', 'GetThreadContext', 
-            'Wow64SetThreadContext', 'NtUnmapViewOfSection', 'ZwUnmapViewOfSection', 'RtlCreateUserThread', 
-            'SetWindowsHookExA', 'SetWindowsHookExW', 'UnhookWindowsHookEx', 'LoadLibraryA', 'LoadLibraryW', 
-            'LoadLibraryExA', 'LoadLibraryExW', 'GetProcAddress', 'GetModuleHandleA', 'GetModuleHandleW',
-            'FreeLibrary', 'CreateFileMappingA', 'CreateFileMappingW', 'MapViewOfFile', 'UnmapViewOfSection',
-            'VirtualFree', 'VirtualQuery'
-        },
-        'Synchronization': {
-            'WaitForSingleObject', 'WaitForSingleObjectEx', 'WaitForMultipleObjects', 'WaitForMultipleObjectsEx',
-            'CreateMutexA', 'CreateMutexW', 'OpenMutexW', 'ReleaseMutex', 'CreateEventA', 'CreateEventW', 
-            'OpenEventW', 'SetEvent', 'ResetEvent', 'EnterCriticalSection', 'LeaveCriticalSection', 
-            'InitializeCriticalSection', 'DeleteCriticalSection', 'Sleep', 'SleepEx',
-            'InitializeCriticalSectionAndSpinCount', 'InterlockedDecrement', 'InterlockedIncrement', 
-            'InterlockedExchange', 'InterlockedCompareExchange', 'SetTimer', 'KillTimer'
-        },
-        'MultiThreading': {
-            'CreateThread', 'ResumeThread', 'SuspendThread', 'ExitThread', 'TerminateThread',
-            'GetCurrentThread', 'GetCurrentThreadId', 'TlsAlloc', 'TlsSetValue', 'TlsGetValue',
-            'CreateThreadpoolWork', 'SubmitThreadpoolWork', 'TlsFree'
-        },
-        'Network': {
-            'socket', 'connect', 'send', 'recv', 'bind', 'listen', 'accept', 'gethostbyname', 'getaddrinfo',
-            'WSAStartup', 'WSACleanup', 'WSAIoctl', 'WSASocketA', 'WSASocketW', 'closesocket', 'htons',
-            'InternetOpenA', 'InternetOpenW', 'InternetConnectA', 'InternetConnectW', 'InternetOpenUrlA', 
-            'InternetOpenUrlW', 'HttpOpenRequestA', 'HttpOpenRequestW', 'HttpSendRequestA', 'HttpSendRequestW',
-            'InternetReadFile', 'URLDownloadToFileA', 'URLDownloadToFileW', 'DnsQuery_A', 'DnsQuery_W'
-        },
-        'Encryption': {
-            'CryptAcquireContextA', 'CryptAcquireContextW', 'CryptCreateHash', 'CryptHashData', 
-            'CryptDeriveKey', 'CryptEncrypt', 'CryptDecrypt', 'CryptDestroyKey', 'CryptDestroyHash',
-            'CryptReleaseContext', 'CryptGenKey', 'CryptImportKey', 'CryptExportKey'
-        },
-        'DataObfuscation': {
-            'RtlDecompressBuffer', 'MultiByteToWideChar', 'WideCharToMultiByte', 'Base64Decode', 
-            'CryptDecodeObject', 'IsDBCSLeadByte', 'CharUpperA', 'CharLowerA',
-            'GetStringTypeW', 'LCMapStringW', 'IsValidCodePage', 'DecodePointer', 'EncodePointer'
-        },
-        'FileIO': {
-            'CreateFileA', 'CreateFileW', 'WriteFile', 'ReadFile', 'DeleteFileA', 'DeleteFileW',
-            'CopyFileA', 'CopyFileW', 'MoveFileA', 'MoveFileW', 'FindFirstFileA', 'FindNextFileA',
-            'GetTempPathA', 'GetTempPathW', 'GetTempFileNameA', 'GetTempFileNameW', 'SetFileAttributesA', 
-            'SetFileAttributesW', 'DeviceIoControl', 'SetFileTime', 'GetFileSize', 'GetFileSizeEx',
-            'SetFilePointer', 'FlushFileBuffers', 'ConnectNamedPipe', 'PeekNamedPipe',
-            'CloseHandle', 'GetFileType', 'SetStdHandle', 'SetFilePointerEx', 'FindClose', 
-            'SetHandleCount', 'SetEndOfFile', 'GetFullPathNameA', 'GetFileAttributesA'
-        },
-        'Registry': {
-            'RegOpenKeyExA', 'RegOpenKeyExW', 'RegSetValueExA', 'RegSetValueExW', 
-            'RegCreateKeyExA', 'RegCreateKeyExW', 'RegDeleteKeyA', 'RegDeleteKeyW',
-            'RegEnumValueA', 'RegEnumValueW', 'RegQueryValueExA', 'RegQueryValueExW',
-            'RegDeleteValueA', 'RegDeleteValueW', 'RegCloseKey'
-        },
-        'Services': {
-            'OpenSCManagerA', 'OpenSCManagerW', 'CreateServiceA', 'CreateServiceW',
-            'StartServiceA', 'StartServiceW', 'ControlService', 'DeleteService'
-        },
-        'Privileges': {
-            'AdjustTokenPrivileges', 'LookupPrivilegeValueA', 'LookupPrivilegeValueW', 
-            'OpenProcessToken', 'NetUserAdd', 'NetLocalGroupAddMembers', 'IsAdmin', 
-            'GetUserNameA', 'GetUserNameW'
-        },
-        'Native': {
-            'RtlUnwind', 'RtlVirtualUnwind', 'RtlCaptureContext', 'RtlLookupFunctionEntry',
-            'NtClose', 'NtQueryInformationProcess', 'RtlAllocateHeap', 'RtlFreeHeap',
-            'GetSystemTimeAsFileTime', 'GetLocalTime', 'GlobalMemoryStatus', 
-            'GetVersionExA', 'GetVersionExW', 'GetComputerNameA', 'GetComputerNameW',
-            'GetLastError', 'GetACP', 'RaiseException', 'SetLastError', 'GetEnvironmentStringsW', 
-            'FreeEnvironmentStringsW', 'GetLocaleInfoA', 'lstrlenA', 'GetVersion', 'GetSystemInfo', 
-            'CompareStringA'
-        },
-        'DotNet': {
-            '_CorExeMain', '_CorDllMain'
-        },
-        'AntiDebug': {
-            'IsDebuggerPresent', 'CheckRemoteDebuggerPresent', 'OutputDebugStringA', 'OutputDebugStringW',
-            'GetTickCount', 'GetTickCount64', 'QueryPerformanceCounter', 'FindWindowA', 'FindWindowW',
-            'EnumWindows', 'EnumChildWindows', 'GetWindowRect', 'GetClientRect', 'SetWindowDisplayAffinity',
-            'UnhandledExceptionFilter', 'SetUnhandledExceptionFilter', 'IsProcessorFeaturePresent', 
-            'SetErrorMode', 'GetTimeZoneInformation', 'GetDriveTypeW', 'GetDiskFreeSpaceA'
-        },
-        'Keylogging': {
-            'GetAsyncKeyState', 'GetKeyState', 'GetKeyboardState', 'MapVirtualKeyA', 'MapVirtualKeyW',
-            'ToAscii', 'ToAsciiEx', 'ToUnicode', 'ToUnicodeEx', 'GetKeyNameTextA', 'GetForegroundWindow',
-            'KeybdEvent', 'SendInput', 'MapVirtualKeyExA', 'MapVirtualKeyExW', 'CallNextHookEx'
-        },
-        'Input': {
-            'GetCursorPos', 'SetCursorPos', 'MouseEvent', 'GetDoubleClickTime', 
-            'GetCapture', 'SetCapture'
-        },
-        'ScreenCapture': {
-            'BitBlt', 'StretchBlt', 'GetDC', 'GetWindowDC', 'CreateCompatibleDC', 'CreateCompatibleBitmap',
-            'GdipSaveImageToFile', 'PrintWindow', 'GetDesktopWindow', 'CreateDCW', 'CreateDCA',
-            'SelectObject', 'DeleteDC', 'DeleteObject', 'GetDeviceCaps', 'GetSystemMetrics'
-        },
-        'Graphics': {
-            'Direct3DCreate9', 'D3D11CreateDevice'
-        },
-        'Audio': {
-            'WaveInOpen', 'WaveInClose', 'WaveInStart', 'WaveInStop'
-        },
-        'Clipboard': {
-            'OpenClipboard', 'CloseClipboard', 'GetClipboardData', 'SetClipboardData'
-        },
-        'Camera': {
-            'CapCreateCaptureWindowA', 'CapCreateCaptureWindowW'
-        },
-        'Memory': {
-            'HeapAlloc', 'HeapFree', 'HeapSize', 'HeapCreate', 'GetProcessHeap',
-            'LocalAlloc', 'LocalFree', 'GlobalAlloc', 'GlobalFree', 'GlobalUnlock',
-            'HeapDestroy', 'GlobalLock', 'SysFreeString', 'SysAllocStringLen'
-        },
-        'Resource': {
-            'LoadResource', 'SizeofResource', 'LockResource', 'FreeResource', 'FindResourceA'
-        },
-        'WindowControl': {
-            'ShowWindow', 'DestroyWindow', 'TranslateMessage', 'DispatchMessageA', 'GetWindow',
-            'PeekMessageA', 'GetWindowLongA', 'CallWindowProcA', 'SetWindowLongA', 'GetWindowTextA',
-            'ScreenToClient', 'GetActiveWindow', 'CreateWindowExA', 'DefWindowProcA', 'GetMessageA',
-            'RegisterClassA', 'UnregisterClassA', 'MessageBoxA'
-        },
-        'COM': {
-            'CoCreateInstance', 'CoUninitialize', 'CoInitialize'
-        }
-    }
-
-    TARGET_DLLS = {
-        'kernel32.dll', 'user32.dll', 'gdi32.dll', 'advapi32.dll', 'shell32.dll', 'ntdll.dll', 'hal.dll',
-        'ws2_32.dll', 'wsock32.dll', 'wininet.dll', 'winhttp.dll', 'urlmon.dll', 'crypt32.dll', 'bcrypt.dll',
-        'psapi.dll', 'dbghelp.dll', 'imagehlp.dll', 'shlwapi.dll', 'ole32.dll', 'oleaut32.dll', 'comctl32.dll',
-        'mscoree.dll', 'vbscript.dll', 'netapi32.dll', 'iphlpapi.dll', 'wtsapi32.dll', 'version.dll', 'winmm.dll'
-    }
-
-    BASE_SCHEMA = [
-        "FileEntropy", "SectionMeanEntropy", "IsExe", "IsDll", "IsDriver", "Is64Bit", "Machine", "Magic",
-        "CheckSum", "ImageBase", "SizeOfImage", "SizeOfHeaders",
-        "Characteristics", "DllCharacteristics", "Subsystem", "LoaderFlags",
-        "MajorLinkerVersion", "MinorLinkerVersion", "SizeOfCode", 
-        "SizeOfInitializedData", "SizeOfUninitializedData", "AddressOfEntryPoint",
-        "BaseOfCode", "SectionAlignment", "FileAlignment",
-        "MajorOperatingSystemVersion", "MinorOperatingSystemVersion",
-        "MajorImageVersion", "MinorImageVersion",
-        "MajorSubsystemVersion", "MinorSubsystemVersion",
-        "SizeOfStackReserve", "SizeOfStackCommit", "SizeOfHeapReserve", "SizeOfHeapCommit",
-        "NumberOfSections", "NumberOfRvaAndSizes", "PointerToSymbolTable", "NumberOfSymbols",
-        "SizeOfOptionalHeader",
-        
-        "TextSectionMaxEntropy", "TextSectionMeanEntropy", "TextSizeRatio", 
-        "DataSectionMaxEntropy", "DataSectionMeanEntropy", "DataSizeRatio", 
-        "RsrcSectionMaxEntropy", "RsrcSectionMeanEntropy", "RsrcSizeRatio", 
-        "SectionCount", "ExecutableSections", 
-        "WritableSections", "ReadableSections", "SectionException",
-
-        "Char_00000020_Count", "Char_00000020_MeanEntropy",
-        "Char_00000040_Count", "Char_00000040_MeanEntropy",
-        "Char_00000080_Count", "Char_00000080_MeanEntropy",
-        "Char_02000000_Count", "Char_02000000_MeanEntropy",
-        "Char_20000000_Count", "Char_20000000_MeanEntropy",
-        "Char_40000000_Count", "Char_40000000_MeanEntropy",
-        "Char_80000000_Count", "Char_80000000_MeanEntropy",
-        
-        "IconCount", "ApiCount", "ExportCount", "DebugCount", "ExceptionCount",
-        "ImportCount", "ImportFunctionCount",
-        
-        "FileDescriptionLength", "FileVersionLength", "ProductNameLength", 
-        "ProductVersionLength", "CompanyNameLength", "LegalCopyrightLength", 
-        "CommentsLength", "InternalNameLength", "LegalTrademarksLength",
-        "SpecialBuildLength", "PrivateBuildLength",
-        
-        "TrustSigned", "IsDebug", "IsPatched", "IsPrivateBuild", "IsPreRelease", 
-        "IsSpecialBuild", "IsAdmin", "IsInstall", "HasTlsCallbacks", 
-        "HasInvalidTimestamp", "HasRelocationDirectory", "HasPacked", "FileTimeException"
-    ]
-
-    CAT_SCHEMA = [f"Cat_{k}" for k in sorted(API_CAT_MAPPING.keys())]
-    DLL_SCHEMA = [f"Dll_{d.replace('.', '_')}" for d in sorted(TARGET_DLLS)]
-    
-    _ALL_APIS = {api for apis in API_CAT_MAPPING.values() for api in apis}
-    API_SCHEMA = [f"Api_{api}" for api in sorted(_ALL_APIS)]
-    
-    SCHEMA = BASE_SCHEMA + CAT_SCHEMA + DLL_SCHEMA + API_SCHEMA
-    
-    _API_TO_CATS = {}
-    for _cat, _apis in API_CAT_MAPPING.items():
-        for _api in _apis:
-            if _api not in _API_TO_CATS:
-                _API_TO_CATS[_api] = []
-            _API_TO_CATS[_api].append(_cat)
-
-    PACKERS = {
-        'upx', 'aspack', 'asprotect', 'pecompact', 'upack', 'fsg', 'mew', 
-        'mpress', 'ezip', 'pklt', 'shrink', 'petite', 'telock',
-        'themida', 'winlicense', 'tmd', 'vmp', 'enigma', 'obsidium', 
-        'pelock', 'exestealth', 'yoda', 'armadillo', 'zprotect',
-        'sforce', 'starforce', 'qihoo', 'wisevec', 'megastop',
-    }
-    INSTALLER_SIGS = [b"Nullsoft.NSIS", b"Inno Setup", b"7-Zip.7zip", b"InstallShield"]
-
-####################################################################################################
-
-    @staticmethod
-    def _safe_float(val):
-        try:
-            f = float(val)
-            if math.isinf(f) or math.isnan(f): return 0.0
-            return f
-        except Exception:
-            return 0.0
-
-    @staticmethod
-    def _calc_entropy(data):
-        if not data: return 0.0
-        arr = np.frombuffer(data, dtype=np.uint8)
-        counts = np.bincount(arr, minlength=256)
-        probs = counts[counts > 0] / len(arr)
-        return float(-np.sum(probs * np.log2(probs)))
-
-    @staticmethod
-    def _safe_div(n, d):
-        return float(n) / d if d > 0 else 0.0
-
-####################################################################################################
-
-    @classmethod
-    def extract(cls, file_path):
-        fts = {k: 0.0 for k in cls.SCHEMA}
-        pe = None
-        try:
-            fsize = os.path.getsize(file_path)
-            if fsize == 0 or fsize > MAX_FILE_SIZE:
-                return None
-
-            with open(file_path, "rb") as f:
-                file_bytes = f.read()
-
-            pe = pefile.PE(data=file_bytes, fast_load=True)
-            fts['TrustSigned'] = WinTrust.verify(file_path)
-
-            fh = pe.FILE_HEADER
-            fts['Machine'] = fh.Machine
-            fts['NumberOfSections'] = fh.NumberOfSections
-            fts['TimeDateStamp'] = fh.TimeDateStamp
-            fts['PointerToSymbolTable'] = fh.PointerToSymbolTable
-            fts['NumberOfSymbols'] = fh.NumberOfSymbols
-            fts['SizeOfOptionalHeader'] = fh.SizeOfOptionalHeader
-            fts['Characteristics'] = fh.Characteristics
-
-            curr_ts = datetime.datetime.utcnow().timestamp()
-            fts['HasInvalidTimestamp'] = 1 if (fh.TimeDateStamp < 631152000 or fh.TimeDateStamp > curr_ts + 2592000) else 0
-            fts['FileTimeException'] = 1 if fh.TimeDateStamp == 0 else 0
-
-            if hasattr(pe, 'OPTIONAL_HEADER'):
-                op = pe.OPTIONAL_HEADER
-                fts['Magic'] = getattr(op, 'Magic', 0)
-                fts['MajorLinkerVersion'] = getattr(op, 'MajorLinkerVersion', 0)
-                fts['MinorLinkerVersion'] = getattr(op, 'MinorLinkerVersion', 0)
-                fts['SizeOfCode'] = getattr(op, 'SizeOfCode', 0)
-                fts['SizeOfInitializedData'] = getattr(op, 'SizeOfInitializedData', 0)
-                fts['SizeOfUninitializedData'] = getattr(op, 'SizeOfUninitializedData', 0)
-                fts['AddressOfEntryPoint'] = getattr(op, 'AddressOfEntryPoint', 0)
-                fts['BaseOfCode'] = getattr(op, 'BaseOfCode', 0)
-                fts['ImageBase'] = getattr(op, 'ImageBase', 0)
-                fts['SectionAlignment'] = getattr(op, 'SectionAlignment', 0)
-                fts['FileAlignment'] = getattr(op, 'FileAlignment', 0)
-                fts['MajorOperatingSystemVersion'] = getattr(op, 'MajorOperatingSystemVersion', 0)
-                fts['MinorOperatingSystemVersion'] = getattr(op, 'MinorOperatingSystemVersion', 0)
-                fts['MajorImageVersion'] = getattr(op, 'MajorImageVersion', 0)
-                fts['MinorImageVersion'] = getattr(op, 'MinorImageVersion', 0)
-                fts['MajorSubsystemVersion'] = getattr(op, 'MajorSubsystemVersion', 0)
-                fts['MinorSubsystemVersion'] = getattr(op, 'MinorSubsystemVersion', 0)
-                fts['SizeOfImage'] = getattr(op, 'SizeOfImage', 0)
-                fts['SizeOfHeaders'] = getattr(op, 'SizeOfHeaders', 0)
-                fts['CheckSum'] = getattr(op, 'CheckSum', 0)
-                fts['Subsystem'] = getattr(op, 'Subsystem', 0)
-                fts['DllCharacteristics'] = getattr(op, 'DllCharacteristics', 0)
-                fts['SizeOfStackReserve'] = getattr(op, 'SizeOfStackReserve', 0)
-                fts['SizeOfStackCommit'] = getattr(op, 'SizeOfStackCommit', 0)
-                fts['SizeOfHeapReserve'] = getattr(op, 'SizeOfHeapReserve', 0)
-                fts['SizeOfHeapCommit'] = getattr(op, 'SizeOfHeapCommit', 0)
-                fts['LoaderFlags'] = getattr(op, 'LoaderFlags', 0)
-                fts['NumberOfRvaAndSizes'] = getattr(op, 'NumberOfRvaAndSizes', 0)
-                fts['Is64Bit'] = 1 if fh.Machine in (0x8664, 0xAA64, 0x0200) else 0
-                fts['IsExe'] = 1 if pe.is_exe() else 0
-                fts['IsDll'] = 1 if pe.is_dll() else 0
-                fts['IsDriver'] = 1 if fts['Subsystem'] == 1 else 0
-
-                if hasattr(op, 'DATA_DIRECTORY'):
-                    reloc_idx = pefile.DIRECTORY_ENTRY.get('IMAGE_DIRECTORY_ENTRY_BASERELOC', 5)
-                    if len(op.DATA_DIRECTORY) > reloc_idx and op.DATA_DIRECTORY[reloc_idx].Size > 0:
-                        fts['HasRelocationDirectory'] = 1
-
-            try:
-                fts['FileEntropy'] = cls._calc_entropy(file_bytes)
-            except Exception:
-                pass
-
-            sec_entropies = []
-            text_entropies = []
-            data_entropies = []
-            rsrc_entropies = []
-            char_flags = [0x00000020, 0x00000040, 0x00000080, 0x02000000, 0x20000000, 0x40000000, 0x80000000]
-
-            if hasattr(pe, 'sections'):
-                fts['SectionCount'] = len(pe.sections)
-                for section in pe.sections:
-                    try: 
-                        name = section.Name.decode('ascii', 'ignore').strip('\x00')
-                    except Exception: 
-                        name = ""
-                        
-                    try: 
-                        s_data = section.get_data()
-                        s_entropy = cls._calc_entropy(s_data)
-                    except Exception: 
-                        s_data = b""
-                        s_entropy = 0.0
-
-                    sec_entropies.append(s_entropy)
-
-                    if any(p in name.lower() for p in cls.PACKERS): fts['HasPacked'] = 1
-                    if section.Characteristics & 0x20000000: fts['ExecutableSections'] += 1
-                    if section.Characteristics & 0x80000000: fts['WritableSections'] += 1
-                    if section.Characteristics & 0x40000000: fts['ReadableSections'] += 1
-                    if section.SizeOfRawData + section.PointerToRawData > fsize: fts['SectionException'] = 1
-
-                    for flag in char_flags:
-                        if section.Characteristics & flag:
-                            fts[f'Char_{flag:08X}_Count'] += 1
-                            fts[f'Char_{flag:08X}_MeanEntropy'] += s_entropy
-
-                    ratio = cls._safe_div(section.SizeOfRawData, fsize)
-                    if name.startswith('.text'):
-                        text_entropies.append(s_entropy)
-                        fts['TextSizeRatio'] += ratio
-                    elif name.startswith('.data'):
-                        data_entropies.append(s_entropy)
-                        fts['DataSizeRatio'] += ratio
-                    elif name.startswith('.rsrc'):
-                        rsrc_entropies.append(s_entropy)
-                        fts['RsrcSizeRatio'] += ratio
-                        if b"requireAdministrator" in s_data: fts['IsAdmin'] = 1
-                        for sig in cls.INSTALLER_SIGS:
-                            if sig in s_data:
-                                fts['IsInstall'] = 1
-                                break
-
-            fts['SectionMeanEntropy'] = cls._safe_div(sum(sec_entropies), len(sec_entropies))
-            fts['TextSectionMaxEntropy'] = max(text_entropies) if text_entropies else 0.0
-            fts['TextSectionMeanEntropy'] = cls._safe_div(sum(text_entropies), len(text_entropies))
-            fts['DataSectionMaxEntropy'] = max(data_entropies) if data_entropies else 0.0
-            fts['DataSectionMeanEntropy'] = cls._safe_div(sum(data_entropies), len(data_entropies))
-            fts['RsrcSectionMaxEntropy'] = max(rsrc_entropies) if rsrc_entropies else 0.0
-            fts['RsrcSectionMeanEntropy'] = cls._safe_div(sum(rsrc_entropies), len(rsrc_entropies))
-
-            for flag in char_flags:
-                fts[f'Char_{flag:08X}_MeanEntropy'] = cls._safe_div(fts[f'Char_{flag:08X}_MeanEntropy'], fts[f'Char_{flag:08X}_Count'])
-
-            try:
-                pe.parse_data_directories(directories=[
-                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_IMPORT'],
-                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_EXPORT'],
-                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_RESOURCE'],
-                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_DEBUG'],
-                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_TLS']
-                ])
-            except Exception:
-                pass
-
-            if hasattr(pe, 'DIRECTORY_ENTRY_TLS') and hasattr(pe.DIRECTORY_ENTRY_TLS, 'struct'):
-                if getattr(pe.DIRECTORY_ENTRY_TLS.struct, 'AddressOfCallBacks', 0) != 0:
-                    fts['HasTlsCallbacks'] = 1
-
-            if hasattr(pe, 'VS_FIXEDFILEINFO') and len(pe.VS_FIXEDFILEINFO) > 0:
-                flags = getattr(pe.VS_FIXEDFILEINFO[0], 'FileFlags', 0)
-                fts['IsDebug'] = 1 if flags & 0x1 else 0
-                fts['IsPreRelease'] = 1 if flags & 0x2 else 0
-                fts['IsPatched'] = 1 if flags & 0x4 else 0
-                fts['IsPrivateBuild'] = 1 if flags & 0x8 else 0
-                fts['IsSpecialBuild'] = 1 if flags & 0x20 else 0
-
-            if hasattr(pe, 'FileInfo'):
-                for fileinfo_list in pe.FileInfo:
-                    for fileinfo in fileinfo_list:
-                        if getattr(fileinfo, 'name', '') in ('StringFileInfo', b'StringFileInfo'):
-                            for st in getattr(fileinfo, 'StringTable', []):
-                                for key, val in st.entries.items():
-                                    try:
-                                        k = key.decode('utf-8', 'ignore') if isinstance(key, bytes) else str(key)
-                                        v = val.decode('utf-8', 'ignore') if isinstance(val, bytes) else str(val)
-                                        length = len(v)
-                                        if k == 'FileDescription': fts['FileDescriptionLength'] = length
-                                        elif k == 'FileVersion': fts['FileVersionLength'] = length
-                                        elif k == 'ProductName': fts['ProductNameLength'] = length
-                                        elif k == 'ProductVersion': fts['ProductVersionLength'] = length
-                                        elif k == 'CompanyName': fts['CompanyNameLength'] = length
-                                        elif k == 'LegalCopyright': fts['LegalCopyrightLength'] = length
-                                        elif k == 'Comments': fts['CommentsLength'] = length
-                                        elif k == 'InternalName': fts['InternalNameLength'] = length
-                                        elif k == 'LegalTrademarks': fts['LegalTrademarksLength'] = length
-                                        elif k == 'SpecialBuild': fts['SpecialBuildLength'] = length
-                                        elif k == 'PrivateBuild': fts['PrivateBuildLength'] = length
-                                    except Exception:
-                                        continue
-
-            if hasattr(pe, 'DIRECTORY_ENTRY_IMPORT'):
-                fts['ImportCount'] = len(pe.DIRECTORY_ENTRY_IMPORT)
-                for entry in pe.DIRECTORY_ENTRY_IMPORT:
-                    if getattr(entry, 'dll', None):
-                        try:
-                            dll_name = entry.dll.decode('ascii', 'ignore').lower()
-                            if dll_name in cls.TARGET_DLLS: 
-                                fts[f"Dll_{dll_name.replace('.', '_')}"] = 1.0
-                        except Exception: 
-                            pass
-                    
-                    imports = getattr(entry, 'imports', [])
-                    for imp in imports:
-                        fts['ImportFunctionCount'] += 1
-                        if not getattr(imp, 'name', None): continue
-                        try:
-                            func_name = imp.name.decode('ascii', 'ignore')
-                            if func_name in cls._ALL_APIS:
-                                fts[f'Api_{func_name}'] += 1
-                                fts['ApiCount'] += 1
-                            for cat in cls._API_TO_CATS.get(func_name, []):
-                                fts[f'Cat_{cat}'] += 1
-                        except Exception: 
-                            continue
-
-            if hasattr(pe, 'DIRECTORY_ENTRY_EXPORT') and hasattr(pe.DIRECTORY_ENTRY_EXPORT, 'symbols'):
-                fts['ExportCount'] = len(pe.DIRECTORY_ENTRY_EXPORT.symbols)
-            
-            if hasattr(pe, 'DIRECTORY_ENTRY_RESOURCE'):
-                for entry in pe.DIRECTORY_ENTRY_RESOURCE.entries:
-                    if getattr(entry, 'id', None) == 3 and hasattr(entry, 'directory'):
-                        fts['IconCount'] += len(getattr(entry.directory, 'entries', []))
-                        
-            if hasattr(pe, 'OPTIONAL_HEADER') and hasattr(pe.OPTIONAL_HEADER, 'DATA_DIRECTORY') and len(pe.OPTIONAL_HEADER.DATA_DIRECTORY) > 3:
-                exc_dir = pe.OPTIONAL_HEADER.DATA_DIRECTORY[3]
-                if exc_dir.Size > 0:
-                    fts['ExceptionCount'] = exc_dir.Size // 12 if fts['Machine'] in (0x8664, 0xAA64) else 0
-                
-            if hasattr(pe, 'DIRECTORY_ENTRY_DEBUG'): 
-                fts['DebugCount'] = len(pe.DIRECTORY_ENTRY_DEBUG)
-
-            for k in fts: 
-                fts[k] = cls._safe_float(fts[k])
-                
-            return fts
-
-        except Exception:
-            return None
-        finally:
-            if pe: 
-                pe.close()
-
-####################################################################################################
-
-class ModelPredictor:
-    def __init__(self, model_path, feature_path):
-        self.sess = None
-        self.input_name = None
-        self.feature_order = [] 
-        self.model_features = self._load_features(feature_path)
-        self._load_model(model_path)
-        self._build_input_map()
-
-    def _load_features(self, path):
-        if os.path.exists(path):
-            try:
-                with open(path, 'r') as f:
-                    return json.load(f)
-            except Exception:
-                pass
-        return [re.sub(r'[^A-Za-z0-9_]+', '', f) for f in FeatureExtractor.SCHEMA]
-
-    def _load_model(self, model_path):
-        if not os.path.exists(model_path):
-            raise FileNotFoundError(f"Model missing: {model_path}")
-
-        self.sess = ort.InferenceSession(model_path, providers=['CPUExecutionProvider'])
-        model_inputs = self.sess.get_inputs()
-        self.input_name = model_inputs[0].name
-        expected_dim = model_inputs[0].shape[1]
-        
-        current_dim = len(self.model_features)
-        if current_dim != expected_dim:
-            raise ValueError(f"Dimension Mismatch: Expected {expected_dim}, got {current_dim}.")
-
-    def _build_input_map(self):
-        local_map = {re.sub(r'[^A-Za-z0-9_]+', '', raw_name): raw_name for raw_name in FeatureExtractor.SCHEMA}
-        self.feature_order = [local_map.get(req_feat) for req_feat in self.model_features]
-
-    def predict(self, raw_data):
-        vec_data = [raw_data.get(key, 0.0) if key else 0.0 for key in self.feature_order]
-        vec = np.array(vec_data, dtype=np.float32).reshape(1, -1)
-        outputs = self.sess.run(None, {self.input_name: vec})
-        
-        if len(outputs) > 1:
-            result = outputs[1]
-            if isinstance(result, list) and len(result) > 0:
-                prob_dict = result[0]
-                if hasattr(prob_dict, 'get'):
-                    return float(prob_dict.get(1, prob_dict.get('1', 0.0)))
-            elif isinstance(result, np.ndarray):
-                if result.ndim == 2 and result.shape[1] > 1:
-                    return float(result[0][1])
-        return 0.0
-
-####################################################################################################
-
-def get_threat_name(prob_float):
-    prob_pct = min(int(prob_float * 100), 99)
-    
-    if prob_pct >= 80:
-        return f"General:WinPE/Malware.{prob_pct}!ml"
-    elif prob_pct >= 50:
-        return f"General:WinPE/Suspicious.{prob_pct}!ml"
-    else:
-        return "Undetected"
-
-def scan_target(target, predictor):
-    if not os.path.exists(target):
-        print(json.dumps({"result": "error", "prob": 0.0, "file": target, "details": "Path not found"}))
-        sys.stdout.flush()
-        return
-
-    try:
-        data = FeatureExtractor.extract(target)
-        if not data:
-            print(json.dumps({"result": "error", "prob": 0.0, "file": target, "details": "Extraction failed"}))
-            sys.stdout.flush()
-            return
-        
-        prob = predictor.predict(data)
-        label = get_threat_name(prob)
-        
-        print(json.dumps({"result": label, "prob": round(prob, 4), "file": target}))
-        sys.stdout.flush()
-        
-    except Exception as e:
-        print(json.dumps({"result": "error", "prob": 0.0, "file": target, "details": str(e)}))
-        sys.stdout.flush()
-
-####################################################################################################
-
-if __name__ == "__main__":
-    base_dir = os.path.dirname(sys.executable) if getattr(sys, 'frozen', False) else os.path.dirname(os.path.abspath(__file__))
-    model_path = os.path.join(base_dir, MODEL_FILE)
-    feature_path = os.path.join(base_dir, FEATURE_FILE)
-
-    try:
-        predictor = ModelPredictor(model_path, feature_path)
-    except Exception as e:
-        print(json.dumps({"result": "fatal", "details": str(e)}))
-        sys.stdout.flush()
-        sys.exit(1)
-
-    if len(sys.argv) > 1:
-        for path in sys.argv[1:]:
-            scan_target(path.strip(), predictor)
-    else:
-        for line in sys.stdin:
-            target = line.strip()
-            if not target or target.lower() in ['q', 'exit']:
-                break
-            scan_target(target, predictor)

Embed/requirements.txt

@@ -1,4 +0,0 @@
-onnxruntime
-numpy
-pefile
-signify[full]

Engine/Pattern/convert.py

@@ -1,55 +0,0 @@
-from PIL import Image
-import numpy, os
-
-####################################################################################################
-
-def preprocess_image(file_data, size, channels=1):
-    width, height = size
-    wah = int(numpy.ceil(numpy.sqrt(len(file_data) / channels)))
-    arr = numpy.frombuffer(file_data, dtype=numpy.uint8)
-    img = numpy.zeros(wah*wah*channels, dtype=numpy.uint8)
-    img[:len(file_data)] = arr
-    image = Image.fromarray(img.reshape((wah, wah)), 'L')
-    return image.resize((width, height), Image.Resampling.NEAREST)
-
-####################################################################################################
-
-def get_type(file_path):
-    suffix = {".com", ".dll", ".drv", ".exe", ".ocx", ".scr", ".sys", ".mui", ".cpl"}
-    try:
-        file_content = None
-        if not os.path.splitext(file_path)[-1].lower() in suffix:
-            return file_content
-        with open(file_path, 'rb') as f:
-            file_content = f.read()
-    except:
-        pass
-    return file_content
-
-####################################################################################################
-
-def file_to_images(input_dir, output_dir):
-    for root, dirs, files in os.walk(input_dir):
-        for file in files:
-            try:
-                file_path = os.path.join(root, file)
-                file_content = get_type(file_path)
-                if file_content:
-                    print(file_path)
-                    relative_path = os.path.relpath(root, input_dir)
-                    output_path_dir = os.path.join(output_dir, relative_path)
-
-                    if not os.path.exists(output_path_dir):
-                        os.makedirs(output_path_dir)
-                    image = preprocess_image(file_content, (224, 224))
-                    safe_name = os.path.basename(file_path).replace('/', '_').replace('\\', '_')
-                    image.save(os.path.join(output_path_dir, f"{safe_name}.png"))
-            except Exception as e:
-                print(e)
-
-####################################################################################################
-
-input_directory = input('Enter the folder path: ')
-output_directory = "./Image_Output"
-file_to_images(input_directory, output_directory)
-input('Conversion Complete')

Engine/Pattern/deduplicate.py

@@ -1,34 +0,0 @@
-import os, hashlib
-
-####################################################################################################
-
-def calc_sha256(path):
-    with open(path, "rb") as f:
-        return hashlib.sha256(f.read()).digest()
-
-def dedup_realtime(root):
-    seen = set()
-    deleted = 0
-    for dirpath, _, files in os.walk(root):
-        for name in files:
-            p = os.path.join(dirpath, name)
-            try:
-                h = calc_sha256(p)
-            except Exception:
-                continue
-            if h in seen:
-                try:
-                    os.remove(p)
-                    print(p)
-                    deleted += 1
-                except Exception:
-                    pass
-            else:
-                seen.add(h)
-    print(f"deleted {deleted}")
-
-####################################################################################################
-
-if __name__ == "__main__":
-    dedup_realtime(input("Input file path: "))
-input('Deduplicate Complete')

Engine/Pattern/train.py

@@ -1,165 +0,0 @@
-import tensorflow as tf
-import os, tf2onnx, numpy, random
-from PIL import Image
-from tensorflow.keras import *
-from collections import Counter
-
-####################################################################################################
-
-Image.MAX_IMAGE_PIXELS = None
-tf.keras.mixed_precision.set_global_policy('mixed_float16')
-
-####################################################################################################
-
-def load_dataset(data_dir, image_size=(224, 224), val_split=0.0001, batch_size=256, color_mode="grayscale"):
-    channels = 1 if color_mode == "grayscale" else 3
-    file_paths, labels, class_indices = get_file_list(data_dir)
-    
-    combined = list(zip(file_paths, labels))
-    random.shuffle(combined)
-    file_paths[:], labels[:] = zip(*combined)
-
-    num_val = int(val_split * len(file_paths))
-    train_files = file_paths[num_val:]
-    train_labels = labels[num_val:]
-    val_files = file_paths[:num_val]
-    val_labels = labels[:num_val]
-
-    train_ds = tf.data.Dataset.from_tensor_slices((train_files, train_labels))
-    train_ds = train_ds.map(lambda f, l: parse_fn(f, l, image_size, channels), num_parallel_calls=tf.data.AUTOTUNE)
-    train_ds = train_ds.batch(batch_size).prefetch(tf.data.AUTOTUNE)
-
-    val_ds = tf.data.Dataset.from_tensor_slices((val_files, val_labels))
-    val_ds = val_ds.map(lambda f, l: parse_fn(f, l, image_size, channels), num_parallel_calls=tf.data.AUTOTUNE)
-    val_ds = val_ds.batch(batch_size).prefetch(tf.data.AUTOTUNE)
-
-    train_ds.class_indices = class_indices
-    return train_ds, val_ds
-
-####################################################################################################
-
-def parse_fn(filename, label, image_size, channels):
-    img = tf.io.read_file(filename)
-    img = tf.image.decode_image(img, channels=channels, expand_animations=False)
-    img = tf.cond(tf.reduce_all(tf.equal(tf.shape(img)[:2], image_size)), lambda: tf.cast(img, tf.float32), lambda: tf.image.resize(img, image_size))
-    img = tf.cast(img, tf.float32) / 255.0
-    label = tf.cast(label, tf.float32)
-    return img, label
-
-def get_file_list(directory):
-    file_paths, labels, class_indices = [], [], {}
-    for i, cls in enumerate(sorted([d for d in os.listdir(directory) if os.path.isdir(os.path.join(directory, d))])):
-        class_indices[cls] = i
-        cls_dir = os.path.join(directory, cls)
-
-        for root, _, files in os.walk(cls_dir):
-            for file in files:
-                if file.lower().endswith(('.jpg', '.jpeg', '.png', '.bmp', '.gif')):
-                    file_paths.append(os.path.join(root, file))
-                    labels.append(i)
-    return file_paths, labels, class_indices
-
-####################################################################################################
-
-def multi_conv(x, strides):
-    convs = []
-    for k in [(1, 7), (1, 1), (3, 3), (5, 5)]:
-        c = layers.DepthwiseConv2D(kernel_size=k, strides=strides, padding='same', activation='gelu')(x)
-        convs.append(c)
-
-    x = layers.Concatenate()(convs)
-    x = layers.BatchNormalization()(x)
-    return layers.Activation('gelu')(x)
-
-def gated_conv(x, strides):
-    c = layers.DepthwiseConv2D(3, strides=strides, padding='same', activation='gelu')(x)
-    g = layers.DepthwiseConv2D(3, strides=strides, padding='same', activation='sigmoid')(x)
-    return layers.Multiply()([c, g])
-
-def coordinate_attention(x, reduction):
-    input_shape = tf.shape(x)
-    h, w = input_shape[1], input_shape[2]
-    filters = x.shape[-1]
-    mip = max(8, filters // reduction)
-
-    x_h = layers.Lambda(lambda t: tf.reduce_mean(t, axis=2, keepdims=True))(x)
-    x_w = layers.Lambda(lambda t: tf.reduce_mean(t, axis=1, keepdims=True))(x)
-    x_w_t = layers.Permute((2, 1, 3))(x_w)
-
-    x_cat = layers.Concatenate(axis=1)([x_h, x_w_t])
-    x_cat = layers.Conv2D(mip, 1, padding='valid', use_bias=False)(x_cat)
-    x_cat = layers.BatchNormalization()(x_cat)
-    x_cat = layers.Activation('gelu')(x_cat)
-
-    x_cat_h, x_cat_w = layers.Lambda(lambda t: tf.split(t[0], [t[1], t[2]], axis=1))([x_cat, h, w])
-    x_h_sigmoid = layers.Conv2D(filters, 1, padding='valid', activation='sigmoid')(x_cat_h)
-    x_cat_w = layers.Permute((2, 1, 3))(x_cat_w)
-    x_w_sigmoid = layers.Conv2D(filters, 1, padding='valid', activation='sigmoid')(x_cat_w)
-
-    return layers.Multiply()([x, x_h_sigmoid, x_w_sigmoid])
-
-def build_model(input_shape):
-    i = layers.Input(shape=input_shape)
-    x = multi_conv(i, strides=1)
-    x = gated_conv(x, strides=2)
-    x = multi_conv(x, strides=2)
-    x = multi_conv(x, strides=2)
-    x = multi_conv(x, strides=2)
-    x = multi_conv(x, strides=2)
-
-    x = coordinate_attention(x, reduction=4)
-    x = layers.GlobalMaxPooling2D()(x)
-
-    x = layers.Dense(x.shape[-1] // 2, activation='gelu', dtype='float32')(x)
-    o = layers.Dense(1, activation='sigmoid', dtype='float32')(x)
-    return models.Model(i, o)
-
-####################################################################################################
-
-def calculate_lr_cosine_sq(epoch, total_epochs=30, lr_start=5e-4, lr_end=5e-7):
-    cos_val = 0.5 * (1 + numpy.cos(epoch / total_epochs * numpy.pi))
-    return lr_end + (lr_start - lr_end) * (cos_val ** 2)
-
-def lr_scheduler(epoch):
-    return calculate_lr_cosine_sq(epoch)
-
-def binary_focal_loss(gamma=2.0, alpha=0.25):
-    def focal_loss(y_true, y_pred):
-        y_true = tf.cast(y_true, tf.float32)
-        y_pred = tf.clip_by_value(y_pred, tf.keras.backend.epsilon(), 1.0 - tf.keras.backend.epsilon())
-        p_t = tf.where(tf.equal(y_true, 1), y_pred, 1 - y_pred)
-        alpha_t = tf.where(tf.equal(y_true, 1), alpha, 1 - alpha)
-        loss = -alpha_t * tf.math.pow(1.0 - p_t, gamma) * tf.math.log(p_t)
-        return tf.reduce_mean(loss)
-    return focal_loss
-
-class CustomModelCheckpoint(callbacks.Callback):
-    def on_epoch_end(self, epoch, logs=False):
-        models.save_model(self.model, f"PYAS_Model_Epoch_{epoch + 1}.h5")
-        spec = (tf.TensorSpec((None,) + self.model.input.shape[1:], tf.float32),)
-        model_proto, _ = tf2onnx.convert.from_keras(self.model, input_signature=spec, opset=17)
-        with open(f"PYAS_Model_Epoch_{epoch + 1}.onnx", "wb") as f:
-            f.write(model_proto.SerializeToString())
-
-####################################################################################################
-
-train_ds, val_ds = load_dataset(r'.\Image_Full_Pefile')
-for imgs, _ in train_ds.take(1):
-    train_ds.image_shape = imgs.shape[1:]
-    break
-
-try:
-    model = models.load_model('PYAS_Model_Epoch_0.h5', compile=False)
-    print("Load model from disk")
-except:
-    print("Creating a new model")
-    model = build_model(train_ds.image_shape)
-
-print(f"Total parameters: {model.count_params()}")
-model.compile(optimizer='adam', loss=binary_focal_loss(gamma=2.0, alpha=0.25), 
-    metrics=[metrics.BinaryAccuracy(name='accuracy'), metrics.AUC(name='auc'),
-    metrics.Precision(name='precision'), metrics.Recall(name='recall'),
-    metrics.FalsePositives(name='fp'), metrics.TrueNegatives(name='tn')])
-
-model.fit(train_ds, epochs=30, callbacks=[CustomModelCheckpoint(), callbacks.LearningRateScheduler(lr_scheduler)], validation_data=val_ds, class_weight={0: 10.0, 1: 1.0})
-input('Training Complete')

Engine/Properties/scanner.py

@@ -0,0 +1,680 @@
+import os, sys, math, json, pefile, datetime
+import numpy as np
+import onnxruntime as ort
+import ctypes, ctypes.wintypes
+import re, zlib
+
+####################################################################################################
+
+MODEL_FILE = "Pefile_General_S1.onnx"
+FEATURE_FILE = "features.json"
+MAX_FILE_SIZE = 4 * 1024 * 1024 * 1024
+
+####################################################################################################
+
+class WINTRUST_FILE_INFO(ctypes.Structure):
+    _fields_ = [
+        ("cbStruct", ctypes.wintypes.DWORD),
+        ("pcwszFilePath", ctypes.wintypes.LPCWSTR),
+        ("hFile", ctypes.wintypes.HANDLE),
+        ("pgKnownSubject", ctypes.wintypes.LPVOID)
+    ]
+
+class WINTRUST_DATA_UNION(ctypes.Union):
+    _fields_ = [
+        ("pFile", ctypes.POINTER(WINTRUST_FILE_INFO)),
+        ("pCatalog", ctypes.wintypes.LPVOID),
+        ("pBlob", ctypes.wintypes.LPVOID),
+        ("pSgnr", ctypes.wintypes.LPVOID),
+        ("pCert", ctypes.wintypes.LPVOID)
+    ]
+
+class WINTRUST_DATA(ctypes.Structure):
+    _fields_ = [
+        ("cbStruct", ctypes.wintypes.DWORD),
+        ("pPolicyCallbackData", ctypes.wintypes.LPVOID),
+        ("pSIPClientData", ctypes.wintypes.LPVOID),
+        ("dwUIChoice", ctypes.wintypes.DWORD),
+        ("fdwRevocationChecks", ctypes.wintypes.DWORD),
+        ("dwUnionChoice", ctypes.wintypes.DWORD),
+        ("u", WINTRUST_DATA_UNION),
+        ("dwStateAction", ctypes.wintypes.DWORD),
+        ("hWVTStateData", ctypes.wintypes.HANDLE),
+        ("pwszURLReference", ctypes.wintypes.LPCWSTR),
+        ("dwProvFlags", ctypes.wintypes.DWORD),
+        ("dwUIContext", ctypes.wintypes.DWORD),
+        ("pSignatureSettings", ctypes.wintypes.LPVOID)
+    ]
+
+class GUID(ctypes.Structure):
+    _fields_ = [
+        ("Data1", ctypes.wintypes.DWORD),
+        ("Data2", ctypes.wintypes.WORD),
+        ("Data3", ctypes.wintypes.WORD),
+        ("Data4", ctypes.c_ubyte * 8)
+    ]
+
+V2_GUID = GUID(0x00AAC56B, 0xCD44, 0x11D0, (ctypes.c_ubyte * 8)(0x8C, 0xC2, 0x00, 0xC0, 0x4F, 0xC2, 0x95, 0xEE))
+
+####################################################################################################
+
+class WinTrust:
+    @staticmethod
+    def verify(file_path):
+        if os.name != 'nt':
+            return 0
+        try:
+            wintrust = ctypes.windll.wintrust
+            wintrust.WinVerifyTrust.argtypes = [ctypes.wintypes.HWND, ctypes.POINTER(GUID), ctypes.wintypes.LPVOID]
+            wintrust.WinVerifyTrust.restype = ctypes.wintypes.LONG
+
+            fi = WINTRUST_FILE_INFO()
+            fi.cbStruct = ctypes.sizeof(WINTRUST_FILE_INFO)
+            fi.pcwszFilePath = os.path.abspath(file_path)
+            fi.hFile = None
+            fi.pgKnownSubject = None
+
+            wt_union = WINTRUST_DATA_UNION()
+            wt_union.pFile = ctypes.pointer(fi)
+
+            td = WINTRUST_DATA()
+            td.cbStruct = ctypes.sizeof(WINTRUST_DATA)
+            td.pPolicyCallbackData = None
+            td.pSIPClientData = None
+            td.dwUIChoice = 2
+            td.fdwRevocationChecks = 0
+            td.dwUnionChoice = 1
+            td.u = wt_union
+            td.dwStateAction = 0
+            td.hWVTStateData = None
+            td.pwszURLReference = None
+            td.dwProvFlags = 0
+            td.dwUIContext = 0
+            td.pSignatureSettings = None
+
+            return 1 if wintrust.WinVerifyTrust(None, ctypes.byref(V2_GUID), ctypes.byref(td)) == 0 else 0
+        except Exception:
+            return 0
+
+####################################################################################################
+
+class FeatureExtractor:
+    _STRING_PATTERN = re.compile(b'[\x20-\x7E]{5,}')
+
+    @staticmethod
+    def _safe_float(val):
+        try:
+            f = float(val)
+            return f if not (math.isinf(f) or math.isnan(f)) else 0.0
+        except Exception: 
+            return 0.0
+
+    @staticmethod
+    def _calc_entropy(data):
+        if not data: return 0.0
+        import numpy as np
+        arr = np.frombuffer(data, dtype=np.uint8)
+        counts = np.bincount(arr, minlength=256)
+        probs = counts[counts > 0] / len(arr)
+        return float(-np.sum(probs * np.log2(probs)))
+
+    @classmethod
+    def _extract_strings(cls, file_bytes):
+        res = {"StringCount": 0.0, "StringMeanLength": 0.0, "StringEntropy": 0.0}
+        for i in range(95):
+            res[f'StringHist_{i:02d}'] = 0.0
+
+        count = 0
+        total_len = 0
+        char_counts = [0] * 95
+        combined_data = bytearray()
+
+        for match in cls._STRING_PATTERN.finditer(file_bytes):
+            m = match.group()
+            count += 1
+            length = len(m)
+            total_len += length
+            combined_data.extend(m)
+            for b in m:
+                char_counts[b - 0x20] += 1
+
+        if count == 0:
+            return res
+
+        res["StringCount"] = float(count)
+        res["StringMeanLength"] = float(total_len) / count
+        res["StringEntropy"] = cls._calc_entropy(combined_data)
+
+        for i in range(95):
+            res[f'StringHist_{i:02d}'] = float(char_counts[i]) / total_len
+
+        return res
+
+    @classmethod
+    def _extract_histograms(cls, file_bytes):
+        import numpy as np
+        arr = np.frombuffer(file_bytes, dtype=np.uint8)
+        sz = len(arr)
+        res = {}
+
+        if sz == 0:
+            for i in range(256):
+                res[f'ByteHist_{i:02X}'] = 0.0
+                res[f'ByteEnt_{i:02X}'] = 0.0
+            return res
+
+        byte_counts = np.bincount(arr, minlength=256)
+        byte_hist = byte_counts / sz
+        for i, v in enumerate(byte_hist):
+            res[f'ByteHist_{i:02X}'] = float(v)
+
+        ent_hist = np.zeros(256, dtype=np.float64)
+        window = 2048
+        step = 1024
+        num_windows = (sz - window) // step + 1 if sz >= window else 1
+
+        for i in range(num_windows):
+            w = arr if sz < window else arr[i*step : i*step+window]
+            w_counts = np.bincount(w, minlength=256)
+            
+            p = w_counts[w_counts > 0] / len(w)
+            entropy = -np.sum(p * np.log2(p))
+            
+            ent_bin = int(entropy * 2.0)
+            if ent_bin > 15:
+                ent_bin = 15
+                
+            byte_bins = w_counts.reshape(16, 16).sum(axis=1)
+            
+            idx_start = ent_bin * 16
+            ent_hist[idx_start : idx_start+16] += byte_bins
+
+        ent_sum = np.sum(ent_hist)
+        if ent_sum > 0:
+            ent_hist /= ent_sum
+
+        for i, v in enumerate(ent_hist):
+            res[f'ByteEnt_{i:02X}'] = float(v)
+
+        return res
+
+    @classmethod
+    def _extract_overlay_features(cls, pe, fsize):
+        overlay_offset = pe.get_overlay_data_start_offset()
+        if not overlay_offset or overlay_offset >= fsize:
+            return {"HasOverlay": 0.0, "OverlaySize": 0.0, "OverlayRatio": 0.0, "OverlayEntropy": 0.0}
+        
+        overlay_data = pe.get_overlay()
+        if not overlay_data:
+            return {"HasOverlay": 0.0, "OverlaySize": 0.0, "OverlayRatio": 0.0, "OverlayEntropy": 0.0}
+
+        sz = len(overlay_data)
+        return {
+            "HasOverlay": 1.0,
+            "OverlaySize": float(sz),
+            "OverlayRatio": float(sz) / float(fsize),
+            "OverlayEntropy": cls._calc_entropy(overlay_data)
+        }
+
+    @classmethod
+    def _extract_rich_header(cls, pe):
+        if not hasattr(pe, 'RICH_HEADER') or not pe.RICH_HEADER:
+            return {"HasRichHeader": 0.0, "RichHeaderCount": 0.0}
+        return {
+            "HasRichHeader": 1.0,
+            "RichHeaderCount": float(len(pe.RICH_HEADER.values) // 2) if hasattr(pe.RICH_HEADER, 'values') else 0.0
+        }
+
+    @classmethod
+    def _extract_ep_anomalies(cls, pe):
+        if not hasattr(pe, 'OPTIONAL_HEADER') or not hasattr(pe, 'sections') or not pe.sections:
+            return {"EntryPointSectionIndex": -1.0, "EntryPointInExecutable": 0.0, "EntryPointInLastSection": 0.0}
+
+        ep = pe.OPTIONAL_HEADER.AddressOfEntryPoint
+        ep_section_idx = -1
+        ep_in_exec = 0.0
+        
+        for idx, sec in enumerate(pe.sections):
+            if sec.VirtualAddress <= ep < (sec.VirtualAddress + sec.Misc_VirtualSize):
+                ep_section_idx = idx
+                if sec.Characteristics & 0x20000000:
+                    ep_in_exec = 1.0
+                break
+                
+        return {
+            "EntryPointSectionIndex": float(ep_section_idx),
+            "EntryPointInExecutable": ep_in_exec,
+            "EntryPointInLastSection": 1.0 if ep_section_idx == len(pe.sections) - 1 else 0.0
+        }
+
+    @classmethod
+    def _extract_advanced_resources(cls, pe):
+        res_data = {
+            "ResourceMaxEntropy": 0.0,
+            "ResourceMinEntropy": 0.0,
+            "ResourceMeanEntropy": 0.0,
+            "ResourceLangCount": 0.0,
+            "ResourceRCDataCount": 0.0
+        }
+        
+        if not hasattr(pe, 'DIRECTORY_ENTRY_RESOURCE'):
+            return res_data
+            
+        entropies = []
+        langs = set()
+        rcdata_count = 0
+        
+        for entry_type in pe.DIRECTORY_ENTRY_RESOURCE.entries:
+            if hasattr(entry_type, 'id') and entry_type.id == 10: 
+                rcdata_count += len(getattr(entry_type.directory, 'entries', []))
+                
+            if not hasattr(entry_type, 'directory'):
+                continue
+                
+            for entry_id in entry_type.directory.entries:
+                if not hasattr(entry_id, 'directory'):
+                    continue
+                    
+                for entry_lang in entry_id.directory.entries:
+                    if hasattr(entry_lang, 'id'):
+                        langs.add(entry_lang.id)
+                    if hasattr(entry_lang, 'data'):
+                        try:
+                            data = pe.get_data(entry_lang.data.struct.OffsetToData, entry_lang.data.struct.Size)
+                            entropies.append(cls._calc_entropy(data))
+                        except Exception:
+                            continue
+                            
+        res_data["ResourceLangCount"] = float(len(langs))
+        res_data["ResourceRCDataCount"] = float(rcdata_count)
+        
+        if entropies:
+            res_data["ResourceMaxEntropy"] = max(entropies)
+            res_data["ResourceMinEntropy"] = min(entropies)
+            res_data["ResourceMeanEntropy"] = sum(entropies) / len(entropies)
+            
+        return res_data
+
+    @classmethod
+    def _extract_load_config(cls, pe):
+        cfg = {"HasLoadConfig": 0.0, "HasCFG": 0.0, "HasSEHTable": 0.0}
+        if hasattr(pe, 'DIRECTORY_ENTRY_LOAD_CONFIG'):
+            cfg["HasLoadConfig"] = 1.0
+            struct = pe.DIRECTORY_ENTRY_LOAD_CONFIG.struct
+            if getattr(struct, 'GuardCFFunctionTable', 0) != 0:
+                cfg["HasCFG"] = 1.0
+            if getattr(struct, 'SEHandlerTable', 0) != 0:
+                cfg["HasSEHTable"] = 1.0
+        return cfg
+
+    @classmethod
+    def _extract_security_directory(cls, pe, file_bytes, fsize):
+        res = {"HasSignature": 0.0, "SignatureCount": 0.0}
+        if not hasattr(pe, 'OPTIONAL_HEADER') or not hasattr(pe.OPTIONAL_HEADER, 'DATA_DIRECTORY'):
+            return res
+
+        sec_idx = 4
+        directories = pe.OPTIONAL_HEADER.DATA_DIRECTORY
+        if len(directories) <= sec_idx:
+            return res
+
+        sec_dir = directories[sec_idx]
+        if sec_dir.Size == 0 or sec_dir.VirtualAddress == 0:
+            return res
+
+        res["HasSignature"] = 1.0
+        offset = sec_dir.VirtualAddress
+        size = sec_dir.Size
+
+        if offset + size > fsize or offset < 0 or size < 0:
+            return res
+
+        count = 0
+        curr = offset
+        end = offset + size
+
+        while curr + 8 <= end:
+            dw_length = int.from_bytes(file_bytes[curr:curr+4], 'little')
+            if dw_length < 8:
+                break
+            count += 1
+            curr += (dw_length + 7) & ~7
+
+        res["SignatureCount"] = float(count)
+        return res
+
+    @classmethod
+    def extract(cls, file_path):
+        pe = None
+        try:
+            fsize = os.path.getsize(file_path)
+            if fsize == 0 or fsize > MAX_FILE_SIZE: 
+                return None
+
+            with open(file_path, "rb") as f:
+                file_bytes = f.read()
+
+            base, dlls, apis = {}, set(), set()
+            pe = pefile.PE(data=file_bytes, fast_load=True)
+
+            try:
+                pe.parse_rich_header()
+                pe.parse_data_directories(directories=[
+                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_IMPORT'], 
+                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_EXPORT'], 
+                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_RESOURCE'], 
+                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_DEBUG'], 
+                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_TLS'],
+                    pefile.DIRECTORY_ENTRY['IMAGE_DIRECTORY_ENTRY_LOAD_CONFIG']
+                ])
+            except Exception: 
+                pass
+            
+            base['TrustSigned'] = float(WinTrust.verify(file_path))
+            base['FileEntropy'] = cls._calc_entropy(file_bytes)
+            base['FileSize'] = float(fsize)
+            
+            fh = pe.FILE_HEADER
+            base['Machine'] = getattr(fh, 'Machine', 0)
+            base['NumberOfSections'] = getattr(fh, 'NumberOfSections', 0)
+            base['TimeDateStamp'] = getattr(fh, 'TimeDateStamp', 0)
+            base['PointerToSymbolTable'] = getattr(fh, 'PointerToSymbolTable', 0)
+            base['NumberOfSymbols'] = getattr(fh, 'NumberOfSymbols', 0)
+            base['SizeOfOptionalHeader'] = getattr(fh, 'SizeOfOptionalHeader', 0)
+            base['Characteristics'] = getattr(fh, 'Characteristics', 0)
+
+            curr_ts = datetime.datetime.utcnow().timestamp()
+            base['HasInvalidTimestamp'] = 1.0 if (base['TimeDateStamp'] < 631152000 or base['TimeDateStamp'] > curr_ts + 2592000) else 0.0
+            base['FileTimeException'] = 1.0 if base['TimeDateStamp'] == 0 else 0.0
+            base['Is64Bit'] = 1.0 if base['Machine'] in (0x8664, 0xAA64, 0x0200) else 0.0
+            base['IsExe'] = 1.0 if pe.is_exe() else 0.0
+            base['IsDll'] = 1.0 if pe.is_dll() else 0.0
+
+            base['ExceptionCount'] = 0.0
+
+            if hasattr(pe, 'OPTIONAL_HEADER'):
+                op = pe.OPTIONAL_HEADER
+                fields = ['Magic', 'MajorLinkerVersion', 'MinorLinkerVersion', 'SizeOfCode', 'SizeOfInitializedData', 'SizeOfUninitializedData', 'AddressOfEntryPoint', 'BaseOfCode', 'ImageBase', 'SectionAlignment', 'FileAlignment', 'MajorOperatingSystemVersion', 'MinorOperatingSystemVersion', 'MajorImageVersion', 'MinorImageVersion', 'MajorSubsystemVersion', 'MinorSubsystemVersion', 'SizeOfImage', 'SizeOfHeaders', 'CheckSum', 'Subsystem', 'DllCharacteristics', 'SizeOfStackReserve', 'SizeOfStackCommit', 'SizeOfHeapReserve', 'SizeOfHeapCommit', 'LoaderFlags', 'NumberOfRvaAndSizes']
+                for f in fields: base[f] = getattr(op, f, 0)
+                base['IsDriver'] = 1.0 if base.get('Subsystem') == 1 else 0.0
+
+                if hasattr(op, 'DATA_DIRECTORY'):
+                    for i, directory in enumerate(op.DATA_DIRECTORY):
+                        base[f'DataDirectory_{i}_Size'] = directory.Size
+                        base[f'DataDirectory_{i}_VA'] = directory.VirtualAddress
+                    
+                    exc_idx = pefile.DIRECTORY_ENTRY.get('IMAGE_DIRECTORY_ENTRY_EXCEPTION', 3)
+                    if len(op.DATA_DIRECTORY) > exc_idx and op.DATA_DIRECTORY[exc_idx].Size > 0:
+                        base['ExceptionCount'] = op.DATA_DIRECTORY[exc_idx].Size // 12 if base['Machine'] in (0x8664, 0xAA64) else 0.0
+
+            char_flags = [0x00000020, 0x00000040, 0x00000080, 0x02000000, 0x20000000, 0x40000000, 0x80000000]
+            for flag in char_flags:
+                base[f'Char_{flag:08X}_Count'] = 0.0
+                base[f'Char_{flag:08X}_MeanEntropy'] = 0.0
+
+            for i in range(50):
+                base[f'SectionHash_{i:02d}'] = 0.0
+
+            if hasattr(pe, 'sections'):
+                base['SectionCount'] = len(pe.sections)
+                entropies, raw_sizes, v_sizes = [], [], []
+                exec_sec, write_sec, read_sec, sec_exc = 0, 0, 0, 0
+                
+                for section in pe.sections:
+                    sec_name = section.Name.rstrip(b'\x00')
+                    hash_val = zlib.crc32(sec_name) % 50
+                    base[f'SectionHash_{hash_val:02d}'] += 1.0
+
+                    try:
+                        s_data = section.get_data()
+                        s_entropy = cls._calc_entropy(s_data)
+                    except Exception: 
+                        s_entropy = 0.0
+
+                    entropies.append(s_entropy)
+                    raw_sizes.append(section.SizeOfRawData)
+                    v_sizes.append(section.Misc_VirtualSize)
+
+                    if section.Characteristics & 0x20000000: exec_sec += 1
+                    if section.Characteristics & 0x80000000: write_sec += 1
+                    if section.Characteristics & 0x40000000: read_sec += 1
+                    if section.SizeOfRawData + section.PointerToRawData > fsize: sec_exc = 1
+
+                    for flag in char_flags:
+                        if section.Characteristics & flag:
+                            base[f'Char_{flag:08X}_Count'] += 1.0
+                            base[f'Char_{flag:08X}_MeanEntropy'] += s_entropy
+
+                base['SectionMaxEntropy'] = max(entropies) if entropies else 0.0
+                base['SectionMinEntropy'] = min(entropies) if entropies else 0.0
+                base['SectionMeanEntropy'] = sum(entropies) / len(entropies) if entropies else 0.0
+                base['SectionMaxRawSize'] = max(raw_sizes) if raw_sizes else 0.0
+                base['SectionMinRawSize'] = min(raw_sizes) if raw_sizes else 0.0
+                base['SectionMeanRawSize'] = sum(raw_sizes) / len(raw_sizes) if raw_sizes else 0.0
+                base['SectionMaxVSize'] = max(v_sizes) if v_sizes else 0.0
+                base['SectionMinVSize'] = min(v_sizes) if v_sizes else 0.0
+                base['SectionMeanVSize'] = sum(v_sizes) / len(v_sizes) if v_sizes else 0.0
+                base['ExecutableSections'] = exec_sec
+                base['WritableSections'] = write_sec
+                base['ReadableSections'] = read_sec
+                base['SectionException'] = float(sec_exc)
+
+                for flag in char_flags:
+                    if base[f'Char_{flag:08X}_Count'] > 0:
+                        base[f'Char_{flag:08X}_MeanEntropy'] = base[f'Char_{flag:08X}_MeanEntropy'] / base[f'Char_{flag:08X}_Count']
+
+            string_keys = ['FileDescription', 'FileVersion', 'ProductName', 'ProductVersion', 'CompanyName', 'LegalCopyright', 'Comments', 'InternalName', 'LegalTrademarks', 'SpecialBuild', 'PrivateBuild']
+            for key in string_keys: 
+                base[f'{key}Length'] = 0.0
+                
+            if hasattr(pe, 'FileInfo'):
+                for fileinfo_list in pe.FileInfo:
+                    for fileinfo in fileinfo_list:
+                        if getattr(fileinfo, 'name', '') in ('StringFileInfo', b'StringFileInfo'):
+                            for st in getattr(fileinfo, 'StringTable', []):
+                                for key, val in st.entries.items():
+                                    try:
+                                        k = key.decode('utf-8', 'ignore') if isinstance(key, bytes) else str(key)
+                                        if k in string_keys:
+                                            v = val.decode('utf-8', 'ignore') if isinstance(val, bytes) else str(val)
+                                            base[f'{k}Length'] = float(len(v))
+                                    except Exception: 
+                                        continue
+
+            if hasattr(pe, 'DIRECTORY_ENTRY_TLS') and hasattr(pe.DIRECTORY_ENTRY_TLS, 'struct'):
+                base['HasTlsCallbacks'] = 1.0 if getattr(pe.DIRECTORY_ENTRY_TLS.struct, 'AddressOfCallBacks', 0) != 0 else 0.0
+            
+            if hasattr(pe, 'VS_FIXEDFILEINFO') and len(pe.VS_FIXEDFILEINFO) > 0:
+                flags = getattr(pe.VS_FIXEDFILEINFO[0], 'FileFlags', 0)
+                base['IsDebug'] = 1.0 if flags & 0x1 else 0.0
+                base['IsPreRelease'] = 1.0 if flags & 0x2 else 0.0
+                base['IsPatched'] = 1.0 if flags & 0x4 else 0.0
+                base['IsPrivateBuild'] = 1.0 if flags & 0x8 else 0.0
+                base['IsSpecialBuild'] = 1.0 if flags & 0x20 else 0.0
+
+            if hasattr(pe, 'DIRECTORY_ENTRY_IMPORT'):
+                base['ImportCount'] = len(pe.DIRECTORY_ENTRY_IMPORT)
+                func_count = 0
+                for entry in pe.DIRECTORY_ENTRY_IMPORT:
+                    if getattr(entry, 'dll', None):
+                        try: dlls.add(entry.dll.decode('ascii', 'ignore').lower())
+                        except Exception: pass
+                    for imp in getattr(entry, 'imports', []):
+                        func_count += 1
+                        if getattr(imp, 'name', None):
+                            try: apis.add(imp.name.decode('ascii', 'ignore'))
+                            except Exception: pass
+                base['ImportFunctionCount'] = func_count
+
+            base['ExportCount'] = len(pe.DIRECTORY_ENTRY_EXPORT.symbols) if (hasattr(pe, 'DIRECTORY_ENTRY_EXPORT') and hasattr(pe.DIRECTORY_ENTRY_EXPORT, 'symbols')) else 0.0
+
+            if hasattr(pe, 'DIRECTORY_ENTRY_RESOURCE'):
+                icon_count = 0
+                for entry in pe.DIRECTORY_ENTRY_RESOURCE.entries:
+                    if getattr(entry, 'id', None) == 3 and hasattr(entry, 'directory'):
+                        icon_count += len(getattr(entry.directory, 'entries', []))
+                base['IconCount'] = icon_count
+            else: 
+                base['IconCount'] = 0.0
+
+            base['DebugCount'] = len(pe.DIRECTORY_ENTRY_DEBUG) if hasattr(pe, 'DIRECTORY_ENTRY_DEBUG') else 0.0
+
+            base.update(cls._extract_strings(file_bytes))
+            base.update(cls._extract_histograms(file_bytes))
+            base.update(cls._extract_overlay_features(pe, fsize))
+            base.update(cls._extract_rich_header(pe))
+            base.update(cls._extract_ep_anomalies(pe))
+            base.update(cls._extract_advanced_resources(pe))
+            base.update(cls._extract_load_config(pe))
+            base.update(cls._extract_security_directory(pe, file_bytes, fsize))
+
+            for k in base: base[k] = cls._safe_float(base[k])
+            return {"Base": base, "DLLs": list(dlls), "APIs": list(apis)}
+
+        except Exception: return None
+        finally:
+            if pe: pe.close()
+
+####################################################################################################
+
+class ModelPredictor:
+    def __init__(self, model_path, feature_path):
+        self.model_features = self._load_features(feature_path)
+        self.sess = ort.InferenceSession(model_path, providers=['CPUExecutionProvider'])
+        self.input_name = self.sess.get_inputs()[0].name
+        
+        expected_dim = self.sess.get_inputs()[0].shape[1]
+        current_dim = len(self.model_features)
+        if current_dim != expected_dim:
+            raise ValueError(f"Dimension mismatch! Model expects {expected_dim} features, but feature file lists {current_dim}.")
+
+        self.feat_map = {feat: i for i, feat in enumerate(self.model_features)}
+
+    def _load_features(self, path):
+        if not os.path.exists(path):
+            raise FileNotFoundError(f"Feature file not found: {path}")
+        with open(path, 'r') as f:
+            return json.load(f)
+
+    def predict(self, raw_data):
+        vec = np.zeros((1, len(self.model_features)), dtype=np.float32)
+        base = raw_data.get('Base', {})
+        dlls = raw_data.get('DLLs', [])
+        apis = raw_data.get('APIs', [])
+
+        for k, v in base.items():
+            if k in self.feat_map:
+                vec[0, self.feat_map[k]] = v
+
+        for d in dlls:
+            h = zlib.crc32(d.encode('utf-8', 'ignore')) % 256
+            feat_name = f"DllHash_{h:03d}"
+            if feat_name in self.feat_map:
+                vec[0, self.feat_map[feat_name]] += 1.0
+
+        for a in apis:
+            h = zlib.crc32(a.encode('utf-8', 'ignore')) % 1024
+            feat_name = f"ApiHash_{h:04d}"
+            if feat_name in self.feat_map:
+                vec[0, self.feat_map[feat_name]] += 1.0
+
+        outputs = self.sess.run(None, {self.input_name: vec})
+        
+        if len(outputs) > 1:
+            result = outputs[1]
+            if isinstance(result, list) and len(result) > 0:
+                prob_dict = result[0]
+                if hasattr(prob_dict, 'get'):
+                    return float(prob_dict.get(1, prob_dict.get('1', 0.0)))
+            elif isinstance(result, np.ndarray):
+                if result.ndim == 2 and result.shape[1] > 1:
+                    return float(result[0][1])
+        return 0.0
+
+####################################################################################################
+
+def scan_target(target, predictor):
+    files = []
+    if os.path.isfile(target):
+        files.append(target)
+    elif os.path.isdir(target):
+        for r, _, fs in os.walk(target):
+            for f in fs:
+                files.append(os.path.join(r, f))
+    
+    if not files:
+        print("[-] No valid PE files found.")
+        return
+
+    print(f"\n[*] Scanning {len(files)} files...\n")
+    print(f"{'RESULT':<10} | {'PROB':<8} | {'FILE'}")
+    print("-" * 80)
+
+    safe_count = 0
+    mal_count = 0
+    
+    for fpath in files:
+        try:
+            data = FeatureExtractor.extract(fpath)
+            if not data:
+                print(f"{'ERROR':<10} | {'----':<8} | {fpath}")
+                continue
+            
+            prob = predictor.predict(data)
+            is_malware = prob > 0.5
+            
+            label = "MALWARE" if is_malware else "SAFE"
+            if is_malware:
+                mal_count += 1
+            else:
+                safe_count += 1
+
+            print(f"{label:<10} | {prob:.4f}   | {fpath}")
+            
+        except Exception as e:
+            print(f"{'FAIL':<10} | {'----':<8} | {fpath} ({str(e)})")
+
+    print("-" * 80)
+    print(f"[*] Summary: Safe={safe_count}, Malware={mal_count}, Total={len(files)}")
+
+####################################################################################################
+
+if __name__ == "__main__":
+    print("\n-------------------------- PE Malware Predictor v4.0 --------------------------\n")
+    print(f"[*] © 2020-2026 87owo (PYAS Security)")
+    print(f"[*] Loading model features and weights...")
+
+    base_dir = os.path.dirname(sys.executable) if getattr(sys, 'frozen', False) else os.path.dirname(os.path.abspath(__file__))
+    model_path = os.path.join(base_dir, MODEL_FILE)
+    feature_path = os.path.join(base_dir, FEATURE_FILE)
+
+    try:
+        predictor = ModelPredictor(model_path, feature_path)
+    except Exception as e:
+        print(f"[-] Critical Error: {e}")
+        sys.exit(1)
+
+    if len(sys.argv) > 1:
+        for path in sys.argv[1:]:
+            target = path.strip('"').strip("'")
+            if os.path.exists(target):
+                print()
+                print("-" * 80)
+                scan_target(target, predictor)
+            else:
+                print(f"[-] Path does not exist: {target}")
+    else:
+        while True:
+            try:
+                print()
+                print("-" * 80)
+                path = input("\n[?] Enter File or Folder Path (or 'q' to exit): ").strip().strip('"').strip("'")
+                if path.lower() in ['q', 'exit']: break
+                if not os.path.exists(path):
+                    print("[-] Path does not exist.")
+                    continue
+                scan_target(path, predictor)
+            except KeyboardInterrupt:
+                break
+            except Exception as e:
+                print(f"[-] Error: {e}")

Engine/Properties/train_server.py

@@ -1,109 +1,138 @@
-import os, sys, time, sqlite3, re, json
-import pandas as pd
+import os, sys, time, json, onnxmltools, zlib
 import numpy as np
+import pandas as pd
 import lightgbm as lgb
-import onnxmltools
+import scipy.sparse as sp
 
+from collections import defaultdict
 from onnxmltools.convert.common.data_types import FloatTensorType
 from sklearn.model_selection import train_test_split
-from sklearn.metrics import classification_report, accuracy_score, roc_auc_score
+from sklearn.metrics import accuracy_score, roc_auc_score
+
+try:
+    import orjson
+    JSON_LOADS = orjson.loads
+except ImportError:
+    JSON_LOADS = json.loads
 
 ####################################################################################################
 
-DB_PATH = "pe_features.db"
+JSONL_PATH = "pe_features.jsonl"
 MODEL_FILE = "model.txt"
-ONNX_FILE = "model.onnx"
+ONNX_FILE = "Pefile_General_S1.onnx"
 FEATURE_FILE = "features.json"
 TEST_SIZE = 0.0001
 RANDOM_SEED = 42
 
+DLL_HASH_DIM = 256
+API_HASH_DIM = 1024
+
+EXCLUDE_FEATURES = {
+    'label', 'filehash',
+}
+
 LGBM_PARAMS = {
     'objective': 'binary',
     'metric': ['binary_logloss', 'auc'],
     'boosting_type': 'gbdt',
-    'num_leaves': 512,
-    'learning_rate': 0.05,
+    'num_leaves': 256,
     'feature_fraction': 0.8,
-    'bagging_fraction': 0.8,
+    'bagging_fraction': 1.0,
     'bagging_freq': 5,
     'verbose': -1,
     'seed': RANDOM_SEED,
     'n_jobs': -1,
     'max_depth': -1,
-    'min_data_in_leaf': 10,
-    'lambda_l1': 0.1,
-    'lambda_l2': 0.1,
+    'min_data_in_leaf': 50,
 }
 
 ####################################################################################################
 
-def clean_col_name(name):
-    return re.sub(r'[^A-Za-z0-9_]+', '', name)
+def analyze_schema(jsonl_path):
+    print("[*] Stage 1: Scanning global schema...")
+    base_keys = set()
+    num_lines = 0
 
-def get_raw_schema(db_path):
-    if not os.path.exists(db_path):
-        return None
-    conn = sqlite3.connect(db_path)
-    try:
-        cursor = conn.cursor()
-        cursor.execute("PRAGMA table_info(PeData)")
-        columns = [row[1] for row in cursor.fetchall()]
-        exclude = {'label', 'id', 'filename', 'filelength', 'rowid', 'probability', 'predictedlabel', 'score', 'filehash', 'timedatestamp'}
-        return [c for c in columns if c.lower().strip() not in exclude]
-    except Exception as e:
-        print(f"[-] Schema extraction error: {e}")
-        return None
-    finally:
-        conn.close()
+    with open(jsonl_path, 'rb') as f:
+        for line in f:
+            try:
+                data = JSON_LOADS(line)
+                base_data = data.get('Base')
+                if base_data:
+                    base_keys.update(base_data.keys())
+                num_lines += 1
+            except Exception:
+                continue
 
-####################################################################################################
-
-def load_data(db_path, raw_cols):
-    print(f"[*] Connecting to database: {db_path}")
-    conn = sqlite3.connect(db_path)
-    req_cols = list(set(raw_cols + ['Label']))
-    sql = f"SELECT {', '.join(req_cols)} FROM PeData"
+    base_schema = sorted([k for k in base_keys if k.lower().strip() not in EXCLUDE_FEATURES])
+    dll_schema = [f"DllHash_{i:03d}" for i in range(DLL_HASH_DIM)]
+    api_schema = [f"ApiHash_{i:04d}" for i in range(API_HASH_DIM)]
     
-    try:
-        chunks = []
-        for chunk in pd.read_sql_query(sql, conn, chunksize=20000):
-            label_col = next((c for c in chunk.columns if c.lower().strip() == 'label'), None)
-            if not label_col:
-                print("[-] Critical Error: Label column not found.")
-                return None, None, None
-
-            cols_to_cast = [c for c in chunk.columns if c != label_col]
-            chunk[cols_to_cast] = chunk[cols_to_cast].astype(np.float32)
-            chunk[label_col] = chunk[label_col].astype(np.int8)
-            chunks.append(chunk)
-
-        if not chunks:
-            return None, None, None
-
-        df = pd.concat(chunks, ignore_index=True)
-
-        label_col = next((c for c in df.columns if c.lower().strip() == 'label'), None)
-        y = df[label_col].astype(int)
-        X = df.drop(columns=[label_col], errors='ignore')
-        
-        valid_features = [c for c in raw_cols if c in X.columns]
-        X = X[valid_features].copy()
-        
-        rename_map = {old: clean_col_name(old) for old in X.columns}
-        X = X.rename(columns=rename_map)
-        
-        if X.columns.duplicated().any():
-            print("[-] Warning: Duplicate column names detected after cleaning. Deduplicating...")
-            X = X.loc[:, ~X.columns.duplicated()]
-
-        final_features = X.columns.tolist()
-        return X, y, final_features
-    finally:
-        conn.close()
+    return base_schema, dll_schema, api_schema, num_lines
 
 ####################################################################################################
 
-def train_process(X, y):
+def load_data_efficiently(jsonl_path, base_schema, dll_schema, api_schema, num_lines):
+    print(f"[*] Stage 2: Building sparse feature matrix dynamically (Expected samples: {num_lines})...")
+    final_features = base_schema + dll_schema + api_schema
+    num_features = len(final_features)
+
+    base_idx = {feat: i for i, feat in enumerate(base_schema)}
+    offset_dll = len(base_schema)
+    offset_api = offset_dll + DLL_HASH_DIM
+
+    rows, cols, vals = [], [], []
+    y = np.zeros(num_lines, dtype=np.int8)
+
+    with open(jsonl_path, 'rb') as f:
+        row_idx = 0
+        for line in f:
+            try:
+                data = JSON_LOADS(line)
+                y[row_idx] = data.get('Label', 0)
+
+                base_data = data.get('Base')
+                if base_data:
+                    for k, v in base_data.items():
+                        idx = base_idx.get(k)
+                        if idx is not None:
+                            val = float(v)
+                            if val != 0.0:
+                                rows.append(row_idx)
+                                cols.append(idx)
+                                vals.append(val)
+
+                dll_data = data.get('DLLs')
+                if dll_data:
+                    for d in dll_data:
+                        idx = zlib.crc32(d.encode('utf-8', 'ignore')) % DLL_HASH_DIM
+                        rows.append(row_idx)
+                        cols.append(offset_dll + idx)
+                        vals.append(1.0)
+
+                api_data = data.get('APIs')
+                if api_data:
+                    for a in api_data:
+                        idx = zlib.crc32(a.encode('utf-8', 'ignore')) % API_HASH_DIM
+                        rows.append(row_idx)
+                        cols.append(offset_api + idx)
+                        vals.append(1.0)
+
+                row_idx += 1
+            except Exception:
+                continue
+
+    y = y[:row_idx]
+    X = sp.csr_matrix((vals, (rows, cols)), shape=(row_idx, num_features), dtype=np.float32)
+    
+    return X, pd.Series(y), final_features
+
+####################################################################################################
+
+def _calculate_dynamic_lr(current_iter: int) -> float:
+    return max(0.01, 0.1 - (current_iter // 80) * 0.01)
+
+def train_process(X, y, feature_names):
     print(f"[*] Dataset shape: {X.shape}")
     
     X_train, X_test, y_train, y_test = train_test_split(
@@ -114,14 +143,14 @@ def train_process(X, y):
     n_neg = (y_train == 0).sum()
     
     base_weight = n_neg / n_pos if n_pos > 0 else 1.0
-    weight_ratio_target = 0.1
+    weight_ratio_target = 0.005
     final_pos_weight = base_weight * weight_ratio_target
     
-    print(f"[*] Balance Report: Safe={n_neg}, Malware={n_pos}")
-    print(f"[*] Weight Config: Base Balanced={base_weight:.4f}, Final Adjusted={final_pos_weight:.4f}")
+    print(f"[*] Sample distribution: Safe={n_neg}, Malware={n_pos}")
+    print(f"[*] Weight correction: Base={base_weight:.4f}, Final={final_pos_weight:.4f}")
     
-    train_data = lgb.Dataset(X_train, label=y_train)
-    valid_data = lgb.Dataset(X_test, label=y_test, reference=train_data)
+    train_data = lgb.Dataset(X_train, label=y_train, feature_name=feature_names)
+    valid_data = lgb.Dataset(X_test, label=y_test, reference=train_data, feature_name=feature_names)
     
     params = LGBM_PARAMS.copy()
     params['scale_pos_weight'] = final_pos_weight
@@ -133,14 +162,15 @@ def train_process(X, y):
         params,
         train_data,
         valid_sets=[valid_data],
-        num_boost_round=1000,
+        num_boost_round=500,
         callbacks=[
-            lgb.log_evaluation(period=100)
+            lgb.log_evaluation(period=50),
+            lgb.reset_parameter(learning_rate=_calculate_dynamic_lr)
         ]
     )
     
     elapsed = time.time() - start_time
-    print(f"\n[+] Training finished in {elapsed:.2f}s")
+    print(f"\n[+] Training complete, time elapsed {elapsed:.2f} seconds")
     
     return model, X_test, y_test
 
@@ -156,12 +186,10 @@ def export_onnx_model(model, feature_names):
         with open(FEATURE_FILE, 'w') as f:
             json.dump(feature_names, f)
             
-        print(f"[+] ONNX export success. Features synced to {FEATURE_FILE}")
+        print(f"[+] ONNX export successful. Feature order saved to {FEATURE_FILE}")
     except Exception as e:
         print(f"[-] ONNX export failed: {e}")
 
-####################################################################################################
-
 def evaluate_and_save(model, X_test, y_test):
     print("\n------------------- Evaluation Report -------------------\n")
     y_prob = model.predict(X_test, num_iteration=model.best_iteration)
@@ -170,12 +198,25 @@ def evaluate_and_save(model, X_test, y_test):
     acc = accuracy_score(y_test, y_pred)
     auc = roc_auc_score(y_test, y_prob)
     
-    print(f"Accuracy : {acc:.4f}")
-    print(f"ROC AUC  : {auc:.4f}")
-    print("\n" + classification_report(y_test, y_pred, zero_division=0))
+    tp = np.sum((y_test == 1) & (y_pred == 1))
+    fn = np.sum((y_test == 1) & (y_pred == 0))
+    tn = np.sum((y_test == 0) & (y_pred == 0))
+    fp = np.sum((y_test == 0) & (y_pred == 1))
+    
+    total_malware = tp + fn
+    total_safe = tn + fp
+    
+    detection_rate = (tp / total_malware * 100) if total_malware > 0 else 0.0
+    fpr = (fp / total_safe * 100) if total_safe > 0 else 0.0
+    
+    print(f"Accuracy : {acc:.6f}")
+    print(f"ROC AUC  : {auc:.6f}\n")
+    
+    print(f"True Positive (Class 1) : {detection_rate:.3f}% ({tp}/{total_malware})")
+    print(f"False Positive (Class 0) : {fpr:.3f}% ({fp}/{total_safe})")
 
-    print("---------------------------------------------------------\n")
-    print("[*] Top 20 Features (Importance by Gain):")
+    print("\n---------------------------------------------------------\n")
+    print("[*] Top 20 Features:")
     
     feature_names = model.feature_name()
     importance = model.feature_importance(importance_type='gain')
@@ -192,25 +233,27 @@ def evaluate_and_save(model, X_test, y_test):
 ####################################################################################################
 
 if __name__ == "__main__":
-    print("\n---------------- PE Malware Trainer v3.1 ----------------\n")
+    print("\n---------------- PE Malware Trainer v4.0 ----------------\n")
 
-    if not os.path.exists(DB_PATH):
-        print(f"[-] Error: Database {DB_PATH} not found.")
+    if not os.path.exists(JSONL_PATH):
+        print(f"[-] Error: Feature file {JSONL_PATH} not found.")
         sys.exit(1)
 
-    raw_schema = get_raw_schema(DB_PATH)
-    if not raw_schema:
-        print("[-] Error: Could not read schema.")
+    base_schema, dll_schema, api_schema, num_lines = analyze_schema(JSONL_PATH)
+    if num_lines == 0:
+        print("[-] Error: Feature file is empty.")
         sys.exit(1)
 
-    X, y, _ = load_data(DB_PATH, raw_schema)
-    if X is None:
-        sys.exit(1)
+    print(f"[*] Detected Base features: {len(base_schema)}")
+    print(f"[*] Hashing DLL features: {len(dll_schema)}")
+    print(f"[*] Hashing API features: {len(api_schema)}")
 
+    X, y, final_features = load_data_efficiently(JSONL_PATH, base_schema, dll_schema, api_schema, num_lines)
+    
     try:
-        model, X_test, y_test = train_process(X, y)
+        model, X_test, y_test = train_process(X, y, final_features)
         evaluate_and_save(model, X_test, y_test)
     except KeyboardInterrupt:
-        print("\n\n[-] Training interrupted.")
+        print("\n\n[-] Training aborted.")
     except Exception as e:
-        print(f"\n[-] Critical Error: {e}")
+        print(f"\n[-] System exception: {e}")

Engine/Properties/train_server_lfp.py

@@ -1,216 +0,0 @@
-import os, sys, time, sqlite3, re, json
-import pandas as pd
-import numpy as np
-import lightgbm as lgb
-import onnxmltools
-
-from onnxmltools.convert.common.data_types import FloatTensorType
-from sklearn.model_selection import train_test_split
-from sklearn.metrics import classification_report, accuracy_score, roc_auc_score
-
-####################################################################################################
-
-DB_PATH = "pe_features.db"
-MODEL_FILE = "model.txt"
-ONNX_FILE = "model.onnx"
-FEATURE_FILE = "features.json"
-TEST_SIZE = 0.0001
-RANDOM_SEED = 42
-
-LGBM_PARAMS = {
-    'objective': 'binary',
-    'metric': ['binary_logloss', 'auc'],
-    'boosting_type': 'gbdt',
-    'num_leaves': 512,
-    'learning_rate': 0.05,
-    'feature_fraction': 0.8,
-    'bagging_fraction': 0.8,
-    'bagging_freq': 5,
-    'verbose': -1,
-    'seed': RANDOM_SEED,
-    'n_jobs': -1,
-    'max_depth': -1,
-    'min_data_in_leaf': 10,
-    'lambda_l1': 0.1,
-    'lambda_l2': 0.1,
-}
-
-####################################################################################################
-
-def clean_col_name(name):
-    return re.sub(r'[^A-Za-z0-9_]+', '', name)
-
-def get_raw_schema(db_path):
-    if not os.path.exists(db_path):
-        return None
-    conn = sqlite3.connect(db_path)
-    try:
-        cursor = conn.cursor()
-        cursor.execute("PRAGMA table_info(PeData)")
-        columns = [row[1] for row in cursor.fetchall()]
-        exclude = {'label', 'id', 'filename', 'filelength', 'rowid', 'probability', 'predictedlabel', 'score', 'filehash', 'timedatestamp'}
-        return [c for c in columns if c.lower().strip() not in exclude]
-    except Exception as e:
-        print(f"[-] Schema extraction error: {e}")
-        return None
-    finally:
-        conn.close()
-
-####################################################################################################
-
-def load_data(db_path, raw_cols):
-    print(f"[*] Connecting to database: {db_path}")
-    conn = sqlite3.connect(db_path)
-    req_cols = list(set(raw_cols + ['Label']))
-    sql = f"SELECT {', '.join(req_cols)} FROM PeData"
-    
-    try:
-        chunks = []
-        for chunk in pd.read_sql_query(sql, conn, chunksize=20000):
-            label_col = next((c for c in chunk.columns if c.lower().strip() == 'label'), None)
-            if not label_col:
-                print("[-] Critical Error: Label column not found.")
-                return None, None, None
-
-            cols_to_cast = [c for c in chunk.columns if c != label_col]
-            chunk[cols_to_cast] = chunk[cols_to_cast].astype(np.float32)
-            chunk[label_col] = chunk[label_col].astype(np.int8)
-            chunks.append(chunk)
-
-        if not chunks:
-            return None, None, None
-
-        df = pd.concat(chunks, ignore_index=True)
-
-        label_col = next((c for c in df.columns if c.lower().strip() == 'label'), None)
-        y = df[label_col].astype(int)
-        X = df.drop(columns=[label_col], errors='ignore')
-        
-        valid_features = [c for c in raw_cols if c in X.columns]
-        X = X[valid_features].copy()
-        
-        rename_map = {old: clean_col_name(old) for old in X.columns}
-        X = X.rename(columns=rename_map)
-        
-        if X.columns.duplicated().any():
-            print("[-] Warning: Duplicate column names detected after cleaning. Deduplicating...")
-            X = X.loc[:, ~X.columns.duplicated()]
-
-        final_features = X.columns.tolist()
-        return X, y, final_features
-    finally:
-        conn.close()
-
-####################################################################################################
-
-def train_process(X, y):
-    print(f"[*] Dataset shape: {X.shape}")
-    
-    X_train, X_test, y_train, y_test = train_test_split(
-        X, y, test_size=TEST_SIZE, random_state=RANDOM_SEED, stratify=y
-    )
-    
-    n_pos = (y_train == 1).sum()
-    n_neg = (y_train == 0).sum()
-    
-    base_weight = n_neg / n_pos if n_pos > 0 else 1.0
-    weight_ratio_target = 0.001
-    final_pos_weight = base_weight * weight_ratio_target
-    
-    print(f"[*] Balance Report: Safe={n_neg}, Malware={n_pos}")
-    print(f"[*] Weight Config: Base Balanced={base_weight:.4f}, Final Adjusted={final_pos_weight:.4f}")
-    
-    train_data = lgb.Dataset(X_train, label=y_train)
-    valid_data = lgb.Dataset(X_test, label=y_test, reference=train_data)
-    
-    params = LGBM_PARAMS.copy()
-    params['scale_pos_weight'] = final_pos_weight
-
-    print("\n[*] Starting LightGBM training...")
-    start_time = time.time()
-    
-    model = lgb.train(
-        params,
-        train_data,
-        valid_sets=[valid_data],
-        num_boost_round=1000,
-        callbacks=[
-            lgb.log_evaluation(period=100)
-        ]
-    )
-    
-    elapsed = time.time() - start_time
-    print(f"\n[+] Training finished in {elapsed:.2f}s")
-    
-    return model, X_test, y_test
-
-####################################################################################################
-
-def export_onnx_model(model, feature_names):
-    print(f"[*] Exporting ONNX model to {ONNX_FILE}...")
-    try:
-        initial_type = [('float_input', FloatTensorType([None, len(feature_names)]))]
-        onnx_model = onnxmltools.convert_lightgbm(model, initial_types=initial_type)
-        onnxmltools.utils.save_model(onnx_model, ONNX_FILE)
-        
-        with open(FEATURE_FILE, 'w') as f:
-            json.dump(feature_names, f)
-            
-        print(f"[+] ONNX export success. Features synced to {FEATURE_FILE}")
-    except Exception as e:
-        print(f"[-] ONNX export failed: {e}")
-
-####################################################################################################
-
-def evaluate_and_save(model, X_test, y_test):
-    print("\n------------------- Evaluation Report -------------------\n")
-    y_prob = model.predict(X_test, num_iteration=model.best_iteration)
-    y_pred = (y_prob > 0.5).astype(int)
-    
-    acc = accuracy_score(y_test, y_pred)
-    auc = roc_auc_score(y_test, y_prob)
-    
-    print(f"Accuracy : {acc:.4f}")
-    print(f"ROC AUC  : {auc:.4f}")
-    print("\n" + classification_report(y_test, y_pred, zero_division=0))
-
-    print("---------------------------------------------------------\n")
-    print("[*] Top 20 Features (Importance by Gain):")
-    
-    feature_names = model.feature_name()
-    importance = model.feature_importance(importance_type='gain')
-    feature_imp = pd.DataFrame(sorted(zip(importance, feature_names), reverse=True), columns=['Value', 'Feature'])
-    print(feature_imp.head(20).to_string(index=False))
-    
-    print("\n---------------------------------------------------------\n")
-    
-    model.save_model(MODEL_FILE)
-    print(f"[+] Native model saved to: {os.path.abspath(MODEL_FILE)}")
-    
-    export_onnx_model(model, feature_names)
-
-####################################################################################################
-
-if __name__ == "__main__":
-    print("\n---------------- PE Malware Trainer v3.1 ----------------\n")
-
-    if not os.path.exists(DB_PATH):
-        print(f"[-] Error: Database {DB_PATH} not found.")
-        sys.exit(1)
-
-    raw_schema = get_raw_schema(DB_PATH)
-    if not raw_schema:
-        print("[-] Error: Could not read schema.")
-        sys.exit(1)
-
-    X, y, _ = load_data(DB_PATH, raw_schema)
-    if X is None:
-        sys.exit(1)
-
-    try:
-        model, X_test, y_test = train_process(X, y)
-        evaluate_and_save(model, X_test, y_test)
-    except KeyboardInterrupt:
-        print("\n\n[-] Training interrupted.")
-    except Exception as e:
-        print(f"\n[-] Critical Error: {e}")

Engine/Properties/train_user.py

@@ -1,109 +1,138 @@
-import os, sys, time, sqlite3, re, json
-import pandas as pd
+import os, sys, time, json, onnxmltools, zlib
 import numpy as np
+import pandas as pd
 import lightgbm as lgb
-import onnxmltools
+import scipy.sparse as sp
 
+from collections import defaultdict
 from onnxmltools.convert.common.data_types import FloatTensorType
 from sklearn.model_selection import train_test_split
-from sklearn.metrics import classification_report, accuracy_score, roc_auc_score
+from sklearn.metrics import accuracy_score, roc_auc_score
+
+try:
+    import orjson
+    JSON_LOADS = orjson.loads
+except ImportError:
+    JSON_LOADS = json.loads
 
 ####################################################################################################
 
-DB_PATH = "pe_features.db"
+JSONL_PATH = "pe_features.jsonl"
 MODEL_FILE = "model.txt"
 ONNX_FILE = "Pefile_General_T1.onnx"
 FEATURE_FILE = "features.json"
 TEST_SIZE = 0.0001
 RANDOM_SEED = 42
 
+DLL_HASH_DIM = 256
+API_HASH_DIM = 1024
+
+EXCLUDE_FEATURES = {
+    'label', 'filehash',
+}
+
 LGBM_PARAMS = {
     'objective': 'binary',
     'metric': ['binary_logloss', 'auc'],
     'boosting_type': 'gbdt',
-    'num_leaves': 63,
-    'learning_rate': 0.05,
+    'num_leaves': 128,
     'feature_fraction': 0.8,
-    'bagging_fraction': 0.8,
+    'bagging_fraction': 1.0,
     'bagging_freq': 5,
     'verbose': -1,
     'seed': RANDOM_SEED,
     'n_jobs': -1,
     'max_depth': -1,
-    'min_data_in_leaf': 10,
-    'lambda_l1': 0.1,
-    'lambda_l2': 0.1,
+    'min_data_in_leaf': 50,
 }
 
 ####################################################################################################
 
-def clean_col_name(name):
-    return re.sub(r'[^A-Za-z0-9_]+', '', name)
+def analyze_schema(jsonl_path):
+    print("[*] Stage 1: Scanning global schema...")
+    base_keys = set()
+    num_lines = 0
 
-def get_raw_schema(db_path):
-    if not os.path.exists(db_path):
-        return None
-    conn = sqlite3.connect(db_path)
-    try:
-        cursor = conn.cursor()
-        cursor.execute("PRAGMA table_info(PeData)")
-        columns = [row[1] for row in cursor.fetchall()]
-        exclude = {'label', 'id', 'filename', 'filelength', 'rowid', 'probability', 'predictedlabel', 'score', 'filehash', 'timedatestamp'}
-        return [c for c in columns if c.lower().strip() not in exclude]
-    except Exception as e:
-        print(f"[-] Schema extraction error: {e}")
-        return None
-    finally:
-        conn.close()
+    with open(jsonl_path, 'rb') as f:
+        for line in f:
+            try:
+                data = JSON_LOADS(line)
+                base_data = data.get('Base')
+                if base_data:
+                    base_keys.update(base_data.keys())
+                num_lines += 1
+            except Exception:
+                continue
 
-####################################################################################################
-
-def load_data(db_path, raw_cols):
-    print(f"[*] Connecting to database: {db_path}")
-    conn = sqlite3.connect(db_path)
-    req_cols = list(set(raw_cols + ['Label']))
-    sql = f"SELECT {', '.join(req_cols)} FROM PeData"
+    base_schema = sorted([k for k in base_keys if k.lower().strip() not in EXCLUDE_FEATURES])
+    dll_schema = [f"DllHash_{i:03d}" for i in range(DLL_HASH_DIM)]
+    api_schema = [f"ApiHash_{i:04d}" for i in range(API_HASH_DIM)]
     
-    try:
-        chunks = []
-        for chunk in pd.read_sql_query(sql, conn, chunksize=20000):
-            label_col = next((c for c in chunk.columns if c.lower().strip() == 'label'), None)
-            if not label_col:
-                print("[-] Critical Error: Label column not found.")
-                return None, None, None
-
-            cols_to_cast = [c for c in chunk.columns if c != label_col]
-            chunk[cols_to_cast] = chunk[cols_to_cast].astype(np.float32)
-            chunk[label_col] = chunk[label_col].astype(np.int8)
-            chunks.append(chunk)
-
-        if not chunks:
-            return None, None, None
-
-        df = pd.concat(chunks, ignore_index=True)
-
-        label_col = next((c for c in df.columns if c.lower().strip() == 'label'), None)
-        y = df[label_col].astype(int)
-        X = df.drop(columns=[label_col], errors='ignore')
-        
-        valid_features = [c for c in raw_cols if c in X.columns]
-        X = X[valid_features].copy()
-        
-        rename_map = {old: clean_col_name(old) for old in X.columns}
-        X = X.rename(columns=rename_map)
-        
-        if X.columns.duplicated().any():
-            print("[-] Warning: Duplicate column names detected after cleaning. Deduplicating...")
-            X = X.loc[:, ~X.columns.duplicated()]
-
-        final_features = X.columns.tolist()
-        return X, y, final_features
-    finally:
-        conn.close()
+    return base_schema, dll_schema, api_schema, num_lines
 
 ####################################################################################################
 
-def train_process(X, y):
+def load_data_efficiently(jsonl_path, base_schema, dll_schema, api_schema, num_lines):
+    print(f"[*] Stage 2: Building sparse feature matrix dynamically (Expected samples: {num_lines})...")
+    final_features = base_schema + dll_schema + api_schema
+    num_features = len(final_features)
+
+    base_idx = {feat: i for i, feat in enumerate(base_schema)}
+    offset_dll = len(base_schema)
+    offset_api = offset_dll + DLL_HASH_DIM
+
+    rows, cols, vals = [], [], []
+    y = np.zeros(num_lines, dtype=np.int8)
+
+    with open(jsonl_path, 'rb') as f:
+        row_idx = 0
+        for line in f:
+            try:
+                data = JSON_LOADS(line)
+                y[row_idx] = data.get('Label', 0)
+
+                base_data = data.get('Base')
+                if base_data:
+                    for k, v in base_data.items():
+                        idx = base_idx.get(k)
+                        if idx is not None:
+                            val = float(v)
+                            if val != 0.0:
+                                rows.append(row_idx)
+                                cols.append(idx)
+                                vals.append(val)
+
+                dll_data = data.get('DLLs')
+                if dll_data:
+                    for d in dll_data:
+                        idx = zlib.crc32(d.encode('utf-8', 'ignore')) % DLL_HASH_DIM
+                        rows.append(row_idx)
+                        cols.append(offset_dll + idx)
+                        vals.append(1.0)
+
+                api_data = data.get('APIs')
+                if api_data:
+                    for a in api_data:
+                        idx = zlib.crc32(a.encode('utf-8', 'ignore')) % API_HASH_DIM
+                        rows.append(row_idx)
+                        cols.append(offset_api + idx)
+                        vals.append(1.0)
+
+                row_idx += 1
+            except Exception:
+                continue
+
+    y = y[:row_idx]
+    X = sp.csr_matrix((vals, (rows, cols)), shape=(row_idx, num_features), dtype=np.float32)
+    
+    return X, pd.Series(y), final_features
+
+####################################################################################################
+
+def _calculate_dynamic_lr(current_iter: int) -> float:
+    return max(0.01, 0.1 - (current_iter // 80) * 0.01)
+
+def train_process(X, y, feature_names):
     print(f"[*] Dataset shape: {X.shape}")
     
     X_train, X_test, y_train, y_test = train_test_split(
@@ -117,11 +146,11 @@ def train_process(X, y):
     weight_ratio_target = 0.001
     final_pos_weight = base_weight * weight_ratio_target
     
-    print(f"[*] Balance Report: Safe={n_neg}, Malware={n_pos}")
-    print(f"[*] Weight Config: Base Balanced={base_weight:.4f}, Final Adjusted={final_pos_weight:.4f}")
+    print(f"[*] Sample distribution: Safe={n_neg}, Malware={n_pos}")
+    print(f"[*] Weight correction: Base={base_weight:.4f}, Final={final_pos_weight:.4f}")
     
-    train_data = lgb.Dataset(X_train, label=y_train)
-    valid_data = lgb.Dataset(X_test, label=y_test, reference=train_data)
+    train_data = lgb.Dataset(X_train, label=y_train, feature_name=feature_names)
+    valid_data = lgb.Dataset(X_test, label=y_test, reference=train_data, feature_name=feature_names)
     
     params = LGBM_PARAMS.copy()
     params['scale_pos_weight'] = final_pos_weight
@@ -133,14 +162,15 @@ def train_process(X, y):
         params,
         train_data,
         valid_sets=[valid_data],
-        num_boost_round=1000,
+        num_boost_round=500,
         callbacks=[
-            lgb.log_evaluation(period=100)
+            lgb.log_evaluation(period=50),
+            lgb.reset_parameter(learning_rate=_calculate_dynamic_lr)
         ]
     )
     
     elapsed = time.time() - start_time
-    print(f"\n[+] Training finished in {elapsed:.2f}s")
+    print(f"\n[+] Training complete, time elapsed {elapsed:.2f} seconds")
     
     return model, X_test, y_test
 
@@ -156,12 +186,10 @@ def export_onnx_model(model, feature_names):
         with open(FEATURE_FILE, 'w') as f:
             json.dump(feature_names, f)
             
-        print(f"[+] ONNX export success. Features synced to {FEATURE_FILE}")
+        print(f"[+] ONNX export successful. Feature order saved to {FEATURE_FILE}")
     except Exception as e:
         print(f"[-] ONNX export failed: {e}")
 
-####################################################################################################
-
 def evaluate_and_save(model, X_test, y_test):
     print("\n------------------- Evaluation Report -------------------\n")
     y_prob = model.predict(X_test, num_iteration=model.best_iteration)
@@ -170,12 +198,25 @@ def evaluate_and_save(model, X_test, y_test):
     acc = accuracy_score(y_test, y_pred)
     auc = roc_auc_score(y_test, y_prob)
     
-    print(f"Accuracy : {acc:.4f}")
-    print(f"ROC AUC  : {auc:.4f}")
-    print("\n" + classification_report(y_test, y_pred, zero_division=0))
+    tp = np.sum((y_test == 1) & (y_pred == 1))
+    fn = np.sum((y_test == 1) & (y_pred == 0))
+    tn = np.sum((y_test == 0) & (y_pred == 0))
+    fp = np.sum((y_test == 0) & (y_pred == 1))
+    
+    total_malware = tp + fn
+    total_safe = tn + fp
+    
+    detection_rate = (tp / total_malware * 100) if total_malware > 0 else 0.0
+    fpr = (fp / total_safe * 100) if total_safe > 0 else 0.0
+    
+    print(f"Accuracy : {acc:.6f}")
+    print(f"ROC AUC  : {auc:.6f}\n")
+    
+    print(f"True Positive (Class 1) : {detection_rate:.3f}% ({tp}/{total_malware})")
+    print(f"False Positive (Class 0) : {fpr:.3f}% ({fp}/{total_safe})")
 
-    print("---------------------------------------------------------\n")
-    print("[*] Top 20 Features (Importance by Gain):")
+    print("\n---------------------------------------------------------\n")
+    print("[*] Top 20 Features:")
     
     feature_names = model.feature_name()
     importance = model.feature_importance(importance_type='gain')
@@ -192,25 +233,27 @@ def evaluate_and_save(model, X_test, y_test):
 ####################################################################################################
 
 if __name__ == "__main__":
-    print("\n---------------- PE Malware Trainer v3.1 ----------------\n")
+    print("\n---------------- PE Malware Trainer v4.0 ----------------\n")
 
-    if not os.path.exists(DB_PATH):
-        print(f"[-] Error: Database {DB_PATH} not found.")
+    if not os.path.exists(JSONL_PATH):
+        print(f"[-] Error: Feature file {JSONL_PATH} not found.")
         sys.exit(1)
 
-    raw_schema = get_raw_schema(DB_PATH)
-    if not raw_schema:
-        print("[-] Error: Could not read schema.")
+    base_schema, dll_schema, api_schema, num_lines = analyze_schema(JSONL_PATH)
+    if num_lines == 0:
+        print("[-] Error: Feature file is empty.")
         sys.exit(1)
 
-    X, y, _ = load_data(DB_PATH, raw_schema)
-    if X is None:
-        sys.exit(1)
+    print(f"[*] Detected Base features: {len(base_schema)}")
+    print(f"[*] Hashing DLL features: {len(dll_schema)}")
+    print(f"[*] Hashing API features: {len(api_schema)}")
 
+    X, y, final_features = load_data_efficiently(JSONL_PATH, base_schema, dll_schema, api_schema, num_lines)
+    
     try:
-        model, X_test, y_test = train_process(X, y)
+        model, X_test, y_test = train_process(X, y, final_features)
         evaluate_and_save(model, X_test, y_test)
     except KeyboardInterrupt:
-        print("\n\n[-] Training interrupted.")
+        print("\n\n[-] Training aborted.")
     except Exception as e:
-        print(f"\n[-] Critical Error: {e}")
+        print(f"\n[-] System exception: {e}")

Interface/static/css/style.css

@@ -56,7 +56,7 @@ body {
 }
 
 .navigate-title {
-    font-size: 16px;
+    font-size: 17px;
     font-weight: 600;
     letter-spacing: -0.2px;
 }
@@ -292,17 +292,14 @@ body {
     border: 1px solid var(--border-color);
     border-radius: 12px;
     background-color: var(--bg-panel);
+    overflow-y: auto;
+    overflow-x: auto;
 }
 
 .virus-list {
     list-style: none;
-    height: 100%;
-    overflow-y: auto;
-    overflow-x: auto;
-    padding: 12px;
-}
-
-.virus-list .manage-list-item {
+    padding: 0;
+    margin: 0;
     min-width: max-content;
 }
 
@@ -498,6 +495,7 @@ body {
     height: 16px;
     accent-color: var(--accent-color);
     cursor: pointer;
+    flex-shrink: 0;
 }
 
 .manage-list-item-content {
@@ -510,13 +508,16 @@ body {
 
 .custom-select-wrapper {
     position: relative;
-    min-width: 120px;
+    min-width: 100px;
+    display: inline-grid;
+    vertical-align: middle;
     user-select: none;
 }
 select.hidden + .custom-select-wrapper {
     display: none !important;
 }
 .custom-select-trigger {
+    grid-area: 1 / 1;
     display: flex;
     justify-content: space-between;
     align-items: center;
@@ -530,7 +531,24 @@ select.hidden + .custom-select-wrapper {
     cursor: pointer;
     transition: border-color 0.2s, box-shadow 0.2s;
     gap: 12px;
+    box-sizing: border-box;
 }
+.custom-select-phantom {
+    grid-area: 1 / 1;
+    visibility: hidden;
+    pointer-events: none;
+    display: grid; 
+    padding: 8px 16px;
+    font-size: 14px;
+    font-weight: 500;
+    box-sizing: border-box;
+}
+.custom-select-phantom span {
+    grid-area: 1 / 1; 
+    white-space: nowrap;
+    padding-right: 28px; 
+}
+
 .custom-select-wrapper.open .custom-select-trigger,
 .custom-select-trigger:hover {
     border-color: var(--accent-color); 
@@ -550,7 +568,10 @@ select.hidden + .custom-select-wrapper {
     position: absolute;
     top: calc(100% + 8px);
     left: 0;
-    right: 0;
+    min-width: 100%;
+    width: max-content;
+    white-space: nowrap;
+    
     background-color: var(--bg-panel);
     border: 1px solid var(--border-color);
     border-radius: 10px;
@@ -558,12 +579,10 @@ select.hidden + .custom-select-wrapper {
     z-index: 100;
     list-style: none;
     margin: 0;
-    
     max-height: 0;
     padding: 0 6px;
     border-width: 0;
     overflow: hidden;
-    
     opacity: 0;
     visibility: hidden;
     transform: translateY(-10px);
@@ -660,6 +679,162 @@ select.hidden + .custom-select-wrapper {
     opacity: 1 !important;
 }
 
+.manage-list-header {
+    display: flex;
+    align-items: center;
+    gap: 12px;
+    padding: 12px 16px;
+    border-bottom: 1px solid var(--border-color);
+    background-color: var(--bg-panel);
+    font-weight: 600;
+    font-size: 13px;
+    color: var(--text-secondary);
+    position: sticky;
+    top: 0;
+    z-index: 10;
+}
+
+.manage-list-header input[type="checkbox"] {
+    width: 16px;
+    height: 16px;
+    accent-color: var(--accent-color);
+    cursor: pointer;
+    flex-shrink: 0;
+}
+
+.header-cols-container, .manage-list-item-content {
+    display: flex;
+    flex-grow: 1;
+    min-width: 0;
+    gap: 16px;
+    align-items: center;
+}
+
+.col-header {
+    position: relative;
+    cursor: pointer;
+    display: flex;
+    align-items: center;
+    padding: 0 8px;
+    border-right: 1px solid var(--border-color);
+    background-color: var(--bg-panel);
+    user-select: none;
+    -webkit-user-select: none;
+}
+
+.col-header:last-child {
+    border-right: none;
+}
+
+.header-text {
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+    flex-grow: 1;
+}
+
+.manage-list-header, .col-header, .col-resizer {
+    user-select: none;
+    -webkit-user-select: none;
+}
+
+.col-resizer {
+    position: absolute;
+    right: -5px;
+    top: 0;
+    bottom: 0;
+    width: 10px;
+    cursor: col-resize;
+    z-index: 10;
+    background-color: transparent !important; 
+}
+
+.col-resizer::after {
+    content: "";
+    position: absolute;
+    left: 50%;
+    top: 0;
+    bottom: 0;
+    width: 1px;
+    background-color: transparent;
+    transition: background-color 0.2s;
+}
+
+.col-resizer:hover::after,
+.col-resizer.resizing::after {
+    background-color: var(--text-secondary) !important;
+    opacity: 0.6;
+}
+
+body.resizing-active, 
+body.resizing-active * {
+    user-select: none !important;
+    -webkit-user-select: none !important;
+    cursor: col-resize !important;
+}
+
+.col-resizer:hover {
+    background-color: var(--accent-color);
+    opacity: 0.5;
+}
+
+.col-header:hover {
+    color: var(--text-primary);
+}
+
+.sort-icon {
+    font-size: 10px;
+    margin-left: 4px;
+    color: var(--accent-color);
+    width: 12px;
+}
+
+.row-col {
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+    font-size: 14px;
+    color: var(--text-primary);
+}
+
+.custom-context-menu {
+    position: absolute;
+    z-index: 10000;
+    background-color: var(--bg-panel);
+    border: 1px solid var(--border-color);
+    border-radius: 8px;
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
+    padding: 4px;
+    display: none;
+    min-width: 160px;
+}
+
+.custom-context-menu.show {
+    display: block;
+}
+
+.custom-context-menu-item {
+    display: flex;
+    align-items: center;
+    gap: 10px;
+    padding: 8px 12px;
+    border-radius: 6px;
+    cursor: pointer;
+    font-size: 13px;
+    color: var(--text-primary);
+    transition: background-color 0.2s;
+}
+
+.custom-context-menu-item:hover {
+    background-color: var(--bg-hover);
+}
+
+.custom-context-menu-item svg {
+    width: 16px;
+    height: 16px;
+    color: var(--text-secondary);
+}
+
 ::-webkit-scrollbar { width: 6px; height: 6px; }
 ::-webkit-scrollbar-track { background: transparent; }
 ::-webkit-scrollbar-thumb { background: var(--border-color); border-radius: 10px; }

Interface/templates/index.html

@@ -5,6 +5,7 @@
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>PYAS Security</title>
     <link rel="stylesheet" href="/static/css/style.css">
+    <script defer src="/static/js/i18n.js"></script>
     <script defer src="/static/js/main.js"></script>
 </head>
 <body>
@@ -59,13 +60,13 @@
                         <div class="quick-actions">
                             <div class="list-item" style="cursor: pointer;" id="quick_scan_btn" data-action="scan">
                                 <div class="item-info">
-                                    <h2 data-i18n>智能掃描</h2><p data-i18n>此選項可以快速掃病毒</p>
+                                    <h2 data-i18n>智能掃描</h2><p data-i18n>此選項可以快速掃描裝置安全性</p>
                                 </div>
                                 <button class="icon-action-btn"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="9 18 15 12 9 6"></polyline></svg></button>
                             </div>
                             <div class="list-item" style="cursor: pointer;" data-target="log_export_window">
                                 <div class="item-info">
-                                    <h2 data-i18n>日誌導出</h2><p data-i18n>此選項可以篩選導出日誌</p>
+                                    <h2 data-i18n>日誌導出</h2><p data-i18n>此選項可以篩選日誌並匯出存檔</p>
                                 </div>
                                 <button class="icon-action-btn"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="9 18 15 12 9 6"></polyline></svg></button>
                             </div>
@@ -80,16 +81,15 @@
                     <div class="progress-widget">
                         <div class="header-group">
                             <h2 class="section-title" data-i18n>病毒掃描</h2>
-                            <p class="section-desc" id="progress_text" data-i18n>此選項可以選擇掃描方式</p>
+                            <p class="section-desc" id="progress_text" data-i18n>此選項可以選擇進階掃描方式</p>
                         </div>
                         <div class="action-group modern-action-group">
-                            <button class="action-btn modern-btn danger-btn hidden" id="solve_btn" data-i18n>刪除</button>
                             <select id="scan_method_select" class="modern-select">
                                 <option value="none" selected disabled data-i18n>選擇</option>
-                                <option value="smart" data-i18n>智能</option>
-                                <option value="file" data-i18n>檔案</option>
-                                <option value="path" data-i18n>路徑</option>
-                                <option value="full" data-i18n>全盤</option>
+                                <option value="smart" data-i18n>智能掃描</option>
+                                <option value="file" data-i18n>檔案掃描</option>
+                                <option value="path" data-i18n>路徑掃描</option>
+                                <option value="full" data-i18n>全盤掃描</option>
                             </select>
                             <button class="action-btn modern-btn hidden" id="stop_btn" data-i18n>停止</button>
                         </div>
@@ -105,37 +105,37 @@
                     <div class="list-widget">
                         <div class="list-item">
                             <div class="item-info">
-                                <h2 data-i18n>進程防護</h2><p data-i18n>此選項可以攔截進程病毒</p>
+                                <h2 data-i18n>進程防護</h2><p data-i18n>此選項可以終止惡意進程運行</p>
                             </div>
                             <label class="toggle-switch"><input type="checkbox" checked><span class="slider"></span></label>
                         </div>
                         <div class="list-item">
                             <div class="item-info">
-                                <h2 data-i18n>檔案防護</h2><p data-i18n>此選項可以攔截檔案變更</p>
+                                <h2 data-i18n>檔案防護</h2><p data-i18n>此選項可以隔離惡意檔案建立</p>
                             </div>
                             <label class="toggle-switch"><input type="checkbox" checked><span class="slider"></span></label>
                         </div>
                         <div class="list-item">
                             <div class="item-info">
-                                <h2 data-i18n>系統防護</h2><p data-i18n>此選項可以攔截系統項目</p>
+                                <h2 data-i18n>系統防護</h2><p data-i18n>此選項可以實時修復系統異常</p>
                             </div>
                             <label class="toggle-switch"><input type="checkbox" checked><span class="slider"></span></label>
                         </div>
                         <div class="list-item">
                             <div class="item-info">
-                                <h2 data-i18n>驅動防護</h2><p data-i18n>此選項可以增強自身防護</p>
+                                <h2 data-i18n>驅動防護</h2><p data-i18n>此選項可以實時攔截惡意行為</p>
                             </div>
                             <label class="toggle-switch"><input type="checkbox" checked><span class="slider"></span></label>
                         </div>
                         <div class="list-item">
                             <div class="item-info">
-                                <h2 data-i18n>網路防護</h2><p data-i18n>此選項可以攔截網路通訊</p>
+                                <h2 data-i18n>網路防護</h2><p data-i18n>此選項可以攔截惡意網路連接</p>
                             </div>
                             <label class="toggle-switch"><input type="checkbox" checked><span class="slider"></span></label>
                         </div>
                         <div class="list-item" style="cursor: pointer;" data-target="custom_protect_window">
                             <div class="item-info">
-                                <h2 data-i18n>自訂防護</h2><p data-i18n>此選項可以導入自訂防護</p>
+                                <h2 data-i18n>自訂防護</h2><p data-i18n>此選項可以導入自訂防護規則</p>
                             </div>
                             <button class="icon-action-btn"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="9 18 15 12 9 6"></polyline></svg></button>
                         </div>
@@ -158,7 +158,7 @@
                         </div>
                         <div class="list-item" style="cursor: pointer;" data-target="repair_window">
                             <div class="item-info">
-                                <h2 data-i18n>系統修復</h2><p data-i18n>此選項可以修復系統註冊項目</p>
+                                <h2 data-i18n>系統修復</h2><p data-i18n>此選項可以修復系統登錄檔項目</p>
                             </div>
                             <button class="icon-action-btn"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="9 18 15 12 9 6"></polyline></svg></button>
                         </div>
@@ -170,13 +170,13 @@
                         </div>
                         <div class="list-item" style="cursor: pointer;" data-target="whitelist_window">
                             <div class="item-info">
-                                <h2 data-i18n>白名單</h2><p data-i18n>此選項可以管理系統白名單</p>
+                                <h2 data-i18n>白名單</h2><p data-i18n>此選項可以查看並管理白名單</p>
                             </div>
                             <button class="icon-action-btn"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="9 18 15 12 9 6"></polyline></svg></button>
                         </div>
                         <div class="list-item" style="cursor: pointer;" data-target="quarantine_window">
                             <div class="item-info">
-                                <h2 data-i18n>隔離區</h2><p data-i18n>此選項可以管理已隔離的檔案</p>
+                                <h2 data-i18n>隔離區</h2><p data-i18n>此選項可以查看並管理隔離區</p>
                             </div>
                             <button class="icon-action-btn"><svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="9 18 15 12 9 6"></polyline></svg></button>
                         </div>
@@ -187,22 +187,28 @@
                     <div class="list-widget">
                         <div class="list-item">
                             <div class="item-info">
-                                <h2 data-i18n>增強模式</h2><p data-i18n>此選項可以增強掃描引擎</p>
+                                <h2 data-i18n>增強模式</h2><p data-i18n>此選項可以增強靜態掃描引擎</p>
                             </div>
                             <label class="toggle-switch"><input type="checkbox"><span class="slider"></span></label>
                         </div>
                         <div class="list-item">
                             <div class="item-info">
-                                <h2 data-i18n>擴展引擎</h2><p data-i18n>此選項可以使用擴展引擎</p>
+                                <h2 data-i18n>擴展引擎</h2><p data-i18n>此選項可以使用擴展規則引擎</p>
                             </div>
                             <label class="toggle-switch"><input type="checkbox"><span class="slider"></span></label>
                         </div>
                         <div class="list-item">
                             <div class="item-info">
-                                <h2 data-i18n>雲端服務</h2><p data-i18n>此選項可以上報雲端引擎</p>
+                                <h2 data-i18n>雲端服務</h2><p data-i18n>此選項可以自動上報可疑檔案</p>
                             </div>
                             <label class="toggle-switch"><input type="checkbox" checked><span class="slider"></span></label>
                         </div>
+                        <div class="list-item">
+                            <div class="item-info">
+                                <h2 data-i18n>選單掃描</h2><p data-i18n>此選項可以啟用右鍵掃描功能</p>
+                            </div>
+                            <label class="toggle-switch"><input type="checkbox"><span class="slider"></span></label>
+                        </div>
                         <div class="list-item">
                             <div class="item-info">
                                 <h2 data-i18n>顯色主題</h2><p data-i18n>此選項可以選擇主題顏色</p>

PYAS_Version.py

@@ -2,7 +2,7 @@ import pyinstaller_versionfile
 
 pyinstaller_versionfile.create_versionfile(
 output_file="versionfile.txt",
-version='3.5.0.0',
+version='3.5.6.0',
 company_name="PYAS Security",
 file_description="PYAS Security Antivirus",
 internal_name="PYAS",

Plugins/Filter/DriverCommon.h

@@ -114,8 +114,8 @@ typedef struct _DRIVER_DATA {
     PEPROCESS PyasProcess;
     ULONG PyasPid;
     LARGE_INTEGER Cookie;
-    FAST_MUTEX PortMutex;
-    FAST_MUTEX TrackerMutex;
+    KSPIN_LOCK PortMutex;
+    KSPIN_LOCK TrackerMutex;
     EX_RUNDOWN_REF PortRundown;
 } DRIVER_DATA, * PDRIVER_DATA;
 

Plugins/Filter/DriverEntry.cpp

@@ -1,6 +1,7 @@
 #include "DriverCommon.h"
 
 DRIVER_DATA GlobalData;
+static BOOLEAN g_ImageNotifyRegistered = FALSE;
 
 static NTSTATUS InstanceSetup(PCFLT_RELATED_OBJECTS FltObjects, FLT_INSTANCE_SETUP_FLAGS Flags, DEVICE_TYPE VolumeDeviceType, FLT_FILESYSTEM_TYPE VolumeFilesystemType) {
     UNREFERENCED_PARAMETER(FltObjects);
@@ -27,9 +28,7 @@ static VOID InstanceTeardownComplete(PCFLT_RELATED_OBJECTS FltObjects, FLT_INSTA
 }
 
 static NTSTATUS DriverUnload(FLT_FILTER_UNLOAD_FLAGS Flags) {
-    if (!(Flags & FLTFL_FILTER_UNLOAD_MANDATORY)) {
-        return STATUS_FLT_DO_NOT_DETACH;
-    }
+    UNREFERENCED_PARAMETER(Flags);
 
     if (GlobalData.ServerPort) {
         FltCloseCommunicationPort(GlobalData.ServerPort);
@@ -41,12 +40,14 @@ static NTSTATUS DriverUnload(FLT_FILTER_UNLOAD_FLAGS Flags) {
         GlobalData.FilterHandle = NULL;
     }
 
-    PsRemoveLoadImageNotifyRoutine(ImageLoadNotify);
+    if (g_ImageNotifyRegistered) {
+        PsRemoveLoadImageNotifyRoutine(ImageLoadNotify);
+        g_ImageNotifyRegistered = FALSE;
+    }
+
     UninitializeRegistryProtection();
     UninitializeProcessProtection();
 
-    ExWaitForRundownProtectionRelease(&GlobalData.PortRundown);
-
     UnloadRules();
     UninitializeRulesEngine();
 
@@ -61,12 +62,9 @@ static NTSTATUS PortMessage(PVOID PortCookie, PVOID InputBuffer, ULONG InputBuff
     if (InputBuffer && InputBufferLength >= sizeof(PYAS_USER_MESSAGE)) {
         PPYAS_USER_MESSAGE msg = (PPYAS_USER_MESSAGE)InputBuffer;
         if (msg->Command == 1 || msg->Command == 2) {
-
             msg->Path[MAX_PATH_LEN - 1] = L'\0';
-
             UNICODE_STRING us;
             RtlInitUnicodeString(&us, msg->Path);
-
             if (us.Length > 0) {
                 if (msg->Command == 1) {
                     AddDynamicWhitelist(&us);
@@ -90,7 +88,8 @@ static NTSTATUS PortConnect(PFLT_PORT ClientPort, PVOID ServerPortCookie, PVOID
     UNREFERENCED_PARAMETER(SizeOfContext);
     UNREFERENCED_PARAMETER(ConnectionPortCookie);
 
-    ExAcquireFastMutex(&GlobalData.PortMutex);
+    KIRQL OldIrql;
+    KeAcquireSpinLock(&GlobalData.PortMutex, &OldIrql);
 
     GlobalData.ClientPort = ClientPort;
     GlobalData.PyasPid = (ULONG)(ULONG_PTR)PsGetCurrentProcessId();
@@ -98,7 +97,7 @@ static NTSTATUS PortConnect(PFLT_PORT ClientPort, PVOID ServerPortCookie, PVOID
 
     ExReInitializeRundownProtection(&GlobalData.PortRundown);
 
-    ExReleaseFastMutex(&GlobalData.PortMutex);
+    KeReleaseSpinLock(&GlobalData.PortMutex, OldIrql);
 
     return STATUS_SUCCESS;
 }
@@ -106,9 +105,14 @@ static NTSTATUS PortConnect(PFLT_PORT ClientPort, PVOID ServerPortCookie, PVOID
 static VOID PortDisconnect(PVOID ConnectionCookie) {
     UNREFERENCED_PARAMETER(ConnectionCookie);
 
-    ExAcquireFastMutex(&GlobalData.PortMutex);
+    KIRQL OldIrql;
+    KeAcquireSpinLock(&GlobalData.PortMutex, &OldIrql);
+
     GlobalData.ClientPort = NULL;
-    ExReleaseFastMutex(&GlobalData.PortMutex);
+    GlobalData.PyasPid = 0;
+    GlobalData.PyasProcess = NULL;
+
+    KeReleaseSpinLock(&GlobalData.PortMutex, OldIrql);
 
     ExWaitForRundownProtectionRelease(&GlobalData.PortRundown);
 }
@@ -147,8 +151,8 @@ extern "C" NTSTATUS DriverEntry(PDRIVER_OBJECT DriverObject, PUNICODE_STRING Reg
 
     RtlZeroMemory(&GlobalData, sizeof(GlobalData));
     GlobalData.DriverObject = DriverObject;
-    ExInitializeFastMutex(&GlobalData.PortMutex);
-    ExInitializeFastMutex(&GlobalData.TrackerMutex);
+    KeInitializeSpinLock(&GlobalData.PortMutex);
+    KeInitializeSpinLock(&GlobalData.TrackerMutex);
 
     ExInitializeRundownProtection(&GlobalData.PortRundown);
 
@@ -172,22 +176,29 @@ extern "C" NTSTATUS DriverEntry(PDRIVER_OBJECT DriverObject, PUNICODE_STRING Reg
     }
 
     if (!NT_SUCCESS(status)) {
-        if (GlobalData.FilterHandle) {
-            FltUnregisterFilter(GlobalData.FilterHandle);
-            GlobalData.FilterHandle = NULL;
-        }
+        FltUnregisterFilter(GlobalData.FilterHandle);
+        GlobalData.FilterHandle = NULL;
         UnloadRules();
         UninitializeRulesEngine();
         return status;
     }
 
     InitializeProcessProtection();
+
     InitializeRegistryProtection(DriverObject);
-    PsSetLoadImageNotifyRoutine(ImageLoadNotify);
+
+    NTSTATUS imageNotifyStatus = PsSetLoadImageNotifyRoutine(ImageLoadNotify);
+    if (NT_SUCCESS(imageNotifyStatus)) {
+        g_ImageNotifyRegistered = TRUE;
+    }
 
     status = FltStartFiltering(GlobalData.FilterHandle);
     if (!NT_SUCCESS(status)) {
-        PsRemoveLoadImageNotifyRoutine(ImageLoadNotify);
+        if (g_ImageNotifyRegistered) {
+            PsRemoveLoadImageNotifyRoutine(ImageLoadNotify);
+            g_ImageNotifyRegistered = FALSE;
+        }
+
         UninitializeRegistryProtection();
         UninitializeProcessProtection();
 

Plugins/Filter/PYAS_Driver.inf

@@ -3,7 +3,7 @@ Signature   = "$WINDOWS NT$"
 Class       = ActivityMonitor
 ClassGuid   = {b86dff51-a31e-4bac-b3cf-e8cfe75c9fc2}
 Provider    = %ManufacturerName%
-DriverVer   = 04/12/2026,3.5.0.0
+DriverVer   = 04/26/2026,3.5.1.0
 CatalogFile = PYAS_Driver.cat
 PnpLockdown = 1
 

Plugins/Filter/ProtectFile.cpp

@@ -199,6 +199,7 @@ FLT_PREOP_CALLBACK_STATUS ProtectFile_PreWrite(PFLT_CALLBACK_DATA Data, PCFLT_RE
     UNREFERENCED_PARAMETER(FltObjects);
 
     if (Data->RequestorMode == KernelMode) return FLT_PREOP_SUCCESS_NO_CALLBACK;
+    if (KeGetCurrentIrql() > APC_LEVEL) return FLT_PREOP_SUCCESS_NO_CALLBACK;
 
     if (Data->Iopb->IrpFlags & (IRP_PAGING_IO | IRP_SYNCHRONOUS_PAGING_IO | IRP_NOCACHE)) {
         return FLT_PREOP_SUCCESS_NO_CALLBACK;
@@ -235,12 +236,10 @@ FLT_PREOP_CALLBACK_STATUS ProtectFile_PreWrite(PFLT_CALLBACK_DATA Data, PCFLT_RE
                 SystemBuffer = MmGetSystemAddressForMdlSafe(Mdl, NormalPagePriority | MdlMappingNoExecute);
             }
 
-            if (SystemBuffer) {
-                if (CheckRansomActivity(Pid, &nameInfo->Name, SystemBuffer, WriteLength, TRUE)) {
-                    SendMessageToUser(5001, (ULONG)(ULONG_PTR)Pid, nameInfo->Name.Buffer, nameInfo->Name.Length);
-                    Data->IoStatus.Status = STATUS_ACCESS_DENIED;
-                    callbackStatus = FLT_PREOP_COMPLETE;
-                }
+            if (CheckRansomActivity(Pid, &nameInfo->Name, SystemBuffer, WriteLength, TRUE)) {
+                SendMessageToUser(5001, (ULONG)(ULONG_PTR)Pid, nameInfo->Name.Buffer, nameInfo->Name.Length);
+                Data->IoStatus.Status = STATUS_ACCESS_DENIED;
+                callbackStatus = FLT_PREOP_COMPLETE;
             }
         }
     }

Plugins/Filter/ProtectProcess.cpp

@@ -34,6 +34,36 @@ VOID ImageLoadNotify(PUNICODE_STRING FullImageName, HANDLE ProcessId, PIMAGE_INF
     }
 }
 
+static BOOLEAN IsCriticalSystemProcess(HANDLE ProcessId) {
+    if (ProcessId == (HANDLE)4) return TRUE;
+
+    if (KeGetCurrentIrql() != PASSIVE_LEVEL) return FALSE;
+
+    NTSTATUS status;
+    BOOLEAN isCritical = FALSE;
+    PEPROCESS Process = NULL;
+    PUNICODE_STRING imageFileName = NULL;
+
+    status = PsLookupProcessByProcessId(ProcessId, &Process);
+    if (!NT_SUCCESS(status)) return FALSE;
+
+    status = SeLocateProcessImageName(Process, &imageFileName);
+
+    if (NT_SUCCESS(status) && imageFileName && imageFileName->Buffer) {
+        if (WildcardMatch(L"*\\Windows\\System32\\csrss.exe", imageFileName->Buffer, imageFileName->Length) ||
+            WildcardMatch(L"*\\Windows\\System32\\lsass.exe", imageFileName->Buffer, imageFileName->Length) ||
+            WildcardMatch(L"*\\Windows\\System32\\services.exe", imageFileName->Buffer, imageFileName->Length) ||
+            WildcardMatch(L"*\\Windows\\System32\\wininit.exe", imageFileName->Buffer, imageFileName->Length) ||
+            WildcardMatch(L"*\\Windows\\System32\\smss.exe", imageFileName->Buffer, imageFileName->Length)) {
+            isCritical = TRUE;
+        }
+        ExFreePool(imageFileName);
+    }
+
+    ObDereferenceObject(Process);
+    return isCritical;
+}
+
 static BOOLEAN IsBlacklistedAdminTool(HANDLE ProcessId) {
     if (KeGetCurrentIrql() != PASSIVE_LEVEL) return FALSE;
 
@@ -79,6 +109,8 @@ static OB_PREOP_CALLBACK_STATUS PreOpenProcess(PVOID RegistrationContext, POB_PR
     if (SourcePid == (HANDLE)4) return OB_PREOP_SUCCESS;
 
     if (IsTargetProtected(TargetPid)) {
+        if (IsCriticalSystemProcess(SourcePid)) return OB_PREOP_SUCCESS;
+
         BOOLEAN bIsTrusted = IsProcessTrusted(SourcePid);
 
         if (bIsTrusted) {
@@ -99,10 +131,10 @@ static OB_PREOP_CALLBACK_STATUS PreOpenProcess(PVOID RegistrationContext, POB_PR
             PROCESS_SET_INFORMATION |
             PROCESS_SET_QUOTA;
 
-        OperationInformation->Parameters->CreateHandleInformation.DesiredAccess &= ~DenyMask;
+        OperationInformation->Parameters->CreateHandleInformation.DesiredAccess &= (ACCESS_MASK)(~DenyMask);
 
         if (OperationInformation->Operation == OB_OPERATION_HANDLE_DUPLICATE) {
-            OperationInformation->Parameters->DuplicateHandleInformation.DesiredAccess &= ~DenyMask;
+            OperationInformation->Parameters->DuplicateHandleInformation.DesiredAccess &= (ACCESS_MASK)(~DenyMask);
         }
     }
 
@@ -128,6 +160,8 @@ static OB_PREOP_CALLBACK_STATUS PreOpenThread(PVOID RegistrationContext, POB_PRE
     if (SourcePid == (HANDLE)4) return OB_PREOP_SUCCESS;
 
     if (IsTargetProtected(TargetPid)) {
+        if (IsCriticalSystemProcess(SourcePid)) return OB_PREOP_SUCCESS;
+
         BOOLEAN bIsTrusted = IsProcessTrusted(SourcePid);
 
         if (bIsTrusted) {
@@ -144,10 +178,10 @@ static OB_PREOP_CALLBACK_STATUS PreOpenThread(PVOID RegistrationContext, POB_PRE
             THREAD_SET_INFORMATION |
             THREAD_SET_THREAD_TOKEN;
 
-        OperationInformation->Parameters->CreateHandleInformation.DesiredAccess &= ~DenyMask;
+        OperationInformation->Parameters->CreateHandleInformation.DesiredAccess &= (ACCESS_MASK)(~DenyMask);
 
         if (OperationInformation->Operation == OB_OPERATION_HANDLE_DUPLICATE) {
-            OperationInformation->Parameters->DuplicateHandleInformation.DesiredAccess &= ~DenyMask;
+            OperationInformation->Parameters->DuplicateHandleInformation.DesiredAccess &= (ACCESS_MASK)(~DenyMask);
         }
     }
 
@@ -155,8 +189,7 @@ static OB_PREOP_CALLBACK_STATUS PreOpenThread(PVOID RegistrationContext, POB_PRE
 }
 
 NTSTATUS InitializeProcessProtection() {
-    static UNICODE_STRING Altitude = { 0 };
-    RtlInitUnicodeString(&Altitude, L"320000");
+    static UNICODE_STRING Altitude = RTL_CONSTANT_STRING(L"320000.PYAS.Ob");
 
     ObCallbacks[0].ObjectType = PsProcessType;
     ObCallbacks[0].Operations = OB_OPERATION_HANDLE_CREATE | OB_OPERATION_HANDLE_DUPLICATE;
@@ -174,7 +207,15 @@ NTSTATUS InitializeProcessProtection() {
     ObRegistration.RegistrationContext = NULL;
     ObRegistration.OperationRegistration = ObCallbacks;
 
-    return ObRegisterCallbacks(&ObRegistration, &ObRegistrationHandle);
+    NTSTATUS status = ObRegisterCallbacks(&ObRegistration, &ObRegistrationHandle);
+
+    if (!NT_SUCCESS(status) && (status == STATUS_FLT_INSTANCE_ALTITUDE_COLLISION || status == STATUS_OBJECT_NAME_COLLISION)) {
+        static UNICODE_STRING FallbackAltitude = RTL_CONSTANT_STRING(L"320000.PYAS.Ob.Fallback");
+        ObRegistration.Altitude = FallbackAltitude;
+        status = ObRegisterCallbacks(&ObRegistration, &ObRegistrationHandle);
+    }
+
+    return status;
 }
 
 VOID UninitializeProcessProtection() {

Plugins/Filter/ProtectRegistry.cpp

@@ -149,30 +149,32 @@ static NTSTATUS RegistryCallback(PVOID CallbackContext, PVOID Argument1, PVOID A
                             (Info->ValueName ? Info->ValueName->Length : 0) +
                             sizeof(WCHAR);
 
-                        PWCHAR Buffer = (PWCHAR)PyasAllocate(FullSize);
-                        if (Buffer) {
-                            UNICODE_STRING FullPath;
-                            FullPath.Buffer = Buffer;
-                            FullPath.Length = 0;
-                            FullPath.MaximumLength = (USHORT)FullSize;
+                        if (FullSize <= 0xFFFF) {
+                            PWCHAR Buffer = (PWCHAR)PyasAllocate(FullSize);
+                            if (Buffer) {
+                                UNICODE_STRING FullPath;
+                                FullPath.Buffer = Buffer;
+                                FullPath.Length = 0;
+                                FullPath.MaximumLength = (USHORT)FullSize;
 
-                            RtlCopyUnicodeString(&FullPath, KeyName);
+                                RtlCopyUnicodeString(&FullPath, KeyName);
 
-                            if (Info->ValueName && Info->ValueName->Length > 0) {
-                                if (FullPath.Length > 0 && FullPath.Buffer[(FullPath.Length / sizeof(WCHAR)) - 1] != L'\\') {
-                                    RtlAppendUnicodeToString(&FullPath, L"\\");
+                                if (Info->ValueName && Info->ValueName->Length > 0) {
+                                    if (FullPath.Length > 0 && FullPath.Buffer[(FullPath.Length / sizeof(WCHAR)) - 1] != L'\\') {
+                                        RtlAppendUnicodeToString(&FullPath, L"\\");
+                                    }
+                                    RtlAppendUnicodeStringToString(&FullPath, Info->ValueName);
                                 }
-                                RtlAppendUnicodeStringToString(&FullPath, Info->ValueName);
-                            }
 
-                            if (CheckRegistryRule(&FullPath)) {
-                                HANDLE Pid = PsGetCurrentProcessId();
-                                if (!IsProcessTrusted(Pid)) {
-                                    SendMessageToUser(3001, (ULONG)(ULONG_PTR)Pid, FullPath.Buffer, FullPath.Length);
-                                    status = STATUS_ACCESS_DENIED;
+                                if (CheckRegistryRule(&FullPath)) {
+                                    HANDLE Pid = PsGetCurrentProcessId();
+                                    if (!IsProcessTrusted(Pid)) {
+                                        SendMessageToUser(3001, (ULONG)(ULONG_PTR)Pid, FullPath.Buffer, FullPath.Length);
+                                        status = STATUS_ACCESS_DENIED;
+                                    }
                                 }
+                                PyasFree(Buffer);
                             }
-                            PyasFree(Buffer);
                         }
                     }
                 }
@@ -194,30 +196,32 @@ static NTSTATUS RegistryCallback(PVOID CallbackContext, PVOID Argument1, PVOID A
                             (Info->ValueName ? Info->ValueName->Length : 0) +
                             sizeof(WCHAR);
 
-                        PWCHAR Buffer = (PWCHAR)PyasAllocate(FullSize);
-                        if (Buffer) {
-                            UNICODE_STRING FullPath;
-                            FullPath.Buffer = Buffer;
-                            FullPath.Length = 0;
-                            FullPath.MaximumLength = (USHORT)FullSize;
+                        if (FullSize <= 0xFFFF) {
+                            PWCHAR Buffer = (PWCHAR)PyasAllocate(FullSize);
+                            if (Buffer) {
+                                UNICODE_STRING FullPath;
+                                FullPath.Buffer = Buffer;
+                                FullPath.Length = 0;
+                                FullPath.MaximumLength = (USHORT)FullSize;
 
-                            RtlCopyUnicodeString(&FullPath, KeyName);
+                                RtlCopyUnicodeString(&FullPath, KeyName);
 
-                            if (Info->ValueName && Info->ValueName->Length > 0) {
-                                if (FullPath.Length > 0 && FullPath.Buffer[(FullPath.Length / sizeof(WCHAR)) - 1] != L'\\') {
-                                    RtlAppendUnicodeToString(&FullPath, L"\\");
+                                if (Info->ValueName && Info->ValueName->Length > 0) {
+                                    if (FullPath.Length > 0 && FullPath.Buffer[(FullPath.Length / sizeof(WCHAR)) - 1] != L'\\') {
+                                        RtlAppendUnicodeToString(&FullPath, L"\\");
+                                    }
+                                    RtlAppendUnicodeStringToString(&FullPath, Info->ValueName);
                                 }
-                                RtlAppendUnicodeStringToString(&FullPath, Info->ValueName);
-                            }
 
-                            if (CheckRegistryRule(&FullPath)) {
-                                HANDLE Pid = PsGetCurrentProcessId();
-                                if (!IsProcessTrusted(Pid)) {
-                                    SendMessageToUser(3001, (ULONG)(ULONG_PTR)Pid, FullPath.Buffer, FullPath.Length);
-                                    status = STATUS_ACCESS_DENIED;
+                                if (CheckRegistryRule(&FullPath)) {
+                                    HANDLE Pid = PsGetCurrentProcessId();
+                                    if (!IsProcessTrusted(Pid)) {
+                                        SendMessageToUser(3001, (ULONG)(ULONG_PTR)Pid, FullPath.Buffer, FullPath.Length);
+                                        status = STATUS_ACCESS_DENIED;
+                                    }
                                 }
+                                PyasFree(Buffer);
                             }
-                            PyasFree(Buffer);
                         }
                     }
                 }
@@ -231,9 +235,15 @@ static NTSTATUS RegistryCallback(PVOID CallbackContext, PVOID Argument1, PVOID A
 }
 
 NTSTATUS InitializeRegistryProtection(PDRIVER_OBJECT DriverObject) {
-    UNICODE_STRING Altitude;
-    RtlInitUnicodeString(&Altitude, L"320000");
-    return CmRegisterCallbackEx(RegistryCallback, &Altitude, DriverObject, NULL, &Cookie, NULL);
+    static UNICODE_STRING Altitude = RTL_CONSTANT_STRING(L"320000.PYAS.Cm");
+    NTSTATUS status = CmRegisterCallbackEx(RegistryCallback, &Altitude, DriverObject, NULL, &Cookie, NULL);
+
+    if (!NT_SUCCESS(status)) {
+        static UNICODE_STRING FallbackAltitude = RTL_CONSTANT_STRING(L"320000.PYAS.Cm.Fallback");
+        status = CmRegisterCallbackEx(RegistryCallback, &FallbackAltitude, DriverObject, NULL, &Cookie, NULL);
+    }
+
+    return status;
 }
 
 VOID UninitializeRegistryProtection() {

Plugins/Filter/ProtectRules.cpp

@@ -10,19 +10,21 @@ constexpr auto TRUST_CACHE_TTL_SEC = 300;
 
 typedef struct _RANSOM_TRACKER {
     PEPROCESS Process;
+    LARGE_INTEGER ProcessCreateTime;
     ULONG ActivityCount;
     LARGE_INTEGER LastActivityTime;
 } RANSOM_TRACKER, * PRANSOM_TRACKER;
 
 typedef struct _TRUST_CACHE_ENTRY {
     PEPROCESS Process;
+    LARGE_INTEGER ProcessCreateTime;
     BOOLEAN IsTrusted;
     LARGE_INTEGER CacheTime;
 } TRUST_CACHE_ENTRY, * PTRUST_CACHE_ENTRY;
 
 static RANSOM_TRACKER RansomTrackers[MAX_TRACKERS];
 static TRUST_CACHE_ENTRY TrustCache[TRUST_CACHE_SIZE];
-static FAST_MUTEX TrustCacheLock;
+static KSPIN_LOCK TrustCacheLock;
 static BOOLEAN g_CacheInitialized = FALSE;
 
 static ERESOURCE RuleLock;
@@ -107,7 +109,7 @@ static BOOLEAN HasSuffix(PCUNICODE_STRING String, PCWSTR Suffix) {
 }
 
 BOOLEAN WildcardMatch(PCWSTR Pattern, PCWSTR String, USHORT StringLengthBytes) {
-    if (!Pattern || !String) return FALSE;
+    if (Pattern == NULL || String == NULL) return FALSE;
 
     USHORT StringLenChars = StringLengthBytes / sizeof(WCHAR);
     PCWSTR mp = NULL;
@@ -123,7 +125,7 @@ BOOLEAN WildcardMatch(PCWSTR Pattern, PCWSTR String, USHORT StringLengthBytes) {
             Pattern++;
             String++;
         }
-        else if (mp) {
+        else if (mp != NULL) {
             Pattern = mp;
             String = cp++;
         }
@@ -134,7 +136,8 @@ BOOLEAN WildcardMatch(PCWSTR Pattern, PCWSTR String, USHORT StringLengthBytes) {
     while (*Pattern == L'*') {
         Pattern++;
     }
-    return !*Pattern;
+
+    return (*Pattern == L'\0') ? TRUE : FALSE;
 }
 
 static ULONG ProcessJsonUnescape(PWCHAR Buffer, ULONG LengthChars) {
@@ -202,17 +205,23 @@ static VOID ParseAndLoadRules(PCHAR JsonContent, ULONG ContentLength, PCSTR KeyN
 
                     while (Ptr < End) {
                         SkipWhitespace(&Ptr, End);
-                        if (Ptr >= End) break;
-
-                        if (*Ptr == ']') {
-                            Ptr++;
+                        if (Ptr >= End || *Ptr == ']') {
+                            if (Ptr < End) Ptr++;
                             return;
                         }
 
                         if (*Ptr == '"') {
                             PCHAR StartQuote = ++Ptr;
+                            BOOLEAN Escaped = FALSE;
+
                             while (Ptr < End) {
-                                if (*Ptr == '"' && *(Ptr - 1) != '\\') break;
+                                if (*Ptr == '"' && Escaped == FALSE) break;
+                                if (*Ptr == '\\') {
+                                    Escaped = (Escaped == FALSE) ? TRUE : FALSE;
+                                }
+                                else {
+                                    Escaped = FALSE;
+                                }
                                 Ptr++;
                             }
 
@@ -242,9 +251,6 @@ static VOID ParseAndLoadRules(PCHAR JsonContent, ULONG ContentLength, PCSTR KeyN
                                 Ptr++;
                             }
                         }
-                        else if (*Ptr == ',') {
-                            Ptr++;
-                        }
                         else {
                             Ptr++;
                         }
@@ -259,7 +265,7 @@ static VOID ParseAndLoadRules(PCHAR JsonContent, ULONG ContentLength, PCSTR KeyN
 
 VOID InitializeRulesEngine() {
     ExInitializeResourceLite(&RuleLock);
-    ExInitializeFastMutex(&TrustCacheLock);
+    KeInitializeSpinLock(&TrustCacheLock);
     RtlZeroMemory(TrustCache, sizeof(TrustCache));
     g_CacheInitialized = TRUE;
 }
@@ -298,25 +304,33 @@ static VOID RemoveRule(PRULE_NODE* Head, PUNICODE_STRING RuleStr) {
 }
 
 VOID AddDynamicWhitelist(PUNICODE_STRING RuleStr) {
+    KeEnterCriticalRegion();
     ExAcquireResourceExclusiveLite(&RuleLock, TRUE);
     AddRule(&g_ProcessTrustedPaths, RuleStr);
     AddRule(&g_FileExceptionPaths, RuleStr);
 
-    ExAcquireFastMutex(&TrustCacheLock);
+    KIRQL OldIrql;
+    KeAcquireSpinLock(&TrustCacheLock, &OldIrql);
     RtlZeroMemory(TrustCache, sizeof(TrustCache));
-    ExReleaseFastMutex(&TrustCacheLock);
+    KeReleaseSpinLock(&TrustCacheLock, OldIrql);
+
     ExReleaseResourceLite(&RuleLock);
+    KeLeaveCriticalRegion();
 }
 
 VOID RemoveDynamicWhitelist(PUNICODE_STRING RuleStr) {
+    KeEnterCriticalRegion();
     ExAcquireResourceExclusiveLite(&RuleLock, TRUE);
     RemoveRule(&g_ProcessTrustedPaths, RuleStr);
     RemoveRule(&g_FileExceptionPaths, RuleStr);
 
-    ExAcquireFastMutex(&TrustCacheLock);
+    KIRQL OldIrql;
+    KeAcquireSpinLock(&TrustCacheLock, &OldIrql);
     RtlZeroMemory(TrustCache, sizeof(TrustCache));
-    ExReleaseFastMutex(&TrustCacheLock);
+    KeReleaseSpinLock(&TrustCacheLock, OldIrql);
+
     ExReleaseResourceLite(&RuleLock);
+    KeLeaveCriticalRegion();
 }
 
 NTSTATUS LoadRulesFromDisk(PUNICODE_STRING RegistryPath) {
@@ -359,58 +373,58 @@ NTSTATUS LoadRulesFromDisk(PUNICODE_STRING RegistryPath) {
     }
 
     if (Info->Type == REG_EXPAND_SZ || Info->Type == REG_SZ) {
-        PathBufferSize = ResultLength + 1024;
+        PathBufferSize = Info->DataLength + 1024;
         PathBuffer = (PWCHAR)PyasAllocate(PathBufferSize);
 
         if (PathBuffer) {
             RtlZeroMemory(PathBuffer, PathBufferSize);
-            PWCHAR Src = (PWCHAR)Info->Data;
+            if (Info->DataLength > 0) {
+                RtlCopyMemory(PathBuffer, Info->Data, Info->DataLength);
+            }
 
-            if (NT_SUCCESS(RtlStringCbCopyW(PathBuffer, PathBufferSize, Src))) {
-                PWCHAR LastSlash = NULL;
-                PWCHAR Current = PathBuffer;
-                while (*Current) {
-                    if (*Current == L'\\') LastSlash = Current;
-                    Current++;
-                }
+            PWCHAR LastSlash = NULL;
+            PWCHAR Current = PathBuffer;
+            while (*Current) {
+                if (*Current == L'\\') LastSlash = Current;
+                Current++;
+            }
 
-                if (LastSlash) {
-                    *LastSlash = L'\0';
+            if (LastSlash) {
+                *LastSlash = L'\0';
 
-                    SIZE_T CurrentPathLen = wcslen(PathBuffer);
-                    const WCHAR FilterSuffix[] = L"\\Filter";
-                    SIZE_T FilterLen = (sizeof(FilterSuffix) / sizeof(WCHAR)) - 1;
+                SIZE_T CurrentPathLen = wcslen(PathBuffer);
+                const WCHAR FilterSuffix[] = L"\\Filter";
+                SIZE_T FilterLen = (sizeof(FilterSuffix) / sizeof(WCHAR)) - 1;
 
-                    if (CurrentPathLen >= FilterLen) {
-                        PWCHAR SuffixStart = PathBuffer + CurrentPathLen - FilterLen;
-                        BOOLEAN Match = TRUE;
-                        for (SIZE_T i = 0; i < FilterLen; i++) {
-                            if (RtlDowncaseUnicodeChar(SuffixStart[i]) != RtlDowncaseUnicodeChar(FilterSuffix[i])) {
-                                Match = FALSE;
-                                break;
-                            }
-                        }
-                        if (Match) {
-                            *SuffixStart = L'\0';
+                if (CurrentPathLen >= FilterLen) {
+                    PWCHAR SuffixStart = PathBuffer + CurrentPathLen - FilterLen;
+                    BOOLEAN Match = TRUE;
+                    for (SIZE_T i = 0; i < FilterLen; i++) {
+                        if (RtlDowncaseUnicodeChar(SuffixStart[i]) != RtlDowncaseUnicodeChar(FilterSuffix[i])) {
+                            Match = FALSE;
+                            break;
                         }
                     }
-
-                    RtlStringCbCatW(PathBuffer, PathBufferSize, L"\\Rules\\Rules_Driver_P1.json");
-
-                    if (wcsncmp(PathBuffer, L"\\??\\", 4) != 0 &&
-                        wcsncmp(PathBuffer, L"\\SystemRoot", 11) != 0 &&
-                        wcsncmp(PathBuffer, L"\\DosDevices\\", 12) != 0) {
-
-                        PWCHAR TmpBuffer = (PWCHAR)PyasAllocate(PathBufferSize + 16);
-                        if (TmpBuffer) {
-                            RtlStringCbCopyW(TmpBuffer, PathBufferSize + 16, L"\\??\\");
-                            RtlStringCbCatW(TmpBuffer, PathBufferSize + 16, PathBuffer);
-                            PyasFree(PathBuffer);
-                            PathBuffer = TmpBuffer;
-                        }
+                    if (Match) {
+                        *SuffixStart = L'\0';
                     }
-                    RtlInitUnicodeString(&FinalPath, PathBuffer);
                 }
+
+                RtlStringCbCatW(PathBuffer, PathBufferSize, L"\\Rules\\Rules_Driver_P1.json");
+
+                if (wcsncmp(PathBuffer, L"\\??\\", 4) != 0 &&
+                    wcsncmp(PathBuffer, L"\\SystemRoot", 11) != 0 &&
+                    wcsncmp(PathBuffer, L"\\DosDevices\\", 12) != 0) {
+
+                    PWCHAR TmpBuffer = (PWCHAR)PyasAllocate(PathBufferSize + 16);
+                    if (TmpBuffer) {
+                        RtlStringCbCopyW(TmpBuffer, PathBufferSize + 16, L"\\??\\");
+                        RtlStringCbCatW(TmpBuffer, PathBufferSize + 16, PathBuffer);
+                        PyasFree(PathBuffer);
+                        PathBuffer = TmpBuffer;
+                    }
+                }
+                RtlInitUnicodeString(&FinalPath, PathBuffer);
             }
         }
     }
@@ -435,6 +449,7 @@ NTSTATUS LoadRulesFromDisk(PUNICODE_STRING RegistryPath) {
                 if (NT_SUCCESS(status)) {
                     ((PCHAR)FileBuffer)[FileInfo.EndOfFile.LowPart] = '\0';
 
+                    KeEnterCriticalRegion();
                     ExAcquireResourceExclusiveLite(&RuleLock, TRUE);
                     ParseAndLoadRules((PCHAR)FileBuffer, FileInfo.EndOfFile.LowPart, "Rule_Registry_BlockList", &g_RegistryBlockList);
                     ParseAndLoadRules((PCHAR)FileBuffer, FileInfo.EndOfFile.LowPart, "Rule_Registry_TrustedList", &g_RegistryTrustedList);
@@ -444,6 +459,7 @@ NTSTATUS LoadRulesFromDisk(PUNICODE_STRING RegistryPath) {
                     ParseAndLoadRules((PCHAR)FileBuffer, FileInfo.EndOfFile.LowPart, "Rule_File_ExceptionPaths", &g_FileExceptionPaths);
                     ParseAndLoadRules((PCHAR)FileBuffer, FileInfo.EndOfFile.LowPart, "Rule_File_RansomwareExtensions", &g_FileRansomExts);
                     ExReleaseResourceLite(&RuleLock);
+                    KeLeaveCriticalRegion();
                 }
                 PyasFree(FileBuffer);
             }
@@ -456,6 +472,7 @@ NTSTATUS LoadRulesFromDisk(PUNICODE_STRING RegistryPath) {
 }
 
 VOID UnloadRules() {
+    KeEnterCriticalRegion();
     ExAcquireResourceExclusiveLite(&RuleLock, TRUE);
     FreeList(&g_RegistryBlockList);
     FreeList(&g_RegistryTrustedList);
@@ -465,9 +482,14 @@ VOID UnloadRules() {
     FreeList(&g_FileExceptionPaths);
     FreeList(&g_FileRansomExts);
     ExReleaseResourceLite(&RuleLock);
+    KeLeaveCriticalRegion();
 }
 
 NTSTATUS GetProcessImageName(HANDLE ProcessId, PUNICODE_STRING* ImageName) {
+    if (KeGetCurrentIrql() != PASSIVE_LEVEL) {
+        return STATUS_UNSUCCESSFUL;
+    }
+
     NTSTATUS status;
     PEPROCESS Process = NULL;
 
@@ -492,33 +514,42 @@ BOOLEAN IsProcessTrusted(HANDLE ProcessId) {
     if ((ULONG)(ULONG_PTR)ProcessId == GlobalData.PyasPid) return TRUE;
     if (ProcessId == (HANDLE)4) return TRUE;
 
-    if (KeGetCurrentIrql() != PASSIVE_LEVEL) return FALSE;
-
     PEPROCESS Process = NULL;
     if (!NT_SUCCESS(PsLookupProcessByProcessId(ProcessId, &Process))) {
         return FALSE;
     }
 
+    LARGE_INTEGER createTime;
+    createTime.QuadPart = PsGetProcessCreateTimeQuadPart(Process);
+
     if (g_CacheInitialized) {
-        ExAcquireFastMutex(&TrustCacheLock);
-        ULONG Hash = ((ULONG)(ULONG_PTR)ProcessId) & (TRUST_CACHE_SIZE - 1);
-        if (TrustCache[Hash].Process == Process) {
+        KIRQL OldIrql;
+        KeAcquireSpinLock(&TrustCacheLock, &OldIrql);
+        ULONG Hash = (((ULONG)(ULONG_PTR)ProcessId) >> 2) & (TRUST_CACHE_SIZE - 1);
+
+        if (TrustCache[Hash].Process == Process && TrustCache[Hash].ProcessCreateTime.QuadPart == createTime.QuadPart) {
             LARGE_INTEGER Now;
             KeQuerySystemTime(&Now);
             if ((Now.QuadPart - TrustCache[Hash].CacheTime.QuadPart) < (TRUST_CACHE_TTL_SEC * 10000000LL)) {
                 BOOLEAN cachedResult = TrustCache[Hash].IsTrusted;
-                ExReleaseFastMutex(&TrustCacheLock);
+                KeReleaseSpinLock(&TrustCacheLock, OldIrql);
                 ObDereferenceObject(Process);
                 return cachedResult;
             }
         }
-        ExReleaseFastMutex(&TrustCacheLock);
+        KeReleaseSpinLock(&TrustCacheLock, OldIrql);
+    }
+
+    if (KeGetCurrentIrql() != PASSIVE_LEVEL) {
+        ObDereferenceObject(Process);
+        return FALSE;
     }
 
     PUNICODE_STRING imageFileName = NULL;
     NTSTATUS status = GetProcessImageName(ProcessId, &imageFileName);
     BOOLEAN isTrusted = FALSE;
 
+    KeEnterCriticalRegion();
     ExAcquireResourceSharedLite(&RuleLock, TRUE);
 
     if (NT_SUCCESS(status) && imageFileName && imageFileName->Buffer) {
@@ -547,15 +578,18 @@ BOOLEAN IsProcessTrusted(HANDLE ProcessId) {
 
 update_cache:
     if (g_CacheInitialized) {
-        ExAcquireFastMutex(&TrustCacheLock);
-        ULONG Hash = ((ULONG)(ULONG_PTR)ProcessId) & (TRUST_CACHE_SIZE - 1);
+        KIRQL OldIrql;
+        KeAcquireSpinLock(&TrustCacheLock, &OldIrql);
+        ULONG Hash = (((ULONG)(ULONG_PTR)ProcessId) >> 2) & (TRUST_CACHE_SIZE - 1);
         TrustCache[Hash].Process = Process;
+        TrustCache[Hash].ProcessCreateTime = createTime;
         TrustCache[Hash].IsTrusted = isTrusted;
         KeQuerySystemTime(&TrustCache[Hash].CacheTime);
-        ExReleaseFastMutex(&TrustCacheLock);
+        KeReleaseSpinLock(&TrustCacheLock, OldIrql);
     }
 
     ExReleaseResourceLite(&RuleLock);
+    KeLeaveCriticalRegion();
 
     if (imageFileName) ExFreePool(imageFileName);
     ObDereferenceObject(Process);
@@ -575,12 +609,14 @@ BOOLEAN CheckRegistryRule(PCUNICODE_STRING KeyName) {
         return FALSE;
     }
 
+    KeEnterCriticalRegion();
     ExAcquireResourceSharedLite(&RuleLock, TRUE);
 
     PRULE_NODE AllowNode = g_RegistryTrustedList;
     while (AllowNode) {
         if (WildcardMatch(AllowNode->Pattern.Buffer, KeyName->Buffer, KeyName->Length)) {
             ExReleaseResourceLite(&RuleLock);
+            KeLeaveCriticalRegion();
             return FALSE;
         }
         AllowNode = AllowNode->Next;
@@ -596,18 +632,21 @@ BOOLEAN CheckRegistryRule(PCUNICODE_STRING KeyName) {
         Node = Node->Next;
     }
     ExReleaseResourceLite(&RuleLock);
+    KeLeaveCriticalRegion();
     return Match;
 }
 
 BOOLEAN CheckFileExtensionRule(PCUNICODE_STRING FileName) {
     if (!FileName || !FileName->Buffer) return FALSE;
 
+    KeEnterCriticalRegion();
     ExAcquireResourceSharedLite(&RuleLock, TRUE);
 
     PRULE_NODE ExNode = g_FileExceptionPaths;
     while (ExNode) {
         if (WildcardMatch(ExNode->Pattern.Buffer, FileName->Buffer, FileName->Length)) {
             ExReleaseResourceLite(&RuleLock);
+            KeLeaveCriticalRegion();
             return FALSE;
         }
         ExNode = ExNode->Next;
@@ -623,6 +662,7 @@ BOOLEAN CheckFileExtensionRule(PCUNICODE_STRING FileName) {
         Node = Node->Next;
     }
     ExReleaseResourceLite(&RuleLock);
+    KeLeaveCriticalRegion();
     return Match;
 }
 
@@ -633,12 +673,14 @@ BOOLEAN CheckProtectedPathRule(PCUNICODE_STRING FileName) {
         return FALSE;
     }
 
+    KeEnterCriticalRegion();
     ExAcquireResourceSharedLite(&RuleLock, TRUE);
 
     PRULE_NODE ExNode = g_FileExceptionPaths;
     while (ExNode) {
         if (WildcardMatch(ExNode->Pattern.Buffer, FileName->Buffer, FileName->Length)) {
             ExReleaseResourceLite(&RuleLock);
+            KeLeaveCriticalRegion();
             return FALSE;
         }
         ExNode = ExNode->Next;
@@ -654,13 +696,16 @@ BOOLEAN CheckProtectedPathRule(PCUNICODE_STRING FileName) {
         Node = Node->Next;
     }
     ExReleaseResourceLite(&RuleLock);
+    KeLeaveCriticalRegion();
     return Match;
 }
 
 static BOOLEAN IsHighEntropy(PVOID Buffer, ULONG Length) {
     if (!Buffer || Length < 256) return FALSE;
 
-    ULONG Histogram[256] = { 0 };
+    PUSHORT Histogram = (PUSHORT)PyasAllocate(256 * sizeof(USHORT));
+    if (!Histogram) return FALSE;
+
     PUCHAR Ptr = (PUCHAR)Buffer;
     ULONG ScanLen = (Length > 1024) ? 1024 : Length;
 
@@ -670,16 +715,20 @@ static BOOLEAN IsHighEntropy(PVOID Buffer, ULONG Length) {
         }
     }
     __except (EXCEPTION_EXECUTE_HANDLER) {
+        PyasFree(Histogram);
         return FALSE;
     }
 
-    ULONG MaxFreq = 0;
+    USHORT MaxFreq = 0;
     for (int i = 0; i < 256; i++) {
         if (Histogram[i] > MaxFreq) MaxFreq = Histogram[i];
     }
 
     ULONG ExpectedAvg = ScanLen / 256;
-    return (MaxFreq < (ExpectedAvg + HIGH_ENTROPY_THRESHOLD));
+    BOOLEAN Result = (MaxFreq < (ExpectedAvg + HIGH_ENTROPY_THRESHOLD));
+
+    PyasFree(Histogram);
+    return Result;
 }
 
 static BOOLEAN IsNaturallyCompressed(PCUNICODE_STRING FileName) {
@@ -707,19 +756,33 @@ static BOOLEAN IsNoisyRansomPath(PCUNICODE_STRING FileName) {
     return FALSE;
 }
 
+static BOOLEAN IsUserDirectoryPath(PCUNICODE_STRING FileName) {
+    if (!FileName || !FileName->Buffer) return FALSE;
+    return WildcardMatch(L"*\\Users\\*", FileName->Buffer, FileName->Length);
+}
+
 static BOOLEAN IsExplorerProcess(HANDLE ProcessId) {
-    if (KeGetCurrentIrql() != PASSIVE_LEVEL) return FALSE;
+    if (KeGetCurrentIrql() > APC_LEVEL) return FALSE;
+
     PUNICODE_STRING imageFileName = NULL;
     NTSTATUS status = GetProcessImageName(ProcessId, &imageFileName);
     BOOLEAN isExplorer = FALSE;
-    if (NT_SUCCESS(status) && imageFileName && imageFileName->Buffer) {
-        if (HasSuffix(imageFileName, L"\\explorer.exe")) isExplorer = TRUE;
+
+    if (NT_SUCCESS(status) && imageFileName) {
+        if (imageFileName->Buffer && HasSuffix(imageFileName, L"\\explorer.exe")) {
+            isExplorer = TRUE;
+        }
         ExFreePool(imageFileName);
     }
+
     return isExplorer;
 }
 
 BOOLEAN CheckRansomActivity(HANDLE ProcessId, PUNICODE_STRING FileName, PVOID WriteBuffer, ULONG WriteLength, BOOLEAN IsWrite) {
+    if (!IsUserDirectoryPath(FileName)) {
+        return FALSE;
+    }
+
     if (IsNoisyRansomPath(FileName)) {
         return FALSE;
     }
@@ -746,9 +809,12 @@ BOOLEAN CheckRansomActivity(HANDLE ProcessId, PUNICODE_STRING FileName, PVOID Wr
 
     LARGE_INTEGER Now = { 0 };
     KeQuerySystemTime(&Now);
+    LARGE_INTEGER createTime;
+    createTime.QuadPart = PsGetProcessCreateTimeQuadPart(Process);
     BOOLEAN Result = FALSE;
 
-    ExAcquireFastMutex(&GlobalData.TrackerMutex);
+    KIRQL OldIrql;
+    KeAcquireSpinLock(&GlobalData.TrackerMutex, &OldIrql);
 
     PRANSOM_TRACKER Tracker = NULL;
     PRANSOM_TRACKER CandidateSlot = NULL;
@@ -761,7 +827,7 @@ BOOLEAN CheckRansomActivity(HANDLE ProcessId, PUNICODE_STRING FileName, PVOID Wr
             LruSlot = Current;
         }
 
-        if (Current->Process == Process) {
+        if (Current->Process == Process && Current->ProcessCreateTime.QuadPart == createTime.QuadPart) {
             Tracker = Current;
             break;
         }
@@ -789,6 +855,7 @@ BOOLEAN CheckRansomActivity(HANDLE ProcessId, PUNICODE_STRING FileName, PVOID Wr
         }
 
         Tracker->Process = Process;
+        Tracker->ProcessCreateTime = createTime;
         Tracker->ActivityCount = 0;
         Tracker->LastActivityTime = Now;
     }
@@ -808,7 +875,8 @@ BOOLEAN CheckRansomActivity(HANDLE ProcessId, PUNICODE_STRING FileName, PVOID Wr
     if (Tracker->ActivityCount >= RANSOM_COUNT_THRESHOLD) {
         Result = TRUE;
     }
-    ExReleaseFastMutex(&GlobalData.TrackerMutex);
+
+    KeReleaseSpinLock(&GlobalData.TrackerMutex, OldIrql);
     ObDereferenceObject(Process);
     return Result;
 }
@@ -816,34 +884,48 @@ BOOLEAN CheckRansomActivity(HANDLE ProcessId, PUNICODE_STRING FileName, PVOID Wr
 NTSTATUS SendMessageToUser(ULONG Code, ULONG Pid, PWCHAR Path, USHORT PathSize) {
     if (KeGetCurrentIrql() > APC_LEVEL) return STATUS_UNSUCCESSFUL;
 
-    PYAS_MESSAGE msg;
-    RtlZeroMemory(&msg, sizeof(msg));
-    msg.MessageCode = Code;
-    msg.ProcessId = Pid;
-
-    if (Path && PathSize > 0) {
-        size_t MaxSize = sizeof(msg.Path) - sizeof(WCHAR);
-        size_t BytesToCopy = PathSize;
-        if (BytesToCopy > MaxSize) BytesToCopy = MaxSize;
-
-        __try {
-            RtlCopyMemory(msg.Path, Path, BytesToCopy);
-            msg.Path[BytesToCopy / sizeof(WCHAR)] = L'\0';
-        }
-        __except (EXCEPTION_EXECUTE_HANDLER) {
-            return STATUS_ACCESS_VIOLATION;
-        }
-    }
-
     if (!ExAcquireRundownProtection(&GlobalData.PortRundown)) {
         return STATUS_PORT_DISCONNECTED;
     }
 
     NTSTATUS status = STATUS_PORT_DISCONNECTED;
+
     if (GlobalData.ClientPort) {
-        LARGE_INTEGER timeout;
-        timeout.QuadPart = -(5 * 10000);
-        status = FltSendMessage(GlobalData.FilterHandle, &GlobalData.ClientPort, &msg, sizeof(msg), NULL, NULL, &timeout);
+        PPYAS_MESSAGE msg = (PPYAS_MESSAGE)PyasAllocate(sizeof(PYAS_MESSAGE));
+        if (msg) {
+            msg->MessageCode = Code;
+            msg->ProcessId = Pid;
+
+            if (Path && PathSize > 0) {
+                size_t MaxSize = sizeof(msg->Path) - sizeof(WCHAR);
+                size_t BytesToCopy = PathSize > MaxSize ? MaxSize : PathSize;
+
+                __try {
+                    RtlCopyMemory(msg->Path, Path, BytesToCopy);
+                    msg->Path[BytesToCopy / sizeof(WCHAR)] = L'\0';
+                }
+                __except (EXCEPTION_EXECUTE_HANDLER) {
+                    PyasFree(msg);
+                    ExReleaseRundownProtection(&GlobalData.PortRundown);
+                    return STATUS_ACCESS_VIOLATION;
+                }
+            }
+
+            LARGE_INTEGER timeout;
+            if (KeGetCurrentIrql() == PASSIVE_LEVEL) {
+                timeout.QuadPart = -(5 * 10000);
+            }
+            else {
+                timeout.QuadPart = 0;
+            }
+
+            status = FltSendMessage(GlobalData.FilterHandle, &GlobalData.ClientPort, msg, sizeof(PYAS_MESSAGE), NULL, NULL, &timeout);
+
+            PyasFree(msg);
+        }
+        else {
+            status = STATUS_INSUFFICIENT_RESOURCES;
+        }
     }
 
     ExReleaseRundownProtection(&GlobalData.PortRundown);

Plugins/Filter/Resource.rc

@@ -9,11 +9,11 @@
 #define VER_ORIGINALFILENAME_STR    "PYAS_Driver.sys"
 #define VER_PRODUCTNAME_STR         "PYAS"
 
-#define VER_FILEVERSION             3,5.0,0
-#define VER_FILEVERSION_STR         "3,5.0,0"
+#define VER_FILEVERSION             3,5,1,0
+#define VER_FILEVERSION_STR         "3,5,1,0"
 
-#define VER_PRODUCTVERSION          3,5.0,0
-#define VER_PRODUCTVERSION_STR      "3,5.0,0"
+#define VER_PRODUCTVERSION          3,5,1,0
+#define VER_PRODUCTVERSION_STR      "3,5,1,0"
 
 #define VER_COMPANYNAME_STR         "PYAS Security"
 

Plugins/Rules/Rules_Driver_P1.json

@@ -2,7 +2,6 @@
   "Rule_Registry_BlockList": [
     "\\REGISTRY\\MACHINE\\BCD00000000",
     "\\REGISTRY\\MACHINE\\BCD00000000\\*",
-    "*\\Image File Execution Options\\*",
     
     "*\\Classes\\.exe",
     "*\\Classes\\.bat",
@@ -47,7 +46,6 @@
     "*\\DisableTaskMgr",
     "*\\DisableRegistryTools",
     "*\\DisableChangePassword",
-    "*\\Wallpaper",
     "*\\NoComponents",
     "*\\NoStartMenuMorePrograms",
     "*\\NoActiveDesktop",
@@ -79,12 +77,10 @@
     "*\\FirmwareBootDevice",
     "*\\BootDriverFlags",
     "*\\SystemStartOptions",
-    "*\\CrashDumpEnabled",
     "*\\DisableAutomaticRestartOnFailure",
     "*\\SystemBiosVersion",
     "*\\NoTheme",
     "*\\SystemSetupInProgress",
-    "*\\CmdLine",
     "*\\SetupType",
     "*\\AutoReboot",
     "*\\Userinit",
@@ -107,24 +103,38 @@
     
     "\\Device\\HarddiskVolume*\\ProgramData\\Microsoft\\Windows Defender\\*",
     "\\Device\\HarddiskVolume*\\ProgramData\\Microsoft\\Windows Defender Advanced Threat Protection\\*",
+    "*\\Sources\\SetupHost.exe",
+    "*\\Work\\*\\DismHost.exe",
     
     "*\\Google\\Chrome\\Application\\chrome.exe",
     "*\\Microsoft\\Edge\\Application\\msedge.exe",
     "*\\Mozilla Firefox\\firefox.exe",
+    "*\\Thorium\\Application\\thorium.exe",
     
     "*\\Steam\\steam.exe",
     "*\\steam\\*\\steam.exe",
     "*\\Battle.net\\*\\Battle.net.exe",
     "*\\Epic Games\\Launcher\\Portal\\Binaries\\*\\EpicGamesLauncher.exe",
     
+    "*\\resources\\bin\\SDK\\DownloadSDKServer.exe",
     "*\\ThunderEv.exe",
     "*\\ThunderStart.exe",
-    "*\\resources\\bin\\SDK\\DownloadSDKServer.exe",
     "*\\KuGou.exe",
     "*\\XLGame.exe",
     "*\\XLLiveUD.exe",
+    
+    "*\\hrkill-*.exe",
+    "*\\bin\\HipsDaemon.exe",
+    "*\\360Safe.exe",
+    "*\\bilibili\\bilibili.exe",
+    
+    "*\\Kingsoft\\WPS Office\\ksolaunch.exe",
+    "*\\Kingsoft\\WPS Office\\*\\wps.exe",
+    
     "*\\PC4399_WPFLauncher.exe",
     "*\\bin\\APlayer.exe",
+    "*\\Neverness To Everness\\NTELauncher.exe",
+    "*\\Application\\AndrowsLauncher.exe",
   ],
   "Rule_Process_ExploitableBlacklist": [
     "*\\cmd.exe",
@@ -163,9 +173,9 @@
   ],
   "Rule_File_ProtectedPaths": [
     "*\\PYAS.exe",
-    "*\\PYAS_Driver.sys",
-    "*\\ProgramData\\PYAS\\*.json",
+    "*\\Plugins\\Filter\\PYAS_Driver.sys",
     "*\\Plugins\\Rules\\Rules_Driver_P1.json",
+    "*\\ProgramData\\PYAS\\*.json",
     "*\\Engine\\Pattern\\*.onnx",
     "*\\Engine\\Properties\\*.onnx",
     
@@ -203,6 +213,7 @@
     "*\\ventoy\\Boot\\*",
     "*\\AdminRegionConfig.*",
     "*\\nt_qq\\nt_*\\*",
+    "*\\cache\\*",
   ],
   "Rule_File_RansomwareExtensions": [
     ".zip", ".7z", ".rar", ".tar", ".gz",

README.md

@@ -1,6 +1,6 @@
-# PYAS
+# PYAS Security
 
-Antivirus software written in Python and C++ that blocks threats through deep learning and behavioral monitoring!
+Antivirus software written in Python and C++ that blocks threats through Machine Learning and behavioral monitoring!
 
 <img width="2440" height="1600" alt="PYAS_All" src="https://github.com/user-attachments/assets/1991aad3-64cc-4266-ac67-dab70c891ce7" />
 
@@ -24,10 +24,9 @@ Non-essential requirements installation, only used for model training or other f
 ```
 pip install pandas
 pip install scikit-learn
-pip install tensorflow
-pip install tf2onnx
 pip install lightgbm
 pip install onnxmltools
+pip install orjson
 ```
 
 ## File Information
@@ -36,15 +35,9 @@ The following lists the storage locations of all relevant code and other related
 
 ```
 PYAS/
-├── Embed/                           # Deploy an embedded command line antivirus engine
-│   ├── Dockerfile
-│   └── ...
-│
 ├── Engine/                          # Complete code for Yara signatures and AI model training
 │   ├── Heuristic/
 │   │   └── ...                      # Yara Rules
-│   ├── Pattern/
-│   │   └── ...                      # CNN Model
 │   └── Properties/
 │       └── ...                      # LightGBM Model
 │
@@ -84,7 +77,6 @@ graph TD
         
         subgraph Engines ["Scanning Engines (PYAS_Engine.py)"]
             PEScanner["PE/ML Scanner (pe_scanner)"]:::userMode
-            CNNScanner["CNN Scanner (cnn_scanner)"]:::userMode
             RuleScanner["YARA Scanner (rule_scanner)"]:::userMode
             CloudScanner["Cloud API (cloud_scanner)"]:::userMode
             SignScanner["Signature Verify (sign_scanner)"]:::userMode
@@ -136,6 +128,12 @@ graph TD
     BootProtect -->|IOCTL_DISK_FORMAT_TRACKS...| Disk
 ```
 
+## Machine Learning
+
+The machine learning-based virus scanning engine training achieved extremely high accuracy.
+
+<img width="895" height="1097" alt="train" src="https://github.com/user-attachments/assets/fa7cf0e2-01a1-4234-9358-718c2b8a2c9a" />
+
 ## Support System
 
 Please ensure your computer supports Microsoft Visual C++ 2015-2022 Redistributable and Edge Webview2.