import os, re, sys, math, json, zlib, pefile, datetime import ctypes, ctypes.wintypes import numpy as np import onnxruntime as ort #################################################################################################### MODEL_FILE = "Pefile_General_T1.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 #################################################################################################### def _entropy_from_counts(counts, size): if size <= 0: return 0.0 nonzero = counts[counts > 0] return float(np.log2(size) - np.sum(nonzero * np.log2(nonzero)) / size) def _bounded_entropy(data, batch_size=1048576): size = len(data) if size == 0: return 0.0 counts = np.zeros(256, dtype=np.int64) view = memoryview(data) try: for start in range(0, size, batch_size): chunk = np.frombuffer( view[start:min(start + batch_size, size)], dtype=np.uint8 ) counts += np.bincount(chunk, minlength=256) finally: view.release() return _entropy_from_counts(counts, size) def _accumulate_string_chunk(chunk, array, state, pattern): separators = (array < 0x20) | (array > 0x7E) if not separators.any(): state["pending_counts"] += np.bincount(array, minlength=256) state["pending_length"] += len(array) return first_separator = int(np.argmax(separators)) last_separator = len(separators) - 1 - int(np.argmax(separators[::-1])) if first_separator: state["pending_counts"] += np.bincount( array[:first_separator], minlength=256 ) state["pending_length"] += first_separator if state["pending_length"] >= 5: state["count"] += 1 state["total_length"] += state["pending_length"] state["counts"] += state["pending_counts"] state["pending_length"] = 0 state["pending_counts"].fill(0) middle_start = first_separator + 1 middle_end = last_separator if middle_end > middle_start: matches = pattern.findall(chunk[middle_start:middle_end]) if matches: combined = b"".join(matches) state["count"] += len(matches) state["total_length"] += len(combined) state["counts"] += np.bincount( np.frombuffer(combined, dtype=np.uint8), minlength=256 ) trailing_start = last_separator + 1 if trailing_start < len(array): trailing = array[trailing_start:] state["pending_counts"] += np.bincount(trailing, minlength=256) state["pending_length"] = len(trailing) def _accumulate_entropy_windows(data, entropy_histogram, c_log_c_table): block_count = len(data) // 1024 if block_count < 2: return data complete_size = block_count * 1024 blocks = np.frombuffer( data, dtype=np.uint8, count=complete_size ).reshape(block_count, 1024) encoded = blocks.astype(np.int32) encoded += np.arange(block_count, dtype=np.int32)[:, None] * 256 block_counts = np.bincount( encoded.ravel(), minlength=block_count * 256 ).reshape(block_count, 256) window_counts = block_counts[:-1] + block_counts[1:] sum_c_log_c = np.sum(c_log_c_table[window_counts], axis=1) entropies = 11.0 - sum_c_log_c / 2048.0 entropy_bins = (entropies * 2.0).astype(np.int32) np.clip(entropy_bins, 0, 15, out=entropy_bins) byte_bins = window_counts.reshape(block_count - 1, 16, 16).sum(axis=2) flat_indices = (entropy_bins[:, None] * 16 + np.arange(16)).ravel() np.add.at(entropy_histogram, flat_indices, byte_bins.ravel()) return data[(block_count - 1) * 1024:] def _collect_resource_ranges(pe, file_size): ranges = [] if not hasattr(pe, "DIRECTORY_ENTRY_RESOURCE"): return ranges for entry_type in pe.DIRECTORY_ENTRY_RESOURCE.entries: for entry_id in getattr( getattr(entry_type, "directory", None), "entries", [] ): for entry_lang in getattr( getattr(entry_id, "directory", None), "entries", [] ): if not hasattr(entry_lang, "data"): continue try: struct = entry_lang.data.struct offset = int(pe.get_offset_from_rva(int(struct.OffsetToData))) size = int(struct.Size) start = max(0, offset) end = min(file_size, start + max(0, size)) ranges.append((start, max(start, end))) except Exception: ranges.append((0, 0)) return ranges def _extract_stream_features(file_path, file_size, ranges, extractor): normalized = [] for start, end in ranges: start = max(0, min(file_size, int(start))) end = max(start, min(file_size, int(end))) normalized.append((start, end)) byte_counts = np.zeros(256, dtype=np.int64) range_counts = [np.zeros(256, dtype=np.int64) for _ in normalized] entropy_histogram = np.zeros(256, dtype=np.float64) string_state = { "count": 0, "total_length": 0, "counts": np.zeros(256, dtype=np.int64), "pending_length": 0, "pending_counts": np.zeros(256, dtype=np.int64), } histogram_tail = b"" position = 0 with open(file_path, "rb") as source: while True: chunk = source.read(4194304) if not chunk: break array = np.frombuffer(chunk, dtype=np.uint8) _accumulate_string_chunk( chunk, array, string_state, extractor._STRING_PATTERN ) histogram_tail = _accumulate_entropy_windows( histogram_tail + chunk, entropy_histogram, extractor._C_LOG_C_TABLE, ) chunk_end = position + len(chunk) boundaries = {0, len(chunk)} for start, end in normalized: if position < start < chunk_end: boundaries.add(start - position) if position < end < chunk_end: boundaries.add(end - position) ordered = sorted(boundaries) for index in range(len(ordered) - 1): local_start = ordered[index] local_end = ordered[index + 1] if local_end <= local_start: continue counts = np.bincount( array[local_start:local_end], minlength=256 ) byte_counts += counts absolute_start = position + local_start absolute_end = position + local_end for range_index, (start, end) in enumerate(normalized): if start <= absolute_start and absolute_end <= end: range_counts[range_index] += counts position = chunk_end if string_state["pending_length"] >= 5: string_state["count"] += 1 string_state["total_length"] += string_state["pending_length"] string_state["counts"] += string_state["pending_counts"] string_count = string_state["count"] total_string_length = string_state["total_length"] result = { "StringCount": float(string_count), "StringMeanLength": ( float(total_string_length) / string_count if string_count else 0.0 ), "StringEntropy": _entropy_from_counts( string_state["counts"], total_string_length ), } result.update(dict.fromkeys(extractor._STRING_KEYS, 0.0)) if total_string_length: valid_counts = string_state["counts"][0x20:0x7F] result.update(dict(zip( extractor._STRING_KEYS, valid_counts.astype(np.float64) / total_string_length, ))) result["FileEntropy"] = _entropy_from_counts(byte_counts, file_size) result.update(dict(zip( extractor._BYTE_HIST_KEYS, byte_counts.astype(np.float64) / file_size, ))) entropy_sum = np.sum(entropy_histogram) if entropy_sum: entropy_histogram /= entropy_sum result.update(dict(zip(extractor._BYTE_ENT_KEYS, entropy_histogram))) range_entropies = [ _entropy_from_counts(counts, end - start) for counts, (start, end) in zip(range_counts, normalized) ] return result, range_entropies class FeatureExtractor: _STRING_PATTERN = re.compile(b'[\x20-\x7E]{5,}') _STRING_FAST_PATH_BYTES = 4194304 _STRING_BATCH_BYTES = 4194304 _HISTOGRAM_BATCH_WINDOWS = 1024 _BYTE_HIST_KEYS = [f'ByteHist_{i:02X}' for i in range(256)] _BYTE_ENT_KEYS = [f'ByteEnt_{i:02X}' for i in range(256)] _STRING_KEYS = [f'StringHist_{i:02d}' for i in range(95)] _SECTION_HASH_KEYS = [f'SectionHash_{i:02d}' for i in range(50)] _CHAR_FLAGS = [0x00000020, 0x00000040, 0x00000080, 0x02000000, 0x20000000, 0x40000000, 0x80000000] _CHAR_COUNT_KEYS = {flag: f'Char_{flag:08X}_Count' for flag in _CHAR_FLAGS} _CHAR_ENT_KEYS = {flag: f'Char_{flag:08X}_MeanEntropy' for flag in _CHAR_FLAGS} _C_LOG_C_TABLE = np.zeros(2049, dtype=np.float64) _C_LOG_C_TABLE[1:] = np.arange(1, 2049) * np.log2(np.arange(1, 2049)) _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' ] _SECTION_DEFAULTS = { 'SectionCount': 0.0, 'SectionMaxEntropy': 0.0, 'SectionMinEntropy': 0.0, 'SectionMeanEntropy': 0.0, 'SectionMaxRawSize': 0.0, 'SectionMinRawSize': 0.0, 'SectionMeanRawSize': 0.0, 'SectionMaxVSize': 0.0, 'SectionMinVSize': 0.0, 'SectionMeanVSize': 0.0, 'ExecutableSections': 0.0, 'WritableSections': 0.0, 'ReadableSections': 0.0, 'SectionException': 0.0 } _CONDITIONAL_DEFAULTS = { 'IsDriver': 0.0, 'HasTlsCallbacks': 0.0, 'IsDebug': 0.0, 'IsPreRelease': 0.0, 'IsPatched': 0.0, 'IsPrivateBuild': 0.0, 'IsSpecialBuild': 0.0, 'ImportCount': 0.0, 'ImportFunctionCount': 0.0, 'ExportCount': 0.0, 'IconCount': 0.0, 'DebugCount': 0.0 } @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 @classmethod def _base_defaults(cls): base = dict.fromkeys(cls._OPTIONAL_HEADER_FIELDS, 0.0) base.update(cls._SECTION_DEFAULTS) base.update(cls._CONDITIONAL_DEFAULTS) for i in range(16): base[f'DataDirectory_{i}_Size'] = 0.0 base[f'DataDirectory_{i}_VA'] = 0.0 return base @staticmethod def _calc_entropy(data): return _bounded_entropy(data) @classmethod def _extract_strings(cls, file_bytes): res = {"StringCount": 0.0, "StringMeanLength": 0.0, "StringEntropy": 0.0} res.update(dict.fromkeys(cls._STRING_KEYS, 0.0)) if len(file_bytes) <= cls._STRING_FAST_PATH_BYTES: matches = cls._STRING_PATTERN.findall(file_bytes) if not matches: return res combined_data = b''.join(matches) count = len(matches) total_len = len(combined_data) global_counts = np.bincount(np.frombuffer(combined_data, dtype=np.uint8), minlength=256) else: count = 0 total_len = 0 global_counts = np.zeros(256, dtype=np.int64) mv = memoryview(file_bytes) pos = 0 size = len(file_bytes) while pos < size: chunk_end = min(pos + cls._STRING_BATCH_BYTES, size) chunk_arr = np.frombuffer(mv[pos:chunk_end], dtype=np.uint8) separators = (chunk_arr < 0x20) | (chunk_arr > 0x7E) if separators.any(): last_separator = len(separators) - 1 - int(np.argmax(separators[::-1])) segment_end = pos + last_separator + 1 matches = cls._STRING_PATTERN.findall(mv[pos:segment_end]) if matches: combined_data = b''.join(matches) count += len(matches) total_len += len(combined_data) global_counts += np.bincount(np.frombuffer(combined_data, dtype=np.uint8), minlength=256) pos = segment_end continue pending_len = 0 pending_counts = np.zeros(256, dtype=np.int64) while pos < size: chunk_end = min(pos + cls._STRING_BATCH_BYTES, size) chunk_arr = np.frombuffer(mv[pos:chunk_end], dtype=np.uint8) separators = (chunk_arr < 0x20) | (chunk_arr > 0x7E) if separators.any(): first_separator = int(np.argmax(separators)) if first_separator: pending_counts += np.bincount(chunk_arr[:first_separator], minlength=256) pending_len += first_separator pos += first_separator + 1 break pending_counts += np.bincount(chunk_arr, minlength=256) pending_len += len(chunk_arr) pos = chunk_end if pending_len >= 5: count += 1 total_len += pending_len global_counts += pending_counts if count == 0 or total_len == 0: return res res["StringCount"] = float(count) res["StringMeanLength"] = float(total_len) / count counts_nonzero = global_counts[global_counts > 0] if len(counts_nonzero) > 0: res["StringEntropy"] = float(np.log2(total_len) - np.sum(counts_nonzero * np.log2(counts_nonzero)) / total_len) valid_chars = global_counts[0x20:0x7F] res.update(dict(zip(cls._STRING_KEYS, valid_chars.astype(np.float64) / total_len))) return res @classmethod def _extract_histograms(cls, file_bytes): arr = np.frombuffer(file_bytes, dtype=np.uint8) sz = len(arr) res = {} if sz == 0: res['FileEntropy'] = 0.0 res.update(dict.fromkeys(cls._BYTE_HIST_KEYS, 0.0)) res.update(dict.fromkeys(cls._BYTE_ENT_KEYS, 0.0)) return res byte_counts = np.zeros(256, dtype=np.int64) ent_hist = np.zeros(256, dtype=np.float64) window = 2048 step = 1024 if sz < window: byte_counts += np.bincount(arr, minlength=256) p = byte_counts[byte_counts > 0] / float(sz) entropy = float(-np.sum(p * np.log2(p))) ent_bin = min(int(entropy * 2.0), 15) byte_bins = byte_counts.reshape(16, 16).sum(axis=1) idx_start = ent_bin * 16 ent_hist[idx_start : idx_start+16] += byte_bins else: num_windows = (sz - window) // step + 1 for w_start in range(0, num_windows, cls._HISTOGRAM_BATCH_WINDOWS): w_end = min(w_start + cls._HISTOGRAM_BATCH_WINDOWS, num_windows) b_num = w_end - w_start start_byte = w_start * step end_byte = start_byte + b_num * step + step encoded = arr[start_byte:end_byte].astype(np.int32).reshape(b_num + 1, step) encoded += np.arange(b_num + 1, dtype=np.int32)[:, None] * 256 chunk_counts = np.bincount(encoded.ravel(), minlength=(b_num + 1) * 256).reshape(b_num + 1, 256) del encoded byte_counts += np.sum(chunk_counts[:-1], axis=0) if w_end == num_windows: byte_counts += chunk_counts[-1] window_counts = chunk_counts[:-1] + chunk_counts[1:] sum_c_log_c = np.sum(cls._C_LOG_C_TABLE[window_counts], axis=1) entropies = 11.0 - sum_c_log_c / 2048.0 ent_bins = (entropies * 2.0).astype(np.int32) np.clip(ent_bins, 0, 15, out=ent_bins) byte_bins = window_counts.reshape(b_num, 16, 16).sum(axis=2) flat_ent_bins = (ent_bins[:, None] * 16 + np.arange(16)).ravel() np.add.at(ent_hist, flat_ent_bins, byte_bins.ravel()) covered_size = (num_windows + 1) * step if covered_size < sz: byte_counts += np.bincount(arr[covered_size:], minlength=256) counts_nonzero = byte_counts[byte_counts > 0] res['FileEntropy'] = float(np.log2(sz) - np.sum(counts_nonzero * np.log2(counts_nonzero)) / sz) byte_hist = byte_counts.astype(np.float64) / sz res.update(dict(zip(cls._BYTE_HIST_KEYS, byte_hist))) ent_sum = np.sum(ent_hist) if ent_sum > 0: ent_hist /= ent_sum res.update(dict(zip(cls._BYTE_ENT_KEYS, ent_hist))) 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, range_entropies=None): 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 = [] entropy_iter = iter(range_entropies or ()) 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: entropies.append(float(next(entropy_iter))) except (StopIteration, TypeError, ValueError): entropies.append(0.0) 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_path, fsize): res = {"HasSignature": 0.0, "SignatureCount": 0.0} if not hasattr(pe, 'OPTIONAL_HEADER') or not hasattr(pe.OPTIONAL_HEADER, 'DATA_DIRECTORY'): return res directories = pe.OPTIONAL_HEADER.DATA_DIRECTORY if len(directories) <= 4: return res sec_dir = directories[4] offset = int(sec_dir.VirtualAddress) size = int(sec_dir.Size) if offset <= 0 or size <= 0 or offset + size > fsize: return res res["HasSignature"] = 1.0 count = 0 curr = offset end = offset + size with open(file_path, "rb") as source: while curr + 8 <= end: source.seek(curr) header = source.read(4) if len(header) != 4: break length = int.from_bytes(header, 'little') if length < 8 or curr + length > end: break count += 1 curr += (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 base, dlls, apis = cls._base_defaults(), set(), set() pe = pefile.PE(name=file_path, 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 sections = list(getattr(pe, 'sections', [])) section_ranges = [] for section in sections: start = max(0, int(section.get_PointerToRawData_adj())) end = min(fsize, start + max(0, int(section.SizeOfRawData))) section_ranges.append((start, max(start, end))) resource_ranges = _collect_resource_ranges(pe, fsize) overlay_offset = pe.get_overlay_data_start_offset() if not overlay_offset or overlay_offset >= fsize: overlay_offset = fsize all_ranges = section_ranges + resource_ranges + [ (int(overlay_offset), fsize) ] stream_features, range_entropies = _extract_stream_features( file_path, fsize, all_ranges, cls ) section_entropies = range_entropies[:len(section_ranges)] resource_start = len(section_ranges) resource_entropies = range_entropies[ resource_start:resource_start + len(resource_ranges) ] overlay_entropy = range_entropies[-1] base['TrustSigned'] = float(WinTrust.verify(file_path)) 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 field_name in fields: base[field_name] = getattr(op, field_name, 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 res_flags_count = dict.fromkeys(cls._CHAR_COUNT_KEYS.values(), 0.0) res_flags_ent = dict.fromkeys(cls._CHAR_ENT_KEYS.values(), 0.0) res_sec_hash = dict.fromkeys(cls._SECTION_HASH_KEYS, 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_index, section in enumerate(pe.sections): sec_name = section.Name.rstrip(b'\x00') hash_val = zlib.crc32(sec_name) % 50 res_sec_hash[cls._SECTION_HASH_KEYS[hash_val]] += 1.0 s_entropy = ( section_entropies[section_index] if section_index < len(section_entropies) else 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 cls._CHAR_FLAGS: if section.Characteristics & flag: res_flags_count[cls._CHAR_COUNT_KEYS[flag]] += 1.0 res_flags_ent[cls._CHAR_ENT_KEYS[flag]] += 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'] = float(exec_sec) base['WritableSections'] = float(write_sec) base['ReadableSections'] = float(read_sec) base['SectionException'] = float(sec_exc) for flag in cls._CHAR_FLAGS: cnt_key = cls._CHAR_COUNT_KEYS[flag] if res_flags_count[cnt_key] > 0: res_flags_ent[cls._CHAR_ENT_KEYS[flag]] /= res_flags_count[cnt_key] base.update(res_flags_count) base.update(res_flags_ent) base.update(res_sec_hash) 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'] = float(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'] = float(func_count) base['ExportCount'] = float(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'] = float(icon_count) else: base['IconCount'] = 0.0 base['DebugCount'] = float(len(pe.DIRECTORY_ENTRY_DEBUG)) if hasattr(pe, 'DIRECTORY_ENTRY_DEBUG') else 0.0 base.update(stream_features) overlay_size = fsize - int(overlay_offset) base.update({ "HasOverlay": 1.0 if overlay_size else 0.0, "OverlaySize": float(overlay_size), "OverlayRatio": float(overlay_size) / float(fsize) if overlay_size else 0.0, "OverlayEntropy": overlay_entropy if overlay_size else 0.0 }) base.update(cls._extract_rich_header(pe)) base.update(cls._extract_ep_anomalies(pe)) base.update(cls._extract_advanced_resources(pe, resource_entropies)) base.update(cls._extract_load_config(pe)) base.update(cls._extract_security_directory(pe, file_path, fsize)) for k in base: base[k] = cls._safe_float(base[k]) return {"Base": base, "DLLs": list(dlls), "APIs": list(apis)} except pefile.PEFormatError: return None finally: if pe is not None: try: pe.close() except Exception: pass #################################################################################################### 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 error: Model expects {expected_dim}, but feature file has {current_dim}") self.feat_map = {feat: i for i, feat in enumerate(self.model_features)} self.dll_hash_dim = 512 self.api_hash_dim = 4096 self.dll_hash_pad = 3 self.api_hash_pad = 4 self._parse_hash_dims() 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 _parse_hash_dims(self): max_dll = -1 max_api = -1 for feat in self.model_features: if feat.startswith("DllHash_"): try: val_str = feat.split("_")[1] max_dll = max(max_dll, int(val_str)) self.dll_hash_pad = len(val_str) except Exception: pass elif feat.startswith("ApiHash_"): try: val_str = feat.split("_")[1] max_api = max(max_api, int(val_str)) self.api_hash_pad = len(val_str) except Exception: pass if max_dll >= 0: self.dll_hash_dim = max_dll + 1 if max_api >= 0: self.api_hash_dim = max_api + 1 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')) % self.dll_hash_dim feat_name = f"DllHash_{h:0{self.dll_hash_pad}d}" 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')) % self.api_hash_dim feat_name = f"ApiHash_{h:0{self.api_hash_pad}d}" 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 log_buffer = [] def _log(message): print(message) log_buffer.append(message) _log(f"[*] Scanning {len(files)} files...\n") _log(f"{'RESULT':<10} | {'PROB':<8} | {'FILE'}") _log("-" * 80) safe_count = 0 mal_count = 0 unsupport_count = 0 error_count = 0 try: for fpath in files: try: data = FeatureExtractor.extract(fpath) if not data: _log(f"{'UNSUPPORT':<10} | {'-':<8} | {fpath}") unsupport_count += 1 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 _log(f"{label:<10} | {prob:.4f} | {fpath}") except Exception as e: _log(f"{'FAIL':<10} | {'-':<8} | {fpath} ({str(e)})") error_count += 1 except KeyboardInterrupt: _log("\n[-] Scan aborted by user (Ctrl+C).\n") _log("-" * 80) _log(f"\n[*] Summary: Safe={safe_count}, Malware={mal_count}, Unsupport={unsupport_count}, Error={error_count}, Total={len(files)}") log_filename = datetime.datetime.now().strftime("%Y%m%d_%H%M%S.log") try: with open(log_filename, "w", encoding="utf-8") as f: f.write("\n".join(log_buffer) + "\n") print(f"[*] Log saved successfully: {log_filename}") except Exception as e: print(f"[-] Failed to save log: {e}") #################################################################################################### if __name__ == "__main__": base_dir = os.path.dirname(sys.executable) if getattr(sys, 'frozen', False) else os.path.dirname(os.path.abspath(__file__)) custom_model = MODEL_FILE targets = [] args = sys.argv[1:] i = 0 while i < len(args): if args[i] in ("-m", "-model", "--model") and i + 1 < len(args): custom_model = args[i+1] i += 2 else: targets.append(args[i]) i += 1 print("\n-------------------------- PE Malware Predictor v4.0 --------------------------\n") print(f"[*] © 2020-2026 87owo (PYAS Security)") print(f"[*] Official Website: https://github.com/87owo/PYAS") print(f"[*] Loading model: {custom_model}") model_path = os.path.join(base_dir, custom_model) if not os.path.isabs(custom_model) else custom_model 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 targets: for path in targets: 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}")