finish all table analyze

This commit is contained in:
Burgess Leo
2025-05-20 16:26:58 +08:00
parent 846c7f6beb
commit 08a47c6d8a
7 changed files with 560 additions and 177 deletions

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@@ -23,7 +23,12 @@ def ClearTableRecordsWithReset(db_path, table_name):
if __name__ == '__main__': if __name__ == '__main__':
# ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_path') ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_path')
# ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_device')
# ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_config')
ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_node') ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_node')
ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_device')
ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_config')
ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_user')
ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_group')
# ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_extend_extent')
ClearTableRecordsWithReset(db_path='../src/db_ntfs_info.db', table_name='db_extend_name')

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@@ -4,6 +4,7 @@ from db_extend_name import InsertExtensionsToDB
from db_group import InsertGroupToDB from db_group import InsertGroupToDB
from db_path import GenerateHash, ShouldSkipPath, ScanVolume, InsertPathDataToDB from db_path import GenerateHash, ShouldSkipPath, ScanVolume, InsertPathDataToDB
from db_user import InsertUserToDB from db_user import InsertUserToDB
from db_node import InsertNodeDataToDB
def main(): def main():
@@ -40,6 +41,8 @@ def main():
count = InsertExtensionsToDB(common_extensions) count = InsertExtensionsToDB(common_extensions)
print(f"共插入 {count} 个新扩展名。") print(f"共插入 {count} 个新扩展名。")
InsertNodeDataToDB()
if __name__ == '__main__': if __name__ == '__main__':
main() main()

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@@ -1,10 +1,10 @@
import hashlib import hashlib
import os import os
import random
import sqlite3 import sqlite3
from datetime import datetime from datetime import datetime
from mft_analyze import GetFile80hPattern # 导入你的模块函数
from mft_analyze import GetFile80hPattern, GetFragmentData, ExtractSequenceHexValues, hex_list_to_int
# 工具函数:获取文件扩展名 # 工具函数:获取文件扩展名
@@ -52,7 +52,6 @@ def GetFilesTime(file_path):
st_atime: 最后一次访问时间FileAccessTime st_atime: 最后一次访问时间FileAccessTime
st_mtime: 最后一次修改内容的时间FileModifyTime st_mtime: 最后一次修改内容的时间FileModifyTime
st_ctime: 文件元数据metadata更改时间在 Windows 中是文件创建时间FileCreateTime st_ctime: 文件元数据metadata更改时间在 Windows 中是文件创建时间FileCreateTime
注意Windows 和 Linux 在这些字段的定义上略有不同,比如 Linux 中 st_ctime 是元数据变更时间,而不是创建时间。
参数: 参数:
file_path (str): 文件的绝对路径 file_path (str): 文件的绝对路径
@@ -71,7 +70,6 @@ def GetFilesTime(file_path):
try: try:
stat_info = os.stat(file_path) stat_info = os.stat(file_path)
# 将时间戳转换为可读格式字符串 ISO 8601 格式
def ts_to_str(timestamp): def ts_to_str(timestamp):
return datetime.fromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S') return datetime.fromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S')
@@ -79,7 +77,7 @@ def GetFilesTime(file_path):
modify_time = ts_to_str(stat_info.st_mtime) modify_time = ts_to_str(stat_info.st_mtime)
access_time = ts_to_str(stat_info.st_atime) access_time = ts_to_str(stat_info.st_atime)
# 权限变更时间,Linux 上是 metadata 修改时间,Windows 可能不适用 # 权限变更时间Windows 可能不适用
try: try:
auth_time = ts_to_str(getattr(stat_info, 'st_birthtime', stat_info.st_ctime)) auth_time = ts_to_str(getattr(stat_info, 'st_birthtime', stat_info.st_ctime))
except Exception: except Exception:
@@ -110,8 +108,13 @@ def GetDeviceId(cursor: sqlite3.Cursor) -> int:
# 获取文件大小(伪数据) # 获取文件大小(伪数据)
def GetFileSize(full_path: str) -> int: def GetFileSize(file80h_pattern):
return random.randint(100, 999) if file80h_pattern[0].get('is_resident'):
return GetFragmentData(file80h_pattern)[0].get('byte_length')
else:
size_list = ExtractSequenceHexValues(file80h_pattern)[56:64]
size = hex_list_to_int(size_list)
return size
# 获取文件内容哈希(伪数据) # 获取文件内容哈希(伪数据)
@@ -119,85 +122,16 @@ def GetFileHash(full_path: str) -> str:
return hashlib.sha256(full_path.encode()).hexdigest() return hashlib.sha256(full_path.encode()).hexdigest()
# 获取分片数1~4 # 新增:获取文件片段位置和长度
def GetExtentCount(data): def GetFragmentLocation(fragment):
""" return fragment.get('starting_byte', 0)
分析 NTFS 数据结构中的80属性($DATA),返回文件分片数量
参数:
data (list): 包含字典的列表,每个字典需有'sequence'
(示例结构见问题描述)
返回:
int: 分片数量(常驻属性返回1非常驻属性返回数据运行的分片数)
异常:
ValueError: 当输入数据无效时抛出
"""
# 第一步提取并转换sequence数据
hex_bytes = []
for entry in data:
if 'sequence' in entry:
for hex_str in entry['sequence']:
hex_bytes.extend(hex_str.split())
# 将十六进制字符串转换为整数列表
try:
attribute_data = [int(x, 16) for x in hex_bytes]
except ValueError:
raise ValueError("无效的十六进制数据")
# 第二步:分析属性结构
if len(attribute_data) < 24:
raise ValueError("属性数据过短,无法解析头部信息")
# 检查属性类型(0x80)
if attribute_data[0] != 0x80:
raise ValueError("不是80属性($DATA属性)")
# 检查是否常驻(偏移0x08)
is_resident = attribute_data[8] == 0
if is_resident:
return 1
else:
# 解析非常驻属性的数据运行列表
data_run_offset = attribute_data[0x20] | (attribute_data[0x21] << 8)
if data_run_offset >= len(attribute_data):
raise ValueError("数据运行偏移超出属性长度")
data_runs = attribute_data[data_run_offset:]
fragment_count = 0
pos = 0
while pos < len(data_runs):
header_byte = data_runs[pos]
if header_byte == 0x00:
break
len_len = (header_byte >> 4) & 0x0F
offset_len = header_byte & 0x0F
if len_len == 0 or offset_len == 0:
break
pos += 1 + len_len + offset_len
fragment_count += 1
return fragment_count
# 获取随机位置 def GetFragmentLength(fragment):
def GetRandomLocation() -> int: return fragment.get('byte_length', 0)
return random.randint(1000, 9999)
# 获取随机长度
def GetRandomLength() -> int:
return random.randint(1000, 9999)
# 主函数:将 db_path 数据导入 db_node
# 主函数:将 db_path 数据导入 db_node # 主函数:将 db_path 数据导入 db_node
def InsertNodeDataToDB(db_path='../src/db_ntfs_info.db', table_name='db_node'): def InsertNodeDataToDB(db_path='../src/db_ntfs_info.db', table_name='db_node'):
conn = sqlite3.connect(db_path) conn = sqlite3.connect(db_path)
@@ -220,11 +154,30 @@ def InsertNodeDataToDB(db_path='../src/db_ntfs_info.db', table_name='db_node'):
print(f"⚠️ PathID {path_id} 已存在,跳过插入") print(f"⚠️ PathID {path_id} 已存在,跳过插入")
continue continue
# 获取文件的80h属性数据
try:
file80h_pattern = GetFile80hPattern(full_path)
fragments = GetFragmentData(file80h_pattern)
extent_count = min(len(fragments), 4) # 最多支持4个fragment
print(f"✅ 分片数量为: {extent_count}")
except Exception as e:
print(f"⚠️ 获取 ExtentCount 失败,使用默认值 0: {e}")
fragments = []
extent_count = 0
# 计算字段 # 计算字段
name_hash = hashlib.sha256(name.encode()).hexdigest() name_hash = hashlib.sha256(name.encode()).hexdigest()
dir_layer = GetDirLayer(full_path) dir_layer = GetDirLayer(full_path)
extend_name_id = GetExtendNameId(name, cursor) extend_name_id = GetExtendNameId(name, cursor)
file_size = GetFileSize(full_path)
# ✅ 现在可以安全调用 GetFileSize(file80h_pattern)
try:
file_size = GetFileSize(file80h_pattern)
except Exception as e:
print(f"⚠️ 获取文件大小失败,使用默认值 0: {e}")
file_size = 0
file_hash = GetFileHash(full_path) file_hash = GetFileHash(full_path)
# 获取文件的时间属性 # 获取文件的时间属性
@@ -234,20 +187,10 @@ def InsertNodeDataToDB(db_path='../src/db_ntfs_info.db', table_name='db_node'):
access_time = file_times["FileAccessTime"] access_time = file_times["FileAccessTime"]
auth_time = file_times["FileAuthTime"] auth_time = file_times["FileAuthTime"]
# 新增:根据 $80 属性获取更精确的 ExtentCount # 查询 PathHash
try: cursor.execute("SELECT PathHash FROM db_path WHERE ID = ?", (path_id,))
attribute_80_data = GetFile80hPattern(full_path) path_hash_result = cursor.fetchone()
path_hash = path_hash_result[0] if path_hash_result else ""
if not attribute_80_data or not isinstance(attribute_80_data, list):
raise ValueError("无效的 80h 属性数据")
extent_count = GetExtentCount(attribute_80_data)
print(f"✅ 分片数量为: {extent_count}")
except Exception as e:
print(f"⚠️ 获取 ExtentCount 失败,使用默认值 0: {e}")
extent_count = 0
# 构建插入语句字段和参数(保持原样) # 构建插入语句字段和参数(保持原样)
fields = [ fields = [
@@ -257,24 +200,19 @@ def InsertNodeDataToDB(db_path='../src/db_ntfs_info.db', table_name='db_node'):
'FileSize', 'FileMode', 'FileHash', 'ExtentCount' 'FileSize', 'FileMode', 'FileHash', 'ExtentCount'
] ]
values = [ values = [
path_id, parent_id, name_hash, '', # PathHash 待填 path_id, parent_id, name_hash, path_hash,
extend_name_id, dir_layer, group_id, user_id, extend_name_id, dir_layer, group_id, user_id,
create_time, modify_time, access_time, auth_time, create_time, modify_time, access_time, auth_time,
file_size, 'default', file_hash, extent_count file_size, 'default', file_hash, extent_count
] ]
# 查询 PathHash与 db_path.PathHash 一致)
cursor.execute("SELECT PathHash FROM db_path WHERE ID = ?", (path_id,))
path_hash_result = cursor.fetchone()
path_hash = path_hash_result[0] if path_hash_result else ""
values[3] = path_hash # 替换 PathHash
# 处理 Extent 片段字段 # 处理 Extent 片段字段
extent_data = [] extent_data = []
for i in range(1, 5): for i in range(4): # 最多4个 extent
if i <= extent_count: if i < len(fragments):
location = GetRandomLocation() frag = fragments[i]
length = GetRandomLength() location = GetFragmentLocation(frag)
length = GetFragmentLength(frag)
extent_data.extend([device_id, location, length]) extent_data.extend([device_id, location, length])
else: else:
extent_data.extend([None, None, None]) extent_data.extend([None, None, None])

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@@ -227,96 +227,197 @@ def GetFile80hPattern(file_path):
# if __name__ == '__main__': # if __name__ == '__main__':
# GetFile80hPattern(r"Z:\demo.jpg") # data = GetFile80hPattern(r"Z:\hello.txt")
# print(data)
def analyze_ntfs_data_attribute(data): def ExtractSequenceHexValues(file80h_pattern):
""" """
分析 NTFS 数据结构中的80属性($DATA),返回文件分片数量 从给定的数据结构中提取所有 sequence 的十六进制字符串,并合并成一个标准列表
参数: 参数:
data (list): 包含字典的列表,每个字典'sequence' data (list): 包含字典的列表,每个字典有 'sequence'
(示例结构见问题描述)
返回: 返回:
int: 分片数量(常驻属性返回1非常驻属性返回数据运行的分片数) list: 包含所有 sequence 值的合并列表
异常:
ValueError: 当输入数据无效时抛出
""" """
# 第一步提取并转换sequence数据 sequence_list = []
hex_bytes = [] for entry in file80h_pattern:
for entry in data:
if 'sequence' in entry: if 'sequence' in entry:
# 将每个十六进制字符串按空格分割,然后合并到结果列表
for hex_str in entry['sequence']: for hex_str in entry['sequence']:
hex_bytes.extend(hex_str.split()) # 分割字符串并添加到结果
sequence_list.extend(hex_str.split())
return sequence_list
# 将十六进制字符串转换为整数列表
try:
attribute_data = [int(x, 16) for x in hex_bytes]
except ValueError:
raise ValueError("无效的十六进制数据")
# 第二步:分析属性结构 def ExportDataRunList(data_run):
if len(attribute_data) < 24: """
raise ValueError("属性数据过短,无法解析头部信息") 将 data_run 中的多个 Data Run 提取为独立的 list 片段。
# 检查属性类型(0x80) 参数:
if attribute_data[0] != 0x80: data_run (list): 十六进制字符串组成的列表,表示 Data Run 内容
raise ValueError("不是80属性($DATA属性)")
# 检查是否常驻(偏移0x08) 返回:
is_resident = attribute_data[8] == 0 list: 每个元素是一个代表单个 Data Run 的 list
"""
result = []
pos = 0
if is_resident: while pos < len(data_run):
return 1 current_byte = data_run[pos]
else:
# 解析非常驻属性的数据运行列表
data_run_offset = attribute_data[0x20] | (attribute_data[0x21] << 8)
if data_run_offset >= len(attribute_data): if current_byte == '00':
raise ValueError("数据运行偏移超出属性长度") # 遇到空运行块,停止解析
break
data_runs = attribute_data[data_run_offset:] try:
fragment_count = 0 header = int(current_byte, 16)
pos = 0 len_bytes = (header >> 4) & 0x0F
offset_bytes = header & 0x0F
while pos < len(data_runs): if len_bytes == 0 or offset_bytes == 0:
header_byte = data_runs[pos] print(f"⚠️ 无效的字段长度,跳过位置 {pos}")
if header_byte == 0x00:
break break
len_len = (header_byte >> 4) & 0x0F # 计算当前 Data Run 总长度
offset_len = header_byte & 0x0F run_length = 1 + offset_bytes + len_bytes
if len_len == 0 or offset_len == 0: # 截取当前 Data Run
break fragment = data_run[pos: pos + run_length]
pos += 1 + len_len + offset_len result.append(fragment)
fragment_count += 1
return fragment_count # 移动指针
pos += run_length
except Exception as e:
print(f"❌ 解析失败,位置 {pos}{e}")
break
return result
input_data = [ def hex_list_to_int(lst, byteorder='little'):
{ """
'start_byte': 3221267456, 将十六进制字符串列表转换为整数(支持小端序)
'offset': 264, """
'sequence': [ if byteorder == 'little':
'80 00 00 00 48 00 00 00', lst = list(reversed(lst))
'01 00 00 00 00 00 01 00', return int(''.join(f"{int(b, 16):02x}" for b in lst), 16)
'00 00 00 00 00 00 00 00',
'79 00 00 00 00 00 00 00',
'40 00 00 00 00 00 00 00', def parse_data_run(data_run, previous_cluster=0, cluster_size=512):
'00 a0 07 00 00 00 00 00', """
'0b 93 07 00 00 00 00 00', 解析 NTFS 单个 Data Run返回起始字节、结束字节、长度字节
'0b 93 07 00 00 00 00 00',
'31 7a 00 ee 0b 00 00 00' 参数:
], data_run (list): Data Run 的十六进制字符串列表
'is_resident': False, previous_cluster (int): 上一个运行块的最后一个簇号(用于相对偏移)
'total_groups': 9, cluster_size (int): 簇大小(默认为 512 字节)
'attribute_length': 72
返回:
dict: 包含起始字节、结束字节、长度等信息
"""
if not data_run or data_run[0] == '00':
return None
header = int(data_run[0], 16)
len_bytes = (header >> 4) & 0x0F
offset_bytes = header & 0x0F
# 提取偏移字段和长度字段
offset_data = data_run[1:1 + offset_bytes]
length_data = data_run[1 + offset_bytes:1 + offset_bytes + len_bytes]
# 小端序转整数
def hex_list_to_int(lst):
return int(''.join(f"{int(b, 16):02x}" for b in reversed(lst)), 16)
offset = hex_list_to_int(offset_data)
run_length = hex_list_to_int(length_data)
# 计算起始簇号
starting_cluster = previous_cluster + offset
ending_cluster = starting_cluster + run_length - 1
# 转换为字节偏移
cluster_per_sector = 8
byte_per_sector = cluster_size
byte_length = starting_cluster * cluster_per_sector * byte_per_sector
starting_byte = run_length * cluster_per_sector * byte_per_sector
ending_byte = starting_byte + byte_length - 1
return {
"starting_byte": starting_byte,
"ending_byte": ending_byte,
"byte_length": byte_length,
"starting_cluster": starting_cluster,
"run_length_clusters": run_length
} }
]
print(analyze_ntfs_data_attribute(input_data)) # 输出分片数量
def ParseMultipleDataRuns(fragments, cluster_size=512):
"""
批量解析多个 Data Run 片段,返回字节偏移信息。
参数:
fragments (list): 多个 Data Run 字符串列表
cluster_size (int): 簇大小(默认为 512
返回:
list: 每个元素是一个包含字节偏移信息的 dict
"""
results = []
previous_starting_cluster = 0
for fragment in fragments:
result = parse_data_run(fragment, previous_starting_cluster, cluster_size)
if result:
results.append(result)
previous_starting_cluster = result["starting_cluster"]
return results
def GetFragmentData(file80h_pattern):
if not file80h_pattern or not isinstance(file80h_pattern, list):
return []
if file80h_pattern[0].get('is_resident'):
start_byte = file80h_pattern[0].get('start_byte')
offset = file80h_pattern[0].get('offset')
content_start = file80h_pattern[0].get('sequence')[2]
content_start_list = content_start.split()
content_len = content_start_list[::-1][4:8]
content_offset = content_start_list[::-1][:4]
content_len_str = ''.join(content_len)
content_len_decimal_value = int(content_len_str, 16)
content_offset_str = ''.join(content_offset)
content_offset_decimal_value = int(content_offset_str, 16)
file_offset = start_byte + offset + content_offset_decimal_value
return [{
'starting_byte': file_offset,
'byte_length': content_len_decimal_value
}]
else:
sequence_list = ExtractSequenceHexValues(file80h_pattern)
data_run_offset = sequence_list[32:34][::-1]
data_run_offset_str = ''.join(data_run_offset)
data_run_offset_decimal_value = int(data_run_offset_str, 16)
data_run_list = sequence_list[data_run_offset_decimal_value:]
fragments = ExportDataRunList(data_run_list)
results = ParseMultipleDataRuns(fragments)
return results
# if __name__ == '__main__':
# arri80_data = GetFile80hPattern(r"Z:\hello.txt")
# data = GetFragmentData(arri80_data)
# print(data)

View File

@@ -0,0 +1,139 @@
def extract_data_run_fragments(data_run):
"""
将 data_run 中的多个 Data Run 提取为独立的 list 片段。
参数:
data_run (list): 十六进制字符串组成的列表,表示 Data Run 内容
返回:
list: 每个元素是一个代表单个 Data Run 的 list
"""
result = []
pos = 0
while pos < len(data_run):
current_byte = data_run[pos]
if current_byte == '00':
# 遇到空运行块,停止解析
break
try:
header = int(current_byte, 16)
len_bytes = (header >> 4) & 0x0F
offset_bytes = header & 0x0F
if len_bytes == 0 or offset_bytes == 0:
print(f"⚠️ 无效的字段长度,跳过位置 {pos}")
break
# 计算当前 Data Run 总长度
run_length = 1 + offset_bytes + len_bytes
# 截取当前 Data Run
fragment = data_run[pos: pos + run_length]
result.append(fragment)
# 移动指针
pos += run_length
except Exception as e:
print(f"❌ 解析失败,位置 {pos}{e}")
break
return result
def hex_list_to_int(lst, byteorder='little'):
"""
将十六进制字符串列表转换为整数(支持小端序)
"""
if byteorder == 'little':
lst = list(reversed(lst))
return int(''.join(f"{int(b, 16):02x}" for b in lst), 16)
def parse_data_run(data_run, previous_cluster=0):
"""
解析 NTFS 单个 Data Run返回起始簇号和结束簇号
参数:
data_run (list): Data Run 的十六进制字符串列表
previous_cluster (int): 上一个运行块的最后一个簇号(用于相对偏移)
返回:
dict: 包含起始簇、结束簇、运行长度等信息
"""
if not data_run or data_run[0] == '00':
return None
header = int(data_run[0], 16)
len_bytes = (header >> 4) & 0x0F
offset_bytes = header & 0x0F
# 提取偏移字段和长度字段(注意顺序是先偏移后长度)
offset_data = data_run[1:1 + offset_bytes]
length_data = data_run[1 + offset_bytes:1 + offset_bytes + len_bytes]
# 解析偏移和长度
offset = hex_list_to_int(offset_data, 'little')
run_length = hex_list_to_int(length_data, 'little')
# 计算起始簇号(如果是第一个就是绝对偏移,否则是相对偏移)
starting_cluster = previous_cluster + offset
ending_cluster = starting_cluster + run_length - 1
return {
"starting_cluster": starting_cluster,
"ending_cluster": ending_cluster,
"run_length": run_length
}
def parse_multiple_data_runs(fragments):
"""
批量解析多个 Data Run 片段,支持相对偏移。
参数:
fragments (list): 多个 Data Run 字符串列表,如:
[
['31', '7a', '00', 'ee', '0b'],
['22', '29', '06', 'bb', '00'],
...
]
返回:
list: 每个元素是一个 dict包含该片段的解析结果
"""
results = []
previous_starting_cluster = 0
for fragment in fragments:
result = parse_data_run(fragment, previous_starting_cluster)
if result:
results.append(result)
previous_starting_cluster = result["starting_cluster"]
return results
data_run = [
'31', '7a', '00', 'ee', '0b',
'22', '29', '06', 'bb', '00',
'32', '7a', '02', 'ee', '00', '00',
'00', 'a0', 'f8', 'ff', 'ff', 'ff', 'ff', 'ff'
]
# Step 1: 提取所有有效片段
fragments = extract_data_run_fragments(data_run)
print("提取到的片段:")
for i, frag in enumerate(fragments):
print(f"片段{i + 1}: {frag}")
# Step 2: 批量解析这些片段
results = parse_multiple_data_runs(fragments)
print("\n解析结果:")
for i, res in enumerate(results):
print(f"片段{i + 1}: {res}")

92
test/get_extent_counts.py Normal file
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def analyze_ntfs_data_attribute(data):
"""
分析 NTFS 数据结构中的80属性($DATA),返回文件分片数量
参数:
data (list): 包含字典的列表,每个字典需有'sequence'
(示例结构见问题描述)
返回:
int: 分片数量(常驻属性返回1非常驻属性返回数据运行的分片数)
异常:
ValueError: 当输入数据无效时抛出
"""
# 第一步提取并转换sequence数据
hex_bytes = []
for entry in data:
if 'sequence' in entry:
for hex_str in entry['sequence']:
hex_bytes.extend(hex_str.split())
print(hex_bytes)
# 将十六进制字符串转换为整数列表
try:
attribute_data = [int(x, 16) for x in hex_bytes]
except ValueError:
raise ValueError("无效的十六进制数据")
# 第二步:分析属性结构
if len(attribute_data) < 24:
raise ValueError("属性数据过短,无法解析头部信息")
# 检查属性类型(0x80)
if attribute_data[0] != 0x80:
raise ValueError("不是80属性($DATA属性)")
# 检查是否常驻(偏移0x08)
is_resident = attribute_data[8] == 0
if is_resident:
return 1
else:
# 解析非常驻属性的数据运行列表
data_run_offset = attribute_data[0x20] | (attribute_data[0x21] << 8)
if data_run_offset >= len(attribute_data):
raise ValueError("数据运行偏移超出属性长度")
data_runs = attribute_data[data_run_offset:]
fragment_count = 0
pos = 0
while pos < len(data_runs):
header_byte = data_runs[pos]
if header_byte == 0x00:
break
len_len = (header_byte >> 4) & 0x0F
offset_len = header_byte & 0x0F
if len_len == 0 or offset_len == 0:
break
pos += 1 + len_len + offset_len
fragment_count += 1
return fragment_count
input_data = [
{
'start_byte': 3221267456,
'offset': 264,
'sequence': [
'80 00 00 00 48 00 00 00',
'01 00 00 00 00 00 01 00',
'00 00 00 00 00 00 00 00',
'79 00 00 00 00 00 00 00',
'40 00 00 00 00 00 00 00',
'00 a0 07 00 00 00 00 00',
'0b 93 07 00 00 00 00 00',
'0b 93 07 00 00 00 00 00',
'31 7a 00 ee 0b 00 00 00'
],
'is_resident': False,
'total_groups': 9,
'attribute_length': 72
}
]
print(analyze_ntfs_data_attribute(input_data)) # 输出分片数量

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def ParseDataRuns(data_bytes: list, cluster_size=512):
"""
解析 NTFS $80 属性中的数据运行Data Run返回每个分片的起始字节数和长度。
参数:
data_bytes (list): 十六进制字符串组成的列表,表示完整的 $80 属性内容。
cluster_size (int): 簇大小(默认为 512 字节)
返回:
dict: 包含每个分片信息的字典,格式如下:
{
"is_resident": False,
"data_runs": {
"片段1": {"起始字节数": 3202351104, "字节长度": 499712 - 1},
"片段2": {...}
}
}
"""
def hex_list_to_int(lst, length, byteorder='little'):
"""从列表中提取指定长度的字节并转换为整数"""
bytes_data = bytes([int(x, 16) for x in lst[:length]])
return int.from_bytes(bytes_data, byteorder=byteorder)
result = {
"is_resident": True,
"data_runs": {}
}
# 检查是否是 $80 属性
if data_bytes[0] != '80':
raise ValueError("不是 $80 属性")
# 常驻标志在偏移 0x08第 8 个字节)
is_resident = data_bytes[8] == '00'
result["is_resident"] = is_resident
if is_resident:
result["data_runs"]["常驻文件"] = {
"起始字节数": 0,
"字节长度": "该文件为常驻,无分片"
}
return result
# 非常驻属性:获取数据运行偏移(偏移 0x20 处的 DWORD
data_run_offset = hex_list_to_int(data_bytes[0x20:0x20 + 4], 4)
if data_run_offset >= len(data_bytes):
raise ValueError("数据运行偏移超出范围")
# 提取数据运行部分
data_run_bytes = data_bytes[data_run_offset:]
pos = 0
fragment_index = 1
while pos < len(data_run_bytes):
header_byte = int(data_run_bytes[pos], 16)
if header_byte == 0x00:
break
# 高4位长度字段数量低4位偏移字段数量
len_len = (header_byte >> 4) & 0x0F
offset_len = header_byte & 0x0F
if len_len == 0 or offset_len == 0:
break
pos += 1
# 提取偏移量(小端序)
offset_bytes = data_run_bytes[pos:pos + offset_len]
offset = hex_list_to_int(offset_bytes, offset_len, byteorder='little')
# 提取长度(小端序)
length_bytes = data_run_bytes[pos + offset_len:pos + offset_len + len_len]
length = hex_list_to_int(length_bytes, len_len, byteorder='little')
# 计算起始字节数 = offset * cluster_size
start_byte = offset * cluster_size
byte_length = length * cluster_size - 1
result["data_runs"][f"片段{fragment_index}"] = {
"起始字节数": start_byte,
"字节长度": byte_length
}
pos += offset_len + len_len
fragment_index += 1
return result
input_data = [
'80', '00', '00', '00', '48', '00', '00', '00',
'01', '00', '00', '00', '00', '00', '01', '00',
'00', '00', '00', '00', '00', '00', '00', '00',
'79', '00', '00', '00', '00', '00', '00', '00',
'40', '00', '00', '00', '00', '00', '00', '00',
'00', 'a0', '07', '00', '00', '00', '00', '00',
'0b', '93', '07', '00', '00', '00', '00', '00',
'0b', '93', '07', '00', '00', '00', '00', '00',
'31', '7a', '00', 'ee', '0b', '00', '00', '00'
]
result = ParseDataRuns(input_data)
print(result)