import io
import logging
from abc import ABC
from typing import List, Optional
import pandas as pd
from credsweeper.credentials.augment_candidates import augment_candidates
from credsweeper.credentials.candidate import Candidate
from credsweeper.deep_scanner.abstract_scanner import AbstractScanner
from credsweeper.file_handler.data_content_provider import DataContentProvider
from credsweeper.file_handler.string_content_provider import StringContentProvider
from credsweeper.utils.util import Util
logger = logging.getLogger(__name__)
[docs]
class XlsxScanner(AbstractScanner, ABC):
"""Implements xlsx scanning"""
[docs]
@staticmethod
def match(data: bytes | bytearray) -> bool:
"""According https://en.wikipedia.org/wiki/List_of_file_signatures"""
if data.startswith(b"\xD0\xCF\x11\xE0\xA1\xB1\x1A\xE1"):
# Compound File Binary Format: doc, xls, ppt, msi, msg
return True
return False
[docs]
def data_scan(
self, #
data_provider: DataContentProvider, #
depth: int, #
recursive_limit_size: int) -> Optional[List[Candidate]]:
"""Tries to scan xlsx text elements for all slides"""
try:
candidates = []
book = pd.read_excel(io.BytesIO(data_provider.data), sheet_name=None, header=None)
for sheet_name, sheet_data in book.items():
sheet_info = f"{data_provider.info}|{sheet_name}"
# replace open xml carriage returns _x000D_ before line feed only
df = sheet_data.replace(to_replace="_x000D_\n", value='\n', regex=True).fillna('').astype(str)
for row_pos, row in enumerate(df.values):
for col_pos, cell in enumerate(row):
cell_info = f"{sheet_info}:{Util.get_excel_column_name(col_pos)}{row_pos + 1}"
cell_provider = StringContentProvider(lines=cell.splitlines(),
file_path=data_provider.file_path,
file_type=data_provider.file_type,
info=cell_info)
cell_candidates = self.scanner.scan(cell_provider)
candidates.extend(cell_candidates)
row_line = '\t'.join(row)
row_provider = StringContentProvider(lines=[row_line],
file_path=data_provider.file_path,
file_type=data_provider.file_type,
info=f"{sheet_info}:R{row_pos + 1}")
row_candidates = self.scanner.scan(row_provider)
augment_candidates(candidates, row_candidates)
return candidates
except Exception as xlsx_exc:
logger.warning("%s:%s", data_provider.file_path, xlsx_exc)
return None