Caizi Li

18 papers Journal 15Unranked 3
YearRankTypeTitle / Venue / Authors
2024 J jnl
Biomed. Signal Process. Control.
Congyu Tian, Yaoqian Li, Xin Xiong, Caizi Li, Kang Li, Xiangyun Liao, Yongzhi Deng, Weixin Si
2024 J jnl
Int. J. Comput. Assist. Radiol. Surg.
Renzhe Tu, Doudou Zhang, Caizi Li, Linxia Xiao, Yong Zhang, Xiaodong Cai, Weixin Si
2024 J jnl
IEEE Trans. Instrum. Meas.
Caizi Li, Yaoqian Li, Ruiqiang Liu, Guangsuo Wang, Jianping Lv, Yueming Jin, Weixin Si, Pheng-Ann Heng
2024 J jnl
IEEE J. Biomed. Health Informatics
Qian Yang, Caizi Li, Chubin Ou, Kang Li, Xiangyun Liao, Chuanzhi Duan, Lequan Yu, Weixin Si
2023 J jnl
J. Comput. Sci. Technol.
Caizi Li, Ruiqiang Liu, Huan-Xin Zhong, Jun-Ming Fan, Wei-Xin Si, Meng Zhang, Pheng-Ann Heng
2022 J jnl
Sci. China Inf. Sci.
Linxia Xiao, Caizi Li, Yanjiang Wang, Weixin Si, Hai Lin, Doudou Zhang, Xiaodong Cai, Pheng-Ann Heng
2021 J jnl
Medical Image Anal.
Zhaohan Xiong, Qing Xia, Zhiqiang Hu, Ning Huang, Cheng Bian, Yefeng Zheng, Sulaiman Vesal, Nishant Ravikumar, Andreas K. Maier, Xin Yang, Pheng-Ann Heng, Dong Ni, Caizi Li, Qianqian Tong, Weixin Si, Élodie Puybareau, Younes Khoudli, Thierry Géraud, Jichao Zhao
2021 J jnl
Int. J. Comput. Assist. Radiol. Surg.
Linxia Xiao, Caizi Li, Yanjiang Wang, Weixin Si, Doudou Zhang, Hai Lin, Xiaodong Cai, Pheng-Ann Heng
2021 J jnl
IEEE Trans. Medical Imaging
Yue Sun, Kun Gao, Zhengwang Wu, Guannan Li, Xiaopeng Zong, Zhihao Lei, Ying Wei, Jun Ma, Xiaoping Yang, Xue Feng, Li Zhao, Trung Le Phan, Jitae Shin, Tao Zhong, Yu Zhang, Lequan Yu, Caizi Li, Ramesh Basnet, M. Omair Ahmad, M. N. S. Swamy, Wenao Ma, Qi Dou, Toan Duc Bui, Camilo Bermudez Noguera, Bennett A. Landman, Ian H. Gotlib, Kathryn L. Humphreys, Sarah Shultz, Longchuan Li, Sijie Niu, Weili Lin, Valerie Jewells, Dinggang Shen, Gang Li, Li Wang
2021 J jnl
IEEE J. Biomed. Health Informatics
Caizi Li, Li Dong, Qi Dou, Fan Lin, Kebao Zhang, Zuxin Feng, Weixin Si, XueSong Deng, Zhe Deng, Pheng-Ann Heng
2020 J jnl
CoRR
Zhaohan Xiong, Qing Xia, Zhiqiang Hu, Ning Huang, Cheng Bian, Yefeng Zheng, Sulaiman Vesal, Nishant Ravikumar, Andreas K. Maier, Xin Yang, Pheng-Ann Heng, Dong Ni, Caizi Li, Qianqian Tong, Weixin Si, Élodie Puybareau, Younes Khoudli, Thierry Géraud, Chen Chen, Wenjia Bai, Daniel Rueckert, Lingchao Xu, Xiahai Zhuang, Xinzhe Luo, Shuman Jia, Maxime Sermesant, Yashu Liu, Kuanquan Wang, Davide Borra, Alessandro Masci, Cristiana Corsi, Coen de Vente, Mitko Veta, Rashed Karim, Chandrakanth Jayachandran Preetha, Sandy Engelhardt, Mengyun Qiao, Yuanyuan Wang, Qian Tao, Marta Nuñez Garcia, Oscar Camara, Nicoló Savioli, Pablo Lamata, Jichao Zhao
2020 conf
ECCV (9)
Shujun Wang, Lequan Yu, Caizi Li, Chi-Wing Fu, Pheng-Ann Heng
2020 J jnl
CoRR
Shujun Wang, Lequan Yu, Caizi Li, Chi-Wing Fu, Pheng-Ann Heng
2020 J jnl
CoRR
Yue Sun, Kun Gao, Zhengwang Wu, Zhihao Lei, Ying Wei, Jun Ma, Xiaoping Yang, Xue Feng, Li Zhao, Trung Le Phan, Jitae Shin, Tao Zhong, Yu Zhang, Lequan Yu, Caizi Li, Ramesh Basnet, M. Omair Ahmad, M. N. S. Swamy, Wenao Ma, Qi Dou, Toan Duc Bui, Camilo Bermudez Noguera, Bennett A. Landman, Ian H. Gotlib, Kathryn L. Humphreys, Sarah Shultz, Longchuan Li, Sijie Niu, Weili Lin, Valerie Jewells, Gang Li, Dinggang Shen, Li Wang
2019 conf
ISBI
Caizi Li, Qianqian Tong, Xiangyun Liao, Weixin Si, Shu Chen, Qiong Wang, Zhiyong Yuan
2019 J jnl
IEEE Netw.
Qianqian Tong, Xiaosa Li, Kai Lin, Caizi Li, Weixin Si, Zhiyong Yuan
2019 J jnl
Comput. Biol. Medicine
Qianqian Tong, Caizi Li, Weixin Si, Xiangyun Liao, Yaliang Tong, Zhiyong Yuan, Pheng-Ann Heng
2018 conf
STACOM@MICCAI
Caizi Li, Qianqian Tong, Xiangyun Liao, Weixin Si, Yinzi Sun, Qiong Wang, Pheng-Ann Heng
redb/extractors/macho_extractor.py
← Index redb/extractors/macho_extractor.py python
import logging
from abc import ABCMeta, abstractmethod
import inspect
import sys
import os

import machofile

from redb.extractors.extractor import Extractor

logger = logging.getLogger(__name__)


@abstractmethod
class MachOExtractor(Extractor, metaclass=ABCMeta):

    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        macho=None,
    ):
        # Read binary and parse machofile BEFORE calling super().__init__
        # This avoids reading the file twice
        with open(filepath, "rb") as f:
            binary_data = f.read()

        # Parse machofile with binary data
        self.macho = macho if macho else self._generate_machofile_object(binary_data)

        # Extract hashes from machofile to pass to parent
        precomputed_hashes = None
        if self.macho:
            try:
                general_info = self.macho.get_general_info()
                if general_info:
                    # For FAT binaries, get_general_info() returns dict with 'fat' key
                    # For single-arch, it returns the info directly
                    if 'fat' in general_info:
                        fat_info = general_info['fat']
                        precomputed_hashes = {
                            'MD5': fat_info.get('MD5'),
                            'SHA1': fat_info.get('SHA1'),
                            'SHA256': fat_info.get('SHA256'),
                        }
                    else:
                        precomputed_hashes = {
                            'MD5': general_info.get('MD5'),
                            'SHA1': general_info.get('SHA1'),
                            'SHA256': general_info.get('SHA256'),
                        }
            except Exception as e:
                logger.debug(f"Could not get hashes from machofile: {e}")

        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            elastic_index,
            known_benign,
            known_malicious,
            precomputed_hashes=precomputed_hashes,
        )

        # Store binary data so base class doesn't re-read
        self._binary_data = binary_data

    @property
    def binary(self):
        """Override to use already-read binary data."""
        return self._binary_data

    def _generate_machofile_object(self, binary_data):
        """Generate and parse a machofile object from binary data."""
        macho = None
        try:
            macho = machofile.UniversalMachO(data=binary_data)
            if not macho:
                raise Exception("Empty file?")

            # Parse the MachO object once during initialization
            macho.parse()

        except Exception as e:
            logger.error(f"Format error parsing MachO: {e}")
        return macho

    # def _is_macho_file(self):
    #     """Check if the file is a valid Mach-O binary."""
    #     try:
    #         if not self.macho:
    #             return False
            
    #         # For Universal/FAT binaries, check if any architecture is valid
    #         if hasattr(self.macho, 'is_fat') and self.macho.is_fat:
    #             return len(self.macho.architectures) > 0
    #         else:
    #             # Single architecture binary
    #             return hasattr(self.macho, 'macho') and self.macho.macho is not None
    #     except Exception as e:
    #         self.log.error(f"Error checking Mach-O file: {e}")
    #         return False

    def _is_signed(self):
        """Check if the Mach-O binary is code signed using new API."""
        try:
            if not self.macho:
                return False

            # Get architectures using new API
            architectures = self.macho.get_architectures()

            # For each architecture, check if signed
            for arch in architectures:
                try:
                    signature_info = self.macho.get_code_signature_info(arch=arch)
                    if signature_info and signature_info.get('signed', False):
                        return True
                except Exception:
                    continue

            return False
        except Exception as e:
            self.log.error(f"Error checking Mach-O signature: {e}")
            return False

    def _get_architectures(self):
        """Get list of architectures in the Mach-O binary using new API."""
        try:
            if not self.macho:
                return []

            # Use new API method
            architectures = self.macho.get_architectures()
            return architectures if architectures else []
        except Exception as e:
            self.log.error(f"Error getting architectures: {e}")
            return []

    # def _get_macho_for_arch(self, arch_name=None):
    #     """Get MachO instance for specific architecture or default."""
    #     try:
    #         if not self.macho:
    #             return None
            
    #         if hasattr(self.macho, 'is_fat') and self.macho.is_fat:
    #             if arch_name:
    #                 return self.macho.architectures.get(arch_name)
    #             else:
    #                 # Return first available architecture
    #                 return next(iter(self.macho.architectures.values())) if self.macho.architectures else None
    #         else:
    #             # Single architecture binary
    #             return self.macho.macho if hasattr(self.macho, 'macho') else None
    #     except Exception as e:
    #         self.log.error(f"Error getting MachO for architecture: {e}")
    #         return None

    # def _get_formatted_header_values(self, header):
    #     """Get both raw and human-readable header values."""
    #     try:
    #         macho_instance = self._get_macho_for_arch()
    #         if not macho_instance:
    #             return None
            
    #         # Parse the MachO if not already parsed
    #         if not hasattr(macho_instance, 'header') or not macho_instance.header:
    #             macho_instance.parse()
            
    #         # Get human-readable values using machofile's formatting methods
    #         magic_str = macho_instance.format_magic_value(header.get('magic', 0))
            
    #         # Simple CPU type mapping since CPU_TYPE_MAP is not exposed
    #         cputype = header.get('cputype', 0)
    #         if cputype == 0x7:
    #             cputype_str = "x86"
    #         elif cputype == 0x1000007:
    #             cputype_str = "x86_64"
    #         elif cputype == 0xC:
    #             cputype_str = "ARM"
    #         elif cputype == 0x100000C:
    #             cputype_str = "ARM 64-bit"
    #         else:
    #             cputype_str = str(cputype)
            
    #         cpusubtype_str = macho_instance.decode_cpusubtype(header.get('cputype', 0), header.get('cpusubtype', 0))
    #         filetype_str = macho_instance.format_file_type(header.get('filetype', 0))
    #         flags_str = macho_instance.decode_flags(header.get('flags', 0))
            
    #         return {
    #             'raw': {
    #                 'magic': header.get('magic', 0),
    #                 'cputype': header.get('cputype', 0),
    #                 'cpusubtype': header.get('cpusubtype', 0),
    #                 'filetype': header.get('filetype', 0),
    #                 'flags': header.get('flags', 0),
    #             },
    #             'formatted': {
    #                 'magic_str': magic_str,
    #                 'cputype_str': cputype_str,
    #                 'cpusubtype_str': cpusubtype_str,
    #                 'filetype_str': filetype_str,
    #                 'flags_str': flags_str,
    #             }
    #         }
    #     except Exception as e:
    #         self.log.error(f"Error formatting header values: {e}")
    #         return None