Chandan Dasgupta

52 papers A* 1B 14C 17Journal 9Unranked 11
YearRankTypeTitle / Venue / Authors
2024 B conf
ICALT
Anveshna Srivastava, Sahana Murthy, Chandan Dasgupta
2024 J jnl
Br. J. Educ. Technol.
Anveshna Srivastava, Vihang Vaidya, Sahana Murthy, Chandan Dasgupta
2023 C conf
ICCE
Herold P. C., Chandan Dasgupta
2023 B conf
ICALT
Sandeep Yadav, Chandan Dasgupta
2023 B conf
ICALT
Herold P. C., Chandan Dasgupta
2023 B conf
EDM
Vishwas Badhe, Chandan Dasgupta, Ramkumar Rajendran
2023 B conf
ICALT
Sonika Pal, Vishwas Badhe, Chandan Dasgupta
2023 C conf
ICCE
Alekh V., Chandan Dasgupta
2023 C conf
ICCE
Alekh V., Chandan Dasgupta
2023 C conf
ICCE
Rajashri Priyadarshini, Chandan Dasgupta, Sahana Murthy
2023 C conf
ICCE
Anveshna Srivastava, Chandan Dasgupta
2022 C conf
ICCE
Anveshna Srivastava, Chandan Dasgupta
2022 C conf
ICCE
Narasimha Swamy, Anveshna Srivastava, Chandan Dasgupta
2022 B conf
ICALT
Anveshna Srivastava, Chandan Dasgupta
2022 C conf
ICCE
Navneet Kaur, Chandan Dasgupta
2022 B conf
ICALT
K. Nisumba Soodhani, Meera Pawar, Jyoti Kolap, Rajashri Priyadarshini, Chandan Dasgupta
2022 C conf
ICCE
Alekh V., Chandan Dasgupta
2022 C conf
ICCE
Gomathy Soundararaj, Vishwas Badhe, Ishika, Meera Pawar, Chandan Dasgupta, Sahana Murthy
2022 C conf
ICCE
Alekh V., Chandan Dasgupta
2021 B conf
ICALT
Rajashri Priyadarshini, Indrayani Nishane, Nagesh Pokle, Ulfa Khwaja, Chandan Dasgupta
2021 C conf
ICCE
Aastha Patel, Chandan Dasgupta, Sahana Murthy, Rashi Dhanani
2021 C conf
ICCE
Vishwas Badhe, Gargi Banerjee, Chandan Dasgupta
2021 J jnl
Comput. Appl. Eng. Educ.
Chandan Dasgupta, Alejandra J. Magana, Lisa Kirkham
2021 C conf
ICCE
Sahana Murthy, Chandan Dasgupta, Rashi Dhanani
2020 B conf
ICALT
Priya C. Lotlikar, Deepak Pathak, Herold P. C., Chandan Dasgupta
2019 conf
CSCL
Navneet Kaur, Aastha Patel, Chandan Dasgupta
2019 conf
T4E
Navneet Kaur, Chandan Dasgupta
2019 J jnl
Comput. Educ.
Chandan Dasgupta, Alejandra J. Magana, Camilo Vieira
2019 B conf
ICALT
Herold P. C., Chandan Dasgupta, Sahana Murthy, Anirudha Joshi
2019 conf
T4E
Herold P. C., Ulfa Khwaja, Sahana Murthy, Chandan Dasgupta
2019 B conf
ICALT
Aastha Patel, Chandan Dasgupta
2018 conf
ICLS
Chandan Dasgupta
2018 conf
ICLS
Chandan Dasgupta
2018 C conf
ICCE
Navneet Kaur, Chandan Dasgupta
2018 conf
ICLS
James P. Bywater, Mark Floryan, Jennifer L. Chiu, Jie Chao, Corey Schimpf, Charles Xie, Camilo Vieira, Alejandra J. Magana, Chandan Dasgupta
2017 J jnl
J. Enterp. Inf. Manag.
Bijith Marakarkandy, Nilay Yajnik, Chandan Dasgupta
2016 C conf
FIE
Ying Ying Seah, Camilo Vieira, Chandan Dasgupta, Alejandra J. Magana
2016 B conf
ICALT
Chandan Dasgupta
2016 C conf
ICCE
Chandan Dasgupta, Alejandra J. Magana
2015 conf
CSCL
Tom Moher, James D. Slotta, Alisa Acosta, Rebecca Cober, Chandan Dasgupta, Cresencia Fong, Alessandro Gnoli, Alexandra Silva, Brenda López Silva, Anthony Perritano, Kylie Peppler
2015 J jnl
Technol. Knowl. Learn.
Tia Shelley, Chandan Dasgupta, Alexandra Silva, Leilah Lyons, Tom Moher
2015 J jnl
Ind. Manag. Data Syst.
Dipak Damodar Gaikar, Bijith Marakarkandy, Chandan Dasgupta
2014 A* conf
CHI
Tia Shelley, Leilah Lyons, Tom Moher, Chandan Dasgupta, Brenda López Silva, Alexandra Silva
2014 conf
ICLS
Chandan Dasgupta, Tom Moher
2012 conf
ICLS
Brian Slattery, Chandan Dasgupta, Tia Shelley, Leilah Lyons, Emily Minor, Moira Zellner
2011 B conf
TEI
Hyungsin Kim, Anya Kogan, Chandan Dasgupta, Michael Misha Novitzky, Ellen Yi-Luen Do
2010 conf
ICLS
Chandan Dasgupta, Leilah Lyons, Moira L. Zellner, Andrew Greenlee
2010 conf
ACM Southeast Regional Conference
Chandan Dasgupta
2009 B conf
Creativity & Cognition
Chandan Dasgupta, Janet L. Kolodner
2000 J jnl
Neural Comput.
Chengxiang Zhang, Chandan Dasgupta, Manoranjan P. Singh
1997 J jnl
IEEE Trans. Neural Networks
Gopalasamy Athithan, Chandan Dasgupta
1993 J jnl
Biol. Cybern.
Mayank R. Mehta, Chandan Dasgupta, Gautam R. Ullal
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