Onkar Susladkar

30 papers A* 1A 3C 1Misc 1Journal 19Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Onkar Susladkar, Tushar Prakash, Gayatri Deshmukh, Kiet A. Nguyen, Jiaxun Zhang, Adheesh Sunil Juvekar, Tianshu Bao, Lin Chai, Sparsh Mittal, Inderjit S. Dhillon, Ismini Lourentzou
2026 J jnl
CoRR
Onkar Susladkar, Tushar Prakash, Adheesh Sunil Juvekar, Kiet A. Nguyen, Dong-Hwan Jang, Inderjit S. Dhillon, Ismini Lourentzou
2025 conf
ICDAR (5)
Harshal Kausadikar, Tanvi Kale, Onkar Susladkar, Sparsh Mittal
2025 J jnl
CoRR
Harshal Kausadikar, Tanvi Kale, Onkar Susladkar, Sparsh Mittal
2025 J jnl
Medical Image Anal.
Zheyuan Zhang, Elif Keles, Gorkem Durak, Yavuz Taktak, Onkar Susladkar, Vandan Gorade, Debesh Jha, Asli C. Ormeci, Alpay Medetalibeyoglu, Lanhong Yao, Bin Wang, Ilkin Sevgi Isler, Linkai Peng, Hongyi Pan, Camila Lopes Vendrami, Amir Bourhani, Yury Velichko, Boqing Gong, Concetto Spampinato, Ayis Pyrros, Pallavi Tiwari, Derk C. F. Klatte, Megan Engels, Sanne Hoogenboom, Candice W. Bolan, Emil Agarunov, Nassier Harfouch, Chenchan Huang, Marco J. Bruno, Ivo Schoots, Rajesh N. Keswani, Frank H. Miller, Tamas Gonda, Cemal Yazici, Temel Tirkes, Baris Turkbey, Michael B. Wallace, Ulas Bagci
2025 J jnl
CoRR
Elif Keles, Merve Yazol, Gorkem Durak, Ziliang Hong, Halil Ertugrul Aktas, Zheyuan Zhang, Linkai Peng, Onkar Susladkar, Necati Guzelyel, Oznur Leman Boyunaga, Cemal Yazici, Mark Lowe, Aliye Uc, Ulas Bagci
2025 J jnl
CoRR
Onkar Susladkar, Gayatri Deshmukh, Yalcin Tur, Gorkhem Durak, Ulas Bagci
2024 conf
EMNLP (Findings)
Onkar Susladkar, Vishesh Tripathi, Biddwan Ahmed
2024 J jnl
CoRR
Onkar Susladkar, Vishesh Tripathi, Biddwan Ahmed
2024 J jnl
CoRR
Debesh Jha, Onkar Susladkar, Vandan Gorade, Elif Keles, Matthew Antalek, Deniz Seyithanoglu, Timurhan Cebeci, Ertugrul Aktas, Gulbiz Dagoglu Kartal, Sabahattin Kaymakoglu, Sukru Mehmet Erturk, Yuri S. Velichko, Daniela P. Ladner, Amir Borhani, Alpay Medetalibeyoglu, Gorkem Durak, Ulas Bagci
2024 conf
ICPR (6)
Onkar Susladkar, Gayatri Deshmukh, Sparsh Mittal, Parth Shastri
2024 J jnl
CoRR
Onkar Susladkar, Gayatri Deshmukh, Sparsh Mittal, Parth Shastri
2024 J jnl
CoRR
Abhijit Das, Debesh Jha, Jasmer Sanjotra, Onkar Susladkar, Suramyaa Sarkar, Ashish Rauniyar, Nikhil Kumar Tomar, Vanshali Sharma, Ulas Bagci
2024 A* conf
EMNLP
Onkar Susladkar, Gayatri Deshmukh, Vandan Gorade, Sparsh Mittal
2024 A conf
WACV
Dhruv Makwana, Gayatri Deshmukh, Onkar Susladkar, Sparsh Mittal, R. Sai Chandra Teja
2024 J jnl
CoRR
Zheyuan Zhang, Elif Keles, Gorkem Durak, Yavuz Taktak, Onkar Susladkar, Vandan Gorade, Debesh Jha, Asli C. Ormeci, Alpay Medetalibeyoglu, Lanhong Yao, Bin Wang, Ilkin Sevgi Isler, Linkai Peng, Hongyi Pan, Camila Lopes Vendrami, Amir Bourhani, Yury Velichko, Boqing Gong, Concetto Spampinato, Ayis Pyrros, Pallavi Tiwari, Derk C. F. Klatte, Megan Engels, Sanne Hoogenboom, Candice W. Bolan, Emil Agarunov, Nassier Harfouch, Chenchan Huang, Marco J. Bruno, Ivo Schoots, Rajesh N. Keswani, Frank H. Miller, Tamas Gonda, Cemal Yazici, Temel Tirkes, Baris Turkbey, Michael B. Wallace, Ulas Bagci
2024 J jnl
Pattern Recognit.
Prashant Kumar, Dhruv Makwana, Onkar Susladkar, Anurag Mittal, Prem Kumar Kalra
2024 J jnl
CoRR
Onkar Susladkar, Jishu Sen Gupta, Chirag Sehgal, Sparsh Mittal, Rekha Singhal
2024 A conf
WACV
Gayatri Deshmukh, Onkar Susladkar, Dhruv Makwana, Sparsh Mittal, R. Sai Chandra Teja
2024 J jnl
CoRR
Vandan Gorade, Onkar Susladkar, Gorkem Durak, Elif Keles, Ertugrul Aktas, Timurhan Cebeci, Alpay Medetalibeyoglu, Daniela P. Ladner, Debesh Jha, Ulas Bagci
2023 A conf
WACV
Onkar Susladkar, Gayatri Deshmukh, Dhruv Makwana, Sparsh Mittal, R. Sai Chandra Teja, Rekha Singhal
2023 conf
AIMLSystems
Onkar Susladkar, Gayatri S. Deshmukh, Sparsh Mittal, R. Sai Chandra Teja, Rekha Singhal
2023 J jnl
CoRR
Prashant Kumar, Onkar Susladkar, Dhruv Makwana, Anurag Mittal, Prem Kumar Kalra
2023 Misc conf
ICASSP
Onkar Susladkar, Prajwal Gatti, Santosh Kumar Yadav
2023 conf
ICDAR (6)
Onkar Susladkar, Dhruv Makwana, Gayatri Deshmukh, Sparsh Mittal, R. Sai Chandra Teja, Rekha Singhal
2023 J jnl
CoRR
Onkar Susladkar, Prajwal Gatti, Anand Mishra
2022 J jnl
CoRR
Dhruv Makwana, Subhrajit Nag, Onkar Susladkar, Gayatri Deshmukh, R. Sai Chandra Teja, Sparsh Mittal, C. Krishna Mohan
2022 J jnl
J. Syst. Archit.
Onkar Susladkar, Gayatri Deshmukh, Subhrajit Nag, Ananya Mantravadi, Dhruv Makwana, Sujitha Ravichandran, R. Sai Chandra Teja, Gajanan H. Chavhan, C. Krishna Mohan, Sparsh Mittal
2022 J jnl
CoRR
Onkar Susladkar, Dhruv Makwana, Gayatri Deshmukh, Sparsh Mittal, R. Sai Chandra Teja, Rekha Singhal
2021 C conf
PACLIC
Devika Verma, Ramprasad Joshi, Shubhamkar Joshi, Onkar Susladkar
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