Karan Aggarwal

39 papers A* 2A 6Journal 20Unranked 10
YearRankTypeTitle / Venue / Authors
2024 A conf
WSDM
Revanth Gangi Reddy, Sharath Chandra Etagi Suresh, Hao Bai, Wentao Yao, Mankeerat Sidhu, Karan Aggarwal, Prathamesh Sonawane, ChengXiang Zhai
2024 J jnl
CoRR
Yong Xie, Karan Aggarwal, Aitzaz Ahmad, Stephen Lau
2024 conf
ACL (Findings)
Yong Xie, Karan Aggarwal, Aitzaz Ahmad
2024 J jnl
CoRR
Mingqi Li, Karan Aggarwal, Yong Xie, Aitzaz Ahmad, Stephen Lau
2023 conf
ACL (Findings)
Karan Aggarwal, Henry Jin, Aitzaz Ahmad
2023 J jnl
CoRR
Yong Xie, Karan Aggarwal, Aitzaz Ahmad
2023 J jnl
CoRR
Karan Aggarwal, Jaideep Srivastava
2023 J jnl
J. Supercomput.
Kiranbir Kaur, Salil Bharany, Sumit Badotra, Karan Aggarwal, Anand Nayyar, Sandeep Sharma
2023 J jnl
CoRR
Karan Aggarwal, Jaideep Srivastava
2022 J jnl
Multim. Tools Appl.
Maad M. Mijwil, Karan Aggarwal
2021 J jnl
Expert Syst. Appl.
Rachna Mehta, Karan Aggarwal, Deepika Koundal, Adi Alhudhaif, Kemal Polat
2020 A* conf
SIGIR
Karan Aggarwal, Georgios Theocharous, Anup B. Rao
2020 J jnl
ACM Trans. Parallel Comput.
Karan Aggarwal, Uday Bondhugula
2019 A* conf
AAAI
Karan Aggarwal, Shafiq R. Joty, Luis Fernández-Luque, Jaideep Srivastava
2019 conf
IEEE BigData
Mark Capelo, Karan Aggarwal, Pranjul Yadav
2019 conf
IRICT
Karan Aggarwal, Manjit Singh Bhamrah, Hardeep Singh Ryait
2019 J jnl
EURASIP J. Image Video Process.
Karan Aggarwal, Manjit Singh Bhamrah, Hardeep Singh Ryait
2019 A conf
RecSys
Karan Aggarwal, Pranjul Yadav, S. Sathiya Keerthi
2019 J jnl
CoRR
Karan Aggarwal, Uday Bondhugula, Varsha Sreenivasan, Devarajan Sridharan
2019 A conf
ICS
Karan Aggarwal, Uday Bondhugula
2019 J jnl
CoRR
Karan Aggarwal, Matthieu Kirchmeyer, Pranjul Yadav, S. Sathiya Keerthi, Patrick Gallinari
2019 conf
CHI Extended Abstracts
Arun Kumar, Karan Aggarwal, Paul R. Schrater
2019 conf
EMNLP/IJCNLP (1)
Swaraj Khadanga, Karan Aggarwal, Shafiq R. Joty, Jaideep Srivastava
2019 J jnl
CoRR
Swaraj Khadanga, Karan Aggarwal, Shafiq R. Joty, Jaideep Srivastava
2018 conf
IEEE BigData
Karan Aggarwal, Swaraj Khadanga, Shafiq R. Joty, Louis Kazaglis, Jaideep Srivastava
2018 J jnl
CoRR
Karan Aggarwal, Shafiq R. Joty, Luis Fernández-Luque, Jaideep Srivastava
2018 ch.
Encyclopedia of Social Network Analysis and Mining. 2nd Ed.
Karan Aggarwal, Komal Kapoor, Jaideep Srivastava
2018 J jnl
CoRR
Karan Aggarwal, Swaraj Khadanga, Shafiq R. Joty, Louis Kazaglis, Jaideep Srivastava
2018 J jnl
CoRR
Arun Kumar, Karan Aggarwal, Paul R. Schrater
2018 conf
IEEE BigData
Karan Aggarwal, Onur Atan, Ahmed K. Farahat, Chi Zhang, Kosta Ristovski, Chetan Gupta
2018 J jnl
CoRR
Karan Aggarwal, Onur Atan, Ahmed K. Farahat, Chi Zhang, Kosta Ristovski, Chetan Gupta
2017 J jnl
CoRR
Karan Aggarwal, Shafiq R. Joty, Luis Fernández-Luque, Jaideep Srivastava
2017 J jnl
J. Softw. Evol. Process.
Karan Aggarwal, Finbarr Timbers, Tanner Rutgers, Abram Hindle, Eleni Stroulia, Russell Greiner
2015 conf
IGSC
Shaiful Alam Chowdhury, Luke N. Kumar, Md. Toukir Imam, Mohomed Shazan Mohomed Jabbar, Varun Sapra, Karan Aggarwal, Abram Hindle, Russell Greiner
2015 A conf
SANER
Karan Aggarwal, Tanner Rutgers, Finbarr Timbers, Abram Hindle, Russell Greiner, Eleni Stroulia
2015 A conf
ICSME
Karan Aggarwal, Abram Hindle, Eleni Stroulia
2015 J jnl
PeerJ Prepr.
Karan Aggarwal, Mohammad Salameh, Abram Hindle
2014 A conf
MSR
Karan Aggarwal, Abram Hindle, Eleni Stroulia
2014 conf
CASCON
Karan Aggarwal, Chenlei Zhang, Joshua Charles Campbell, Abram Hindle, Eleni Stroulia
redb/extractors/macho_extractors/macho_dylibs.py
← Index redb/extractors/macho_extractors/macho_dylibs.py python
import hashlib
import inspect
from datetime import datetime, timezone
from typing import Any

from redb.extractors.enum import Tag
from redb.extractors.macho_extractor import MachOExtractor
from redb.models.dataclasses import MachODylib


class MachODylibExtractor(MachOExtractor):

    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        macho=None,
    ):
        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            elastic_index,
            known_benign,
            known_malicious,
            macho,
        )
        self.elastic_index = self.index_prefix + "-macho_dylibs"
        self.log.debug(inspect.currentframe().f_code.co_name)

    def tag(self):
        return Tag.MACHO_DYLIB.value

    def _extract_dylibs(self):
        """Extract dynamic library information from all architectures in the MachO binary."""
        self.log.debug(inspect.currentframe().f_code.co_name)
        dylibs = []

        if not self.macho:
            return dylibs

        try:
            # Get architectures using new API (already parsed in base class)
            architectures = self.macho.get_architectures()
            if not architectures:
                return dylibs

            # Process each architecture
            for arch_name in architectures:
                # Get dylib commands using new API with architecture parameter
                dylib_commands = self.macho.get_dylib_commands(arch=arch_name)
                if not dylib_commands:
                    continue

                # Extract dylib commands for this architecture
                for dylib_cmd in dylib_commands:
                    try:
                        dylib_name = dylib_cmd.get('dylib_name', 'Unknown')
                        if isinstance(dylib_name, bytes):
                            dylib_name = dylib_name.decode('utf-8', errors='replace')

                        # Create dylib dataclass with architecture info
                        macho_dylib = MachODylib(
                            dylib_name=dylib_name,
                            dylib_timestamp=dylib_cmd.get('dylib_timestamp', 0),
                            dylib_current_version=dylib_cmd.get('dylib_current_version', 0),
                            dylib_compat_version=dylib_cmd.get('dylib_compat_version', 0),
                        )
                        # Add architecture info to the dylib
                        macho_dylib.architecture = arch_name
                        dylibs.append(macho_dylib)

                    except Exception as e:
                        self.log.warning(
                            f'Unable to process dylib "{dylib_cmd.get("dylib_name", "Unknown")}" for architecture {arch_name} in {self.hash.sha256}: {e}'
                        )
                        continue

            return dylibs

        except Exception as e:
            self.log.error(f"Error extracting MachO dylibs: {e}")
            return dylibs

    def extract(self):
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            dylibs = self._extract_dylibs()
            return dylibs
        except Exception as e:
            self.log.error(f"Error extracting MachO dylibs: {e}")
            return None

    def prepare_export_data(self, exporter_type: str) -> Any:
        if exporter_type == "ElasticsearchExporter":
            return self.extract()
        elif exporter_type == "ClickHouseExporter":
            if not self.macho:
                return None

            # Get architectures (macho is already parsed in base class)
            try:
                architectures = self.macho.get_architectures()
                is_fat = len(architectures) > 1
            except Exception as e:
                self.log.error(f"Could not get architectures: {e}")
                return None

            data = []
            current_time = datetime.now(timezone.utc)

            # Loop through each architecture (1 for single, multiple for FAT)
            for arch_name in architectures:
                # Get architecture-specific sha256
                try:
                    arch_general_info = self.macho.get_general_info(arch=arch_name)
                    arch_header_raw = self.macho.get_macho_header(arch=arch_name)
                    arch_sha256 = arch_general_info.get('SHA256', self.sha256)
                    arch_cputype_raw = arch_header_raw.get('cputype', 0) if arch_header_raw else 0
                except Exception as e:
                    self.log.warning(f"Could not get arch-specific data for {arch_name}: {e}")
                    arch_sha256 = self.sha256
                    arch_cputype_raw = 0

                # Get dylib commands for this architecture
                dylib_commands = self.macho.get_dylib_commands(arch=arch_name)
                if not dylib_commands:
                    continue

                # Process each dylib for this architecture
                for dylib_cmd in dylib_commands:
                    try:
                        dylib_name = dylib_cmd.get('dylib_name', 'Unknown')
                        if isinstance(dylib_name, bytes):
                            dylib_name = dylib_name.decode('utf-8', errors='replace')

                        data.append([
                            arch_sha256,                          # sha256 (architecture-specific)
                            dylib_name,                           # dylib_name
                            dylib_cmd.get('dylib_timestamp', 0), # dylib_timestamp
                            dylib_cmd.get('dylib_current_version', 0), # dylib_current_version
                            dylib_cmd.get('dylib_compat_version', 0),  # dylib_compat_version
                            current_time,                         # analysis_date
                        ])
                    except Exception as e:
                        self.log.warning(
                            f'Unable to process dylib "{dylib_cmd.get("dylib_name", "Unknown")}" for architecture {arch_name}: {e}'
                        )
                        continue

            column_names = [
                'sha256',
                'dylib_name', 'dylib_timestamp', 'dylib_current_version',
                'dylib_compat_version', 'analysis_date'
            ]

            if not data:
                return None

            column_type_names = [
                'FixedString(64)',
                'String', 'UInt32', 'UInt32',
                'UInt32', 'DateTime64(3, \'UTC\')'
            ]

            return (data, column_names, column_type_names)

        return None

    def get_clickhouse_table(self) -> str:
        return "redb_macho_dylibs"