Ongard Sirisaengtaksin

12 papers Journal 8Unranked 4
YearRankTypeTitle / Venue / Authors
2014 conf
eScience
Sherif Hanie El Meligy Abdelhamid, Md. Maksudul Alam, Richard A. Aló, Shaikh Arifuzzaman, Peter H. Beckman, Tirtha Bhattacharjee, Md Hasanuzzaman Bhuiyan, Keith R. Bisset, Stephen G. Eubank, Albert C. Esterline, Edward A. Fox, Geoffrey C. Fox, S. M. Shamimul Hasan, Harshal Hayatnagarkar, Maleq Khan, Chris J. Kuhlman, Madhav V. Marathe, Natarajan Meghanathan, Henning S. Mortveit, Judy Qiu, S. S. Ravi, Zalia Shams, Ongard Sirisaengtaksin, Samarth Swarup, Anil Kumar S. Vullikanti, Tak-Lon Wu
2012 J jnl
J. Comput. Sci. Coll.
Ongard Sirisaengtaksin, Maxwell Goedjen, Brian Holtkamp
2012 conf
eScience
Sherif Elmeligy Abdelhamid, Richard A. Aló, S. M. Arifuzzaman, Peter H. Beckman, Md Hasanuzzaman Bhuiyan, Keith R. Bisset, Edward A. Fox, Geoffrey Charles Fox, Kevin Hall, S. M. Shamimul Hasan, Anurodh Joshi, Maleq Khan, Chris J. Kuhlman, Spencer J. Lee, Jonathan Leidig, Hemanth Makkapati, Madhav V. Marathe, Henning S. Mortveit, Judy Qiu, S. S. Ravi, Zalia Shams, Ongard Sirisaengtaksin, Rajesh Subbiah, Samarth Swarup, Nick Trebon, Anil Vullikanti, Zhao Zhao
2010 J jnl
J. Comput. Sci. Coll.
Hong Lin, Ongard Sirisaengtaksin, Ping Chen
2009 conf
NAS
Ongard Sirisaengtaksin, Danil Safin
2007 J jnl
Neural Parallel Sci. Comput.
André de Korvin, Plamen Simeonov, Ongard Sirisaengtaksin
2005 J jnl
Neural Parallel Sci. Comput.
André de Korvin, Ongard Sirisaengtaksin, Shohreh Hashemi
2004 J jnl
Neural Parallel Sci. Comput.
André de Korvin, Ongard Sirisaengtaksin
1998 conf
Annual Simulation Symposium
Mohsen Beheshti, Ali Berrached, André de Korvin, Chenyi Hu, Ongard Sirisaengtaksin
1996 J jnl
Fuzzy Sets Syst.
Hung T. Nguyen, Vladik Kreinovich, Ongard Sirisaengtaksin
1994 J jnl
Neural Parallel Sci. Comput.
Paul C. Kainen, Vera Kurková, Vladik Kreinovich, Ongard Sirisaengtaksin
1993 J jnl
Neural Parallel Sci. Comput.
Vladik Kreinovich, Ongard Sirisaengtaksin
redb/extractors/macho_extractors/macho_universal.py
← Index redb/extractors/macho_extractors/macho_universal.py python
import hashlib
import inspect
import json
from datetime import datetime, timezone
from typing import Any, List

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


class MachOUniversalExtractor(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_universal"
        self.log.debug(inspect.currentframe().f_code.co_name)

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

    def _extract_universal_info(self):
        """Extract Universal/FAT binary architecture information using new API."""
        self.log.debug(inspect.currentframe().f_code.co_name)

        if not self.macho:
            return None

        try:
            # Parse at Universal level first (new API requirement)
            self.macho.parse()

            # Get architectures using new API
            architectures = self.macho.get_architectures()
            if not architectures:
                return None

            # Check if this is a FAT binary
            is_fat = len(architectures) > 1

            architecture_info = []

            # Extract info for each architecture
            for arch_name in architectures:
                try:
                    # Get general info for this architecture
                    general_info = self.macho.get_general_info(arch=arch_name)

                    # Get header info for this architecture
                    header_info = self.macho.get_macho_header(arch=arch_name)

                    # Get architecture-specific MachO instance for detailed analysis
                    arch_macho = self.macho.get_macho_for_arch(arch_name)

                    # Calculate architecture slice hash (if we can access the raw data)
                    arch_sha256 = None
                    arch_md5 = None
                    arch_sha1 = None

                    # For FAT binaries, try to get slice-specific info
                    if is_fat and arch_macho:
                        try:
                            # This would require access to the slice data
                            # For now, we'll use the general file info
                            arch_sha256 = general_info.get('SHA256', '') if general_info else ''
                            arch_md5 = general_info.get('MD5', '') if general_info else ''
                            arch_sha1 = general_info.get('SHA1', '') if general_info else ''
                        except Exception as e:
                            self.log.debug(f"Could not extract slice hash for {arch_name}: {e}")

                    architecture_info.append({
                        'architecture': arch_name,
                        'arch_sha256': arch_sha256,
                        'arch_md5': arch_md5,
                        'arch_sha1': arch_sha1,
                        'cputype': header_info.get('cputype') if header_info else None,
                        'cpusubtype': header_info.get('cpusubtype') if header_info else None,
                        'filetype': header_info.get('filetype') if header_info else None
                    })

                except Exception as e:
                    self.log.warning(f"Error extracting info for architecture {arch_name}: {e}")
                    continue

            # Create Universal dataclass
            macho_universal = MachOUniversal(
                is_fat=is_fat,
                architecture_count=len(architectures),
                architectures=architectures,
                architecture_info=architecture_info,
                fat_hash=self.sha256,
                fat_md5=self.md5,
                fat_sha1=self.sha1
            )

            return macho_universal

        except Exception as e:
            self.log.error(f"Error extracting MachO Universal info: {e}")
            return None

    def _extract_fat_architecture_mappings(self):
        """Extract detailed FAT binary architecture mappings for database relationships."""
        self.log.debug(inspect.currentframe().f_code.co_name)

        if not self.macho:
            return []

        try:
            # Parse at Universal level first
            self.macho.parse()

            # Get architectures using new API
            architectures = self.macho.get_architectures()
            if not architectures or len(architectures) <= 1:
                return []  # Not a FAT binary

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

            # For each architecture, create a mapping record
            for arch_name in architectures:
                try:
                    # Get general info
                    general_info = self.macho.get_general_info()

                    # Create mapping record for FAT binary architecture table
                    mapping = {
                        'fat_hash': self.sha256,  # SHA256 of the FAT binary
                        'architecture': arch_name,
                        'arch_sha256': general_info.get('SHA256', '') if general_info else '',  # Will need proper slice extraction
                        'arch_md5': general_info.get('MD5', '') if general_info else '',
                        'arch_sha1': general_info.get('SHA1', '') if general_info else '',
                        'arch_filename': f"{general_info.get('Filename', '')}.{arch_name}" if general_info else '',
                        'analysis_date': current_time
                    }
                    mappings.append(mapping)

                except Exception as e:
                    self.log.warning(f"Error creating mapping for architecture {arch_name}: {e}")
                    continue

            return mappings

        except Exception as e:
            self.log.error(f"Error extracting FAT architecture mappings: {e}")
            return []

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

    def extract_fat_binary_basic_properties_data(self):
        """Extract data needed for creating multiple BasicProperties records for FAT binaries.

        Returns:
            Tuple: (is_fat, fat_sha256, architectures_info) where:
                - is_fat: bool indicating if this is a FAT binary
                - fat_sha256: SHA256 of the FAT wrapper
                - architectures_info: dict with arch names and their hashes
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        if not self.macho:
            return False, None, {}

        try:
            # Parse at Universal level first
            self.macho.parse()

            # Get architectures using new API
            architectures = self.macho.get_architectures()
            if not architectures or len(architectures) <= 1:
                return False, None, {}  # Not a FAT binary

            # This is a FAT binary
            architectures_info = {}

            for arch_name in architectures:
                try:
                    # Get general info for this architecture
                    general_info = self.macho.get_general_info(arch=arch_name)

                    if general_info:
                        architectures_info[arch_name] = {
                            'sha256': general_info.get('SHA256', ''),
                            'md5': general_info.get('MD5', ''),
                            'sha1': general_info.get('SHA1', ''),
                            'filename': general_info.get('Filename', ''),
                            'filesize': general_info.get('Filesize', 0)
                        }
                except Exception as e:
                    self.log.warning(f"Error extracting info for architecture {arch_name}: {e}")
                    continue

            return True, self.sha256, architectures_info

        except Exception as e:
            self.log.error(f"Error extracting FAT binary data: {e}")
            return False, None, {}

    def prepare_export_data(self, exporter_type: str) -> Any:
        if exporter_type == "ElasticsearchExporter":
            return self.extract()
        elif exporter_type == "ClickHouseExporter":
            universal_info = self.extract()
            if universal_info is None:
                return None

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

            # Get architecture info for the binary
            try:
                if universal_info.is_fat:
                    # For FAT binaries, architecture fields should be NULL since it contains multiple
                    architecture_raw = None
                    architecture_str = None
                else:
                    # For single-arch binaries, get the actual architecture info
                    header_info = self.macho.get_macho_header()
                    architecture_raw = header_info.get('cputype', 0) if header_info else 0
                    architecture_str = universal_info.architectures[0] if universal_info.architectures else None
            except Exception as e:
                self.log.warning(f"Could not get architecture info for binary: {e}")
                architecture_raw = None
                architecture_str = None

            # Main Universal binary record
            data.append([
                self.sha256,                              # sha256
                self.md5,                                 # md5
                self.sha1,                                # sha1
                None,                                     # parent_sha256 (always None for main FAT binary)
                architecture_raw,                         # architecture (raw CPU type)
                architecture_str,                         # architecture_str (human-readable)
                universal_info.is_fat,                    # is_fat
                universal_info.architecture_count,       # architecture_count
                universal_info.architectures,            # architectures (array)
                json.dumps(universal_info.architecture_info[0] if len(universal_info.architecture_info) == 1 else {"architectures": universal_info.architecture_info}) if universal_info.architecture_info else None,  # architecture_info (JSON)
                current_time,                             # analysis_date
            ])

            column_names = [
                'sha256', 'md5', 'sha1', 'parent_sha256', 'architecture', 'architecture_str',
                'is_fat', 'architecture_count', 'architectures', 'architecture_info',
                'analysis_date'
            ]

            column_type_names = [
                'FixedString(64)', 'FixedString(32)', 'FixedString(40)',
                'Nullable(FixedString(64))', 'Nullable(UInt32)', 'LowCardinality(Nullable(String))',
                'UInt8', 'UInt32', 'Array(LowCardinality(String))', 'JSON',
                'DateTime64(3, \'UTC\')'
            ]

            return (data, column_names, column_type_names)

        return None

    def prepare_fat_architecture_export_data(self) -> Any:
        """Prepare export data for the FAT binary architecture mapping table."""
        mappings = self._extract_fat_architecture_mappings()
        if not mappings:
            return None

        data = []
        for mapping in mappings:
            data.append([
                mapping['fat_hash'],
                mapping['architecture'],
                mapping['arch_sha256'],
                mapping['arch_md5'],
                mapping['arch_sha1'],
                mapping['arch_filename'],
                mapping['analysis_date'],
            ])

        column_names = [
            'fat_hash', 'architecture', 'arch_sha256', 'arch_md5', 'arch_sha1',
            'arch_filename', 'analysis_date'
        ]

        column_type_names = [
            'FixedString(64)', 'LowCardinality(String)', 'FixedString(64)',
            'FixedString(32)', 'FixedString(40)', 'String',
            'DateTime64(3, \'UTC\')'
        ]

        return (data, column_names, column_type_names)

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

    # def get_fat_architecture_table(self) -> str:
    #     """Return table name for FAT binary architecture mappings."""
    #     return "redb_fat_binary_architectures"