Nathan Salomonis

18 papers Journal 14Unranked 4
YearRankTypeTitle / Venue / Authors
2023 J jnl
Bioinform.
Kyle Ferchen, Nathan Salomonis, H. Leighton Grimes
2022 J jnl
Briefings Bioinform.
Kang Jin, Daniel J. Schnell, Guangyuan Li, Nathan Salomonis, V. B. Surya Prasath, Rhonda Szczesniak, Bruce J. Aronow
2021 J jnl
Briefings Bioinform.
Guangyuan Li, Balaji Iyer, V. B. Surya Prasath, Yizhao Ni, Nathan Salomonis
2021 J jnl
PLoS Comput. Biol.
Derek Reiman, Godhev Kumar Manakkat Vijay, Heping Xu, Andrew Sonin, Dianyu Chen, Nathan Salomonis, Harinder Singh, Aly A. Khan
2020 J jnl
Bioinform.
Meenakshi Venkatasubramanian, Kashish Chetal, Daniel J. Schnell, Gowtham Atluri, Nathan Salomonis
2016 J jnl
Nat.
Andre Olsson, Meenakshi Venkatasubramanian, Viren K. Chaudhri, Bruce J. Aronow, Nathan Salomonis, Harinder Singh, H. Leighton Grimes
2014 J jnl
PLoS Comput. Biol.
Lilach Soreq, Alessandro Guffanti, Nathan Salomonis, Alon Simchovitz, Zvi Israel, Hagai Bergman, Hermona Soreq
2014 J jnl
BMC Bioinform.
Zhuohui Gan, Jianwu Wang, Nathan Salomonis, Jennifer C. Stowe, Gabriel G. Haddad, Andrew D. McCulloch, Ilkay Altintas, Alexander C. Zambon
2013 J jnl
Bioinform.
Inna Dubchak, Matthew Munoz, Alexander Poliakov, Nathan Salomonis, Simon Minovitsky, Rolf Bodmer, Alexander C. Zambon
2012 conf
HISB
Nathan Salomonis
2012 J jnl
Bioinform.
Alexander C. Zambon, Stan Gaj, Isaac Ho, Kristina Hanspers, Karen Vranizan, Chris T. A. Evelo, Bruce R. Conklin, Alexander R. Pico, Nathan Salomonis
2012 conf
HISB
Nathan Salomonis
2012 conf
HISB
Zhuohui Gan, Jianwu Wang, Nathan Salomonis, Ilkay Altintas, Andrew D. McCulloch, Alexander C. Zambon
2012 J jnl
Bioinform.
Chao Zhang, Kristina Hanspers, Allan Kuchinsky, Nathan Salomonis, Dong Xu, Alexander R. Pico
2010 J jnl
Nucleic Acids Res.
Dorothea Emig, Nathan Salomonis, Jan Baumbach, Thomas Lengauer, Bruce R. Conklin, Mario Albrecht
2009 J jnl
PLoS Comput. Biol.
Nathan Salomonis, Brandon Nelson, Karen Vranizan, Alexander R. Pico, Kristina Hanspers, Allan Kuchinsky, Linda Ta, Mark Mercola, Bruce R. Conklin
2007 J jnl
BMC Bioinform.
Nathan Salomonis, Kristina Hanspers, Alexander C. Zambon, Karen Vranizan, Steven C. Lawlor, Kam D. Dahlquist, Scott Doniger, Joshua M. Stuart, Bruce R. Conklin, Alexander R. Pico
2005 conf
ISMB (Supplement of Bioinformatics)
Melissa S. Cline, John Blume, Simon Cawley, Tyson Clark, Jing-Shan Hu, Gang Lu, Nathan Salomonis, Hui Wang, Alan Williams
redb/extractors/macho_extractors/macho_similarity_hashes.py
← Index redb/extractors/macho_extractors/macho_similarity_hashes.py python
import inspect
from datetime import datetime, timezone
from typing import Any

from redb.extractors.enum import Tag
from redb.extractors.macho_extractor import MachOExtractor


class MachOSimilarityHashExtractor(MachOExtractor):
    """Extract Mach-O similarity hashes using machofile API.

    Similarity hashes are MD5 fingerprints of sorted, deduplicated binary components:
    - dylib_hash: MD5 of dynamic library names
    - import_hash: MD5 of imported function names
    - export_hash: MD5 of exported symbol names
    - entitlement_hash: MD5 of entitlement names and array values
    - symhash: MD5 of external undefined symbols

    For FAT binaries:
    - Inserts one row per architecture slice with per-slice hashes
    - Inserts one row for the FAT container with combined hashes

    For single-arch binaries:
    - Inserts one row with that architecture's hashes

    Note: parent_sha256 and architecture relationships are tracked in redb_basic_properties,
    not duplicated here. Use JOIN with redb_basic_properties when needed.
    """

    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_hashes"
        self.log.debug(inspect.currentframe().f_code.co_name)

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

    def _extract_similarity_hashes(self, arch_name=None):
        """Extract similarity hashes for a specific architecture."""
        self.log.debug(inspect.currentframe().f_code.co_name)

        if not self.macho:
            return None

        try:
            similarity_hashes = self.macho.get_similarity_hashes(arch=arch_name)
            return similarity_hashes if similarity_hashes else None
        except Exception as e:
            self.log.error(f"Error extracting similarity hashes for arch {arch_name}: {e}")
            return None

    def extract(self):
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            if not self.macho:
                return None

            architectures = self.macho.get_architectures()
            if not architectures:
                return None

            if len(architectures) > 1:
                # FAT binary - return combined hashes + per-arch hashes
                results = []

                # First add combined hashes for the FAT container
                all_hashes = self.macho.get_similarity_hashes()
                combined_hashes = all_hashes.get('combined', {}) if all_hashes else {}
                if combined_hashes:
                    combined_hashes['arch_identifier'] = 'fat'
                    results.append(combined_hashes)

                # Then add per-arch hashes
                for arch_name in architectures:
                    hashes = self._extract_similarity_hashes(arch_name)
                    if hashes:
                        hashes['arch_identifier'] = arch_name
                        results.append(hashes)
                return results
            else:
                # Single architecture - return single result
                return self._extract_similarity_hashes(architectures[0])
        except Exception as e:
            self.log.error(f"Error extracting similarity hashes: {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

            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)

            # For FAT binaries, first insert a row for the container with combined hashes
            if is_fat:
                all_hashes = self.macho.get_similarity_hashes()  # Without arch returns all including 'combined'
                combined_hashes = all_hashes.get('combined', {}) if all_hashes else {}
                if combined_hashes:
                    data.append([
                        self.sha256,                                    # sha256 (FAT container)
                        combined_hashes.get('dylib_hash'),              # dylib_hash
                        combined_hashes.get('import_hash'),             # import_hash
                        combined_hashes.get('export_hash'),             # export_hash
                        combined_hashes.get('entitlement_hash'),        # entitlement_hash
                        combined_hashes.get('symhash'),                 # symhash
                        current_time,                                   # analysis_date
                    ])

            # Insert rows for each architecture slice
            for arch_name in architectures:
                # Get architecture-specific sha256
                try:
                    arch_general_info = self.macho.get_general_info(arch=arch_name)
                    arch_sha256 = arch_general_info.get('SHA256', self.sha256)
                except Exception as e:
                    self.log.warning(f"Could not get arch-specific sha256 for {arch_name}: {e}")
                    arch_sha256 = self.sha256

                # Get similarity hashes for this architecture
                similarity_hashes = self._extract_similarity_hashes(arch_name)
                if not similarity_hashes:
                    continue

                data.append([
                    arch_sha256,                                    # sha256 (arch-specific)
                    similarity_hashes.get('dylib_hash'),            # dylib_hash
                    similarity_hashes.get('import_hash'),           # import_hash
                    similarity_hashes.get('export_hash'),           # export_hash
                    similarity_hashes.get('entitlement_hash'),      # entitlement_hash
                    similarity_hashes.get('symhash'),               # symhash
                    current_time,                                   # analysis_date
                ])

            if not data:
                return None

            column_names = [
                'sha256',
                'macho_dylib_hash', 'macho_import_hash', 'macho_export_hash',
                'macho_entitlement_hash', 'macho_symhash',
                'analysis_date'
            ]

            column_type_names = [
                'FixedString(64)',
                'Nullable(FixedString(32))', 'Nullable(FixedString(32))', 'Nullable(FixedString(32))',
                'Nullable(FixedString(32))', 'Nullable(FixedString(32))',
                'DateTime64(3, \'UTC\')'
            ]

            return (data, column_names, column_type_names)

        return None

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