Waldo Nogueira

27 papers A 2Misc 4Journal 13Unranked 8
YearRankTypeTitle / Venue / Authors
2025 Misc conf
ICASSP
Tom Gajecki, Waldo Nogueira
2025 J jnl
IEEE Trans. Biomed. Eng.
Yixuan Zhang, Daniel Kipping, Waldo Nogueira
2025 J jnl
IEEE Trans. Biomed. Eng.
Fynn Bensel, Daniel Kipping, Marlis Reiber, Yixuan Zhang, Udo Nackenhorst, Waldo Nogueira
2024 J jnl
IEEE Trans. Biomed. Eng.
Daniel Kipping, Yixuan Zhang, Waldo Nogueira
2024 J jnl
IEEE Trans. Biomed. Eng.
Tom Gajecki, Waldo Nogueira
2023 J jnl
IEEE Trans. Biomed. Eng.
Tom Gajecki, Yichi Zhang, Waldo Nogueira
2023 J jnl
Frontiers Neuroinformatics
Franklin Alvarez Cardinale, Daniel Kipping, Waldo Nogueira
2023 J jnl
IEEE ACM Trans. Audio Speech Lang. Process.
Tom Gajecki, Waldo Nogueira
2022 Misc conf
ICASSP
Tom Gajecki, Waldo Nogueira
2022 A conf
INTERSPEECH
Franklin Alvarez Cardinale, Waldo Nogueira
2021 conf
ISBI
Hendrik Hachmann, Benjamin Krüger, Bodo Rosenhahn, Waldo Nogueira
2021 J jnl
CoRR
Hendrik Hachmann, Benjamin Krüger, Bodo Rosenhahn, Waldo Nogueira
2020 J jnl
IEEE Trans. Biomed. Eng.
Waldo Nogueira, Giulio Cosatti, Irina Schierholz, Maria Egger, Bojana Mirkovic, Andreas Büchner
2020 Misc conf
ICASSP
Waldo Nogueira, Hanna Dolhopiatenko
2019 conf
EMBC
Reemt Hinrichs, Tom Gajecki, Jörn Ostermann, Waldo Nogueira
2019 J jnl
IEEE Signal Process. Mag.
Waldo Nogueira, Anil M. Nagathil, Rainer Martin
2018 conf
ITG Symposium on Speech Communication
Tom Gajecki, Waldo Nogueira
2018 J jnl
J. Intell. Inf. Syst.
Gerard Roma, Perfecto Herrera, Waldo Nogueira
2016 conf
ITG Symposium on Speech Communication
Waldo Nogueira, Tom Gajecki, Benjamin Krüger, Jordi Janer, Andreas Büchner
2015 Misc conf
ICASSP
Waldo Nogueira, Marta Lopez, Thilo Rode, Simon Doclo, Andreas Büchner
2013 conf
WASPAA
Gerard Roma, Waldo Nogueira, Perfecto Herrera
2012 conf
EUSIPCO
Waldo Nogueira, Andreas Büchner
2011 conf
ISABEL
Waldo Nogueira, Martín Haro, Perfecto Herrera, Xavier Serra
2009 J jnl
EURASIP J. Adv. Signal Process.
Waldo Nogueira, Leonid M. Litvak, Bernd Edler, Jörn Ostermann, Andreas Büchner
2007 A conf
INTERSPEECH
Waldo Nogueira, Tamás Harczos, Bernd Edler, Jörn Ostermann, Andreas Büchner
2006 conf
ICASSP (5)
Waldo Nogueira, Andreas Giese, Bernd Edler, Andreas Büchner
2005 J jnl
EURASIP J. Adv. Signal Process.
Waldo Nogueira, Andreas Büchner, Thomas Lenarz, Bernd Edler
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"