Hanbo Wu

21 papers A* 1A 1Misc 1Journal 16Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A conf
IMC
Yuhan Wu, Hanbo Wu, Xilai Liu, Yuxuan Tian, Yikai Zhao, Tong Yang, Rui Qiu, Kaicheng Yang, Sha Wang, Tao Li, Lihua Miao, Gaogang Xie
2025 J jnl
Eng. Appl. Artif. Intell.
Xiang Li, Lizhou Fan, Hanbo Wu, Kunping Chen, Xiaoxiao Yu, Chao Che, Zhifeng Cai, Xiuhong Niu, Aihua Cao, Xin Ma
2025 J jnl
Expert Syst. Appl.
Chuanxin Song, Hanbo Wu, Xin Ma
2025 J jnl
Signal Process. Image Commun.
Hanbo Wu, Xin Ma, Yibin Li
2024 J jnl
CoRR
Yuhan Wu, Hanbo Wu, Xilai Liu, Yikai Zhao, Tong Yang, Kaicheng Yang, Sha Wang, Lihua Miao, Gaogang Xie
2024 conf
ICIRA (5)
Hanbo Wu, Xin Ma
2024 J jnl
CoRR
Xiang Li, Lizhou Fan, Hanbo Wu, Kunping Chen, Xiaoxiao Yu, Chao Che, Zhifeng Cai, Xiuhong Niu, Aihua Cao, Xin Ma
2024 J jnl
Knowl. Based Syst.
Chuanxin Song, Hanbo Wu, Xin Ma
2024 A* conf
ICDE
Yuhan Wu, Hanbo Wu, Chengjun Jia, Bo Peng, Ziyun Zhang, Tong Yang, Peiqing Chen, Kaicheng Yang, Bin Cui
2024 J jnl
Pattern Recognit.
Chuanxin Song, Hanbo Wu, Xin Ma, Yi-Bin Li
2023 J jnl
CoRR
Chuanxin Song, Hanbo Wu, Xin Ma
2023 J jnl
Signal Process. Image Commun.
Hanbo Wu, Xin Ma, Yibin Li
2023 J jnl
CoRR
Chuanxin Song, Hanbo Wu, Xin Ma
2023 J jnl
CoRR
Chuanxin Song, Hanbo Wu, Xin Ma, Yibin Li
2022 J jnl
Neurocomputing
Haoyu Tian, Xin Ma, Hanbo Wu, Yi-Bin Li
2022 J jnl
IEEE Trans. Circuits Syst. Video Technol.
Hanbo Wu, Xin Ma, Yibin Li
2021 Misc conf
NSDI
Yikai Zhao, Kaicheng Yang, Zirui Liu, Tong Yang, Li Chen, Shiyi Liu, Naiqian Zheng, Ruixin Wang, Hanbo Wu, Yi Wang, Nicholas Zhang
2020 J jnl
IEEE Access
Shaocan Liu, Xin Ma, Hanbo Wu, Yibin Li
2020 J jnl
IEEE Trans. Multim.
Hanbo Wu, Xin Ma, Yibin Li
2019 J jnl
IEEE Access
Zhimeng Zhang, Xin Ma, Hanbo Wu, Yibin Li
2014 conf
ICCA
Lubo Geng, Xin Ma, Bingxia Xue, Hanbo Wu, Jason Jianjun Gu, Yibin Li
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"