Nanne van Noord

60 papers A* 7A 3B 1Journal 29Unranked 20
YearRankTypeTitle / Venue / Authors
2026 conf
EACL (Findings)
Carlo Bretti, Pascal Mettes, Nanne van Noord
2025 conf
FAccT
Tim Alpherts, Sennay Ghebreab, Nanne van Noord
2025 J jnl
CoRR
Tim Alpherts, Sennay Ghebreab, Nanne van Noord
2025 A* conf
AAAI
Tim Alpherts, Sennay Ghebreab, Nanne van Noord
2025 J jnl
CoRR
Tim Alpherts, Sennay Ghebreab, Nanne van Noord
2025 A* conf
ICLR
Ivona Najdenkoska, Mohammad Mahdi Derakhshani, Yuki M. Asano, Nanne van Noord, Marcel Worring, Cees G. M. Snoek
2025 J jnl
CoRR
Nanne van Noord, Noa Garcia
2024 conf
>ECCV Workshops (6)
Selina Khan, Nanne van Noord
2024 J jnl
CoRR
Selina J. Khan, Nanne van Noord
2024 A conf
BMVC
Sam Titarsolej, Neil Cohn, Nanne van Noord
2024 J jnl
CoRR
Carlo Bretti, Pascal Mettes, Hendrik Vincent Koops, Daan Odijk, Nanne van Noord
2024 conf
MMM (2)
Carlo Bretti, Pascal Mettes, Hendrik Vincent Koops, Daan Odijk, Nanne van Noord
2024 A* conf
NeurIPS
Jiayi Shen, Qi Wang, Zehao Xiao, Nanne van Noord, Marcel Worring
2024 J jnl
CoRR
Jiayi Shen, Qi (Cheems) Wang, Zehao Xiao, Nanne van Noord, Marcel Worring
2024 J jnl
Trans. Mach. Learn. Res.
Sarah Ibrahimi, Mina Ghadimi Atigh, Nanne van Noord, Pascal Mettes, Marcel Worring
2024 conf
FAccT
Tim Alpherts, Sennay Ghebreab, Yen-Chia Hsu, Nanne van Noord
2024 J jnl
CoRR
Selina J. Khan, Nanne van Noord
2024 J jnl
CoRR
Ivona Najdenkoska, Mohammad Mahdi Derakhshani, Yuki M. Asano, Nanne van Noord, Marcel Worring, Cees G. M. Snoek
2023 conf
CHR
Alexandra Barancová, Melvin Wevers, Nanne van Noord
2023 J jnl
CoRR
Alexandra Barancová, Melvin Wevers, Nanne van Noord
2023 A* conf
ICCV
Teng Long, Nanne van Noord
2023 conf
CVPR Workshops
Sadaf Gulshad, Teng Long, Nanne van Noord
2023 conf
XAI4CV
Sadaf Gulshad, Teng Long, Nanne van Noord
2023 J jnl
CoRR
Sadaf Gulshad, Teng Long, Nanne van Noord
2023 J jnl
Comput. Vis. Image Underst.
Gjorgji Strezoski, Nanne van Noord, Marcel Worring
2023 A* conf
ICCV
Nanne van Noord
2023 J jnl
CoRR
Nanne van Noord
2022 J jnl
Digit. Scholarsh. Humanit.
Nanne van Noord
2022 J jnl
CoRR
Nanne van Noord, Melvin Wevers, Tobias Blanke, Julia Noordegraaf, Marcel Worring
2022 conf
ECIR (1)
Mariya Hendriksen, Maurits J. R. Bleeker, Svitlana Vakulenko, Nanne van Noord, Ernst Kuiper, Maarten de Rijke
2022 A* conf
CVPR
Mina Ghadimi Atigh, Julian Schoep, Erman Acar, Nanne van Noord, Pascal Mettes
2022 J jnl
CoRR
Mina Ghadimi Atigh, Julian Schoep, Erman Acar, Nanne van Noord, Pascal Mettes
2022 conf
CHR
Lisa Saleh, Nanne van Noord
2022 J jnl
CoRR
Nikolaos-Antonios Ypsilantis, Noa Garcia, Guangxing Han, Sarah Ibrahimi, Nanne van Noord, Giorgos Tolias
2021 conf
ICAART (1)
Nanne van Noord, Christian Gosvig Olesen, Roeland Ordelman, Julia Noordegraaf
2021 J jnl
CoRR
Mariya Hendriksen, Maurits J. R. Bleeker, Svitlana Vakulenko, Nanne van Noord, Ernst Kuiper, Maarten de Rijke
2021 A conf
BMVC
Sarah Ibrahimi, Nanne van Noord, Tim Alpherts, Marcel Worring
2021 J jnl
CoRR
Sarah Ibrahimi, Nanne van Noord, Tim Alpherts, Marcel Worring
2021 A conf
BMVC
Selina J. Khan, Nanne van Noord
2021 conf
NeurIPS Datasets and Benchmarks
Nikolaos-Antonios Ypsilantis, Noa Garcia, Guangxing Han, Sarah Ibrahimi, Nanne van Noord, Giorgos Tolias
2020 J jnl
Digit. Humanit. Q.
Eef Masson, Christian Gosvig Olesen, Nanne van Noord, Giovanna Fossati
2020 conf
MMM (1)
Gjorgji Strezoski, Rogier Knoester, Nanne van Noord, Marcel Worring
2019 conf
SUMAC @ ACM Multimedia
Samarth Bhargav, Nanne van Noord, Jaap Kamps
2019 conf
ICCV Workshops
Sarah Ibrahimi, Nanne van Noord, Zeno J. M. H. Geradts, Marcel Worring
2019 conf
ICCV Workshops
Laurens Samson, Nanne van Noord, Olaf Booij, Michael Hofmann, Efstratios Gavves, Mohsen Ghafoorian
2019 J jnl
CoRR
Laurens Samson, Nanne van Noord, Olaf Booij, Michael Hofmann, Efstratios Gavves, Mohsen Ghafoorian
2019 B conf
ICMR
Gjorgji Strezoski, Nanne van Noord, Marcel Worring
2019 J jnl
CoRR
Gjorgji Strezoski, Nanne van Noord, Marcel Worring
2019 A* conf
ICCV
Gjorgji Strezoski, Nanne van Noord, Marcel Worring
2019 J jnl
CoRR
Gjorgji Strezoski, Nanne van Noord, Marcel Worring
2019 conf
ICCV Workshops
Maximilian Müller-Eberstein, Nanne van Noord
2019 J jnl
CoRR
Maximilian Müller-Eberstein, Nanne van Noord
2018 J jnl
CoRR
Nanne van Noord, Eric O. Postma
2017 conf
ICCV Workshops
Nanne van Noord, Eric O. Postma
2017 J jnl
Pattern Recognit.
Nanne van Noord, Eric O. Postma
2016 J jnl
CoRR
Nanne van Noord, Eric O. Postma
2015 J jnl
CoRR
Nanne van Noord, Eric O. Postma
2015 J jnl
IEEE Signal Process. Mag.
Nanne van Noord, Ella Hendriks, Eric O. Postma
2014 conf
ICGI
Menno van Zaanen, Nanne van Noord
2012 conf
ICGI
Menno van Zaanen, Nanne van Noord
redb/extractors/macho_extractors/macho_imports.py
← Index redb/extractors/macho_extractors/macho_imports.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
from redb.models.dataclasses import MachOImport


class MachOImportExtractor(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_imports"
        self.log.debug(inspect.currentframe().f_code.co_name)

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

    def _extract_imports(self, arch_name=None):
        """Extract import information from the MachO binary for a specific architecture.

        Handles machofile v2026.2.4+ API where get_imported_functions() returns:
        Dict[str, List[Dict]] where each dict has {'name': str, 'sources': [str, ...]}
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        if not self.macho:
            return None

        try:
            # Get imported functions using API for specific architecture
            imported_functions = self.macho.get_imported_functions(arch=arch_name)
            if not imported_functions:
                return None

            # Keep the library→functions mapping (like PE does)
            library_names = []
            imports_with_mapping = []  # List of {library: [(name, source), ...]}

            for dylib_name, functions in imported_functions.items():
                # v2026.2.4+: dylib_name is already str, but handle bytes for compatibility
                if isinstance(dylib_name, bytes):
                    dylib_name = dylib_name.decode('utf-8', errors='replace')
                library_names.append(dylib_name)

                # Process function entries
                func_list = []
                for func_entry in functions:
                    # v2026.2.4+: func_entry is {'name': str, 'sources': [str, ...]}
                    if isinstance(func_entry, dict):
                        func_name = func_entry.get('name', '')
                        # Join sources if multiple, take first if single
                        sources = func_entry.get('sources', [])
                        import_source = sources[0] if sources else None
                        func_list.append((func_name, import_source))
                    else:
                        # Legacy format: func_entry is str or bytes
                        if isinstance(func_entry, bytes):
                            func_entry = func_entry.decode('utf-8', errors='replace')
                        func_list.append((func_entry, None))

                imports_with_mapping.append({dylib_name: func_list})

            # Count total functions
            total_functions = sum(len(list(d.values())[0]) for d in imports_with_mapping)

            # Create import dataclass with mapping preserved
            macho_import = MachOImport(
                macho_imports_total=total_functions,
                macho_import_libraryName=library_names if library_names else None,
                macho_import_functions=imports_with_mapping if imports_with_mapping else None
            )

            return macho_import

        except Exception as e:
            self.log.error(f"Error extracting MachO imports for arch {arch_name}: {e}")
            return None

    def extract(self):
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            # Get architectures (macho is already parsed in base class)
            architectures = self.macho.get_architectures()
            if len(architectures) > 1:
                # FAT binary - return list of imports for each architecture
                results = []
                for arch_name in architectures:
                    imports = self._extract_imports(arch_name)
                    if imports:
                        imports.arch_identifier = arch_name
                        results.append(imports)
                return results
            else:
                # Single architecture - return single result
                return self._extract_imports(architectures[0] if architectures else None)
        except Exception as e:
            self.log.error(f"Error extracting MachO imports: {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

            # Flatten the data - one row per function import (like PE imports)
            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 imports for this architecture
                macho_import = self._extract_imports(arch_name)
                if not macho_import or not macho_import.macho_import_functions:
                    continue

                # Flatten to one row per (library, function) pair
                for lib_funcs in macho_import.macho_import_functions:
                    for lib, funcs in lib_funcs.items():
                        for func_name, import_source in funcs:
                            data.append([
                                arch_sha256,        # sha256 (arch-specific)
                                lib,                # library_name
                                func_name,          # function_name
                                import_source,      # import_source (chained_fixups, bind_opcodes, symtab)
                                current_time,       # analysis_date
                            ])

            column_names = [
                'sha256',
                'library_name', 'function_name', 'import_source',
                'analysis_date'
            ]

            if not data:
                return None

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

            return (data, column_names, column_type_names)

        return None

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