Valsamis Ntouskos

30 papers A* 3B 1C 3Journal 10Unranked 12
YearRankTypeTitle / Venue / Authors
2025 J jnl
CoRR
Dionysis Christopoulos, Sotiris Spanos, Eirini Baltzi, Valsamis Ntouskos, Konstantinos Karantzalos
2025 J jnl
IEEE Access
Dionysis Christopoulos, Sotiris Spanos, Valsamis Ntouskos, Konstantinos Karantzalos
2024 C conf
IGARSS
Sotiris Spanos, Christos Antoniou, Simon Vellas, Valsamis Ntouskos, Angelos Mallios, Paraskevi Nomikou, Konstantinos Karantzalos
2024 C conf
IGARSS
Sotiris Spanos, Valsamis Ntouskos, Konstantinos Karantzalos
2024 J jnl
CoRR
Dionysis Christopoulos, Sotiris Spanos, Valsamis Ntouskos, Konstantinos Karantzalos
2023 conf
AIRO@AI*IA
Melkon Chatsikian, Valsamis Ntouskos, Angelos Mallios, Konstantinos Karantzalos
2021 conf
IEEE BigData
Valsamis Ntouskos, Chrysa Iliopoulou, Konstantinos Karantzalos
2019 conf
IntelliSys (1)
Edoardo Alati, Lorenzo Mauro, Valsamis Ntouskos, Fiora Pirri
2019 J jnl
CoRR
Fiora Pirri, Lorenzo Mauro, Edoardo Alati, Valsamis Ntouskos, Mahdieh Izadpanahkakhk, Elham Omrani
2019 J jnl
CoRR
Lorenzo Mauro, Edoardo Alati, Marta Sanzari, Valsamis Ntouskos, Gianluca Massimiani, Fiora Pirri
2019 B conf
ICIP
Edoardo Alati, Lorenzo Mauro, Valsamis Ntouskos, Fiora Pirri
2019 J jnl
Sensors
Benjamin Franchetti, Valsamis Ntouskos, Pierluigi Giuliani, Tiara Herman, Luke Barnes, Fiora Pirri
2019 J jnl
CoRR
Lorenzo Mauro, Francesco Puja, Simone Grazioso, Valsamis Ntouskos, Marta Sanzari, Edoardo Alati, Fiora Pirri
2018 conf
ECCV Workshops (6)
Lorenzo Mauro, Edoardo Alati, Marta Sanzari, Valsamis Ntouskos, Gianluca Massimiani, Fiora Pirri
2018 conf
APPIS
Lorenzo Mauro, Francesco Puja, Simone Grazioso, Valsamis Ntouskos, Marta Sanzari, Edoardo Alati, Luigi Freda, Fiora Pirri
2017 J jnl
CoRR
Marta Sanzari, Valsamis Ntouskos, Simone Grazioso, Francesco Puja, Fiora Pirri
2017
Valsamis Ntouskos
2017 J jnl
CoRR
Francesco Puja, Simone Grazioso, Antonio Tammaro, Valsamis Ntouskos, Marta Sanzari, Fiora Pirri
2016 conf
ECCV Workshops (1)
Mahmoud Qodseya, Marta Sanzari, Valsamis Ntouskos, Fiora Pirri
2016 conf
ECCV (8)
Marta Sanzari, Valsamis Ntouskos, Fiora Pirri
2016 J jnl
CoRR
Valsamis Ntouskos, Fiora Pirri
2016 conf
SSRR
Ivana Kruijff-Korbayová, Luigi Freda, Mario Gianni, Valsamis Ntouskos, Václav Hlavác, Vladimir Kubelka, Erik Zimmermann, Hartmut Surmann, Kresimir Dulic, Wolfgang Rottner, Emanuele Gissi
2016 A* conf
CVPR
Fabrizio Natola, Valsamis Ntouskos, Fiora Pirri, Marta Sanzari
2015 A* conf
ICCV
Fabrizio Natola, Valsamis Ntouskos, Marta Sanzari, Fiora Pirri
2015 A* conf
ICCV
Valsamis Ntouskos, Marta Sanzari, Bruno Cafaro, Federico Nardi, Fabrizio Natola, Fiora Pirri, Manuel A. Ruiz Garcia
2015 conf
GRAPP
Bruno Cafaro, Iman Azimi, Valsamis Ntouskos, Fiora Pirri, Manuel A. Ruiz Garcia
2015 conf
SOCA
Giuseppe De Giacomo, Valsamis Ntouskos, Fabio Patrizi, Stavros Vassos, Davide Aversa
2013 C conf
ICPRAM
Valsamis Ntouskos, Panagiotis Papadakis, Fiora Pirri
2013 conf
ICPRAM (Selected Papers)
Valsamis Ntouskos, Panagiotis Papadakis, Fiora Pirri
2012 conf
VISAPP (1)
Valsamis Ntouskos, Panagiotis Papadakis, Fiora Pirri
tests/scripts/test_macho_extractors_local.py
← Index tests/scripts/test_macho_extractors_local.py python
#!/usr/bin/env python3
"""
Local MachO extractors test - test actual extractors without server connections
"""

import sys
import os
import logging
import hashlib
from datetime import datetime, timezone
from typing import Dict, Any, Optional
from unittest.mock import Mock, patch

# Add the redb directory to the path so we can import the extractors
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'redb'))

# Mock settings to avoid database connections
with patch.dict('os.environ', {'REDB_ENV': 'test'}):
    # Import the actual extractors
    from redb.extractors.macho_extractors.macho_features import MachOFeaturesExtractor
    from redb.extractors.macho_extractors.macho_segments import MachOSegmentExtractor
    from redb.extractors.macho_extractors.macho_imports import MachOImportExtractor
    from redb.extractors.macho_extractors.macho_exports import MachOExportExtractor
    from redb.extractors.macho_extractors.macho_dylibs import MachODylibExtractor
    from redb.extractors.macho_extractors.macho_signature import MachOSignatureExtractor
    from redb.extractors.macho_extractors.macho_universal import MachOUniversalExtractor

def setup_logging():
    """Setup basic logging configuration."""
    logging.basicConfig(
        level=logging.INFO,
        format='%(asctime)s - %(levelname)s - %(message)s'
    )
    return logging.getLogger(__name__)

class MockLogger:
    """Mock logger for testing without RedB dependencies."""
    def __init__(self):
        self.logger = logging.getLogger(__name__)
    
    def debug(self, msg):
        self.logger.debug(msg)
    
    def info(self, msg):
        self.logger.info(msg)
    
    def warning(self, msg):
        self.logger.warning(msg)
    
    def error(self, msg):
        self.logger.error(msg)

class MockExporter:
    """Mock exporter that does nothing."""
    def export(self, data):
        pass

def create_mock_extractor(extractor_class, filepath):
    """Create an extractor instance with mocked dependencies."""
    log = MockLogger()
    
    # Mock the exporters to avoid database connections
    mock_exporters = [MockExporter()]
    
    # Create the extractor with mocked dependencies
    extractor = extractor_class(
        filepath=filepath,
        log=log,
        exporters=mock_exporters,
        index_prefix="test",
        elastic_index="test_macho",
        known_benign=False,
        known_malicious=False
    )
    
    return extractor

def test_extractor(extractor_class, filepath, extractor_name):
    """Test a specific extractor."""
    log = setup_logging()
    log.info(f"Testing {extractor_name}...")
    
    try:
        # Create the extractor with mocked dependencies
        extractor = create_mock_extractor(extractor_class, filepath)
        
        if not extractor.macho:
            log.error(f"{extractor_name}: No MachO object created")
            return False

        # Test the actual extract method
        result = extractor.extract()
        
        if result:
            log.info(f"{extractor_name}: Successfully extracted data")
            print(f"\n{'='*60}")
            print(f"=== {extractor_name.upper()} RESULTS ===")
            print(f"{'='*60}")
            
            if isinstance(result, list):
                print(f"📊 Extracted {len(result)} items")
                print()
                for i, item in enumerate(result):
                    print(f"📦 Item {i+1}:")
                    print(f"   {'─'*40}")
                    # Handle dataclass objects in lists
                    if hasattr(item, '__dataclass_fields__'):
                        from dataclasses import asdict
                        item_dict = asdict(item)
                        for key, value in item_dict.items():
                            if isinstance(value, (list, dict)):
                                if isinstance(value, list):
                                    print(f"   🔹 {key}: List with {len(value)} items")
                                    print(f"      {value}")
                                elif isinstance(value, dict):
                                    print(f"   🔹 {key}: Dict with {len(value)} keys")
                                    for k, v in value.items():
                                        print(f"      {k}: {v}")
                            else:
                                print(f"   🔹 {key}: {value}")
                    else:
                        # Regular dict
                        for key, value in item.items():
                            if isinstance(value, (list, dict)):
                                if isinstance(value, list):
                                    print(f"   🔹 {key}: List with {len(value)} items")
                                    print(f"      {value}")
                                elif isinstance(value, dict):
                                    print(f"   🔹 {key}: Dict with {len(value)} keys")
                                    for k, v in value.items():
                                        print(f"      {k}: {v}")
                            else:
                                print(f"   🔹 {key}: {value}")
                    print()
            else:
                print("📊 Extracted data:")
                print()
                # Handle dataclass objects
                if hasattr(result, '__dataclass_fields__'):
                    # It's a dataclass, use dataclasses.asdict
                    from dataclasses import asdict
                    result_dict = asdict(result)
                    for key, value in result_dict.items():
                        if isinstance(value, (list, dict)):
                            if isinstance(value, list):
                                print(f"🔹 {key}: List with {len(value)} items")
                                print(f"   {value}")
                            elif isinstance(value, dict):
                                print(f"🔹 {key}: Dict with {len(value)} keys")
                                for k, v in value.items():
                                    print(f"   {k}: {v}")
                        else:
                            print(f"🔹 {key}: {value}")
                        print()
                else:
                    # It's a regular dict
                    for key, value in result.items():
                        if isinstance(value, (list, dict)):
                            if isinstance(value, list):
                                print(f"🔹 {key}: List with {len(value)} items")
                                print(f"   {value}")
                            elif isinstance(value, dict):
                                print(f"🔹 {key}: Dict with {len(value)} keys")
                                for k, v in value.items():
                                    print(f"   {k}: {v}")
                        else:
                            print(f"🔹 {key}: {value}")
                        print()
        else:
            log.warning(f"{extractor_name}: No data extracted")
            print(f"\n❌ {extractor_name}: No data extracted")
        
        return True
        
    except Exception as e:
        log.error(f"{extractor_name}: Error during extraction: {e}")
        import traceback
        traceback.print_exc()
        return False

def main():
    """Main function."""
    if len(sys.argv) < 2:
        print("Usage: python test_macho_extractors_local.py <macho_file> [extractor_name]")
        print("\nAvailable extractors:")
        print("  features    - Basic MachO header and metadata")
        print("  segments    - Segment information and analysis")
        print("  imports     - Imported functions and libraries")
        print("  exports     - Exported symbols")
        print("  dylibs      - Dynamic library dependencies")
        print("  signature   - Code signing information")
        print("  universal   - FAT/Universal binary information")
        print("  all         - Test all extractors")
        sys.exit(1)
    
    filepath = sys.argv[1]
    extractor_name = sys.argv[2] if len(sys.argv) > 2 else "all"
    
    if not os.path.exists(filepath):
        print(f"File not found: {filepath}")
        sys.exit(1)
    
    # Define extractors
    extractors = {
        'features': (MachOFeaturesExtractor, "MachO Features"),
        'segments': (MachOSegmentExtractor, "MachO Segments"),
        'imports': (MachOImportExtractor, "MachO Imports"),
        'exports': (MachOExportExtractor, "MachO Exports"),
        'dylibs': (MachODylibExtractor, "MachO Dylibs"),
        'signature': (MachOSignatureExtractor, "MachO Code Signature"),
        'universal': (MachOUniversalExtractor, "MachO Universal/FAT"),
    }
    
    if extractor_name == "all":
        print(f"Testing all extractors with file: {filepath}")
        success_count = 0
        for name, (extractor_class, display_name) in extractors.items():
            if test_extractor(extractor_class, filepath, display_name):
                success_count += 1
            print("-" * 50)
        
        print(f"\n✅ {success_count}/{len(extractors)} extractors completed successfully")
        
    elif extractor_name in extractors:
        extractor_class, display_name = extractors[extractor_name]
        success = test_extractor(extractor_class, filepath, display_name)
        
        if success:
            print(f"\n✅ {display_name} testing completed successfully")
        else:
            print(f"\n❌ {display_name} testing failed")
            sys.exit(1)
    else:
        print(f"Unknown extractor: {extractor_name}")
        print("Available extractors:", ", ".join(extractors.keys()) + ", all")
        sys.exit(1)

if __name__ == "__main__":
    main()