Nadir Kapetanovic

16 papers A 1C 1Journal 7Unranked 6
YearRankTypeTitle / Venue / Authors
2025 conf
WACV (Workshops)
Matej Fabijanic, Maja Magdalenic, Juraj Obradovic, Nadir Kapetanovic, Fausto Ferreira, Nikola Miskovic
2024 conf
WACV (Workshops)
Benjamin Kiefer, Lojze Zust, Matej Kristan, Janez Pers, Matija Tersek, Arnold Wiliem, Martin Messmer, Cheng-Yen Yang, Hsiang-Wei Huang, Zhongyu Jiang, Heng-Cheng Kuo, Jie Mei, Jenq-Neng Hwang, Daniel Stadler, Lars Sommer, Kaer Huang, Aiguo Zheng, Weitu Chong, Kanokphan Lertniphonphan, Jun Xie, Feng Chen, Jian Li, Zhepeng Wang, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Tuan-Anh Vu, Hai Nguyen-Truong, Tan-Sang Ha, Quan-Dung Pham, Sai-Kit Yeung, Yuan Feng, Nguyen Thanh Thien, Lixin Tian, Sheng-Yao Kuan, Yuan-Hao Ho, Ángel Bueno Rodríguez, Borja Carrillo-Perez, Alexander Klein, Antje Alex, Yannik Steiniger, Felix Sattler, Edgardo Solano-Carrillo, Matej Fabijanic, Magdalena Sumunec, Nadir Kapetanovic, Andreas Michel, Wolfgang Gross, Martin Weinmann
2024 J jnl
CoRR
Matej Fabijanic, Nadir Kapetanovic, Nikola Miskovic
2023
Nadir Kapetanovic
2023 J jnl
CoRR
Benjamin Kiefer, Lojze Zust, Matej Kristan, Janez Pers, Matija Tersek, Arnold Wiliem, Martin Messmer, Cheng-Yen Yang, Hsiang-Wei Huang, Zhongyu Jiang, Heng-Cheng Kuo, Jie Mei, Jenq-Neng Hwang, Daniel Stadler, Lars Sommer, Kaer Huang, Aiguo Zheng, Weitu Chong, Kanokphan Lertniphonphan, Jun Xie, Feng Chen, Jian Li, Zhepeng Wang, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Tuan-Anh Vu, Hai Nguyen-Truong, Tan-Sang Ha, Quan-Dung Pham, Sai-Kit Yeung, Yuan Feng, Nguyen Thanh Thien, Lixin Tian, Sheng-Yao Kuan, Yuan-Hao Ho, Ángel Bueno Rodríguez, Borja Carrillo-Perez, Alexander Klein, Antje Alex, Yannik Steiniger, Felix Sattler, Edgardo Solano-Carrillo, Matej Fabijanic, Magdalena Sumunec, Nadir Kapetanovic, Andreas Michel, Wolfgang Gross, Martin Weinmann
2022 J jnl
Sensors
Waseem Akram, Alessandro Casavola, Nadir Kapetanovic, Nikola Miskovic
2022 C conf
IAS
Nadir Kapetanovic, Dula Nad, Ivan Loncar, Vladimir Slosic, Nikola Miskovic
2022 J jnl
Sensors
Nadir Kapetanovic, Jurica Goricanec, Ivo Vatavuk, Ivan Hrabar, Dario Stuhne, Goran Vasiljevic, Zdenko Kovacic, Nikola Miskovic, Nenad Antolovic, Marina Anic, Bernard Kozina
2021 conf
ConTEL
Jurica Goricanec, Nadir Kapetanovic, Ivo Vatavuk, Ivan Hrabar, Goran Vasiljevic, Gordan Gledec, Dario Stuhne, Stjepan Bogdan, Matko Orsag, Tamara Petrovic, Nikola Miskovic, Zdenko Kovacic, Antonia Kurtela, Jaksa Bolotin, Valter Kozul, Niksa Glavic, Nenad Antolovic, Marina Anic, Bernard Kozina, Marko Cukon
2021 conf
MIPRO
Goran Borkovic, Matej Fabijanic, Maja Magdalenic, Andro Malobabic, Jura Vukovic, Igor Zielinski, Nadir Kapetanovic, Igor Kvasic, Anja Babic, Nikola Miskovic
2020 conf
DCAI (Special Sessions)
Nadir Kapetanovic, Antonio Vasilijevic, Krunoslav Zubcic
2020 J jnl
Remote. Sens.
Nadir Kapetanovic, Branko Kordic, Antonio Vasilijevic, Dula Nad, Nikola Miskovic
2020 J jnl
Remote. Sens.
Nadir Kapetanovic, Antonio Vasilijevic, Dula Nad, Krunoslav Zubcic, Nikola Miskovic
2018 J jnl
Annu. Rev. Control.
Nadir Kapetanovic, Nikola Miskovic, Adnan Tahirovic, Marco Bibuli, Massimo Caccia
2018 conf
MED
Nadir Kapetanovic, Nikola Miskovic, Adnan Tahirovic
2015 A conf
IROS
Nadir Kapetanovic, Adnan Tahirovic, GianAntonio Magnani
docs/macho_extractors_README.md
← Index docs/macho_extractors_README.md markdown
# MachO Extractors for RedB

This document describes the MachO extractors implementation for the RedB binary analysis framework.

## Overview

The MachO extractors provide comprehensive analysis capabilities for Mach-O binaries (macOS, iOS, watchOS, tvOS executables) following the same pattern as the existing PE extractors. The implementation uses the `machofile` library located in the `docs/` folder.

## Architecture

### Main Components

1. **MachOExtractor** (`redb/extractors/macho_extractor.py`)
   - Abstract base class for all MachO extractors
   - Handles MachO file parsing and common functionality
   - Supports both single-architecture and Universal/FAT binaries

2. **Individual Extractors** (`redb/extractors/macho_extractors/`)
   - `macho_features.py` - Basic MachO header and metadata
   - `macho_segments.py` - Segment information and analysis
   - `macho_imports.py` - Imported functions and libraries
   - `macho_exports.py` - Exported symbols
   - `macho_dylibs.py` - Dynamic library dependencies
   - `macho_signature.py` - Code signing information

3. **Data Models** (`redb/models/dataclasses.py`)
   - MachO-specific dataclasses for structured data storage
   - Compatible with Elasticsearch and ClickHouse exporters

## Features

### Supported Binary Types
- Single-architecture Mach-O binaries (32-bit and 64-bit)
- Universal/FAT binaries with multiple architectures
- All major CPU architectures (x86, x86_64, ARM, ARM64)

### Extracted Information

#### MachO Features
- Header information (magic, CPU type, file type, flags)
- Architecture detection
- Entry point information
- UUID
- Version information
- Signing status
- Encryption status
- Counts (segments, dylibs, imports, exports)

#### Segments
- Segment names and properties
- Virtual addresses and sizes
- File offsets and sizes
- Protection flags
- Entropy calculation
- Segment hashes (MD5, SHA256)

#### Imports
- Imported function names
- Library dependencies
- Import counts and statistics

#### Exports
- Exported symbol names
- Export counts and statistics

#### Dynamic Libraries
- Dylib names and paths
- Version information
- Timestamps
- Load command types

#### Code Signing
- Signing status
- Certificate information
- Entitlements
- Code directory details

## Usage

### Basic Usage

```python
from redb.extractors.macho_extractors import MachOFeaturesExtractor

# Create extractor
extractor = MachOFeaturesExtractor(
    filepath="/path/to/macho/binary",
    log=logger
)

# Extract data
features = extractor.extract()

# Export to databases
extractor.export_data()
```

### Testing

Use the provided test script to verify functionality:

```bash
python test_macho_extractors.py /path/to/macho/binary
```

## Implementation Details

### Universal Binary Support

The extractors handle Universal/FAT binaries by:
1. Detecting FAT binary format
2. Extracting individual architectures
3. Providing unified interface for both single and multi-arch binaries
4. Supporting architecture-specific extraction

### Error Handling

- Graceful handling of malformed binaries
- Comprehensive logging for debugging
- Fallback mechanisms for missing data
- Exception handling for corrupted files

### Performance Considerations

- Lazy parsing of MachO structures
- Efficient memory usage for large binaries
- Cached property access for repeated queries
- Optimized data extraction patterns

## Integration

### Database Exporters

The extractors support both Elasticsearch and ClickHouse exporters:

- **Elasticsearch**: JSON document storage with full-text search
- **ClickHouse**: Columnar storage for analytical queries

### Schema Compatibility

All extractors follow the established schema patterns:
- Consistent field naming
- Proper data types
- Timestamp handling
- Hash field inclusion

## Future Enhancements

Potential areas for improvement:

1. **Additional Extractors**
   - MachO resources extraction
   - Symbol table analysis
   - Relocation information
   - Thread state analysis

2. **Enhanced Analysis**
   - Malware detection patterns
   - Behavioral analysis
   - Similarity hashing
   - YARA rule integration

3. **Performance Optimizations**
   - Parallel processing for multi-arch binaries
   - Streaming data processing
   - Memory-mapped file access

## Dependencies

- `machofile` library (included in `docs/`)
- Standard Python libraries (hashlib, datetime, etc.)
- RedB framework components

## Contributing

When adding new MachO extractors:

1. Follow the established pattern in existing extractors
2. Add appropriate dataclasses to `dataclasses.py`
3. Update the enum tags in `enum.py`
4. Include comprehensive error handling
5. Add tests for new functionality
6. Update this documentation

## Troubleshooting

### Common Issues

1. **Import Errors**: Ensure `machofile` library is accessible
2. **Memory Issues**: Large Universal binaries may require significant memory
3. **Corrupted Files**: Malformed MachO files may cause parsing errors
4. **Architecture Mismatch**: Some features may not be available for all architectures

### Debugging

Enable debug logging to see detailed extraction process:

```python
import logging
logging.basicConfig(level=logging.DEBUG)
```

## License

This implementation follows the same license as the main RedB project.