Isabell Wochner

11 papers Misc 1Journal 6Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Frontiers Comput. Neurosci.
Pablo Filipe Santana Chacon, Isabell Wochner, Maria Hammer, Jochen Martin Eppler, Susanne Kunkel, Syn Schmitt
2025 conf
ICORR
Winfried Ilg, Isabell Wochner, Jhon P. F. Charaja, Veronika Hofmann, Ole Strenge, Melanie Adam, Regine Lendway, Jan Kerner, Bhavya Deep Vashisht, Marko Ackermann, Friedemann Bunjes, Urs Schneider, Martin A. Giese, Andreas Bulling, Syn Schmitt, Christophe Maufroy, Daniel F. B. Haeufle
2024 conf
BioRob
Isabell Wochner, Tobias Nadler, Katrin Stollenmaier, Christina Pley, Winfried Ilg, Simon Wolfen, Syn Schmitt, Daniel F. B. Haeufle
2024 conf
BioRob
Jhon Charaja, Isabell Wochner, Pierre Schumacher, Winfried Ilg, Martin A. Giese, Christophe Maufroy, Andreas Bulling, Syn Schmitt, Georg Martius, Daniel F. B. Haeufle
2024 J jnl
CoRR
Jhon Charaja, Isabell Wochner, Pierre Schumacher, Winfried Ilg, Martin A. Giese, Christophe Maufroy, Andreas Bulling, Syn Schmitt, Daniel F. B. Haeufle
2024 conf
BioRob
Maria Sapounaki, Pierre Schumacher, Winfried Ilg, Martin A. Giese, Christophe Maufroy, Andreas Bulling, Syn Schmitt, Daniel F. B. Haeufle, Isabell Wochner
2022 J jnl
Robotics
Marcel Waldhof, Isabell Wochner, Katrin Stollenmaier, Nejila Parspour, Syn Schmitt
2022 Misc conf
CoRL
Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt, Daniel F. B. Haeufle
2022 J jnl
CoRR
Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt, Daniel F. B. Haeufle
2020 J jnl
Frontiers Robotics AI
Daniel F. B. Haeufle, Isabell Wochner, David Holzmüller, Danny Driess, Michael Günther, Syn Schmitt
2020 J jnl
Frontiers Comput. Neurosci.
Isabell Wochner, Danny Drieß, Heiko Zimmermann, Daniel F. B. Haeufle, Marc Toussaint, Syn Schmitt
redb/extractors/elf_extractors/elf_dependencies.py
← Index redb/extractors/elf_extractors/elf_dependencies.py python
import inspect
from datetime import datetime, timezone
from typing import Any, List, Dict

from elftools.elf.elffile import ELFFile
from elftools.common.exceptions import ELFError

from redb.extractors.enum import Tag
from redb.extractors.elf_extractor import ELFExtractor
from redb.models.dataclasses import ELFDependency


class ELFDependencyExtractor(ELFExtractor):

    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        elf=None,
    ):
        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            elastic_index,
            known_benign,
            known_malicious,
            elf,
        )
        self.elf_dependencies = []
        self.elastic_index = self.index_prefix + "-elf_dependencies"
        self.log.debug(inspect.currentframe().f_code.co_name)

    def _map_dependency_type(self, dt_tag_str: str) -> int:
        """Map dynamic tag string to enum value."""
        type_map = {
            'DT_NEEDED': 1,
            'DT_SONAME': 14,
            'DT_RPATH': 15,
            'DT_RUNPATH': 29
        }
        return type_map.get(dt_tag_str, 0)

    def _extract_dynamic_dependencies(self, elf) -> List[Dict]:
        """Extract dependencies from the dynamic section."""
        dependencies = []

        try:
            # Get the dynamic section
            dynamic_section = elf.get_section_by_name('.dynamic')
            if not dynamic_section:
                self.log.debug("No .dynamic section found")
                return dependencies

            # Iterate through dynamic tags
            for tag in dynamic_section.iter_tags():
                dt_tag = tag.entry.d_tag

                # Handle different dependency types
                if dt_tag == 'DT_NEEDED':
                    # Required library
                    dependency_name = tag.needed
                    dependencies.append(ELFDependency(
                        dependency_name=dependency_name,
                        dependency_type=self._map_dependency_type('DT_NEEDED'),
                        dependency_type_str='NEEDED'
                    ))

                elif dt_tag == 'DT_SONAME':
                    # Shared object name
                    dependency_name = tag.soname
                    dependencies.append(ELFDependency(
                        dependency_name=dependency_name,
                        dependency_type=self._map_dependency_type('DT_SONAME'),
                        dependency_type_str='SONAME'
                    ))

                elif dt_tag == 'DT_RPATH':
                    # Runtime library search path
                    dependency_name = tag.rpath
                    dependencies.append(ELFDependency(
                        dependency_name=dependency_name,
                        dependency_type=self._map_dependency_type('DT_RPATH'),
                        dependency_type_str='RPATH'
                    ))

                elif dt_tag == 'DT_RUNPATH':
                    # Runtime library search path (newer)
                    dependency_name = tag.runpath
                    dependencies.append(ELFDependency(
                        dependency_name=dependency_name,
                        dependency_type=self._map_dependency_type('DT_RUNPATH'),
                        dependency_type_str='RUNPATH'
                    ))

        except Exception as e:
            self.log.error(f"Error extracting dynamic dependencies: {e}")

        return dependencies

    def tag(self):
        return Tag.ELF_DEPENDENCIES.value if hasattr(Tag, 'ELF_DEPENDENCIES') else "elf_dependencies"

    def extract(self):
        try:
            self.log.debug(inspect.currentframe().f_code.co_name)

            def extract_data(elf):
                # Extract dependencies - returns list of ELFDependency dataclasses
                dependencies = self._extract_dynamic_dependencies(elf)
                return dependencies

            if not self._is_elf_file():
                return None

            result = self._with_elf_file(extract_data)
            if result is None:
                return None

            self.elf_dependencies = result
            return self.elf_dependencies

        except Exception as e:
            self.log.error(f"Error extracting ELF dependencies {self.hash.sha256}: {e}")
            return None

    def prepare_export_data(self, exporter_type: str) -> Any:
        self.log.debug(inspect.currentframe().f_code.co_name)

        if exporter_type == "ElasticsearchExporter":
            return self.elf_dependencies
        elif exporter_type == "ClickHouseExporter":
            try:
                # Return valid empty structure if no dependencies (e.g., statically linked binary)
                # None is reserved for actual errors

                # Prepare data arrays for all dependencies
                data = []
                current_time = datetime.now(timezone.utc)
                for dep in self.elf_dependencies:
                    row = [
                        self.sha256,
                        self.md5,
                        self.sha1,
                        dep.dependency_name,
                        dep.dependency_type,
                        dep.dependency_type_str,
                        current_time
                    ]
                    data.append(row)

                column_names = [
                    'sha256', 'md5', 'sha1',
                    'dependency_name', 'dependency_type', 'dependency_type_str',
                    'analysis_date'
                ]

                if not data:
                    return None

                column_type_names = [
                    'FixedString(64)', 'FixedString(32)', 'FixedString(40)',
                    'LowCardinality(String)',
                    "Enum8('NEEDED'=1, 'SONAME'=14, 'RPATH'=15, 'RUNPATH'=29)",
                    'LowCardinality(String)',
                    'DateTime64(3, \'UTC\')'
                ]

                return (data, column_names, column_type_names)

            except Exception as e:
                self.log.error(f"Error preparing export data: {e}")
                raise

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