Jalil Taghia

38 papers A* 1A 2B 4C 1Misc 4Journal 19Unranked 6
YearRankTypeTitle / Venue / Authors
2025 J jnl
CoRR
Xiaoyu Lan, Jalil Taghia, Hannes Larsson, Andreas Johnsson
2023 J jnl
Frontiers Digit. Health
Arne Leijon, Petra von Gablenz, Inga Holube, Jalil Taghia, Karolina Smeds
2023 B conf
NOMS
Hannes Larsson, Farnaz Moradi, Jalil Taghia, Xiaoyu Lan, Andreas Johnsson
2023 J jnl
CoRR
Maria Bånkestad, Jens Sjölund, Jalil Taghia, Thomas B. Schön
2023 J jnl
Trans. Mach. Learn. Res.
Maria Bånkestad, Jens Sjölund, Jalil Taghia, Thomas B. Schön
2022 conf
INFOCOM Workshops
Jalil Taghia, Farnaz Moradi, Hannes Larsson, Xiaoyu Lan, Masoumeh Ebrahimi, Andreas Johnsson
2022 J jnl
CoRR
Ian Marsh, Wolfgang John, Ali Balador, Federico Tonini, Jalil Taghia, Andreas Johnsson, Paolo Monti, Jonas Gustafsson, Pontus Sköldström, Johan Sjöberg, Jim Dowling
2022 A* conf
INFOCOM
Jalil Taghia, Farnaz Moradi, Hannes Larsson, Xiaoyu Lan, Masoumeh Ebrahimi, Andreas Johnsson
2021 B conf
Networking
Hannes Larsson, Jalil Taghia, Farnaz Moradi, Andreas Johnsson
2021 B conf
IM
Hannes Larsson, Jalil Taghia, Farnaz Moradi, Andreas Johnsson
2020 B conf
NetSoft
Selim Ickin, Konstantinos Vandikas, Farnaz Moradi, Jalil Taghia, Wenfeng Hu
2020 J jnl
IEEE Access
Zhanyu Ma, Sunwoo Kim, Pascual Martínez-Gómez, Jalil Taghia, Yi-Zhe Song, Huiji Gao
2020 J jnl
IEEE Trans. Neural Networks Learn. Syst.
Zhanyu Ma, Jiyang Xie, Yuping Lai, Jalil Taghia, Jing-Hao Xue, Jun Guo
2020 J jnl
CoRR
Maria Bånkestad, Jens Sjölund, Jalil Taghia, Thomas B. Schön
2019 A conf
AISTATS
Jalil Taghia, Thomas B. Schön
2019 J jnl
CoRR
Jalil Taghia, Maria Bånkestad, Fredrik Lindsten, Thomas B. Schön
2019 J jnl
CoRR
Zhanyu Ma, Jalil Taghia, Jun Guo
2019 J jnl
CoRR
Ivo Trowitzsch, Jalil Taghia, Youssef Kashef, Klaus Obermayer
2018 J jnl
Neurocomputing
Zhanyu Ma, Jen-Tzung Chien, Zheng-Hua Tan, Yi-Zhe Song, Jalil Taghia, Ming Xiao
2017 J jnl
NeuroImage
Jalil Taghia, Srikanth Ryali, Tianwen Chen, Kaustubh Supekar, Weidong Cai, Vinod Menon
2016 J jnl
IEEE Trans. Pattern Anal. Mach. Intell.
Jalil Taghia, Arne Leijon
2015 J jnl
Signal Process.
Zhanyu Ma, Jalil Taghia, W. Bastiaan Kleijn, Arne Leijon, Jun Guo
2015 J jnl
IEEE J. Sel. Top. Signal Process.
Pravin Kumar Rana, Jalil Taghia, Zhanyu Ma, Markus Flierl
2014 J jnl
IEEE Trans. Pattern Anal. Mach. Intell.
Jalil Taghia, Zhanyu Ma, Arne Leijon
2014
Jalil Taghia
2014 J jnl
Pattern Recognit.
Zhanyu Ma, Pravin Kumar Rana, Jalil Taghia, Markus Flierl, Arne Leijon
2014 J jnl
IEEE Signal Process. Lett.
Jalil Taghia, Arne Leijon
2014 conf
3DTV-Conference
Pravin Kumar Rana, Jalil Taghia, Markus Flierl
2013 Misc conf
ICASSP
Jalal Taghia, Rainer Martin, Jalil Taghia, Arne Leijon
2013 Misc conf
ICASSP
Pravin Kumar Rana, Zhanyu Ma, Jalil Taghia, Markus Flierl
2013 A conf
INTERSPEECH
Jalil Taghia, Zhanyu Ma, Arne Leijon
2012 C conf
ISM
Pravin Kumar Rana, Jalil Taghia, Markus Flierl
2012 Misc conf
ICASSP
Jalil Taghia, Nasser Mohammadiha, Arne Leijon
2012 conf
ITG Conference on Speech Communication
Jalal Taghia, Rainer Martin, Jalil Taghia, Arne Leijon
2012 conf
EUSIPCO
Hongmei Hu, Nasser Mohammadiha, Jalil Taghia, Arne Leijon, Mark E. Lutman, Shouyan Wang
2011 Misc conf
ICASSP
Jalal Taghia, Jalil Taghia, Nasser Mohammadiha, Jinqiu Sang, Václav Bouse, Rainer Martin
2011 conf
ISSPIT
Jalil Taghia, Timo Gerkmann, Arne Leijon
2007 conf
SCSS (1)
Jalal Taghia, Jalil Taghia
redb/extractors/pe_extractors/pe_resources.py
← Index redb/extractors/pe_extractors/pe_resources.py python
from hashlib import sha256
import inspect
from datetime import datetime, timezone
from typing import Any

import magic
from magika import Magika
import pefile
from pefile import UnicodeStringWrapperPostProcessor

from redb.extractors.enum import Tag
from redb.extractors.pe_extractor import PEExtractor
from redb.models.dataclasses import PEResource


class PEResourceExtractor(PEExtractor):

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

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

    def _extract_resources(self):
        """
        Returns:
        resources: a list of dictionaries, one per each resources type found.
                    each dictionary the key represents the name of the content,
                    which is the value itself.
                    Empty list if no resources present.
        """
        self.log.debug(inspect.currentframe().f_code.co_name)
        resources_list = []
        try:
            if hasattr(self.pe, "DIRECTORY_ENTRY_RESOURCE"):
                for resource_type in self.pe.DIRECTORY_ENTRY_RESOURCE.entries:
                    # if resource_type.name is not None:
                    #     name = resource_type.name
                    # else:
                    #     name = pefile.RESOURCE_TYPE.get(resource_type.struct.Id)
                    # if not name:
                    #     name = resource_type.struct.Id
                    name = (
                        resource_type.name
                        if resource_type.name is not None
                        else pefile.RESOURCE_TYPE.get(resource_type.struct.Id)
                    )
                    if isinstance(name, UnicodeStringWrapperPostProcessor):
                        name = name.decode()
                    try:
                        if hasattr(resource_type, "directory"):
                            for resource_id in resource_type.directory.entries:
                                if hasattr(resource_id, "directory"):
                                    for resource_lang in resource_id.directory.entries:
                                        rsrc_data = self.pe.get_data(
                                            resource_lang.data.struct.OffsetToData,
                                            resource_lang.data.struct.Size,
                                        )
                                        file_type = magic.from_buffer(rsrc_data)
                                        magik = Magika().identify_bytes(rsrc_data).output.label

                                        rsrc_entropy = (
                                            "%.2f"
                                            % pefile.SectionStructure.entropy_H(
                                                self.pe, rsrc_data
                                            )
                                        )
                                        rsrc_sha256 = sha256(rsrc_data).hexdigest()
                                        lang = pefile.LANG.get(
                                            resource_lang.data.lang, "*unknown*"
                                        )
                                        sublang = pefile.get_sublang_name_for_lang(
                                            resource_lang.data.lang,
                                            resource_lang.data.sublang,
                                        )
                                        pe_resource = PEResource(
                                            _id=rsrc_sha256,
                                            resource_type=name,
                                            resource_entropy=rsrc_entropy,
                                            resource_sha256=rsrc_sha256,
                                            resource_filetype=file_type,
                                            resource_magika=magik,
                                            resource_language=lang,
                                            resource_rva=resource_lang.data.struct.OffsetToData,
                                            resource_size=resource_lang.data.struct.Size,
                                            resource_sub_lang=sublang,
                                        )
                                        resources_list.append(pe_resource)
                    except Exception as e:
                        self.log.warning(
                            f"Continue after Error in {self.hash.sha256}: {resource_type.name} "
                            f"Exception: {e}",
                            stack_info=True,
                        )
                        # resources_list.append({f"{e} - {resource_type.name}"})
                        continue
        except Exception as e:
            self.log.exception(
                f"Extract exports error {self.hash.sha256} Exception: {e}"
            )
        self.log.debug(f"Resource list {resources_list}")
        return resources_list

    def extract(self):
        try:
            self.log.debug(inspect.currentframe().f_code.co_name)
            resources = self._extract_resources()
            # self.export_to_elastic(resources)  # Let the exporters handle this
            return resources
        except Exception as e:
            self.log.error(f"Extract resources error {self.hash.sha256} Exception: {e}")
            return None

    def prepare_export_data(self, exporter_type: str) -> Any:
        if exporter_type == "ElasticsearchExporter":
            return self.extract()
        elif exporter_type == "ClickHouseExporter":
            resources = self.extract()
            if resources is None:
                return None
            
            data = []
            current_time = datetime.now(timezone.utc)
            
            for resource in resources:
                data.append([
                    self.sha256,                    # sha256
                    self.md5,                       # md5
                    self.sha1,                      # sha1
                    resource.resource_type,         # resource_type
                    resource.resource_entropy,      # resource_entropy
                    resource.resource_sha256,       # resource_sha256
                    resource.resource_filetype,     # resource_filetype
                    resource.resource_magika,       # resource_magika
                    resource.resource_language,     # resource_language
                    resource.resource_sub_lang,     # resource_sub_lang
                    resource.resource_size,         # resource_size
                    resource.resource_rva,          # resource_rva
                    current_time                    # analysis_date
                ])
            
            column_names = [
                'sha256', 'md5', 'sha1', 'resource_type', 'resource_entropy',
                'resource_sha256', 'resource_filetype', 'resource_magika',
                'resource_language', 'resource_sub_lang', 'resource_size',
                'resource_rva', 'analysis_date'
            ]
            
            if not data:
                return None

            column_type_names = [
                'FixedString(64)', 'FixedString(32)', 'FixedString(40)',
                'LowCardinality(Nullable(String))', 'Float64',
                'FixedString(64)', 'LowCardinality(Nullable(String))', 'LowCardinality(Nullable(String))',
                'LowCardinality(Nullable(String))', 'LowCardinality(Nullable(String))', 'UInt64',
                'UInt64', 'DateTime64(3, \'UTC\')'
            ]

            return (data, column_names, column_type_names)

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