Odysseas Zisimopoulos

13 papers C 1Journal 8Unranked 4
YearRankTypeTitle / Venue / Authors
2025 C conf
PCS
Shakarim Soltanayev, Odysseas Zisimopoulos, Mohammad Ashraful Anam, Man Cheung Kung, Angeliki Katsenou, Yiannis Andreopoulos
2025 J jnl
CoRR
Shakarim Soltanayev, Odysseas Zisimopoulos, Mohammad Ashraful Anam, Man Cheung Kung, Angeliki Katsenou, Yiannis Andreopoulos
2021 J jnl
CoRR
Patrick Brandao, Odysseas Zisimopoulos, Evangelos B. Mazomenos, Gastone Ciuti, Jorge Bernal, Marco Visentini Scarzanella, Arianna Menciassi, Paolo Dario, Anastasios Koulaouzidis, Alberto Arezzo, David J. Hawkes, Danail Stoyanov
2020 conf
ECML/PKDD (5)
Elaine M. Bettaney, Stephen R. Hardwick, Odysseas Zisimopoulos, Benjamin Paul Chamberlain
2019 J jnl
Medical Image Anal.
Hassan Al Hajj, Mathieu Lamard, Pierre-Henri Conze, Soumali Roychowdhury, Xiaowei Hu, Gabija Marsalkaite, Odysseas Zisimopoulos, Muneer Ahmad Dedmari, Fenqiang Zhao, Jonas Prellberg, Manish Sahu, Adrian Galdran, Teresa Araújo, Duc My Vo, Chandan Panda, Navdeep Dahiya, Satoshi Kondo, Zhengbing Bian, Gwenolé Quellec
2019 conf
eCOM@SIGIR
Elaine M. Bettaney, Stephen R. Hardwick, Benjamin Paul Chamberlain, Odysseas Zisimopoulos
2019 J jnl
CoRR
Elaine M. Bettaney, Stephen R. Hardwick, Odysseas Zisimopoulos, Benjamin Paul Chamberlain
2018 conf
MICCAI (4)
Odysseas Zisimopoulos, Evangello Flouty, Imanol Luengo, Petros Giataganas, Jean Nehme, Andre Chow, Danail Stoyanov
2018 J jnl
CoRR
Odysseas Zisimopoulos, Evangello Flouty, Imanol Luengo, Petros Giataganas, Jean Nehme, Andre Chow, Danail Stoyanov
2018 conf
OR 2.0/CARE/CLIP/ISIC@MICCAI
Evangello Flouty, Odysseas Zisimopoulos, Danail Stoyanov
2018 J jnl
CoRR
Evangello Flouty, Odysseas Zisimopoulos, Danail Stoyanov
2018 J jnl
J. Medical Robotics Res.
Patrick Brandao, Odysseas Zisimopoulos, Evangelos B. Mazomenos, Gastone Ciuti, Jorge Bernal, Marco Visentini Scarzanella, Arianna Menciassi, Paolo Dario, Anastasios Koulaouzidis, Alberto Arezzo, David J. Hawkes, Danail Stoyanov
2014 J jnl
Int. J. Interdiscip. Telecommun. Netw.
Jan Holub, Oldrich Slavata, Pavel Soucek, Odysseas Zisimopoulos, Dimitris Toumpakaris, Stavros A. Kotsopoulos
redb/extractors/detectiteasy.py
← Index redb/extractors/detectiteasy.py python
import inspect
from pprint import pprint
import subprocess
import json
from typing import Any
from datetime import datetime, timezone
import os
from dotenv import load_dotenv

from redb.extractors.enum import Tag
from redb.models.dataclasses import DIEinfo
from redb.extractors.extractor import Extractor

load_dotenv(override=True)

class DIEExtractor(Extractor):

    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        precomputed_hashes=None,
    ):
        super().__init__(
            filepath, log, exporters, index_prefix, elastic_index, known_benign, known_malicious,
            precomputed_hashes=precomputed_hashes
        )
        self.log.debug(inspect.currentframe().f_code.co_name)
        self.die_info = None
        self.die_info_dict = {}
        self.elastic_index = self.index_prefix + "-die"

    def _recursive_entry(self, die_dict, master_key):
        self.log.debug(inspect.currentframe().f_code.co_name)
        if master_key:
            self.die_info_dict[master_key] = {}
        else:
            self.die_info_dict = {}
        for value in die_dict:
            if "type" in value:
                type_key = value["type"].lower().replace(" ", "_")
                name = value.get("name", "")
                version = f"({value.get('version')})" if value.get("version") else ""
                info = f"[{value.get('info')}]" if value.get("info") else ""

                if master_key:
                    self.die_info_dict[master_key][type_key] = f"{name}"
                    self.die_info_dict[master_key][f'{type_key}(full)'] = f"{name}{version}{info}"
                else:
                    self.die_info_dict[type_key] = f"{name}"
                    self.die_info_dict[f'{type_key}(full)'] = f"{name}{version}{info}"

            elif "parentfilepart" in value:
                child_key = (
                    value["parentfilepart"].lower().replace(" ", "_")
                    + "."
                    + value["filetype"].lower().replace(" ", "_")
                )
                if master_key:
                    self._recursive_entry(value["values"], f"{master_key}.{child_key}")
                else:
                    self._recursive_entry(value["values"], f"{child_key}")

    def _extract_dieinfo(self):
        """
        Execute a command-line binary with arguments and parse its JSON output.

        :param command: The command or path to the binary to execute
        :param args: Additional arguments to pass to the command
        :return: Parsed JSON output as a Python object
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        # Construct the full command
        # command = "nfdc" # UNCOMMENT FOR PROD
        # command = "/Users/p4c0/_tools/NFD.app/Contents/MacOS/nfdc" # COMMENT FOR TESTING ON MAC
        command = os.getenv("DIE_PATH")
        args = ["-durj", self.filepath]
        full_command = [command] + list(args)
        TIMEOUT = int(os.getenv("DIE_TIMEOUT", "180"))

        try:
            # Execute the command and capture its output
            result = subprocess.run(
                full_command,
                capture_output=True,
                text=True,
                check=True,
                timeout=TIMEOUT,
            )

            # Parse the JSON output
            nfdc_output = json.loads(result.stdout)

            # Extract the DIE information from the json output
            for die_entry in nfdc_output["detects"]:
                if die_entry["parentfilepart"] == "Header":
                    master_key = (
                        die_entry["parentfilepart"].lower().replace(" ", "_")
                        + "."
                        + die_entry["filetype"].lower().replace(" ", "_")
                    )
                    self._recursive_entry(die_entry["values"], None)

            # pprint(json.dumps(self.die_info_dict, indent=2)) #debug
            self.die_info = DIEinfo(result.stdout, self.die_info_dict)
            self.log.debug(f"NFDC-DIE JSON dump: todo")
        except subprocess.TimeoutExpired:
            self.log.error(f"The DIE command timed out after {TIMEOUT} seconds")
            return None
        except subprocess.CalledProcessError as e:
            self.log.error(f"Error executing DIE command: {e}")
            self.log.error(f"Command output (stderr): {e.stderr}")
            return None
        except json.JSONDecodeError as e:
            self.log.error(f"Error parsing DIE JSON output: {e}")
            self.log.error(f"Raw output: {result.stdout}")
            return None

    def prepare_export_data(self, exporter_type: str) -> Any:
        if exporter_type == "ElasticsearchExporter":
            return self.die_info
        elif exporter_type == "ClickHouseExporter":
            # Convert DIE info to JSON string
            die_info_json = json.dumps(self.die_info_dict)
            
            data = [[
                self.sha256,
                self.md5,
                self.sha1,
                die_info_json,
                datetime.now(timezone.utc)
            ]]
            
            column_names = [
                'sha256', 'md5', 'sha1', 'die_info', 'analysis_date'
            ]
            
            column_type_names = [
                'String', 'String', 'String', 'JSON', 'DateTime64(3, \'UTC\')'
            ]
            
            return (data, column_names, column_type_names)

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

    def extract(self):
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            self._extract_dieinfo()
            
            # Check if there's a packer in the DIE results
            is_packed = False
            if self.die_info_dict:
                # Check if 'packer' exists in the DIE results
                is_packed = bool(self.die_info_dict.get('packer'))
            
            return self.die_info  # Return the extracted data instead of exporting directly
        except Exception as e:
            self.log.error(f"Error extracting DIE information: {e}")
            return None

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