Ioannis Georgilas

35 papers A* 2A 2Journal 16Unranked 15
YearRankTypeTitle / Venue / Authors
2024 J jnl
Sensors
Guanlin Ding, Ioannis Georgilas, Andrew R. Plummer
2024 J jnl
Frontiers Robotics AI
Solomon Pekris, Robert D. Williams, Thibaud Atkins, Ioannis Georgilas, Nicola Y. Bailey
2022 J jnl
Sensors
Yu Miao, Alan Hunter, Ioannis Georgilas
2021 J jnl
Frontiers Robotics AI
Appolinaire C. Etoundi, Alexander Dobner, Subham Agrawal, Chathura L. Semasinghe, Ioannis Georgilas, Aghil Jafari
2021 J jnl
Frontiers Robotics AI
Andrew Isbister, Nicola Y. Bailey, Ioannis Georgilas
2021 conf
TAROS
Carmen Larrea, Pierre Berthet-Rayne, S. M. Hadi Sadati, Daniel Richard Leff, Christos Bergeles, Ioannis Georgilas
2021 J jnl
Sensors
Yu Miao, Alan Hunter, Ioannis Georgilas
2020 conf
HAICTA
Thomas Bournaris, Christina Moulogianni, George Vlontzos, Ioannis Georgilas
2020 J jnl
J. Field Robotics
Salua Hamaza, Ioannis Georgilas, Guillermo Heredia, Aníbal Ollero, Thomas Richardson
2019 A conf
IROS
Salua Hamaza, Ioannis Georgilas, Thomas Richardson
2019 conf
TAROS (2)
Yu Miao, Ioannis Georgilas, Alan Hunter
2019 J jnl
Frontiers Robotics AI
Ioannis Georgilas, Giulio Dagnino, Beatriz Alves Martins, Payam Tarassoli, Samir Morad, Konstantinos Georgilas, Paul Kohler, Roger Atkins, Sanja Dogramadzi
2019 conf
TAROS (1)
Salua Hamaza, Ioannis Georgilas, Thomas Richardson
2019 J jnl
IEEE Robotics Autom. Lett.
Salua Hamaza, Ioannis Georgilas, Manuel J. Fernandez, Pedro J. Sanchez-Cuevas, Thomas Richardson, Guillermo Heredia, Aníbal Ollero
2018 conf
TAROS
Carlos Navarro Perez, Ioannis Georgilas, Appolinaire C. Etoundi, Jj Chong, Aghil Jafari
2018 conf
AIM
Salua Hamaza, Ioannis Georgilas, Thomas Richardson
2018 A conf
IROS
Salua Hamaza, Ioannis Georgilas, Thomas Richardson
2017 conf
iThings/GreenCom/CPSCom/SmartData
YingLiang Ma, Giulio Dagnino, Ioannis Georgilas, Sanja Dogramadzi
2017 J jnl
Int. J. Comput. Assist. Radiol. Surg.
Giulio Dagnino, Ioannis Georgilas, Samir Morad, Peter Gibbons, Payam Tarassoli, Roger Atkins, Sanja Dogramadzi
2017 A* conf
ICRA
Giulio Dagnino, Ioannis Georgilas, Samir Morad, Peter Gibbons, Payam Tarassoli, Roger Atkins, Sanja Dogramadzi
2017 J jnl
J. Medical Robotics Res.
Ioannis Georgilas, Giulio Dagnino, Sanja Dogramadzi
2016 A* conf
ICRA
Giulio Dagnino, Ioannis Georgilas, Paul Kohler, Roger Atkins, Sanja Dogramadzi
2016 J jnl
Int. J. Comput. Assist. Radiol. Surg.
Giulio Dagnino, Ioannis Georgilas, Paul Kohler, Samir Morad, Roger Atkins, Sanja Dogramadzi
2016 J jnl
Int. J. Comput. Assist. Radiol. Surg.
Giulio Dagnino, Ioannis Georgilas, Payam Tarassoli, Roger Atkins, Sanja Dogramadzi
2015 J jnl
Int. J. Gen. Syst.
Vicky S. Kalogeiton, Dim P. Papadopoulos, Ioannis Georgilas, George Ch. Sirakoulis, Andrew Adamatzky
2015 conf
EMBC
Giulio Dagnino, Ioannis Georgilas, Payam Tarassoli, Roger Atkins, Sanja Dogramadzi
2015 conf
EMBC
Giulio Dagnino, Ioannis Georgilas, Payam Tarassoli, Roger Atkins, Sanja Dogramadzi
2015 conf
EMBC
Daniel S. Richards, Ioannis Georgilas, Giulio Dagnino, Sanja Dogramadzi
2015 conf
EMBC
Ioannis Georgilas, Giulio Dagnino, Payam Tarassoli, Roger Atkins, Sanja Dogramadzi
2014 J jnl
Auton. Robots
Maria Elena Giannaccini, Ioannis Georgilas, I. Horsfield, B. H. P. M. Peiris, Alexander Lenz, Anthony G. Pipe, Sanja Dogramadzi
2014 J jnl
Int. J. Unconv. Comput.
Ella Gale, Ioannis Georgilas
2013 conf
NICSO
Ioannis Georgilas, Andrew Adamatzky, David Robert Wallace Barr, Piotr Dudek, Chris Melhuish
2013 conf
TAROS
Ioannis Georgilas, Ella Gale, Andrew Adamatzky, Chris Melhuish
2012 conf
CASE
Ioannis Georgilas, Andrew Adamatzky, Chris Melhuish
2012 conf
TAROS
Ioannis Georgilas, Andrew Adamatzky, Chris Melhuish
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