Caroline Yan Zheng

19 papers A* 4A 2B 3Journal 2Unranked 8
YearRankTypeTitle / Venue / Authors
2026 conf
HRI Companion
Caroline Yan Zheng, Maria Elena Giannaccini, Angela Higgins, Feng Zhou, Mark Paterson, Praminda Caleb-Solly
2025 A* conf
CHI
Deepika Yadav, Caroline Yan Zheng, Anna Ståhl, Madeline Balaam
2025 A* conf
CHI
Joo Young Park, Caroline Yan Zheng, Nadia Campo Woytuk, Xuni Huang, Madeline Balaam, Marianela Ciolfi Felice
2025 conf
CHI Extended Abstracts
Paulina Yurman, Matt Malpass, Madeline Balaam, Caroline Yan Zheng, Yoav Luft, Céline Mougenot, Maria Luce Lupetti
2025 A* conf
CHI
Caroline Yan Zheng, Yuting Chen, Adrian Benigno Latupeirissa, Georgios Andrikopoulos, Anna Ståhl, Madeline Balaam
2024 A conf
Conference on Designing Interactive Systems
Madeline Balaam, Anna Ståhl, Guðrún Margrét Ívansdóttir, Hallbjörg Embla Sigtryggsdóttir, Kristina Höök, Caroline Yan Zheng
2024 J jnl
Frontiers Robotics AI
Caroline Yan Zheng, Ker-Jiun Wang, Maitreyee Wairagkar, Mariana von Mohr, Erik M. Lintunen, Aikaterini Fotopoulou
2024 A conf
Conference on Designing Interactive Systems (Companion Volume)
Caroline Yan Zheng, Georgios Andrikopoulos, Mark Paterson, Nadia Berthouze, Minna Orvokki Nygren, Yoav Luft, Madeline Balaam
2023 J jnl
ACM Trans. Hum. Robot Interact.
Mark Paterson, Guy Hoffman, Caroline Yan Zheng
2021 conf
WHC
Caroline Yan Zheng, Ker-Jiun Wang, Maitreyee Wairagkar, Mariana von Mohr, Erik M. Lintunen, Katerina Fotopoulou
2020 conf
HRI (Companion)
Caroline Yan Zheng, Cherie Lacey, Mark Paterson
2020 conf
ICCE-TW
Ker-Jiun Wang, Caroline Yan Zheng, Maitreyee Wairagkar, Mariana von Mohr
2020 B conf
SMC
Ker-Jiun Wang, Caroline Yan Zheng, Mohammad Shidujaman, Maitreyee Wairagkar, Mariana von Mohr
2019 conf
ARSO
Ker-Jiun Wang, Mohammad Shidujaman, Caroline Yan Zheng, Prakash Thakur
2019 A* conf
HRI
Ker-Jiun Wang, Caroline Yan Zheng, Zhi-Hong Mao
2019 B conf
RO-MAN
Ker-Jiun Wang, Caroline Yan Zheng
2019 conf
UbiComp/ISWC Adjunct
Ker-Jiun Wang, Caroline Yan Zheng
2018 B conf
VRST
Ker-Jiun Wang, Quanbo Liu, Soumya Vhasure, Quanfeng Liu, Caroline Yan Zheng, Prakash Thakur
2018 conf
AIVR
Ker-Jiun Wang, Quanbo Liu, Yifan Zhao, Caroline Yan Zheng, Soumya Vhasure, Quanfeng Liu, Prakash Thakur, Mingui Sun, Zhi-Hong Mao
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