Haiyu Pan

22 papers C 1Misc 2Journal 13Unranked 5
YearRankTypeTitle / Venue / Authors
2025 J jnl
Theor. Comput. Sci.
Shasha Zhang, Jie Zhou, Yanfang Ma, Haiyu Pan
2025 J jnl
Fuzzy Sets Syst.
Haiyu Pan, Jie Zhou, Yuming Lin, Yongzhi Cao
2024 C conf
QRS
Fan Shi, Zhiqiu Huang, Haiyu Pan, Yuting Chang, Heng Xu
2022 J jnl
IEEE Trans. Reliab.
Junyan Qian, Fan Shi, Yong Cai, Haiyu Pan
2022 conf
AILA
Xinyu Cui, Zhaokai Li, Yuting Chang, Haiyu Pan
2021 J jnl
IEEE Trans. Fuzzy Syst.
Haiyu Pan, Yongzhi Cao, Liang Chang, Junyan Qian, Yuming Lin
2020 ch.
Decision Making under Constraints
Yongzhi Cao, Yoshinori Ezawa, Guoqing Chen, Haiyu Pan
2019 J jnl
Swarm Evol. Comput.
Yirui Wang, Yang Yu, Shangce Gao, Haiyu Pan, Gang Yang
2019 J jnl
IEEE Trans. Fuzzy Syst.
Haiyu Pan, Fu Song, Yongzhi Cao, Junyan Qian
2017 J jnl
Int. J. Approx. Reason.
Haiyu Pan, Yongming Li, Yongzhi Cao, Ping Li
2017 J jnl
IEEE Trans. Fuzzy Syst.
Haiyu Pan, Yongming Li, Yongzhi Cao, Dechao Li
2017 conf
ISDT
Yanfang Ma, Haiyu Pan
2016 J jnl
Theor. Comput. Sci.
Haiyu Pan, Yongming Li, Yongzhi Cao, Zhanyou Ma
2015 J jnl
Int. J. Approx. Reason.
Haiyu Pan, Yongming Li, Yongzhi Cao
2015 J jnl
Fuzzy Sets Syst.
Haiyu Pan, Yongming Li, Yongzhi Cao, Zhanyou Ma
2014 J jnl
Fundam. Informaticae
Haiyu Pan, Min Zhang, Hengyang Wu, Yixiang Chen
2014 J jnl
Int. J. Approx. Reason.
Haiyu Pan, Yongzhi Cao, Min Zhang, Yixiang Chen
2012 conf
QLSC
Haiyu Pan, Min Zhang, Yixiang Chen
2012 Misc conf
TASE
Haiyu Pan, Min Zhang, Yixiang Chen
2012 conf
SERE (Companion)
Haiyu Pan, Min Zhang, Yixiang Chen
2011 Misc conf
TASE
Haiyu Pan, Min Zhang, Yixiang Chen, Hengyang Wu
2011 conf
SSIRI (Companion)
Haiyu Pan, Min Zhang, Yixiang Chen
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