Ha Manh Do

17 papers A* 1A 3Journal 8Unranked 5
YearRankTypeTitle / Venue / Authors
2023 J jnl
IEEE Instrum. Meas. Mag.
Karla Conn Welch, Robert Pennington, Saipruthvi Vanaparthy, Ha Manh Do, Rohit Narayanan, Dan O. Popa, Gregory Barnes, Grace Kuravackel
2022 J jnl
IEEE Trans Autom. Sci. Eng.
Ha Manh Do, Karla Conn Welch, Weihua Sheng
2021 J jnl
IEEE Trans Autom. Sci. Eng.
Ha Manh Do, Weihua Sheng, Erin E. Harrington, Alex J. Bishop
2021 J jnl
IEEE Robotics Autom. Lett.
Zhidong Su, Fei Liang, Ha Manh Do, Alex J. Bishop, Barbara Carlson, Weihua Sheng
2021 J jnl
Int. J. Soc. Robotics
Jianhao Du, Ha Manh Do, Weihua Sheng
2021 J jnl
IEEE Robotics Autom. Lett.
Minh Pham, Ha Manh Do, Zhidong Su, Alex J. Bishop, Weihua Sheng
2020 A conf
IROS
Duy Tran, Ha Manh Do, Jiaxing Lu, Weihua Sheng
2018 J jnl
Future Gener. Comput. Syst.
Minh Pham, Yehenew Mengistu, Ha Manh Do, Weihua Sheng
2018 J jnl
Robotics Auton. Syst.
Ha Manh Do, Minh Pham, Weihua Sheng, Dan Yang, Meiqin Liu
2017 conf
ROBIO
Francisco Erivaldo Fernandes Junior, Ha Manh Do, Kiran Muniraju, Weihua Sheng, Alex J. Bishop
2016 A conf
IROS
Yehenew Mengistu, Minh Pham, Ha Manh Do, Weihua Sheng
2016 conf
CASE
Minh Pham, Yehenew Mengistu, Ha Manh Do, Weihua Sheng
2016 conf
CASE
Ha Manh Do, Weihua Sheng, Meiqin Liu, Senlin Zhang
2016 conf
CASE
Francisco Erivaldo Fernandes Junior, Guanci Yang, Ha Manh Do, Weihua Sheng
2015 A conf
IROS
Ha Manh Do, Weihua Sheng, Meiqin Liu
2014 A* conf
ICRA
Ha Manh Do, Craig Mouser, Meiqin Liu, Weihua Sheng
2012 conf
ROBIO
Ye Gu, Ha Manh Do, Yongsheng Ou, Weihua Sheng
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