Vamsi K. Ithapu

28 papers A* 7Misc 2Journal 11Unranked 7
YearRankTypeTitle / Venue / Authors
2023 Misc conf
ICASSP
Arjun Gupta, Pablo Hoffmann, Sebastian Prepelita, Philip W. Robinson, Vamsi K. Ithapu, David L. Alon
2022 Misc conf
ICASSP
Efthymios Tzinis, Yossi Adi, Vamsi K. Ithapu, Buye Xu, Anurag Kumar
2022 J jnl
IEEE J. Sel. Top. Signal Process.
Efthymios Tzinis, Yossi Adi, Vamsi K. Ithapu, Buye Xu, Paris Smaragdis, Anurag Kumar
2022 J jnl
CoRR
Pranay Manocha, Anurag Kumar, Buye Xu, Anjali Menon, Israel D. Gebru, Vamsi K. Ithapu, Paul Calamia
2021 J jnl
CoRR
Efthymios Tzinis, Yossi Adi, Vamsi K. Ithapu, Buye Xu, Anurag Kumar
2021 conf
WASPAA
Pranay Manocha, Anurag Kumar, Buye Xu, Anjali Menon, Israel D. Gebru, Vamsi K. Ithapu, Paul Calamia
2021 J jnl
CoRR
Pranay Manocha, Anurag Kumar, Buye Xu, Anjali Menon, Israel D. Gebru, Vamsi K. Ithapu, Paul Calamia
2020 A* conf
ICML
Anurag Kumar, Vamsi K. Ithapu
2017 J jnl
CoRR
Felipe Gutierrez-Barragan, Vamsi K. Ithapu, Chris Hinrichs, Camille Maumet, Sterling C. Johnson, Thomas E. Nichols, Vikas Singh
2017 J jnl
NeuroImage
Felipe Gutierrez-Barragan, Vamsi K. Ithapu, Chris Hinrichs, Camille Maumet, Sterling C. Johnson, Thomas E. Nichols, Vikas Singh
2017 conf
CVPR Workshops
Vamsi K. Ithapu
2017 J jnl
CoRR
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
2017 ch.
Deep Learning for Medical Image Analysis
Vamsi K. Ithapu, Vikas Singh, Sterling C. Johnson
2017 A* conf
CVPR
Vamsi K. Ithapu, Risi Kondor, Sterling C. Johnson, Vikas Singh
2017 J jnl
CoRR
Vamsi K. Ithapu, Risi Kondor, Sterling C. Johnson, Vikas Singh
2017 A* conf
ICML
Hao Henry Zhou, Yilin Zhang, Vamsi K. Ithapu, Sterling C. Johnson, Grace Wahba, Vikas Singh
2016 A* conf
ICML
Sathya N. Ravi, Vamsi K. Ithapu, Sterling C. Johnson, Vikas Singh
2016 conf
NIPS
Hao Henry Zhou, Vamsi K. Ithapu, Sathya Narayanan Ravi, Vikas Singh, Grace Wahba, Sterling C. Johnson
2016 conf
Allerton
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
2015 A* conf
ICCV
Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh
2015 A* conf
ICCV
Lopamudra Mukherjee, Sathya N. Ravi, Vamsi K. Ithapu, Tyler Holmes, Vikas Singh
2015 J jnl
CoRR
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
2015 J jnl
CoRR
Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh
2015 J jnl
CoRR
Chris Hinrichs, Vamsi K. Ithapu, Qinyuan Sun, Sterling C. Johnson, Vikas Singh
2014 conf
MICCAI (2)
Vamsi K. Ithapu, Vikas Singh, Ozioma C. Okonkwo, Sterling C. Johnson
2013 A* conf
ICCV
Jia Xu, Vamsi K. Ithapu, Lopamudra Mukherjee, James M. Rehg, Vikas Singh
2013 conf
NIPS
Chris Hinrichs, Vamsi K. Ithapu, Qinyuan Sun, Sterling C. Johnson, Vikas Singh
2010 conf
Computer-Aided Diagnosis
Vamsi K. Ithapu, Armin Fritsche, Ariane Oppelt, Martin Westhofen, Thomas M. Deserno
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