Vincent Sitzmann

87 papers A* 21Misc 2Journal 60Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
ACM Trans. Graph.
Ana Dodik, Vincent Sitzmann, Justin Solomon, Oded Stein
2026 J jnl
CoRR
Evan Kim, Hyunwoo Ryu, Thomas W. Mitchel, Vincent Sitzmann
2025 J jnl
Nat.
Sizhe Lester Li, Annan Zhang, Boyuan Chen, Hanna Matusik, Chao Liu, Daniela Rus, Vincent Sitzmann
2025 J jnl
CoRR
George Cazenavette, Antonio Torralba, Vincent Sitzmann
2025 conf
3DV
Cameron Smith, David Charatan, Ayush Tewari, Vincent Sitzmann
2025 J jnl
CoRR
Chonghyuk Song, Michal Starý, Boyuan Chen, George Kopanas, Vincent Sitzmann
2025 A* conf
ICML
Kiwhan Song, Boyuan Chen, Max Simchowitz, Yilun Du, Russ Tedrake, Vincent Sitzmann
2025 J jnl
CoRR
Kiwhan Song, Boyuan Chen, Max Simchowitz, Yilun Du, Russ Tedrake, Vincent Sitzmann
2025 J jnl
CoRR
Boyuan Chen, Tianyuan Zhang, Haoran Geng, Kiwhan Song, Caiyi Zhang, Peihao Li, William T. Freeman, Jitendra Malik, Pieter Abbeel, Russ Tedrake, Vincent Sitzmann, Yilun Du
2025 J jnl
CoRR
Artem Lukoianov, Chenyang Yuan, Justin Solomon, Vincent Sitzmann
2025 J jnl
ACM Trans. Graph.
Ana Dodik, Isabella Yu, Kartik Chandra, Jonathan Ragan-Kelley, Joshua B. Tenenbaum, Vincent Sitzmann, Justin Solomon
2025 J jnl
Trans. Mach. Learn. Res.
Cameron Omid Smith, Basile Van Hoorick, Chonghyuk Song, Vincent Sitzmann, Vitor Campagnolo Guizilini, Yue Wang
2025 J jnl
CoRR
Kiwhan Song, Jaeyeon Kim, Sitan Chen, Yilun Du, Sham M. Kakade, Vincent Sitzmann
2025 J jnl
CoRR
Eric M. Chen, Di Liu, Sizhuo Ma, Michael Vasilkovsky, Bing Zhou, Qiang Gao, Wenzhou Wang, Jiahao Luo, Dimitris N. Metaxas, Vincent Sitzmann, Jian Wang
2025 J jnl
CoRR
Thomas W. Mitchel, Hyunwoo Ryu, Vincent Sitzmann
2025 J jnl
CoRR
Michal Starý, Julien Gaubil, Ayush Tewari, Vincent Sitzmann
2024 A* conf
NeurIPS
Boyuan Chen, Diego Marti Monso, Yilun Du, Max Simchowitz, Russ Tedrake, Vincent Sitzmann
2024 J jnl
CoRR
Boyuan Chen, Diego Marti Monso, Yilun Du, Max Simchowitz, Russ Tedrake, Vincent Sitzmann
2024 A* conf
ICLR
Suning Huang, Boyuan Chen, Huazhe Xu, Vincent Sitzmann
2024 J jnl
CoRR
Suning Huang, Boyuan Chen, Huazhe Xu, Vincent Sitzmann
2024 J jnl
CoRR
Cameron Smith, David Charatan, Ayush Tewari, Vincent Sitzmann
2024 A* conf
CVPR
Peter Kocsis, Vincent Sitzmann, Matthias Nießner
2024 A* conf
NeurIPS
Thomas W. Mitchel, Michael J. Taylor, Vincent Sitzmann
2024 J jnl
CoRR
Thomas W. Mitchel, Michael J. Taylor, Vincent Sitzmann
2024 A* conf
CVPR
David Charatan, Sizhe Lester Li, Andrea Tagliasacchi, Vincent Sitzmann
2024 J jnl
CoRR
Ana Dodik, Vincent Sitzmann, Justin Solomon, Oded Stein
2024 A* conf
NeurIPS
Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin M. Solomon
2024 J jnl
CoRR
Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Campagnolo Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin Solomon
2024 J jnl
CoRR
Sizhe Lester Li, Annan Zhang, Boyuan Chen, Hanna Matusik, Chao Liu, Daniela Rus, Vincent Sitzmann
2023 J jnl
CoRR
Thomas P. O'Connell, Tyler Bonnen, Yoni Friedman, Ayush Tewari, Joshua B. Tenenbaum, Vincent Sitzmann, Nancy Kanwisher
2023 A* conf
ICCV
Vitor Guizilini, Igor Vasiljevic, Jiading Fang, Rares Ambrus, Sergey Zakharov, Vincent Sitzmann, Adrien Gaidon
2023 J jnl
CoRR
Vitor Guizilini, Igor Vasiljevic, Jiading Fang, Rares Ambrus, Sergey Zakharov, Vincent Sitzmann, Adrien Gaidon
2023 A* conf
NeurIPS
Ayush Tewari, Tianwei Yin, George Cazenavette, Semon Rezchikov, Josh Tenenbaum, Frédo Durand, Bill Freeman, Vincent Sitzmann
2023 J jnl
CoRR
Ayush Tewari, Tianwei Yin, George Cazenavette, Semon Rezchikov, Joshua B. Tenenbaum, Frédo Durand, William T. Freeman, Vincent Sitzmann
2023 A* conf
NeurIPS
Cameron Smith, Yilun Du, Ayush Tewari, Vincent Sitzmann
2023 J jnl
CoRR
Cameron Smith, Yilun Du, Ayush Tewari, Vincent Sitzmann
2023 J jnl
CoRR
Peter Kocsis, Vincent Sitzmann, Matthias Nießner
2023 A* conf
CVPR
Yilun Du, Cameron Smith, Ayush Tewari, Vincent Sitzmann
2023 J jnl
CoRR
Yilun Du, Cameron Smith, Ayush Tewari, Vincent Sitzmann
2023 conf
SIGGRAPH Courses
Towaki Takikawa, Shunsuke Saito, James Tompkin, Vincent Sitzmann, Srinath Sridhar, Or Litany, Alex Yu
2023 A* conf
ICLR
Prafull Sharma, Ayush Tewari, Yilun Du, Sergey Zakharov, Rares Andrei Ambrus, Adrien Gaidon, William T. Freeman, Frédo Durand, Joshua B. Tenenbaum, Vincent Sitzmann
2023 J jnl
Trans. Mach. Learn. Res.
Cameron Smith, Hong-Xing Yu, Sergey Zakharov, Frédo Durand, Joshua B. Tenenbaum, Jiajun Wu, Vincent Sitzmann
2023 J jnl
CoRR
Ana Dodik, Oded Stein, Vincent Sitzmann, Justin Solomon
2023 J jnl
ACM Trans. Graph.
Ana Dodik, Oded Stein, Vincent Sitzmann, Justin Solomon
2023 J jnl
CoRR
David Charatan, Sizhe Li, Andrea Tagliasacchi, Vincent Sitzmann
2022 J jnl
Comput. Graph. Forum
Ayush Tewari, Justus Thies, Ben Mildenhall, Pratul P. Srinivasan, Edgar Tretschk, Yifan Wang, Christoph Lassner, Vincent Sitzmann, Ricardo Martin-Brualla, Stephen Lombardi, Tomas Simon, Christian Theobalt, Matthias Nießner, Jonathan T. Barron, Gordon Wetzstein, Michael Zollhöfer, Vladislav Golyanik
2022 A* conf
NeurIPS
Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann
2022 J jnl
CoRR
Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann
2022 A* conf
CVPR
Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, A. Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi
2022 J jnl
CoRR
Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi
2022 A* conf
ICRA
Anthony Simeonov, Yilun Du, Andrea Tagliasacchi, Joshua B. Tenenbaum, Alberto Rodriguez, Pulkit Agrawal, Vincent Sitzmann
2022 J jnl
Comput. Graph. Forum
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, Srinath Sridhar
2022 J jnl
CoRR
Prafull Sharma, Ayush Tewari, Yilun Du, Sergey Zakharov, Rares Ambrus, Adrien Gaidon, William T. Freeman, Frédo Durand, Joshua B. Tenenbaum, Vincent Sitzmann
2022 J jnl
CoRR
Cameron Smith, Hong-Xing Yu, Sergey Zakharov, Frédo Durand, Joshua B. Tenenbaum, Jiajun Wu, Vincent Sitzmann
2021 Misc conf
CoRL
Yunzhu Li, Shuang Li, Vincent Sitzmann, Pulkit Agrawal, Antonio Torralba
2021 J jnl
CoRR
Yunzhu Li, Shuang Li, Vincent Sitzmann, Pulkit Agrawal, Antonio Torralba
2021 J jnl
CoRR
Ayush Tewari, Justus Thies, Ben Mildenhall, Pratul P. Srinivasan, Edgar Tretschk, Wang Yifan, Christoph Lassner, Vincent Sitzmann, Ricardo Martin-Brualla, Stephen Lombardi, Tomas Simon, Christian Theobalt, Matthias Nießner, Jonathan T. Barron, Gordon Wetzstein, Michael Zollhöfer, Vladislav Golyanik
2021 conf
SIGGRAPH Courses
Ayush Tewari, Ohad Fried, Justus Thies, Vincent Sitzmann, Stephen Lombardi, Zexiang Xu, Tomas Simon, Matthias Nießner, Edgar Tretschk, Lingjie Liu, Ben Mildenhall, Pratul P. Srinivasan, Rohit Pandey, Sergio Orts-Escolano, Sean Ryan Fanello, Michelle Guo, Gordon Wetzstein, Jun-Yan Zhu, Christian Theobalt, Maneesh Agrawala, Daniel B. Goldman, Michael Zollhöfer
2021 J jnl
CoRR
Daniel Rebain, Ke Li, Vincent Sitzmann, Soroosh Yazdani, Kwang Moo Yi, Andrea Tagliasacchi
2021 J jnl
ACM Trans. Graph.
Steven Diamond, Vincent Sitzmann, Frank D. Julca-Aguilar, Stephen P. Boyd, Gordon Wetzstein, Felix Heide
2021 A* conf
NeurIPS
Yilun Du, Katie Collins, Josh Tenenbaum, Vincent Sitzmann
2021 J jnl
CoRR
Yilun Du, Katherine M. Collins, Joshua B. Tenenbaum, Vincent Sitzmann
2021 A* conf
NeurIPS
Vincent Sitzmann, Semon Rezchikov, Bill Freeman, Josh Tenenbaum, Frédo Durand
2021 J jnl
CoRR
Vincent Sitzmann, Semon Rezchikov, William T. Freeman, Joshua B. Tenenbaum, Frédo Durand
2021 J jnl
CoRR
Anthony Simeonov, Yilun Du, Andrea Tagliasacchi, Joshua B. Tenenbaum, Alberto Rodriguez, Pulkit Agrawal, Vincent Sitzmann
2021 J jnl
CoRR
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, Srinath Sridhar
2021 Misc conf
CoRL
Sergey Zakharov, Rares Andrei Ambrus, Vitor Guizilini, Dennis Park, Wadim Kehl, Frédo Durand, Joshua B. Tenenbaum, Vincent Sitzmann, Jiajun Wu, Adrien Gaidon
2020 A* conf
NeurIPS
Vincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell, Gordon Wetzstein
2020 J jnl
CoRR
Vincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell, Gordon Wetzstein
2020 J jnl
CoRR
Amit P. S. Kohli, Vincent Sitzmann, Gordon Wetzstein
2020 A* conf
NeurIPS
Vincent Sitzmann, Eric R. Chan, Richard Tucker, Noah Snavely, Gordon Wetzstein
2020 J jnl
CoRR
Vincent Sitzmann, Eric R. Chan, Richard Tucker, Noah Snavely, Gordon Wetzstein
2020 conf
3DV
Amit Pal Singh Kohli, Vincent Sitzmann, Gordon Wetzstein
2020 J jnl
Comput. Graph. Forum
Ayush Tewari, Ohad Fried, Justus Thies, Vincent Sitzmann, Stephen Lombardi, Kalyan Sunkavalli, Ricardo Martin-Brualla, Tomas Simon, Jason M. Saragih, Matthias Nießner, Rohit Pandey, Sean Ryan Fanello, Gordon Wetzstein, Jun-Yan Zhu, Christian Theobalt, Maneesh Agrawala, Eli Shechtman, Dan B. Goldman, Michael Zollhöfer
2020 J jnl
CoRR
Ayush Tewari, Ohad Fried, Justus Thies, Vincent Sitzmann, Stephen Lombardi, Kalyan Sunkavalli, Ricardo Martin-Brualla, Tomas Simon, Jason M. Saragih, Matthias Nießner, Rohit Pandey, Sean Ryan Fanello, Gordon Wetzstein, Jun-Yan Zhu, Christian Theobalt, Maneesh Agrawala, Eli Shechtman, Dan B. Goldman, Michael Zollhöfer
2019 A* conf
CVPR
Vincent Sitzmann, Justus Thies, Felix Heide, Matthias Nießner, Gordon Wetzstein, Michael Zollhöfer
2019 A* conf
NeurIPS
Vincent Sitzmann, Michael Zollhöfer, Gordon Wetzstein
2019 J jnl
CoRR
Vincent Sitzmann, Michael Zollhöfer, Gordon Wetzstein
2018 J jnl
CoRR
Vincent Sitzmann, Justus Thies, Felix Heide, Matthias Nießner, Gordon Wetzstein, Michael Zollhöfer
2018 J jnl
ACM Trans. Graph.
Vincent Sitzmann, Steven Diamond, Yifan Peng, Xiong Dun, Stephen P. Boyd, Wolfgang Heidrich, Felix Heide, Gordon Wetzstein
2018 J jnl
CoRR
Ana Serrano, Vincent Sitzmann, Jaime Ruiz-Borau, Gordon Wetzstein, Diego Gutierrez, Belén Masiá
2018 J jnl
IEEE Trans. Vis. Comput. Graph.
Vincent Sitzmann, Ana Serrano, Amy Pavel, Maneesh Agrawala, Diego Gutierrez, Belén Masiá, Gordon Wetzstein
2018 J jnl
IEEE Trans. Vis. Comput. Graph.
Nitish Padmanaban, Timon Ruban, Vincent Sitzmann, Anthony M. Norcia, Gordon Wetzstein
2017 J jnl
CoRR
Steven Diamond, Vincent Sitzmann, Stephen P. Boyd, Gordon Wetzstein, Felix Heide
2017 J jnl
ACM Trans. Graph.
Ana Serrano, Vincent Sitzmann, Jaime Ruiz-Borau, Gordon Wetzstein, Diego Gutierrez, Belén Masiá
2017 J jnl
CoRR
Steven Diamond, Vincent Sitzmann, Felix Heide, Gordon Wetzstein
2016 J jnl
CoRR
Vincent Sitzmann, Ana Serrano, Amy Pavel, Maneesh Agrawala, Diego Gutierrez, Gordon Wetzstein
redb/extractors/hashes.py
← Index redb/extractors/hashes.py python
from dataclasses import asdict
from typing import Any
from datetime import datetime, timezone

import hashlib
import inspect
from struct import pack

from magika import Magika
from signify.fingerprinter import AuthenticodeFingerprinter
import ppdeep
import tlsh

import pefile
from elftools.elf.elffile import ELFFile
from elftools.common.exceptions import ELFError

from redb.extractors.enum import Tag
from redb.models.dataclasses import Hashes
from redb.extractors.extractor import Extractor


class HashExtractor(Extractor):

    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        macho=None,
    ):
        super().__init__(
            filepath, log, exporters, index_prefix, elastic_index, known_benign, known_malicious
        )
        self.hashes = None
        self.elastic_index = self.index_prefix + "-hashes"
        self.filetype = Magika().identify_bytes(self.binary).output.label
        self.pe = None
        self.elf = None
        self.macho = macho
        if self.filetype == "pebin":  # else None
            try:
                self.pe = pefile.PE(self.filepath)
            except Exception as e:
                self.log.error(f"Failed to initialize PE file object: {e}")
                self.pe = None
        elif self.filetype == "elf":
            # ELF file will be created when needed in _extract_elf_hashes
            pass

    def _extract_hashes(self):
        self.log.debug(inspect.currentframe().f_code.co_name)
        
        # Initialize hash values with None
        md5 = None
        sha1 = None
        sha256 = None
        ssdeep_hash = None
        tlsh_hash = None
        
        # Calculate basic hashes with error handling
        try:
            md5 = hashlib.md5(self.binary).hexdigest()
        except Exception as e:
            self.log.error(f"Failed to calculate MD5 hash: {e}")
            
        try:
            sha1 = hashlib.sha1(self.binary).hexdigest()
        except Exception as e:
            self.log.error(f"Failed to calculate SHA1 hash: {e}")
            
        try:
            sha256 = hashlib.sha256(self.binary).hexdigest()
        except Exception as e:
            self.log.error(f"Failed to calculate SHA256 hash: {e}")
            
        try:
            ssdeep_hash = ppdeep.hash_from_file(self.filepath)
        except Exception as e:
            self.log.error(f"Failed to calculate ssdeep hash: {e}")
            
        try:
            tlsh_hash = tlsh.hash(self.binary)
        except Exception as e:
            self.log.error(f"Failed to calculate TLSH hash: {e}")
        
        # Create Hashes object with available values
        self.hashes = Hashes(
            md5 or "",
            sha1 or "",
            sha256 or "",
            ssdeep_hash or "",
            tlsh_hash or "",
        )

        if self.filetype == "pebin" and self.pe is not None:
            self.log.debug("Computing PEBIN related hash values")
            
            # Authentihash
            try:
                with open(self.filepath, 'rb') as f:
                    fingerprinter = AuthenticodeFingerprinter(f)
                    fingerprinter.add_authenticode_hashers(hashlib.sha256)
                    self.hashes.authentihash = fingerprinter.hash()['sha256'].hex()
            except Exception as e:
                self.log.error(f"Failed to calculate Authentihash: {e}")
                self.hashes.authentihash = None
                
            # Imphash
            try:
                self.hashes.imphash = self.pe.get_imphash()
            except Exception as e:
                self.log.error(f"Failed to calculate Imphash: {e}")
                self.hashes.imphash = None
                
            # Rich header hashes
            try:
                if self.pe.parse_rich_header():
                    self.log.debug("Computing RichHeader related hash values")
                    
                    richhash = self._compute_richhash()
                    if richhash:
                        self.hashes.richhash = richhash
                        
                    richpe_hash = self._compute_richpe_hash()
                    if richpe_hash:
                        self.hashes.richpe_hash = richpe_hash
                        
                    richpv_result = self._compute_richpv_hash()
                    if richpv_result:
                        self.hashes.richpv_hash, self.hashes.richpv_hash_sorted = richpv_result
            except Exception as e:
                self.log.error(f"Failed to calculate Rich header hashes: {e}")
        elif self.filetype == "pebin" and self.pe is None:
            self.log.warning("PE file type detected but PE object initialization failed - skipping PE-specific hashes")

        elif self.filetype == "elf":
            self.log.debug("Computing ELF related hash values")
            self._extract_elf_hashes()
        elif self.filetype == "macho":
            self.log.debug("Computing Mach-O related hash values")
            self._extract_macho_hashes()
        elif self.filetype == "apk":
            self.log.debug("Computing APK related hash values")
            self._extract_apk_hashes()
        else:
            pass
        self.log.debug(f"Hashes dump: {asdict(self.hashes)}")
        return self.hashes

    def _compute_richhash(self):
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            rich_header = self.pe.parse_rich_header()
            if not rich_header:
                return ""
            data = rich_header["clear_data"]
            return hashlib.md5(data).hexdigest().lower()
        except:
            return ""

    def _compute_richpe_hash(self):
        """
        Computes the RichPE hash given a file path or PE object.

        RichPE hash is includes RichHeader CompID and count, as well as
        fields from IMAGE_FILE_HEADER and IMAGE_OPTIONAL_HEADER

        Parameters:
        input: it can be either a file path or a PE object

        Returns:
        richpe_hash: md5 hash of the RichPE value
        None: if no Rich Header present
        """
        try:
            # Attempt to parse Rich header
            self.log.debug(inspect.currentframe().f_code.co_name)
            rich_header = self.pe.parse_rich_header()
            if rich_header is None:
                return None

            # Get list of @Comp.IDs and counts from Rich header
            # Elements in rich_fields at even indices are @Comp.IDs
            # Elements in rich_fields at odd indices are counts
            rich_fields = rich_header.get("values", None)
            if not rich_fields or len(rich_fields) % 2 != 0:
                return None

            md5 = hashlib.md5()

            # Update hash using @Comp.IDs and masked counts from Rich header
            while len(rich_fields):
                compid = rich_fields.pop(0)
                count = rich_fields.pop(0)
                mask = 2 ** (count.bit_length() // 2 + 1) - 1
                count |= mask
                md5.update(pack("<L", compid))
                md5.update(pack("<L", count))

            # Update hash using metadata from the PE header
            md5.update(pack("<L", self.pe.FILE_HEADER.Machine))
            md5.update(pack("<L", self.pe.FILE_HEADER.Characteristics))
            md5.update(pack("<L", self.pe.OPTIONAL_HEADER.Subsystem))
            md5.update(pack("<B", self.pe.OPTIONAL_HEADER.MajorLinkerVersion))
            md5.update(pack("<B", self.pe.OPTIONAL_HEADER.MinorLinkerVersion))
            md5.update(pack("<L", self.pe.OPTIONAL_HEADER.MajorOperatingSystemVersion))
            md5.update(pack("<L", self.pe.OPTIONAL_HEADER.MinorOperatingSystemVersion))
            md5.update(pack("<L", self.pe.OPTIONAL_HEADER.MajorImageVersion))
            md5.update(pack("<L", self.pe.OPTIONAL_HEADER.MinorImageVersion))
            md5.update(pack("<L", self.pe.OPTIONAL_HEADER.MajorSubsystemVersion))
            md5.update(pack("<L", self.pe.OPTIONAL_HEADER.MinorSubsystemVersion))

            return md5.hexdigest()
        except Exception as e:
            self.log.error(f"Failed to compute RichPE hash: {e}")
            return None

    def _compute_richpv_hash(self):
        """
        Compute the RichPV hash values, sorted and unsorted.
        RichPV excludes the most volatile Rich Header field from the MD5 input data,
        the Product Count (pC) field.

        Returns:
        richpv_hash_unsorted: md5 hash of the RichPV value unsorted
        richpv_hash_sorted: md5 hash of the RichPV value sorted
        None: if no Rich Header present
        """
        try:
            self.log.debug(inspect.currentframe().f_code.co_name)
            # Attempt to parse Rich header
            rich_header = self.pe.parse_rich_header()
            if rich_header is None:
                return None

            # Get list of @Comp.IDs and counts from Rich header
            # Elements in rich_fields at even indices are @Comp.IDs
            # Elements in rich_fields at odd indices are counts
            rich_fields = rich_header.get("values", None)
            if not rich_fields or len(rich_fields) % 2 != 0:
                return None

            md5 = hashlib.md5()
            md5_sorted = hashlib.md5()
            sorted_vector = []

            # Update hash using @Comp.IDs only
            for i in range(0, len(rich_fields), 2):
                compid = rich_fields[i]
                md5.update(pack("<L", compid))
                sorted_vector.append(compid)

            sorted_vector.sort()
            for compid in sorted_vector:
                md5_sorted.update(pack("<L", compid))

            return md5.hexdigest(), md5_sorted.hexdigest()
        except Exception as e:
            self.log.error(f"Failed to compute RichPV hash: {e}")
            return None

    def _extract_elf_hashes(self):
        """Extract ELF specific similarity hashes."""
        self.log.debug(inspect.currentframe().f_code.co_name)

        try:
            with open(self.filepath, 'rb') as f:
                elf = ELFFile(f)
                if not elf:
                    return

                # Generate all similarity hashes
                import_hash = self._generate_elf_import_hash(elf)
                export_hash = self._generate_elf_export_hash(elf)
                section_hash = self._generate_elf_section_hash(elf)
                symbol_hash = self._generate_elf_symbol_hash(elf)
                dynamic_hash = self._generate_elf_dynamic_hash(elf)

                # Only set hashes if they have meaningful values
                if import_hash:
                    self.hashes.import_hash = import_hash
                if export_hash:
                    self.hashes.export_hash = export_hash
                if section_hash:
                    self.hashes.section_hash = section_hash
                if symbol_hash:
                    self.hashes.symhash = symbol_hash
                if dynamic_hash:
                    self.hashes.dynamic_hash = dynamic_hash

        except Exception as e:
            self.log.error(f"Failed to extract ELF hashes: {e}")

    def _generate_elf_import_hash(self, elf) -> str:
        """Generate MD5 hash of sorted, deduplicated imported symbol names."""
        try:
            imported_symbols = set()

            # Get dynamic symbol table
            dynsym_section = elf.get_section_by_name('.dynsym')
            if dynsym_section and hasattr(dynsym_section, 'iter_symbols'):
                for symbol in dynsym_section.iter_symbols():
                    # Look for undefined symbols (imports)
                    if (symbol.entry.get('st_shndx', 0) == 'SHN_UNDEF' and
                        symbol.name and
                        symbol.entry.get('st_info', {}).get('bind') in ['STB_GLOBAL', 'STB_WEAK']):
                        imported_symbols.add(symbol.name)

            # Also check relocations for additional imports
            for section in elf.iter_sections():
                if hasattr(section, 'iter_relocations'):
                    try:
                        for relocation in section.iter_relocations():
                            if hasattr(relocation, 'symbol') and relocation.symbol and relocation.symbol.name:
                                imported_symbols.add(relocation.symbol.name)
                    except:
                        pass

            # Sort and concatenate
            sorted_imports = sorted(list(imported_symbols))

            # Return None if no imports found
            if not sorted_imports:
                return None

            imports_string = '|'.join(sorted_imports)

            # Generate MD5 hash
            return hashlib.md5(imports_string.encode('utf-8')).hexdigest()

        except Exception as e:
            self.log.error(f"Error generating ELF import hash: {e}")
            return None

    def _generate_elf_export_hash(self, elf) -> str:
        """Generate MD5 hash of sorted, deduplicated exported symbol names."""
        try:
            exported_symbols = set()

            # Check both static and dynamic symbol tables
            symbol_sections = ['.symtab', '.dynsym']

            for section_name in symbol_sections:
                section = elf.get_section_by_name(section_name)
                if not section or not hasattr(section, 'iter_symbols'):
                    continue

                for symbol in section.iter_symbols():
                    # Check if symbol is exported (defined and globally visible)
                    if (symbol.name and
                        symbol.entry.get('st_shndx', 0) != 'SHN_UNDEF' and
                        symbol.entry.get('st_info', {}).get('bind') in ['STB_GLOBAL', 'STB_WEAK'] and
                        symbol.entry.get('st_info', {}).get('type') in ['STT_FUNC', 'STT_OBJECT']):
                        exported_symbols.add(symbol.name)

            # Sort and concatenate
            sorted_exports = sorted(list(exported_symbols))

            # Return None if no exports found
            if not sorted_exports:
                return None

            exports_string = '|'.join(sorted_exports)

            # Generate MD5 hash
            return hashlib.md5(exports_string.encode('utf-8')).hexdigest()

        except Exception as e:
            self.log.error(f"Error generating ELF export hash: {e}")
            return None

    def _generate_elf_section_hash(self, elf) -> str:
        """Generate MD5 hash of section layout (names, types, flags sequence)."""
        try:
            section_info = []

            for section in elf.iter_sections():
                header = section.header
                section_name = section.name or "<unnamed>"
                section_type = header.get('sh_type', 'SHT_NULL')
                section_flags = header.get('sh_flags', 0)

                # Create a consistent representation
                section_repr = f"{section_name}:{section_type}:{section_flags}"
                section_info.append(section_repr)

            # Return None if no meaningful sections found
            if not section_info:
                return None

            # Join all section info
            sections_string = '|'.join(section_info)

            # Generate MD5 hash
            return hashlib.md5(sections_string.encode('utf-8')).hexdigest()

        except Exception as e:
            self.log.error(f"Error generating ELF section hash: {e}")
            return None

    def _generate_elf_symbol_hash(self, elf) -> str:
        """Generate MD5 hash of sorted symbol names and types."""
        try:
            symbol_info = set()

            # Check both static and dynamic symbol tables
            symbol_sections = ['.symtab', '.dynsym']

            for section_name in symbol_sections:
                section = elf.get_section_by_name(section_name)
                if not section or not hasattr(section, 'iter_symbols'):
                    continue

                for symbol in section.iter_symbols():
                    if symbol.name:
                        symbol_type = symbol.entry.get('st_info', {}).get('type', 'STT_NOTYPE')
                        symbol_bind = symbol.entry.get('st_info', {}).get('bind', 'STB_LOCAL')

                        # Create a consistent representation
                        symbol_repr = f"{symbol.name}:{symbol_type}:{symbol_bind}"
                        symbol_info.add(symbol_repr)

            # Sort and concatenate
            sorted_symbols = sorted(list(symbol_info))

            # Return None if no symbols found
            if not sorted_symbols:
                return None

            symbols_string = '|'.join(sorted_symbols)

            # Generate MD5 hash
            return hashlib.md5(symbols_string.encode('utf-8')).hexdigest()

        except Exception as e:
            self.log.error(f"Error generating ELF symbol hash: {e}")
            return None

    def _generate_elf_dynamic_hash(self, elf) -> str:
        """Generate MD5 hash of dynamic section entries (DT_* tags)."""
        try:
            dynamic_info = []

            # Get the dynamic section
            dynamic_section = elf.get_section_by_name('.dynamic')
            if not dynamic_section:
                return None

            # Extract dynamic tags and their values
            for tag in dynamic_section.iter_tags():
                dt_tag = tag.entry.d_tag

                # Create a representation based on tag type
                if dt_tag == 'DT_NEEDED':
                    dynamic_info.append(f"DT_NEEDED:{tag.needed}")
                elif dt_tag == 'DT_SONAME':
                    dynamic_info.append(f"DT_SONAME:{tag.soname}")
                elif dt_tag == 'DT_RPATH':
                    dynamic_info.append(f"DT_RPATH:{tag.rpath}")
                elif dt_tag == 'DT_RUNPATH':
                    dynamic_info.append(f"DT_RUNPATH:{tag.runpath}")
                else:
                    # For other tags, use the tag name and value
                    dt_value = tag.entry.d_val if hasattr(tag.entry, 'd_val') else 0
                    dynamic_info.append(f"{dt_tag}:{dt_value}")

            # Sort to ensure consistent ordering
            dynamic_info.sort()
            dynamics_string = '|'.join(dynamic_info)

            # Generate MD5 hash
            return hashlib.md5(dynamics_string.encode('utf-8')).hexdigest()

        except Exception as e:
            self.log.error(f"Error generating ELF dynamic hash: {e}")
            return None

    def _extract_macho_hashes(self):
        """Extract Mach-O specific similarity hashes using machofile API.

        For FAT binaries, this extracts hashes for the current file being processed
        (either the FAT container or an individual slice). The machofile library
        handles the architecture-specific extraction when an arch parameter is provided.

        For slices: We parse the slice file directly since it's a standalone Mach-O.
        For FAT container: We use the provided macho object with combined/fat hashes.
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        try:
            # If we have a pre-parsed macho object (FAT container or single-arch with passed object)
            if self.macho:
                architectures = self.macho.get_architectures()
                is_fat = len(architectures) > 1

                if is_fat:
                    # For FAT container, get combined hashes (key may be 'fat' or 'combined')
                    all_hashes = self.macho.get_similarity_hashes()
                    if all_hashes:
                        # Try 'fat' first, then 'combined' for backwards compatibility
                        similarity_hashes = all_hashes.get('fat', all_hashes.get('combined', {}))
                    else:
                        similarity_hashes = {}
                else:
                    # Single-arch with pre-parsed object
                    similarity_hashes = self.macho.get_similarity_hashes(arch=architectures[0]) if architectures else {}
            else:
                # No pre-parsed object - parse the file (slice case)
                import machofile
                macho = machofile.UniversalMachO(self.filepath)
                macho.parse()

                architectures = macho.get_architectures()
                if architectures:
                    # For a slice, there's only one architecture
                    similarity_hashes = macho.get_similarity_hashes(arch=architectures[0]) or {}
                else:
                    similarity_hashes = {}

            # Set the hash values on the Hashes object
            if similarity_hashes:
                if similarity_hashes.get('dylib_hash'):
                    self.hashes.macho_dylib_hash = similarity_hashes['dylib_hash']
                if similarity_hashes.get('import_hash'):
                    self.hashes.macho_import_hash = similarity_hashes['import_hash']
                if similarity_hashes.get('export_hash'):
                    self.hashes.macho_export_hash = similarity_hashes['export_hash']
                if similarity_hashes.get('entitlement_hash'):
                    self.hashes.macho_entitlement_hash = similarity_hashes['entitlement_hash']
                if similarity_hashes.get('symhash'):
                    self.hashes.macho_symhash = similarity_hashes['symhash']

        except Exception as e:
            self.log.error(f"Failed to extract Mach-O hashes: {e}")

    def _extract_apk_hashes(self):
        """Extract APK specific similarity hashes (permhash)."""
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            from permhash.functions import permhash_apk
            ph = permhash_apk(self.filepath)
            if ph:
                self.hashes.permhash = ph
        except Exception as e:
            self.log.error(f"Failed to extract APK hashes: {e}")

    def extract(self):
        try:
            self.log.debug(inspect.currentframe().f_code.co_name)
            self._extract_hashes()
            return self.hashes
        except Exception as e:
            self.log.error(f"Error extracting hashes: {e}")
            return None

    def prepare_export_data(self, exporter_type: str) -> Any:
        if exporter_type == "ElasticsearchExporter":
            return self.hashes
        elif exporter_type == "ClickHouseExporter":
            # Safely get hash values with fallbacks for None values
            sha256 = getattr(self.hashes, 'sha256', None) or ""
            md5 = getattr(self.hashes, 'md5', None) or ""
            sha1 = getattr(self.hashes, 'sha1', None) or ""
            ssdeep_hash = getattr(self.hashes, 'ssdeep_hash', None) or ""
            tlsh_hash = getattr(self.hashes, 'tlsh_hash', None) or ""
            authentihash = getattr(self.hashes, 'authentihash', None)
            imphash = getattr(self.hashes, 'imphash', None)
            impfuzzy = getattr(self.hashes, 'impfuzzy', None)
            typerefhash = getattr(self.hashes, 'typerefhash', None)
            richhash = getattr(self.hashes, 'richhash', None)
            richpe_hash = getattr(self.hashes, 'richpe_hash', None)
            richpv_hash = getattr(self.hashes, 'richpv_hash', None)
            richpv_hash_sorted = getattr(self.hashes, 'richpv_hash_sorted', None)
            # ELF hashes
            import_hash = getattr(self.hashes, 'import_hash', None)
            export_hash = getattr(self.hashes, 'export_hash', None)
            section_hash = getattr(self.hashes, 'section_hash', None)
            symbol_hash = getattr(self.hashes, 'symhash', None)
            dynamic_hash = getattr(self.hashes, 'dynamic_hash', None)
            # Mach-O hashes
            macho_dylib_hash = getattr(self.hashes, 'macho_dylib_hash', None)
            macho_import_hash = getattr(self.hashes, 'macho_import_hash', None)
            macho_export_hash = getattr(self.hashes, 'macho_export_hash', None)
            macho_entitlement_hash = getattr(self.hashes, 'macho_entitlement_hash', None)
            macho_symhash = getattr(self.hashes, 'macho_symhash', None)
            # APK hashes
            permhash = getattr(self.hashes, 'permhash', None)

            data = [[
                sha256,
                md5,
                sha1,
                ssdeep_hash,
                tlsh_hash,
                authentihash,
                imphash,
                impfuzzy,
                typerefhash,
                richhash,
                richpe_hash,
                richpv_hash,
                richpv_hash_sorted,
                import_hash,
                export_hash,
                section_hash,
                symbol_hash,
                dynamic_hash,
                macho_dylib_hash,
                macho_import_hash,
                macho_export_hash,
                macho_entitlement_hash,
                macho_symhash,
                permhash,
                datetime.now(timezone.utc)
            ]]

            column_names = [
                'sha256', 'md5', 'sha1', 'ssdeep_hash', 'tlsh_hash',
                'authentihash', 'imphash', 'impfuzzy', 'typerefhash',
                'richhash', 'richpe_hash', 'richpv_hash', 'richpv_hash_sorted',
                'import_hash', 'export_hash', 'section_hash', 'symbol_hash', 'dynamic_hash',
                'macho_dylib_hash', 'macho_import_hash', 'macho_export_hash',
                'macho_entitlement_hash', 'macho_symhash',
                'permhash',
                'analysis_date'
            ]

            column_type_names = [
                # sha256, md5, sha1
                'String', 'String', 'String',
                # ssdeep_hash, tlsh_hash
                'Nullable(String)', 'Nullable(String)',
                # authentihash, imphash, impfuzzy, typerefhash
                'Nullable(String)', 'Nullable(String)',
                'Nullable(String)', 'Nullable(String)',
                # richhash, richpe_hash, richpv_hash, richpv_hash_sorted
                'Nullable(String)', 'Nullable(String)',
                'Nullable(String)', 'Nullable(String)',
                # import_hash, export_hash, section_hash, symbol_hash, dynamic_hash
                'Nullable(FixedString(32))', 'Nullable(FixedString(32))',
                'Nullable(FixedString(32))', 'Nullable(FixedString(32))',
                'Nullable(FixedString(32))',
                # macho_dylib_hash, macho_import_hash, macho_export_hash, macho_entitlement_hash, macho_symhash
                'Nullable(FixedString(32))', 'Nullable(FixedString(32))',
                'Nullable(FixedString(32))', 'Nullable(FixedString(32))',
                'Nullable(FixedString(32))',
                # permhash (APK)
                'Nullable(FixedString(64))',
                # analysis_date
                'DateTime64(3, \'UTC\')'
            ]

            return (data, column_names, column_type_names)

    def get_clickhouse_table(self) -> str:
        return "redb_hashes"

    def tag(self):
        return Tag.HASH.value