Walter J. Gutjahr

83 papers A 2B 1C 2Journal 67Unranked 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
CoRR
Mahdi Mostajabdaveh, F. Sibel Salman, Walter J. Gutjahr
2025 J jnl
Eur. J. Oper. Res.
Mahdi Mostajabdaveh, F. Sibel Salman, Walter J. Gutjahr
2023 J jnl
CoRR
Najmesadat Nazemi, Sophie N. Parragh, Walter J. Gutjahr
2023 J jnl
Manuf. Serv. Oper. Manag.
Walter J. Gutjahr, Raimund M. Kovacevic, David Wozabal
2022 J jnl
OR Spectr.
Sophie N. Parragh, Fabien Tricoire, Walter J. Gutjahr
2022 C conf
ICORES
Najmesadat Nazemi, Sophie N. Parragh, Walter J. Gutjahr
2022 J jnl
Ann. Oper. Res.
Najmesadat Nazemi, Sophie N. Parragh, Walter J. Gutjahr
2022 J jnl
Central Eur. J. Oper. Res.
Roland Braune, Walter J. Gutjahr, Petra Vogl
2021 J jnl
Eur. J. Oper. Res.
Walter J. Gutjahr
2020 J jnl
CoRR
Najmesadat Nazemi, Sophie N. Parragh, Walter J. Gutjahr
2020 J jnl
OR Spectr.
Walter J. Gutjahr, Nilay Noyan, Nico Vandaele, Luk N. Van Wassenhove
2019 J jnl
IISE Trans.
Mahdi Mostajabdaveh, Walter J. Gutjahr, F. Sibel Salman
2019 J jnl
J. Sched.
Thomas Felberbauer, Walter J. Gutjahr, Karl F. Doerner
2019 J jnl
Comput. Manag. Sci.
Walter J. Gutjahr, Alois Pichler
2018 J jnl
Eur. J. Oper. Res.
Walter J. Gutjahr, Sophie Fischer
2017 J jnl
Comput. Oper. Res.
Jürgen Branke, Salvatore Corrente, Salvatore Greco, Walter J. Gutjahr
2017 J jnl
Ann. Oper. Res.
Christian Burkart, Pamela C. Nolz, Walter J. Gutjahr
2016 J jnl
Int. Trans. Oper. Res.
Stefan Rath, Michel Gendreau, Walter J. Gutjahr
2016 J jnl
Eur. J. Oper. Res.
Walter J. Gutjahr, Pamela C. Nolz
2016 J jnl
Ann. Oper. Res.
Walter J. Gutjahr, Alois Pichler
2015 J jnl
Eur. J. Oper. Res.
Walter J. Gutjahr
2015 conf
EMO (2)
Jürgen Branke, Salvatore Corrente, Salvatore Greco, Walter J. Gutjahr
2014 J jnl
Comput. Oper. Res.
Stefan Rath, Walter J. Gutjahr
2012 conf
OR
Walter J. Gutjahr
2012 J jnl
Central Eur. J. Oper. Res.
Peter Reiter, Walter J. Gutjahr
2012 J jnl
Evol. Comput.
Walter J. Gutjahr
2012 J jnl
Comput. Oper. Res.
Fabien Tricoire, Alexandra Graf, Walter J. Gutjahr
2011 ch.
Theory of Randomized Search Heuristics
Walter J. Gutjahr
2011 J jnl
OR Spectr.
Walter J. Gutjahr
2011 J jnl
Central Eur. J. Comput. Sci.
Walter J. Gutjahr
2011 J jnl
OR Spectr.
Karl F. Doerner, Walter J. Gutjahr, Luk N. Van Wassenhove
2010 ch.
Advances in Multi-Objective Nature Inspired Computing
Pamela C. Nolz, Karl F. Doerner, Walter J. Gutjahr, Richard F. Hartl
2010 ch.
Matheuristics
Walter J. Gutjahr
2010 J jnl
Oper. Res.
Marion S. Rauner, Walter J. Gutjahr, Kurt Heidenberger, Joachim Wagner, Joseph M. Pasia
2010 J jnl
Eur. J. Oper. Res.
Walter J. Gutjahr, Stefan Katzensteiner, Peter Reiter, Christian Stummer, Michaela Denk
2009 J jnl
Int. J. Inf. Technol. Decis. Mak.
Christian Stummer, Elmar Kiesling, Walter J. Gutjahr
2009 J jnl
J. Heuristics
Walter J. Gutjahr
2009 J jnl
Nat. Comput.
Leonora Bianchi, Marco Dorigo, Luca Maria Gambardella, Walter J. Gutjahr
2009 J jnl
OR Spectr.
Karl F. Doerner, Walter J. Gutjahr, Pamela C. Nolz
2008 J jnl
Central Eur. J. Oper. Res.
Walter J. Gutjahr, Stefan Katzensteiner, Peter Reiter, Christian Stummer, Michaela Denk
2008 J jnl
Comput. Oper. Res.
Walter J. Gutjahr
2008 J jnl
Comput. Oper. Res.
Walter J. Gutjahr, Mark Harman
2007 conf
SAGA
Walter J. Gutjahr, Stefan Katzensteiner, Peter Reiter
2007 J jnl
Comput. Oper. Res.
Walter J. Gutjahr, Marion S. Rauner
2007 J jnl
Comput. Manag. Sci.
Sally C. Brailsford, Walter J. Gutjahr, Marion S. Rauner, Wolfgang Zeppelzauer
2007 J jnl
Swarm Intell.
Walter J. Gutjahr
2007 book
Metaheuristics
Karl F. Doerner, Michel Gendreau, Peter Greistorfer, Walter J. Gutjahr, Richard F. Hartl, Marc Reimann
2007 J jnl
Eur. J. Oper. Res.
Karl Doerner, Axel Focke, Walter J. Gutjahr
2006 J jnl
Eur. J. Oper. Res.
Karl F. Doerner, Walter J. Gutjahr, Gabriele Kotsis, Martin Polaschek, Christine Strauss
2006 J jnl
Central Eur. J. Oper. Res.
Walter J. Gutjahr
2006 J jnl
Eur. J. Oper. Res.
Karl F. Doerner, Walter J. Gutjahr, Richard F. Hartl, Christine Strauss, Christian Stummer
2005 conf
SAGA
Walter J. Gutjahr
2004 C conf
ACC
Hyeong Soo Chang, Walter J. Gutjahr, Jihoon Yang, Sungyong Park
2004 J jnl
Ann. Oper. Res.
Karl F. Doerner, Walter J. Gutjahr, Richard F. Hartl, Christine Strauss, Christian Stummer
2004 conf
ANTS Workshop
Walter J. Gutjahr
2003 conf
SAGA
Walter J. Gutjahr
2003 A conf
GECCO
Karl Doerner, Walter J. Gutjahr
2002 J jnl
Comput. Oper. Res.
Walter J. Gutjahr, Gabriele Uchida
2002 J jnl
Inf. Process. Lett.
Walter J. Gutjahr
2002 J jnl
Empir. Softw. Eng.
Stefan Biffl, Walter J. Gutjahr
2001 J jnl
Comput. Syst. Sci. Eng.
Walter J. Gutjahr
2001 conf
IEEE METRICS
Stefan Biffl, Walter J. Gutjahr
2000 J jnl
Future Gener. Comput. Syst.
Walter J. Gutjahr
2000 J jnl
INFORMS J. Comput.
Walter J. Gutjahr, Christine Strauss, Eric W. Wagner
2000 J jnl
Bus. Process. Manag. J.
Walter J. Gutjahr, Christine Strauss, Martin Tóth
2000 J jnl
Inf. Softw. Technol.
Karl Doerner, Walter J. Gutjahr
2000 J jnl
Perform. Evaluation
Walter J. Gutjahr
1999 J jnl
Eur. J. Oper. Res.
Walter J. Gutjahr, A. Hellmayr, Georg Ch. Pflug
1999 J jnl
IEEE Trans. Software Eng.
Walter J. Gutjahr
1998 A conf
ISSRE
Walter J. Gutjahr
1997 J jnl
Int. J. Comput. Math.
Walter J. Gutjahr, Ch. E. Wöber
1997 J jnl
Parallel Comput.
Walter J. Gutjahr, Martin Hitz, Thomas A. Mück
1996 B conf
SAFECOMP
Walter J. Gutjahr
1996 J jnl
J. Glob. Optim.
Walter J. Gutjahr, Georg Ch. Pflug
1995 J jnl
IEEE Trans. Software Eng.
Walter J. Gutjahr
1994 J jnl
J. Glob. Optim.
Walter J. Gutjahr
1994 J jnl
Random Struct. Algorithms
Walter J. Gutjahr
1993 J jnl
Inform. Forsch. Entwickl.
Walter J. Gutjahr
1993 J jnl
Random Struct. Algorithms
Walter J. Gutjahr
1992 J jnl
Random Struct. Algorithms
Walter J. Gutjahr
1992 J jnl
Graphs Comb.
Walter J. Gutjahr, Georg Ch. Pflug
1992 J jnl
RAIRO Theor. Informatics Appl.
Walter J. Gutjahr, Georg Ch. Pflug
1991 J jnl
Computing
Walter J. Gutjahr
redb/extractors/decompiler/_archive/DecompileGhidra.py
← Index redb/extractors/decompiler/_archive/DecompileGhidra.py python
from hashlib import sha256, md5
import inspect
import subprocess
import json
import os
import time
from datetime import datetime, timezone
from typing import Dict, List, Any, Optional

from dotenv import load_dotenv
from redb.extractors.enum import Tag
from redb.extractors.extractor import Extractor
import magic
import pefile
import ppdeep
import tlsh


class DecompileGhidra(Extractor):
    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        filetype=None,
    ):
        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            elastic_index,
            known_benign,
            known_malicious,
        )
        self.log.debug(inspect.currentframe().f_code.co_name)
        self.ghidra_path = os.getenv("GHIDRA_PATH", "/opt/ghidra")
        self.java_script_path = os.getenv(
            "GHIDRA_SCRIPT_PATH",
            "/opt/ghidra/Ghidra/Features/Base/ghidra_scripts/GhidraDecompilerScript.java",
        )
        self.analysis_results = None
        self.ghidra_process = None  # Track the current process
        self.project_path = None
        self.filetype = filetype

        # Convert TIMEOUT to integer with a default of 1200 seconds (20 minutes)
        try:
            self.TIMEOUT = int(os.getenv("GHIDRA_TIMEOUT", "1200"))
        except ValueError:
            self.log.warning(
                "Invalid GHIDRA_TIMEOUT value, using default of 1200 seconds"
            )
            self.TIMEOUT = 1200

        self.initialize_project()

    def __enter__(self):
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        self.cleanup_run()

    def is_dotnet(self):
        try:
            if self.filetype == "pebin":
                file_type = magic.from_buffer(self.binary)
                if ".Net" in file_type:
                    return True
                pe = pefile.PE(self.filepath)
                for entry in pe.OPTIONAL_HEADER.DATA_DIRECTORY:
                    # IMAGE_DIRECTORY_ENTRY_COM_DESCRIPTOR is typically 14
                    if (
                        entry.name == "IMAGE_DIRECTORY_ENTRY_COM_DESCRIPTOR"
                        and entry.Size > 0
                    ):
                        return True
                return False
        except AttributeError as e:
            self.log.error(
                f"AttributeError error dotnet file {self.hash.sha256} Full error : {e}"
            )
            return False

    def cleanup_run(self):
        """Clean up after analysis."""
        try:
            if self.ghidra_process and self.ghidra_process.poll() is None:
                self.ghidra_process.terminate()
                try:
                    self.ghidra_process.wait(timeout=5)
                except subprocess.TimeoutExpired:
                    self.ghidra_process.kill()

            # Clean up project directory
            if self.project_path and os.path.exists(self.project_path):
                import shutil

                shutil.rmtree(self.project_path)
                self.log.debug(f"Cleaned up project directory: {self.project_path}")

            # Force garbage collection
            import gc

            gc.collect()
        except Exception as e:
            self.log.error(f"Error in cleanup: {e}")

    # @classmethod
    # def cleanup_batch(cls):
    #     """Clean up the persistent project at the end of a batch."""
    #     print(f"Cleaning up Ghidra project for batch")
    #     if cls._project_path and os.path.exists(cls._project_path):
    #         try:
    #             import shutil
    #             shutil.rmtree(cls._project_path)
    #             cls._project_initialized = False
    #             cls._project_path = None
    #         except Exception as e:
    #             print(f"Error cleaning up project: {e}")

    def _get_environment(self):
        """Setup and return the environment for Ghidra."""
        env = os.environ.copy()
        java_home = os.getenv("GHIDRA_JAVA_HOME", "/usr/lib/jvm/java-17-openjdk-amd64")
        env.update(
            {
                "JAVA_HOME": java_home,
                "PATH": f"{java_home}/bin:{env['PATH']}",
                "LD_LIBRARY_PATH": f"{java_home}/lib:{env.get('LD_LIBRARY_PATH', '')}",
            }
        )
        # Print environment variables for debugging
        self.log.debug(f"JAVA_HOME: {env['JAVA_HOME']}")
        self.log.debug(f"PATH: {env['PATH']}")
        self.log.debug(f"LD_LIBRARY_PATH: {env['LD_LIBRARY_PATH']}")

        return env

    def initialize_project(self):
        """Initialize a temporary Ghidra project for this file."""
        # Create unique project directory
        self.project_path = f"/tmp/ghidra_{os.path.basename(self.filepath)}_{str(int(time.time()))}_{os.getpid()}"
        os.makedirs(self.project_path, exist_ok=True)
        self.log.debug(f"Created temporary project at {self.project_path}")

        # Create a minimal initialization file
        init_file = os.path.join(self.project_path, ".init")
        with open(init_file, "wb") as f:
            f.write(bytes([0x7F, 0x45, 0x4C, 0x46]))  # Valid ELF header magic bytes

        # Initialize project with minimal file
        env = self._get_environment()
        cmd = [
            f"{self.ghidra_path}/support/analyzeHeadless",
            self.project_path,
            "TempProject",
            "-import",
            init_file,
        ]

        try:
            result = subprocess.run(cmd, env=env, capture_output=True, text=True)
            if result.returncode != 0:
                self.log.error(f"Failed to initialize project: {result.stderr}")
                raise RuntimeError("Project initialization failed")

            # Clean up initialization file
            os.remove(init_file)
            self.log.debug("Project initialized successfully")

        except Exception as e:
            self.log.error(f"Error initializing project: {e}")
            raise

    def analyze_binary(self) -> Optional[Dict[str, Any]]:
        """Run Ghidra analysis and return results."""
        self.log.debug("Starting binary analysis")

        # # Check if packed
        # if self.check_binary_protection():
        #     self.log.warning("Skipping protected binary")
        #     return None

        # Check for .NET only if needed
        # if self.is_dotnet():
        #     self.MAX_NAMED_ARG_WARNINGS = 10000  # Higher threshold for .NET
        #     self.log.info("Adjusting parameters for .NET binary")
        # else:
        #     self.MAX_NAMED_ARG_WARNINGS = 1000  # Normal threshold

        if not os.path.exists(self.java_script_path):
            self.log.error(f"Java script not found: {self.java_script_path}")
            return None

        env = self._get_environment()

        try:
            base_cmd = [
                f"{self.ghidra_path}/support/analyzeHeadless",
                self.project_path,
                "TempProject",
                "-import",
                self.filepath,
                "-scriptPath",
                os.path.dirname(self.java_script_path),
                "-postScript",
                self.java_script_path,
                self.sha256,
                self.filepath,
            ]
            return self.run_ghidra(base_cmd, env)

        except Exception as e:
            self.log.error(f"Error in Ghidra analysis: {e}")
            return None

        finally:
            self.cleanup_run()

    def run_ghidra(
        self, cmd: list, env: Optional[Dict[str, str]] = None
    ) -> Optional[Dict[str, Any]]:
        """Run Ghidra process and capture JSON output with improved logging separation."""
        process = None
        try:
            self.log.info(f"Starting Ghidra analysis: {' '.join(cmd)}")
            start_time = time.time()

            process = subprocess.Popen(
                cmd, env=env, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True
            )
            self.ghidra_process = process

            warning_counter = 0
            named_arg_counter = 0
            # Read all output lines
            json_output = None
            while True:
                line = process.stdout.readline()
                if not line and process.poll() is not None:
                    break

                stripped_line = line.strip()
                if not stripped_line:
                    continue

                # if 'Invalid FieldOrProp value in NamedArg' in stripped_line:
                #     named_arg_counter += 1
                #     if named_arg_counter > self.MAX_NAMED_ARG_WARNINGS:
                #         self.log.error(f"Too many NamedArg warnings ({named_arg_counter}), possible protected file.")
                #         self.ghidra_process.kill()
                #         return None
                if (
                    stripped_line.startswith("{")
                    and '"sha256"' in stripped_line
                    and '"decompiled"' in stripped_line
                ):
                    # This is our actual JSON output from GhidraDecompilerScript
                    json_output = stripped_line
                elif any(level in stripped_line for level in ["INFO", "WARN", "ERROR"]):
                    # Ghidra framework logging
                    log_level = (
                        "debug"
                        if "INFO" in stripped_line
                        else "warning"
                        if "WARN" in stripped_line
                        else "error"
                    )
                    if log_level == "warning" and any(
                        expected in stripped_line
                        for expected in [
                            "Unable to disassemble EXTERNAL block",
                            "Failed to markup ELF Note",
                            "Invalid FieldOrProp value in NamedArg",
                            "Unable to resolve constructor",
                            "Could not follow disassembly flow into non-existing memory",
                            "Unable to read bytes at ram",
                        ]
                    ):
                        # Skip expected warnings
                        continue

                    getattr(self.log, log_level)(f"Ghidra info: {stripped_line}")

            # Process completion and stderr
            try:
                stderr = process.stderr.read()
                process.wait(timeout=self.TIMEOUT)

                if stderr:
                    for line in stderr.splitlines():
                        stripped_line = line.strip()
                        if not stripped_line:
                            continue
                        if "ERROR" in stripped_line:
                            self.log.error(f"Ghidra stderr: {stripped_line}")
                        elif "WARN" in stripped_line:
                            self.log.warning(f"Ghidra stderr: {stripped_line}")
                        else:
                            self.log.debug(f"Ghidra stderr: {stripped_line}")

            except subprocess.TimeoutExpired:
                process.kill()
                self.log.error("Ghidra analysis timed out")
                return None

            elapsed_time = time.time() - start_time
            self.log.debug(f"Ghidra analysis completed in {elapsed_time:.2f}s")

            # Parse JSON output if we found it
            if json_output:
                try:
                    result = json.loads(json_output)
                    # Validate the required structure
                    if not isinstance(result, dict) or not all(
                        k in result
                        for k in ["sha256", "decompiled", "disassembled", "cfg"]
                    ):
                        self.log.error("Invalid JSON structure from Ghidra")
                        return None
                    return result
                except json.JSONDecodeError as e:
                    self.log.error(f"Failed to parse Ghidra JSON output: {e}")
                    return None
            else:
                self.log.error("No JSON output received from Ghidra")
                return None

        except Exception as e:
            self.log.error(f"Error running Ghidra: {str(e)}")
            if hasattr(e, "__traceback__"):
                import traceback

                self.log.debug(
                    f"Traceback: {''.join(traceback.format_tb(e.__traceback__))}"
                )
            return None

        finally:
            if process:
                try:
                    # Ensure pipes are closed
                    if process.stdout:
                        process.stdout.close()
                    if process.stderr:
                        process.stderr.close()
                    # Terminate process if still running
                    if process.poll() is None:
                        process.terminate()
                        try:
                            process.wait(timeout=5)
                        except subprocess.TimeoutExpired:
                            process.kill()
                except Exception as e:
                    self.log.error(f"Error cleaning up Ghidra process: {e}")

    def extract(self) -> bool:
        """Extract and process all analysis results."""
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            results = self.analyze_binary()
            if not results:
                return False

            self.analysis_results = results
            return True

        except Exception as e:
            self.log.error(f"Error in extraction: {e}")
            return False

    def prepare_export_data(self, exporter_type: str) -> Any:
        """Prepare data for database export."""
        self.log.debug(inspect.currentframe().f_code.co_name)
        if not self.analysis_results:
            return None

        if exporter_type == "ClickHouseExporter":
            now = datetime.now(timezone.utc)

            def prepare_array_field(value, array_type):
                """Helper to prepare array fields with proper null handling"""
                if value is None:
                    return []
                return value

            def ssdeep_disassembly(func):
                try:
                    if len(func) > 1:
                        return ppdeep.hash(func)
                    return ""
                except Exception as e:
                    self.log.error(f"Error in disassembly ssdeep hash calculation: {e}")
                    return ""

            def tlsh_disassembly(func):
                try:
                    if len(func) >= 50:
                        return tlsh.hash(func.encode("utf-8"))
                    return ""
                except Exception as e:
                    self.log.error(f"Error in disassembly tlsh hash calculation: {e}")
                    return ""

            return {
                "multi_table": True,
                "decompiled_content": {
                    "table": "decompiled_functions_content",
                    "data": [
                        [
                            f["decompiled_content_hash"],
                            f["decompiled_function"],
                            f["function_type"],
                            now,
                        ]
                        for f in self.analysis_results["decompiled"]
                    ],
                    "column_names": [
                        "decompiled_content_hash",
                        "decompiled_function",
                        "function_type",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "String",
                        "Enum8('USER'=1, 'LIBRARY'=2, 'THUNK'=3, 'EXTERNAL'=4, 'UNKNOWN'=5)",
                        "DateTime64(3, 'UTC')",
                    ],
                },
                "decompiled_refs": {
                    "table": "decompiled_functions_references",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            f["decompiled_content_hash"],
                            f["decompiled_function_name"],
                            f["decompiled_function_address"],
                            now,
                        ]
                        for f in self.analysis_results["decompiled"]
                    ],
                    "column_names": [
                        "sha256",
                        "decompiled_content_hash",
                        "decompiled_function_name",
                        "decompiled_function_address",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(64)",
                        "LowCardinality(String)",
                        "String",
                        "DateTime64(3, 'UTC')",
                    ],
                },
                "disassembled_content": {
                    "table": "disassembled_functions_content",
                    "data": [
                        [
                            f["disassembled_content_hash"],
                            f["fully_normalized_content_hash"],
                            f["api_normalized_content_hash"],
                            f["category_normalized_content_hash"],
                            f.get("disassembled_function", ""),
                            f.get("fully_normalized_disassembly", ""),
                            f.get("api_normalized_disassembly", ""),
                            f.get("category_normalized_disassembly", ""),
                            ssdeep_disassembly(f.get("disassembled_function", "")),
                            tlsh_disassembly(f.get("disassembled_function", "")),
                            ssdeep_disassembly(
                                f.get("fully_normalized_disassembly", "")
                            ),
                            tlsh_disassembly(f.get("fully_normalized_disassembly", "")),
                            f.get("function_type", "UNKNOWN"),
                            f.get("instruction_count", 0),
                            prepare_array_field(
                                f.get("instruction_types"), "LowCardinality(String)"
                            ),
                            f.get("control_flow_count", 0),
                            prepare_array_field(
                                f.get("memory_access_pattern"), "LowCardinality(String)"
                            ),
                            prepare_array_field(
                                f.get("register_usage"), "LowCardinality(String)"
                            ),
                            f.get("data_references_count", 0),
                            # prepare_array_field(f.get('opcode_frequency_vector'), 'Float32'),
                            # prepare_array_field(f.get('api_calls_vector'), 'Float32'),
                            # prepare_array_field(f.get('minhash_signature'), 'UInt64'),
                            # f.get('pic_hash', ''),
                            f.get("max_block_size", 0),
                            f.get("num_calls", 0),
                            f.get("stack_size", 0),
                            # prepare_array_field(f.get('instruction_type_ratios'), 'Float32'),
                            # prepare_array_field(f.get('instruction_embedding'), 'Float32'),
                            now,
                        ]
                        for f in self.analysis_results["disassembled"]
                    ],
                    "column_names": [
                        "disassembled_content_hash",
                        "fully_normalized_content_hash",
                        "api_normalized_content_hash",
                        "category_normalized_content_hash",
                        "disassembled_function",
                        "fully_normalized_disassembly",
                        "api_normalized_disassembly",
                        "category_normalized_disassembly",
                        "ssdeep_disassembly",
                        "tlsh_disassembly",
                        "ssdeep_fully_normalized",
                        "tlsh_fully_normalized",
                        "function_type",
                        "instruction_count",
                        "instruction_types",
                        "control_flow_count",
                        "memory_access_pattern",
                        "register_usage",
                        "data_references_count",
                        # 'opcode_frequency_vector',
                        # 'api_calls_vector',
                        # 'minhash_signature',
                        # 'pic_hash',
                        "max_block_size",
                        "num_calls",
                        "stack_size",
                        # 'instruction_type_ratios',
                        # 'instruction_embedding',
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(64)",
                        "FixedString(64)",
                        "FixedString(64)",
                        "String",
                        "String",
                        "String",
                        "String",
                        "Nullable(String)",
                        "Nullable(FixedString(72))",
                        "Nullable(String)",
                        "Nullable(FixedString(72))",
                        "Enum8('USER'=1, 'LIBRARY'=2, 'THUNK'=3, 'EXTERNAL'=4, 'UNKNOWN'=5)",
                        "UInt32",
                        "Array(LowCardinality(String))",
                        "UInt32",
                        "Array(LowCardinality(String))",
                        "Array(LowCardinality(String))",
                        "UInt32",
                        # 'Array(Float32)',
                        # 'Array(Float32)',
                        # 'Array(UInt64)',
                        # 'Nullable(FixedString(16))',
                        "Nullable(UInt32)",
                        "Nullable(UInt32)",
                        "Nullable(Int32)",
                        # 'Array(Float32)',
                        # 'Array(Float32)',
                        "DateTime64(3, 'UTC')",
                    ],
                },
                "disassembled_refs": {
                    "table": "disassembled_functions_references",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            f["disassembled_content_hash"],
                            f["fully_normalized_content_hash"],
                            f["api_normalized_content_hash"],
                            f["category_normalized_content_hash"],
                            f["disassembled_function_name"],
                            f["disassembled_function_address"],
                            now,
                        ]
                        for f in self.analysis_results["disassembled"]
                    ],
                    "column_names": [
                        "sha256",
                        "disassembled_content_hash",
                        "fully_normalized_content_hash",
                        "api_normalized_content_hash",
                        "category_normalized_content_hash",
                        "disassembled_function_name",
                        "disassembled_function_address",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(64)",
                        "FixedString(64)",
                        "FixedString(64)",
                        "FixedString(64)",
                        "LowCardinality(String)",
                        "String",
                        "DateTime64(3, 'UTC')",
                    ],
                },
                "cfg_blocks": {
                    "table": "cfg_blocks",
                    "data": [
                        [
                            b["block_id"],
                            self.analysis_results["sha256"],
                            b["function_address"],
                            b["block_start_address"],
                            b["block_end_address"],
                            b["block_size"],
                            b["block_instructions"],
                            b["fully_normalized_instructions"],
                            b["api_normalized_instructions"],
                            b["category_normalized_instructions"],
                            b.get("predecessor_blocks", []),
                            b.get("successor_blocks", []),  # Use empty array as default
                            b.get("is_entry_block", False),
                            b.get("is_exit_block", False),
                            b.get("branch_type", "UNKNOWN"),
                            b.get("referenced_constants", []),
                            b.get("sign", 1),  # Use 1 as default for sign
                            now,
                        ]
                        for b in self.analysis_results["cfg"]
                    ],
                    "column_names": [
                        "block_id",
                        "sha256",
                        "function_address",
                        "block_start_address",
                        "block_end_address",
                        "block_size",
                        "block_instructions",
                        "fully_normalized_instructions",
                        "api_normalized_instructions",
                        "category_normalized_instructions",
                        "predecessor_blocks",
                        "successor_blocks",
                        "is_entry_block",
                        "is_exit_block",
                        "branch_type",
                        "referenced_constants",
                        "sign",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(64)",
                        "String",
                        "String",
                        "String",
                        "UInt32",
                        "String",
                        "Nullable(String)",
                        "Nullable(String)",
                        "Nullable(String)",
                        "Array(String)",
                        "Array(String)",
                        "Bool",
                        "Bool",
                        "Enum8('DIRECT'=1, 'CONDITIONAL'=2, 'CALL'=3, 'RETURN'=4, 'FALLTHROUGH'=5, 'UNKNOWN'=6)",
                        "Array(String)",
                        "Int8",
                        "DateTime64(3, 'UTC')",
                    ],
                },
                "function_analysis_errors": {
                    "table": "function_analysis_errors",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            f["function_name"],
                            f["function_address"],
                            f["error_location"],
                            f.get(
                                "error_message", ""
                            ),  # it could be empty, how to handle it?
                            f.get("error_details", ""),
                            f.get("error_type", "unknown"),
                            md5(
                                f"{f['error_message']}{f['function_name']}{f['function_address']}{f['error_location']}".encode()
                            ).hexdigest(),
                            "new",
                            now,
                        ]
                        for f in self.analysis_results["errors"]
                    ],
                    "column_names": [
                        "sha256",
                        "function_name",
                        "function_address",
                        "error_location",
                        "error_message",
                        "error_details",
                        "error_type",
                        "error_hash",
                        "status",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "Nullable(String)",
                        "String",
                        "LowCardinality(String)",
                        "Nullable(String)",
                        "Nullable(String)",
                        "Nullable(String)",
                        "FixedString(32)",
                        "Enum8('new'=1, 'investigating'=2, 'fixed'=3, 'wontfix'=4)",
                        "DateTime64(3, 'UTC')",
                    ],
                },
            }

    def tag(self) -> str:
        """Return the tag for this extractor."""
        return Tag.DECOMPILED.value

    def get_clickhouse_table(self) -> str:
        """Not used directly as we're handling multiple tables."""
        pass