Kais Klai

76 papers A 7B 8C 18Misc 1Journal 12Unranked 30
YearRankTypeTitle / Venue / Authors
2024 C conf
VECoS
Kais Klai, Mohamed Taha Bennani, Jaime Arias, Hanen Ochi, Hadhami Elouni
2023 C conf
CoDIT
Nour Elhouda Souid, Kais Klai, Chiheb Ameur Abid, Samir Ben Ahmed
2023 C conf
TAP
Kais Klai, Mohamed Taha Bennani, Jaime Arias, Jörg Desel, Hanen Ochi
2022 B conf
CoopIS
Nour Elhouda Souid, Kais Klai, Chiheb Ameur Abid, Samir Ben Ahmed
2022 conf
ISPA/BDCloud/SocialCom/SustainCom
Hanen Ochi, Kais Klai
2022 C conf
CoDIT
Nour Elhouda Souid, Kais Klai, Chiheb Ameur Abid, Samir Ben Ahmed
2022 conf
ISPA/BDCloud/SocialCom/SustainCom
Nour Elhouda Souid, Kais Klai, Chiheb Ameur Abid, Samir Ben Ahmed
2021 conf
ICICS (2)
Nour Elhouda Souid, Kais Klai
2021 conf
ACSW
Ikram Garfatta, Kais Klai, Walid Gaaloul, Mohamed Graiet
2021 conf
SCC
Rania Ben Halima, Kais Klai, Mohamed Sellami, Zakaria Maamar
2021 C conf
VECoS
Kais Klai, Chiheb Ameur Abid, Jaime Arias, Sami Evangelista
2019 conf
ISPA/BDCloud/SocialCom/SustainCom
Rakesh Jain, Kais Klai, Samir Tata
2019 B conf
ICECCS
Amina Bourouis, Kais Klai, Nejib Ben Hadj-Alouane
2019 conf
HPCS
Hiba Ouni, Kais Klai, Belhassen Zouari
2019 conf
ACSD
Hiba Ouni, Kais Klai, Chiheb Ameur Abid, Belhassen Zouari
2018 conf
OTM Conferences (1)
Souha Boubaker, Kais Klai, Hedi Kortas, Walid Gaaloul
2018 J jnl
Int. J. Crit. Comput. Based Syst.
Abderraouf Boussif, Mohamed Ghazel, Kais Klai
2018 conf
OTM Conferences (1)
Ikram Garfatta, Kais Klai, Mohamed Graiet, Walid Gaaloul
2018 conf
ISPA/IUCC/BDCloud/SocialCom/SustainCom
Hiba Ouni, Kais Klai, Chiheb Ameur Abid, Belhassen Zouari
2018 conf
SOCA
Ikram Garfatta, Kais Klai, Mohamed Graiet, Walid Gaaloul
2017 conf
SCSS
Hiba Ouni, Kais Klai, Chiheb Ameur Abid, Belhassen Zouari
2017 conf
SCC
Amina Burouis, Nejib Ben Hadj-Alouane, Kais Klai
2017 A conf
ICSOC
Souha Boubaker, Kais Klai, Katia Schmitz, Mohamed Graiet, Walid Gaaloul
2017 B conf
ICSSP
Souheib Baarir, Kais Klai
2017 conf
OTM Conferences (1)
Samir Tata, Kais Klai, Rakesh Jain
2017 C conf
iiWAS
Amina Bourouis, Kais Klai, Nejib Ben Hadj-Alouane
2017 J jnl
IEEE Trans. Serv. Comput.
Amina Bourouis, Kais Klai, Nejib Ben Hadj-Alouane, Yamen El Touati
2017 conf
ISPA/IUCC
Hiba Ouni, Kais Klai, Chiheb Ameur Abid, Belhassen Zouari
2017 C conf
WETICE
Mohamed Graiet, Kais Klai
2016 B conf
CCGrid
Kais Klai, Hanen Ochi
2016 conf
OTM Conferences
Rania Ben Halima, Slim Kallel, Kais Klai, Walid Gaaloul, Mohamed Jmaiel
2016 A conf
ICWS
Kais Klai, Hanen Ochi
2016 C conf
WETICE
Mohamed Graiet, Kais Klai
2015 Misc conf
TASE
Kais Klai, Hanen Ochi
2015 J jnl
Int. J. Inf. Technol. Web Eng.
Amina Bourouis, Kais Klai, Yamen El Touati, Nejib Ben Hadj-Alouane
2015 C conf
VECoS
Abderraouf Boussif, Mohamed Ghazel, Kais Klai
2015 C conf
WETICE
Mohamed Graiet, Kais Klai
2015 conf
COMPSAC Workshops
Kais Klai, Hanen Ochi
2015 A conf
ICWS
Amina Bourouis, Kais Klai, Yamen El Touati, Nejib Ben Hadj-Alouane
2015 conf
PNSE @ Petri Nets
Camille Coti, Sami Evangelista, Kais Klai
2015 J jnl
CoRR
Camille Coti, Sami Evangelista, Kais Klai
2015 J jnl
Trans. Petri Nets Other Model. Concurr.
Kais Klai
2014 C conf
WETICE
Kais Klai, Nawel Hamdi, Nejib Ben Hadj-Alouane
2014 conf
OTM Conferences
Sami Yangui, Kais Klai, Samir Tata
2014 conf
PNSE @ Petri Nets
Kais Klai
2014 C conf
WETICE
Mohamed Graiet, Zied Jaoua, Kais Klai
2013 C conf
TIME
Kais Klai, Naim Aber, Laure Petrucci
2013 conf
FSEN
Kais Klai, Hanen Ochi
2013 A conf
ICWS
Kais Klai, Hanen Ochi, Samir Tata
2013 conf
IEEE SCC
Kais Klai, Samir Tata
2013 conf
CloudCom (1)
Mourad Amziani, Kais Klai, Tarek Melliti, Samir Tata
2013 conf
RP
Kais Klai, Naim Aber, Laure Petrucci
2012 conf
Monterey Workshop
Étienne André, Kais Klai, Hanen Ochi, Laure Petrucci
2012 A conf
ICWS
Kais Klai, Hanen Ochi
2012 conf
FMOODS/FORTE
Kais Klai, Jörg Desel
2012 C conf
GPC
Leila Abidi, Christophe Cérin, Kais Klai
2012 J jnl
ACM SIGSOFT Softw. Eng. Notes
Étienne André, Christine Choppy, Kais Klai
2012 J jnl
Int. J. Web Serv. Res.
Kais Klai, Samir Tata, Hanen Ochi
2012 J jnl
Trans. Petri Nets Other Model. Concurr.
Christine Choppy, Anna Dedova, Sami Evangelista, Kais Klai, Laure Petrucci, Samir Youcef
2011 J jnl
CoRR
Alexandre Duret-Lutz, Kais Klai, Denis Poitrenaud, Yann Thierry-Mieg
2011 J jnl
ACM SIGSOFT Softw. Eng. Notes
Christine Choppy, Kais Klai, Hacene Zidani
2011 C conf
WETICE
Kais Klai, Walid Gaaloul
2011 B conf
ATVA
Alexandre Duret-Lutz, Kais Klai, Denis Poitrenaud, Yann Thierry-Mieg
2011 J jnl
Data Knowl. Eng.
Kais Klai, Samir Tata, Jörg Desel
2010 B conf
Petri Nets
Christine Choppy, Anna Dedova, Sami Evangelista, Silien Hong, Kais Klai, Laure Petrucci
2009 A conf
BPM
Kais Klai, Samir Tata, Jörg Desel
2008 J jnl
IEEE Trans. Serv. Comput.
Samir Tata, Kais Klai, Nomane Ould Ahmed M'Bareck
2008 B conf
Petri Nets
Kais Klai, Denis Poitrenaud
2008 conf
ACSD
Kais Klai, Laure Petrucci
2007 C conf
FORTE
Kais Klai, Laure Petrucci, Michel A. Reniers
2006 conf
MSVVEIS
Kais Klai, Samir Tata, Issam Chebbi
2006 A conf
Business Process Management
Kais Klai, Nomane Ould Ahmed M'Bareck, Samir Tata
2005 C conf
WETICE
Kais Klai, Samir Tata
2005 C conf
FORTE
Kais Klai, Serge Haddad, Jean-Michel Ilié
2005 conf
ICATPN
Kamel Barkaoui, Jean-Michel Couvreur, Kais Klai
2004 B conf
ATVA
Serge Haddad, Jean-Michel Ilié, Kais Klai
redb/extractors/decompiler/DecompileBinja.py
← Index redb/extractors/decompiler/DecompileBinja.py python
import hashlib
import inspect
import json
import logging
import os
import signal
import time
from datetime import datetime, timezone
from typing import Dict, Any, Optional
from pathlib import Path
import subprocess
import sys

from redb.extractors.enum import Tag
from redb.extractors.extractor import Extractor
import magic
import pefile
from elftools.elf.elffile import ELFFile

# Import our BinjaDecompiler (conditional)
from redb.extractors.decompiler.bninja.decompiler import BinaryNinjaDecompiler

class DecompileBinja(Extractor):
    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        filetype=None,
        decompile_modules=None,
    ):
        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            elastic_index,
            known_benign,
            known_malicious,
        )
        self.log.debug(inspect.currentframe().f_code.co_name)

        # Check if Binary Ninja is available
       # if not BINARYNINJA_AVAILABLE:
        #     self.log.error("Binary Ninja is not available in this container")
        #    raise ImportError(
        #        "Binary Ninja module not found - not available in feature extraction container"
        #    )
        self.analysis_results = None
        self.binja_decompiler = None
        self.filetype = filetype
        self.decompile_modules = decompile_modules or {"all"}
        self.goresym_data = None
        self.goresym_output_path = None

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

        # Convert TIMEOUT to integer with a default of 1200 seconds (20 minutes)
        try:
            self.DECOMPILE_EXTRACTOR_TIMEOUT = int(
                os.getenv("DECOMPILE_EXTRACTOR_TIMEOUT", "2580")
            )
        except ValueError:
            self.log.warning(
                "Invalid DECOMPILE_EXTRACTOR_TIMEOUT value, using default of 2580 seconds"
            )
            self.DECOMPILE_EXTRACTOR_TIMEOUT = 2580

    def __enter__(self):
        return self

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

    def calculate_md5(self, input_str):
        """Calculate MD5 hash of a string."""
        return hashlib.md5(input_str.encode("utf-8")).hexdigest()

    def is_dotnet(self):
        """Check if the binary is a .NET assembly.

        Returns:
            bool: True if the file is a .NET assembly, False otherwise
        """
        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
            return False
        except AttributeError as e:
            self.log.error(
                f"AttributeError error dotnet file {self.hash.sha256} Full error : {e}"
            )
            return False

    def is_golang(self):
        """Check if the binary is a Go-compiled binary (heuristic).

        Supports PE and ELF binaries.
        """
        try:
            if self.filetype == "pebin":
                pe = pefile.PE(self.filepath)
                signatures = [b"Go build ID:", b"runtime.main", b"main.main"]

                for section in pe.sections:
                    data = section.get_data()
                    if any(sig in data for sig in signatures):
                        return True

                return False

            elif self.filetype == "elf":
                with open(self.filepath, "rb") as f:
                    elf = ELFFile(f)

                    # 1. Section-based checks
                    section_names = [sec.name for sec in elf.iter_sections()]
                    if any(
                        s in section_names
                        for s in (".note.go.buildid", ".gopclntab")
                    ):
                        return True

                    # 2. String scan in loadable sections
                    signatures = [
                        b"Go build ID:",
                        b"runtime.main",
                        b"runtime.goexit",
                        b"runtime.morestack",
                        b"main.main",
                    ]

                    for sec in elf.iter_sections():
                        if sec["sh_flags"] & 0x2:  # SHF_ALLOC
                            data = sec.data()
                            if any(sig in data for sig in signatures):
                                return True

                return False

            return False

        except Exception as e:
            self.log.error(
                f"Golang detection error {self.hash.sha256}: {e}"
            )
            return False

    def cleanup_run(self):
        """Clean up after analysis."""
        try:
            # BinaryNinjaDecompiler uses context manager pattern (__enter__/__exit__)
            # Cleanup happens automatically when exiting the 'with' block
            self.binja_decompiler = None

            # Clean up goresym temp file if it exists (keep in debug mode)
            if self.goresym_output_path and os.path.exists(self.goresym_output_path):
                if self.log.isEnabledFor(logging.DEBUG):
                    self.log.debug(f"Debug mode: keeping goresym output at {self.goresym_output_path}")
                else:
                    os.remove(self.goresym_output_path)
                    self.goresym_output_path = None

            # Force garbage collection
            import gc

            gc.collect()

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

    def run_goresym(self, binary_path, output_json_path):
        """
            Run goresym on a Go binary and export its JSON output to a file.
            binary_path: path to the Go binary to analyze
            output_json_path: path where the JSON output will be saved
            """
        binary_path = str(Path(binary_path).resolve())
        output_json_path = str(Path(output_json_path).resolve())
        goresym_path = os.getenv("GORESYM_PATH", "GoReSym")

        try:
            # Example: goresym -t json /path/to/binary
            self.log.info("DEBUG: starting GoReSym")
            result = subprocess.run(
                [goresym_path, binary_path],
                stdout=subprocess.PIPE,
                stderr=subprocess.PIPE,
                text=True,
            )
        except FileNotFoundError:
            self.log.error("Error: 'goresym' not found in PATH. Make sure it is installed.")
            raise
        except subprocess.CalledProcessError as e:
            self.log.error("Error during goresym execution:")
            self.log.error(e.stderr)


        # Assuming goresym emits valid JSON to stdout.
        try:
            parsed = json.loads(result.stdout)
            # Store parsed JSON for later export to ClickHouse
            self.goresym_data = parsed
        except json.JSONDecodeError:
            # If it's not valid JSON, save the raw output instead.
            self.log.error("Warning: goresym output is not valid JSON; saving raw.")
            with open(output_json_path, "w", encoding="utf-8") as f:
                f.write(result.stdout)
            return

        # Save pretty-printed JSON for readability and debugging (used by BinaryNinja)
        with open(output_json_path, "w", encoding="utf-8") as f:
            json.dump(parsed, f, ensure_ascii=False, indent=2)
        self.goresym_output_path = output_json_path

        self.log.debug(f"goresym output saved to: {output_json_path}")

    def analyze_binary(self) -> Optional[Dict[str, Any]]:
        """Run Binary Ninja analysis and return results."""
        self.log.debug("Starting binary analysis")
        # if the binary is dotnet (only PE)
        if self.is_dotnet():
            self.log.debug("Skipping .NET binary - decompilation not supported")
            return None

        output_json_path = None
        ## if golang: run goresym
        try:
            if self.is_golang():
                output_json_path = "./goResym.json"
                self.run_goresym(self.filepath, output_json_path)
        except Exception as e:
            self.log.error(f"Error on GoReSym extraction: {e}")

        try:
            # Use BinaryNinjaDecompiler as a context manager to ensure proper setup/cleanup
            with BinaryNinjaDecompiler(
                filepath=self.filepath,
                timeout=self.BINJA_TIMEOUT,
                log=self.log,
                exporters=self.exporters,
                index_prefix=self.index_prefix,
                filetype=self.filetype,
                goresym=output_json_path,
                decompile_modules=self.decompile_modules,
            ) as decompiler:
                self.binja_decompiler = decompiler

                if decompiler.extract():
                    # Store results before context manager exits
                    results = decompiler.analysis_results
                    return results
                else:
                    self.log.error("BinaryNinjaDecompiler extraction failed")
                    return None

        except Exception as e:
            self.log.error(f"Error in Binary Ninja analysis: {e}")
            import traceback
            self.log.error(f"Traceback: {traceback.format_exc()}")
            return None

        finally:
            self.cleanup_run()

    def extract(self):
        """Extract and process all analysis results."""
        self.log.debug(inspect.currentframe().f_code.co_name)

        # Create a flag to track if extraction completed
        extraction_completed = False
        extraction_result = False
        extraction_error = None

        # Define the extraction process as a separate function
        def do_extraction():
            nonlocal extraction_completed, extraction_result, extraction_error
            try:
                results = self.analyze_binary()
                if not results:
                    extraction_result = False
                else:
                    self.analysis_results = results
                    # Add file hashes from parent Extractor class to analysis results
                    self.analysis_results["sha256"] = self.sha256
                    self.analysis_results["sha1"] = self.sha1
                    self.analysis_results["md5"] = self.md5
                    extraction_result = True
            except Exception as e:
                extraction_error = e
                extraction_result = False
            finally:
                extraction_completed = True

        # Run extraction directly with signal-based timeout (no thread overhead).
        # SIGALRM is delivered by the OS, so there's no GIL contention or polling.
        old_handler = signal.getsignal(signal.SIGALRM)
        def _timeout_handler(signum, frame):
            raise TimeoutError("Extraction timed out")

        signal.signal(signal.SIGALRM, _timeout_handler)
        signal.alarm(self.DECOMPILE_EXTRACTOR_TIMEOUT)
        try:
            do_extraction()
        except TimeoutError:
            self.log.error(
                f"Extraction timed out after {self.DECOMPILE_EXTRACTOR_TIMEOUT} seconds"
            )
            self.cleanup_run()
            return None
        finally:
            signal.alarm(0)
            signal.signal(signal.SIGALRM, old_handler)

        if extraction_error:
            self.log.error(f"Error in extraction: {extraction_error}")
            return None

        # Return the actual analysis results, not just a boolean
        return self.analysis_results if extraction_result else None

    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

        # # Delegate to the BinjaDecompiler for consistent export formatting
        # if self.binja_decompiler:
        #     return self.binja_decompiler.prepare_export_data(exporter_type)
        # else:
        #     self.log.error("BinjaDecompiler not available for export preparation")
        #     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

            # Add a helper function to handle empty strings
            def ensure_not_empty(value, default="UNKNOWN"):
                """Ensure a string value is not empty"""
                if value is None or value == "":
                    return default
                return value

            def prepare_register_usage_map(register_dict):
                """Convert register usage dict to Map format with tuples
                Input: {"rbx": {"reads": 3, "writes": 1}, ...}
                Output: {"rbx": (3, 1), ...}
                """
                if not register_dict:
                    return {}
                return {
                    reg: (info.get("reads", 0), info.get("writes", 0))
                    for reg, info in register_dict.items()
                }


            decompile_modules = getattr(self, "decompile_modules", {"all"})
            run_all = "all" in decompile_modules
            run_decompilation = run_all or "decompilation" in decompile_modules
            run_disassembly = run_all or "disassembly" in decompile_modules
            run_llil = run_all or "llil" in decompile_modules
            run_cfg = run_all or "cfg" in decompile_modules
            run_strings = run_all or "strings" in decompile_modules

            export = {"multi_table": True}

            # Decompilation tables
            if run_decompilation:
                export["decompiled_content"] = {
                    "table": "code_binja_decompiled_functions_content",
                    "data": [
                        [
                            f["decompiled_function_hash"],
                            f["decompiled_function"],
                            f["function_type"],
                            f.get("flattened_score"),
                            f.get("mba_score"),
                            now,
                        ]
                        for f in self.analysis_results["decompiled"]
                    ],
                    "column_names": [
                        "decompiled_function_hash",
                        "decompiled_function",
                        "function_type",
                        "flattened_score",
                        "mba_score",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "String",
                        "Enum8('USER'=1, 'LIBRARY'=2, 'THUNK'=3, 'EXTERNAL'=4, 'UNKNOWN'=5)",
                        "Nullable(Float64)",
                        "Nullable(Float64)",
                        "DateTime64(3, 'UTC')",
                    ],
                }
                export["decompiled_refs"] = {
                    "table": "code_binja_decompiled_functions_references",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            self.analysis_results["sha1"],
                            self.analysis_results["md5"],
                            f["decompiled_function_hash"],
                            f.get("disassembled_function_hash"),
                            f["decompiled_function_name"],
                            f["decompiled_function_prototype"],
                            f["decompiled_function_address"],
                            prepare_array_field(f.get("functions_caller"), "Array(String)"),
                            prepare_array_field(f.get("functions_call"), "Array(String)"),
                            now,
                        ]
                        for f in self.analysis_results["decompiled"]
                    ],
                    "column_names": [
                        "sha256",
                        "sha1",
                        "md5",
                        "decompiled_function_hash",
                        "disassembled_function_hash",
                        "decompiled_function_name",
                        "decompiled_function_prototype",
                        "decompiled_function_address",
                        "functions_caller",
                        "functions_call",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(40)",
                        "FixedString(32)",
                        "FixedString(64)",
                        "Nullable(FixedString(64))",
                        "LowCardinality(String)",
                        "LowCardinality(String)",
                        "UInt64",
                        "Array(String)",
                        "Array(String)",
                        "DateTime64(3, 'UTC')",
                    ],
                }

            # Disassembly tables
            if run_disassembly:
                export["disassembled_content"] = {
                    "table": "code_binja_disassembled_functions_content",
                    "data": [
                        [
                            f["disassembled_function_hash"],
                            f.get("disassembled_function", ""),
                            f.get("disassembled_function_no_addresses", ""),
                            f.get("function_type", "UNKNOWN"),
                            f.get("instructions_count", 0),
                            prepare_array_field(
                                f.get("instructions_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),
                            f.get("max_block_size"),
                            f.get("num_calls"),
                            f.get("stack_size"),
                            now,
                        ]
                        for f in self.analysis_results["disassembled"]
                    ],
                    "column_names": [
                        "disassembled_function_hash",
                        "disassembled_function",
                        "disassembled_function_no_addresses",
                        "function_type",
                        "instructions_count",
                        "instructions_types",
                        "control_flow_count",
                        "memory_access_pattern",
                        "register_usage",
                        "data_references_count",
                        "max_block_size",
                        "num_calls",
                        "stack_size",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "String",
                        "String",
                        "Enum8('USER'=1, 'LIBRARY'=2, 'THUNK'=3, 'EXTERNAL'=4, 'UNKNOWN'=5)",
                        "UInt32",
                        "Array(LowCardinality(String))",
                        "UInt32",
                        "Array(LowCardinality(String))",
                        "Array(LowCardinality(String))",
                        "UInt32",
                        "Nullable(UInt32)",
                        "Nullable(UInt32)",
                        "Nullable(Int32)",
                        "DateTime64(3, 'UTC')",
                    ],
                }
                export["disassembled_refs"] = {
                    "table": "code_binja_disassembled_functions_references",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            self.analysis_results["sha1"],
                            self.analysis_results["md5"],
                            f["disassembled_function_hash"],
                            f.get("decompiled_function_hash"),
                            f["disassembled_function_name"],
                            f["disassembled_function_address"],
                            f.get("tlsh_disassembly"),
                            f.get("tlsh_llil"),
                            now,
                        ]
                        for f in self.analysis_results["disassembled"]
                    ],
                    "column_names": [
                        "sha256",
                        "sha1",
                        "md5",
                        "disassembled_function_hash",
                        "decompiled_function_hash",
                        "disassembled_function_name",
                        "disassembled_function_address",
                        "tlsh_disassembly",
                        "tlsh_llil",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(40)",
                        "FixedString(32)",
                        "FixedString(64)",
                        "Nullable(FixedString(64))",
                        "LowCardinality(String)",
                        "UInt64",
                        "Nullable(FixedString(72))",
                        "Nullable(FixedString(72))",
                        "DateTime64(3, 'UTC')",
                    ],
                }
                # Function similarity metrics table (derived from disassembly data)
                # Lookup maps to join LLIL/MLIL features by disassembled_function_hash
                llil_by_hash = {
                    l.get("disassembled_function_hash"): l
                    for l in self.analysis_results.get("llil", [])
                    if l and l.get("disassembled_function_hash")
                }
                mlil_by_hash = {
                    m.get("disassembled_function_hash"): m
                    for m in self.analysis_results.get("mlil", [])
                    if m and m.get("disassembled_function_hash")
                }

                export["function_similarity_metrics"] = {
                    "table": "code_binja_function_similarity_metrics",
                    "data": [
                        [
                            f["disassembled_function_hash"],
                            f.get("cyclomatic_complexity"),
                            f.get("tlsh_disassembly"),
                            f.get("tlsh_llil"),
                            prepare_array_field(f.get("minhash"), "Array(UInt8)"),
                            (llil_by_hash.get(f["disassembled_function_hash"]) or {}).get("tlsh_llil"),
                            (llil_by_hash.get(f["disassembled_function_hash"]) or {}).get(
                                "tlsh_instruction_typed_llil"),
                            prepare_array_field(
                                (llil_by_hash.get(f["disassembled_function_hash"]) or {}).get("minhash_llil_skeleton"),
                                "Array(UInt8)",
                            ),
                            prepare_array_field(
                                (llil_by_hash.get(f["disassembled_function_hash"]) or {}).get("minhash_llil_typed"),
                                "Array(UInt8)",
                            ),
                            (mlil_by_hash.get(f["disassembled_function_hash"]) or {}).get("tlsh_mlil_skeleton"),
                            (mlil_by_hash.get(f["disassembled_function_hash"]) or {}).get("tlsh_mlil_typed"),
                            prepare_array_field(
                                (mlil_by_hash.get(f["disassembled_function_hash"]) or {}).get("minhash_mlil_skeleton"),
                                "Array(UInt8)",
                            ),
                            prepare_array_field(
                                (mlil_by_hash.get(f["disassembled_function_hash"]) or {}).get("minhash_mlil_typed"),
                                "Array(UInt8)",
                            ),
                            now,
                        ]
                        for f in self.analysis_results.get("disassembled", [])
                    ],
                    "column_names": [
                        "disassembled_function_hash",
                        "cyclomatic_complexity",
                        "tlsh_disassembly",
                        "tlsh_llil",
                        "minhash",
                        "tlsh_llil_new",
                        "tlsh_instruction_typed_llil",
                        "minhash_llil_skeleton",
                        "minhash_llil_typed",
                        "tlsh_mlil_skeleton",
                        "tlsh_mlil_typed",
                        "minhash_mlil_skeleton",
                        "minhash_mlil_typed",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "Nullable(UInt16)",
                        "Nullable(FixedString(72))",
                        "Nullable(FixedString(72))",
                        "Array(UInt8)",
                        # new
                        "Nullable(FixedString(72))",
                        "Nullable(FixedString(72))",
                        "Array(UInt8)",
                        "Array(UInt8)",
                        "Nullable(FixedString(72))",
                        "Nullable(FixedString(72))",
                        "Array(UInt8)",
                        "Array(UInt8)",
                        "DateTime64(3, 'UTC')",
                    ],
                }


            # LLIL tables
            if run_llil:
                export["llil_content"] = {
                    "table": "code_binja_llil_functions_content",
                    "data": [
                        [
                            f["sha256_llil"],
                            f["function_type"],
                            prepare_array_field(
                                f.get("instructions_types_llil"), "LowCardinality(String)"
                            ),
                            f.get("control_flow_count_llil", 0),
                            prepare_array_field(
                                f.get("memory_access_pattern_llil"), "LowCardinality(String)"
                            ),
                            prepare_register_usage_map(f.get("register_usage", {})),
                            f.get("total_reg_reads", 0),
                            f.get("total_reg_written", 0),
                            f.get("data_references_count", 0),
                            f.get("max_block_size"),
                            f.get("num_calls"),
                            f.get("stack_size"),
                            prepare_array_field(f.get("body_llil_vector"), "Array(Tuple(UInt32, Array(UInt16)))"),
                            now,
                        ]
                        for f in self.analysis_results.get("llil", [])
                    ],
                    "column_names": [
                        "llil_function_hash",
                        "function_type",
                        "instructions_types_llil",
                        "control_flow_count_llil",
                        "memory_access_pattern_llil",
                        "register_usage_llil",
                        "total_reg_reads",
                        "total_reg_written",
                        "data_references_count",
                        "max_block_size",
                        "num_calls",
                        "stack_size",
                        "body_llil_vector",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "Enum8('USER'=1, 'LIBRARY'=2, 'THUNK'=3, 'EXTERNAL'=4, 'UNKNOWN'=5)",
                        "Array(LowCardinality(String))",
                        "UInt32",
                        "Array(LowCardinality(String))",
                        "Map(LowCardinality(String), Tuple(UInt32, UInt32))",
                        "UInt32",
                        "UInt32",
                        "UInt32",
                        "Nullable(UInt32)",
                        "Nullable(UInt32)",
                        "Nullable(Int32)",
                        "Array(Tuple(UInt32, Array(UInt16)))",
                        "DateTime64(3, 'UTC')",
                    ],
                }
                export["llil_refs"] = {
                    "table": "code_binja_llil_functions_references",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            self.analysis_results["sha1"],
                            self.analysis_results["md5"],
                            f.get("sha256_llil"),
                            f.get("disassembled_function_hash"),
                            f.get("function_address"),
                            f.get("tlsh_disassembly"),
                            f.get("tlsh_llil"),
                            now,
                        ]
                        for f in self.analysis_results.get("llil", [])
                    ],
                    "column_names": [
                        "sha256",
                        "sha1",
                        "md5",
                        "llil_function_hash",
                        "disassembled_function_hash",
                        "function_address",
                        "tlsh_disassembly",
                        "tlsh_llil",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(40)",
                        "FixedString(32)",
                        "Nullable(FixedString(64))",
                        "FixedString(64)",
                        "UInt64",
                        "Nullable(FixedString(72))",
                        "Nullable(FixedString(72))",
                        "DateTime64(3, 'UTC')",
                    ],
                }

            # Errors table (always include if per-function loop ran)
            if run_decompilation or run_disassembly or run_llil or run_cfg:
                export["function_analysis_errors"] = {
                    "table": "new_function_analysis_errors_binja",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            f["function_name"],
                            f["function_address"],
                            f.get("error_location", "unknown"),
                            f.get("error_message", ""),
                            f.get("error_details", ""),
                            f.get("error_type", "unknown"),
                            self.calculate_md5(
                                f"{f.get('error_message', '')}{f['function_name']}{f['function_address']}{f.get('error_location', 'unknown')}"
                            ),
                            "new",
                            now,
                        ]
                        for f in self.analysis_results.get("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)",
                        "UInt64",
                        "LowCardinality(String)",
                        "Nullable(String)",
                        "Nullable(String)",
                        "Nullable(String)",
                        "FixedString(32)",
                        "Enum8('new'=1, 'investigating'=2, 'fixed'=3, 'wontfix'=4)",
                        "DateTime64(3, 'UTC')",
                    ],
                }

            # Strings table
            if run_strings:
                export["strings_raw"] = {
                    "table": "code_binja_strings_raw",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            s["string"],
                            s["string_raw"],
                            s["string_encoding"],
                            s["string_offset"],
                            s["string_length"],
                            s["string_raw_length"],
                            s["string_entropy"],
                        ]
                        for s in self.analysis_results.get("strings", [])
                    ],
                    "column_names": [
                        "sha256",
                        "string",
                        "string_raw",
                        "string_encoding",
                        "string_offset",
                        "string_length",
                        "string_raw_length",
                        "string_entropy",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "String",
                        "String",
                        "LowCardinality(String)",
                        "UInt64",
                        "UInt32",
                        "UInt32",
                        "Float32",
                    ],
                }

            # CFG function-level features table
            if run_cfg:
                export["cfg_functions"] = {
                    "table": "code_binja_cfg_functions",
                    "data": [
                        [
                            cfg.get("disassembled_function_hash"),
                            cfg["cfg_topology_hash"],
                            cfg["block_count"],
                            cfg["edge_count"],
                            cfg.get("llil_total_operations", 0),
                            cfg.get("call_count", 0),
                            cfg["cyclomatic_complexity"],
                            cfg.get("loop_count", 0),
                            cfg.get("max_depth", 0),
                            cfg.get("max_fan_out", 0),
                            cfg.get("md_index_topdown", 0),
                            cfg.get("md_index_bottomup", 0),
                            cfg.get("prime_product_llil", 0),
                            cfg.get("cfg_feature_tlsh"),
                            cfg.get("wl_minhash", []),
                            cfg.get("bb_features", []),
                            cfg.get("cfg_adjacency", []),
                            now,
                        ]
                        for cfg in self.analysis_results.get("cfg", [])
                        if cfg is not None
                    ],
                    "column_names": [
                        "disassembled_function_hash",
                        "cfg_topology_hash",
                        "block_count",
                        "edge_count",
                        "llil_total_operations",
                        "call_count",
                        "cyclomatic_complexity",
                        "loop_count",
                        "max_depth",
                        "max_fan_out",
                        "md_index_topdown",
                        "md_index_bottomup",
                        "prime_product_llil",
                        "cfg_feature_tlsh",
                        "wl_minhash",
                        "bb_features",
                        "cfg_adjacency",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "FixedString(16)",
                        "UInt16",
                        "UInt16",
                        "UInt32",
                        "UInt16",
                        "UInt16",
                        "UInt8",
                        "UInt16",
                        "UInt8",
                        "UInt64",
                        "UInt64",
                        "UInt64",
                        "Nullable(FixedString(72))",
                        "Array(UInt8)",
                        "Array(Array(UInt16))",
                        "Array(UInt32)",
                        "DateTime64(3, 'UTC')",
                    ],
                }

            # GoReSym metadata table (only if goresym data exists)
            if self.goresym_data:
                export["golang_metadata"] = {
                    "table": "redb_golang_metadata",
                    "data": [
                        [
                            self.analysis_results["sha256"],
                            json.dumps(self.goresym_data),
                            now,
                        ]
                    ],
                    "column_names": [
                        "sha256",
                        "goresym",
                        "analysis_date",
                    ],
                    "column_type_names": [
                        "FixedString(64)",
                        "JSON",
                        "DateTime64(3, 'UTC')",
                    ],
                }

            return export

    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


if __name__ == "__main__":
    # Setup basic logging
    import logging
    import time

    logging.basicConfig(level=logging.INFO)
    logger = logging.getLogger("DecompileBinja")

    # Parse command line arguments
    import argparse

    parser = argparse.ArgumentParser(description="Binary Ninja Decompiler Wrapper")
    parser.add_argument("filepath", help="Path to the binary file to analyze")
    parser.add_argument(
        "--output", "-o", help="Output JSON file path (default: stdout)"
    )
    parser.add_argument(
        "--timeout",
        "-t",
        type=int,
        default=1200,
        help="Analysis timeout in seconds (default: 1200)",
    )
    args = parser.parse_args()
    start = time.perf_counter()
    # Create and run the extractor
    with DecompileBinja(args.filepath, logger) as extractor:
        success = extractor.extract()
        end = time.perf_counter()
        if not success:
            logger.error("Analysis failed")
            exit(1)

        # Output results
        if args.output:
            with open(args.output, "w") as f:
                json.dump(extractor.analysis_results, f)
            logger.info(f"Results written to {args.output}")
        else:
            print((extractor.analysis_results))
            with open("diff", "w") as f:
                f.write(str(f"{end - start:.3f} seconds"))