Ioanna Mesogiti

34 papers Journal 6Unranked 28
YearRankTypeTitle / Venue / Authors
2026 J jnl
IEEE Commun. Mag.
Evrydiki Kyriazi, Panagiotis Toumasis, George P. Katsikas, L. Papadopoulos, V. Charlaftis, Caro Meysmans, Juan Brenes Baranzano, D. Diakakis, Ioanna Mesogiti, W. Wasko, Raul Muñoz, David Larrabeiti, Zhongxia Simon He, E. Dayan, I. Garcia-Milà, Juan P. Fernández Palacios, Carlos Manso, C. Miralpeix, Luka Korsic, Josep M. Fabrega, O. Segou, I. Avramidis, Eleni Theodoropoulou, George L. Lyberopoulos, Janez Sterle, Guy Torfs, Christos Vagionas, Dimitrios Klonidis, Giannis Giannoulis, Hercules Avramopoulos, Dimitrios Apostolopoulos
2025 J jnl
J. Opt. Commun. Netw.
Markos P. Anastasopoulos, Anna Tzanakaki, Y. Jian, Lukasz Lopacinski, Jesús Gutiérrez, Ioanna Mesogiti, Elina Theodoropoulou, George L. Lyberopoulos
2025 J jnl
J. Opt. Commun. Netw.
Evrydiki Kyriazi, Panagiotis Toumasis, Giorgos Brestas, Panagiotis Kourelias, Argiris Ntanos, Aristeidis Stathis, Giannis Poulopoulos, D. Diakakis, Ioanna Mesogiti, Helen Theodoropoulou, G. Lymperopoulos, Giannis Gannoulis, Jaynez Sterle, Dimitrios Apostolopoulos, Hercules Avramopoulos
2025 conf
AIAI Workshops (1)
Ioanna Mesogiti, Elina Theodoropoulou, George L. Lyberopoulos, Jason Giakoumakos, Markos P. Anastasopoulos, Anna Tzanakaki, Aleksandra Kaszubowska-Anandarajah, Dan Kilper, Carlos Natalino, Paolo Monti, Tommy Svensson, Kaida Kaeval, Simon Pryor, Colm Browning
2025 conf
EuCNC/6G Summit
Evrydiki Kyriazi, Panagiotis Toumasis, George P. Katsikas, L. Papadopoulos, V. Charlaftis, Caro Meysmans, Juan Brenes Baranzano, D. Diakakis, Ioanna Mesogiti, W. Wasko, Raul Muñoz, David Larrabeiti, Zhongxia Simon He, E. Dayan, I. Garcia-Milà, Juan P. Fernández Palacios, Carlos Manso, C. Miralpeix, Luka Korsic, Josep M. Fabrega, O. Segou, I. Avramidis, Victor Lopez Alvarez, Helen Theodoropoulou, George L. Lyberopoulos, Janez Sterle, Guy Torfs, Christos Vagionas, Dimitrios Klonidis, Giannis Giannoulis, Hercules Avramopoulos, Dimitrios Apostolopoulos
2025 conf
AIAI Workshops (1)
Konstantina Papachristopoulou, Themistoklis Anagnostopoulos, Konstantinos Fragkos, Ioanna Mesogiti, George Limperopoulos, Eleni Theodoropoulou, Kostas Kolomvatsos
2024 conf
CAMAD
Markos P. Anastasopoulos, Alexandros-Ioannis Manolopoulos, Anna Tzanakaki, Ioanna Mesogiti, Eleni Theodoropoulou, George L. Lyberopoulos, Charalambos Oxinos, Cristian Patachia, Razvan Mihai, Aggeliki Pragiati, Antonis Panagakis
2024 conf
CAMAD
Foteini Setaki, George Karouzos, Evgenia Petkova, Eleni Theodoropoulou, George L. Lyberopoulos, Kostantinos Theodoropoulos, Nikos Kostopoulos, Kostas Trichias, Ioanna Mesogiti
2024 conf
CAMAD
George Makropoulos, Ioannis Manolopoulos, Harilaos Koumaras, George L. Lyberopoulos, Foteini Setaki, Eleni Theodoropoulou, Ioanna Mesogiti
2024 conf
AIAI (Workshops)
Jesús Gutiérrez, Vladica Sark, Mert Özates, Anna Tzanakaki, Markos P. Anastasopoulos, Valerio Frascolla, Ioanna Mesogiti, Elina Theodoropoulou, George L. Lyberopoulos, Luis Díez, Ramón Agüero, Ignacio Santamaría, Padmanava Sen, Simon Pryor, Shahid Mumtaz, Salvatore Pontarelli, Federico Trombetti, Novella Bartolini, Eduard A. Jorswieck, Xi Ding, Navid Nikaein
2024 conf
CAMAD
Harilaos Koumaras, Dimitrios Fragkos, Vasilis Pitsilis, George Makropoulos, George L. Lyberopoulos, Eleni Theodoropoulou, Fotini Setaki, Ioanna Mesogiti, D. Diakakis, Nikolaos Gkatzios, Constantinos Fragkos, Vaios Koumaras
2024 conf
EuCNC/6G Summit
Rishu Raj, Devika Dass, Kaida Kaeval, Sai Kireet Patri, Vincent Sleiffer, Benedikt Baeuerle, Wolfgang Heni, Marco Ruffini, Colm Browning, Alan Naughton, Ruth Mackey, David Mackey, Boris Vukovic, Jasmin Smajic, Juerg Leuthold, Carlos Natalino, Lena Wosinska, Tommy Svensson, Aleksandra Kaszubowska-Anandarajah, Ioanna Mesogiti, Simon Pryor, Anna Tzanakaki, Reza Nejabati, Paolo Monti, Dan Kilper
2023 conf
AIAI (Workshops)
Maria-Evgenia Xezonaki, Nikos Psaromanolakis, Panteleimon-Konstantinos Chartsias, Konstantinos Stamatis, Dimitrios Kritharidis, Vasileios Theodorou, Christina Tanya Politi, Panagiotis Papaioannou, Christos Tranoris, Spyros G. Denazis, Ioanna Mesogiti, Eleni Theodoropoulou, Fotini Setaki, George L. Lyberopoulos, Nikos Makris, Paris Flegkas, Jesús Gutiérrez Terán, Markos P. Anastasopoulos, Anna Tzanakaki
2023 conf
AIAI (Workshops)
Ioanna Mesogiti, Eleni Theodoropoulou, Fotini Setaki, George L. Lyberopoulos, Konstantinos Stamatis, Panteleimon-Konstantinos Chartsias, Nikos Makris, Paris Flegkas, Jesús Gutiérrez, Christina Tanya Politi, Christos Tranoris, Markos P. Anastasopoulos, Anna Tzanakaki
2022 conf
AIAI (Workshops)
Janez Sterle, Ioanna Mesogiti, Luka Korsic, Eleni Theodoropoulou, Fotini Setaki, George L. Lyberopoulos, Francesca Moscatelli, Konstantina Kanta, Giannis Giannoulis, Panagiotis Toumasis, Dimitris Apostolopoulos, Hercules Avramopoulos, John Avramidis, Yigal Leiba, Dimitrios Klonidis
2022 conf
AIAI (Workshops)
Ioanna Mesogiti, Eleni Theodoropoulou, Fotini Setaki, George L. Lyberopoulos, Francesca Moscateli, Konstantina Kanta, Giannis Giannoulis, Panagiotis Toumasis, Dimitris Apostolopoulos, Hercules Avramopoulos, Lukasz Lopacinski, Jesús Gutiérrez Terán, Anastassios Nanos, Yigal Leiba, Markos P. Anastasopoulos, Anna Tzanakaki
2022 J jnl
JOCN
Konstantina Kanta, Panagiotis Toumasis, Giannis Giannoulis, Ioannis Stratakos, George Lentaris, Elissaios-Alexios Papatheofanous, Ioanna Mesogiti, Eleni Theodoropoulou, Aristotelis Margaris, Dimitris Syrivelis, Evrydiki Kyriazi, Giorgos Brestas, Kostas Tokas, Nikolaos Argyris, Christos Vagionas, Ronis T. Maximidis, Paraskevas Bakopoulos, Agapi Mesodiakaki, Marios Gatzianas, George Kalfas, Kostas Tsagkaris, Nikos Pleros, Dionysios I. Reisis, George L. Lyberopoulos, Dimitrios Apostolopoulos, Dimitrios Soudris, Hercules Avramopoulos
2022 conf
GLOBECOM (Workshops)
Fotini Setaki, Ioanna Mesogiti, Eleni Theodoropoulou, George L. Lyberopoulos, Harilaos Koumaras, David Artuñedo Guillen, Javier Garcia Rodrigo, George Avdikos, Ioannis Margaritis, Emmanouil Kafetzakis, Yiannis Karadimas, Dimitris Tsolkas
2021 conf
AIAI (Workshops)
Ioanna Mesogiti, Eleni Theodoropoulou, Fotini Setaki, George L. Lyberopoulos, Anna Tzanakaki, Markos P. Anastasopoulos, Christina Tanya Politi, Panagiotis Papaioannou, Christos Tranoris, Spyros G. Denazis, Paris Flegkas, Nikos Makris, Nebojsa Maletic, Darko Cvetkovski, Jesús Gutiérrez Terán, Panteleimon-Konstantinos Chartsias, Konstantinos Stamatis, Marievi Xezonaki, Dimitrios Kritharidis, Alexandros Dalkalitsis, Manfred Taferner, Martin Piovarci
2021 conf
ECOC
Panagiotis Toumasis, Konstantina Kanta, Kostas Tokas, Ioannis Stratakos, Elissaios-Alexios Papatheofanous, Giannis Giannoulis, Ioanna Mesogiti, Eleni Theodoropoulou, George L. Lyberopoulos, George Lentaris, Dimitrios Apostolopoulos, Dionysios I. Reisis, Dimitrios Soudris, Hercules Avramopoulos
2021 conf
AIAI (Workshops)
Eleni Theodoropoulou, Ioanna Mesogiti, Fotini Setaki, Konstantinos Filis, George L. Lyberopoulos, Agapi Mesodiakaki, Marios Gatzianas, Christos Vagionas, George Kalfas, Mauro Agus, Annachiara Pagano
2020 conf
AIAI (Workshops)
Eleni Theodoropoulou, Ioanna Mesogiti, George L. Lyberopoulos, George Kalfas, Christos Vagionas, Nikos Pleros, Annachiara Pagano, Mauro Agus, Luiz Anet Neto, Nikos Psaromanolakis, Athina Ropodi
2020 J jnl
Photonic Netw. Commun.
Ioanna Mesogiti, George L. Lyberopoulos, Fotini Setaki, Andrea Di Giglio, Alessandro Pelcelsi, Laura Serra, Jim Zou, Anna Tzanakaki, Markos P. Anastasopoulos, Eleni Theodoropoulou
2019 conf
AIAI (Workshops)
Ioanna Mesogiti, Eleni Theodoropoulou, George L. Lyberopoulos, Fotini Setaki, Aurora Ramos, Panagiotis Gouvas, Anastasios Zafeiropoulos, Roberto Bruschi
2019 conf
ONDM
Ioanna Mesogiti, Elina Theodoropoulou, George L. Lyberopoulos, Fotini Setaki, Konstantinos Filis, Andrea Di Giglio, Alessandero Percelsi, Anna Tzanakaki
2018 conf
CAMAD
Ioanna Mesogiti, Eleni Theodoropoulou, Konstantinos Filis, George L. Lyberopoulos, Athina Ropodi, Kostas Tsagkaris, Panagiotis Demestichas, Nikos Pleros, George Kalfas, Christos Vagionas
2018 conf
CAMAD
Ioanna Mesogiti, Elina Theodoropoulou, Konstantinos Filis, George L. Lyberopoulos, Rafael Cantó Palancar, N. A. Serrano Linares, Daniel Camps-Mur, Jesús Gutiérrez, Anna Tzanakaki
2017 conf
HPCS
George Kousiouris, Fotis Aisopos, Alexandros Psychas, Theodora A. Varvarigou, Jörg Domaschka, Daniel Baur, Frank Griesinger, V. Nikolov, George L. Lyberopoulos, Eleni Theodoropoulou, Ioanna Mesogiti, Dimitrios Charilas, Yiannis Stavroulas, Nunzio Andrea Galante, Gabriele Giammatteo, G. Besombes, D. Speziani, B. Leroy, S. Geller, J. Papper
2015 conf
ISCIS
George L. Lyberopoulos, Helen Theodoropoulou, Konstantinos Filis, Ioanna Mesogiti
2015 conf
EANN Workshops
George L. Lyberopoulos, Eleni Theodoropoulou, Ioanna Mesogiti, Konstantinos Filis, Ioannis Mamounakis, Prodromos Makris, Emmanouel A. Varvarigos
2015 conf
CAMAD
George L. Lyberopoulos, Eleni Theodoropoulou, Ioanna Mesogiti, Konstantinos Filis
2014 conf
CAMAD
George L. Lyberopoulos, Eleni Theodoropoulou, Ioanna Mesogiti, Prodromos Makris, Emmanouel A. Varvarigos
2014 conf
Kaleidoscope
Fidel Liberal, Jose Oscar Fajardo, Naiara Goia, Ioanna Mesogiti
2009 J jnl
IEEE Commun. Mag.
George Korinthios, Elina Theodoropoulou, Niki Marouda, Ioanna Mesogiti, Eftychia Nikolitsa, George L. Lyberopoulos
redb/extractors/decompiler/bninja/decompiler.py
← Index redb/extractors/decompiler/bninja/decompiler.py python
import os
import time
import json

from .analysis.medium_level import MediumLevelAnalysis

# disable the plugins set by user for binary ninja
os.environ["BN_DISABLE_USER_PLUGINS"] = "True"
import traceback

# Binary Ninja imports (conditional)
try:
    import binaryninja
    from binaryninja import mainthread, Symbol
    from binaryninja.enums import SymbolType
    BINARYNINJA_AVAILABLE = True
except Exception:
    BINARYNINJA_AVAILABLE = False
    binaryninja = None
    mainthread = None
    Symbol = None
    SymbolType = None

# Support both package and standalone imports
try:
    # Package import (when imported from redb)
    from .utils.hashes import calculate_sha256, calculate_tlsh
    from .utils.license import set_license
    from .utils.logging import setup_default_logger
    from .analysis.strings import StringAnalysis

    # Only import modules that depend on Binary Ninja when available
    if BINARYNINJA_AVAILABLE:
        from .analysis.cfg import CFGAnalysis
        from .analysis.disassembly import DisassemblyAnalysis
        from .analysis.low_level import LowLevelAnalysis
        from .arch.creator import ArchitectureCreator
        from .custom_options import register_custom_analysis_options
        from .function_type import FunctionTypeAnalysis, FunctionType
        from .analysis.scores import ObfuscationScores

except ImportError:
    # Fallback to absolute imports (for multiprocessing spawned processes)
    from redb.extractors.decompiler.bninja.utils.hashes import calculate_sha256, calculate_tlsh
    from redb.extractors.decompiler.bninja.utils.license import set_license
    from redb.extractors.decompiler.bninja.utils.logging import setup_default_logger

    # Only import modules that depend on Binary Ninja when available
    if BINARYNINJA_AVAILABLE:
        from redb.extractors.decompiler.bninja.analysis.cfg import CFGAnalysis
        from redb.extractors.decompiler.bninja.analysis.disassembly import DisassemblyAnalysis
        from redb.extractors.decompiler.bninja.analysis.low_level import LowLevelAnalysis
        from redb.extractors.decompiler.bninja.arch.creator import ArchitectureCreator
        from redb.extractors.decompiler.bninja.custom_options import register_custom_analysis_options
        from redb.extractors.decompiler.bninja.function_type import FunctionTypeAnalysis


class BinaryNinjaDecompiler:
    """A Binary Ninja-based decompiler that replicates the functionality of GhidraDecompilerScript.
    This class extracts decompiled code, disassembly with multiple normalization levels,
    and control flow graph information from binary files.
    """

    MIN_FUNCTION_SIZE = 10  # instructions
    MIN_BLOCK_SIZE = 4  # instructions
    INVALID_STACK_SIZE = -1

    def __init__(
        self,
        filepath,
        timeout,
        log=None,
        exporters=None,
        index_prefix=None,
        filetype=None,
        goresym=None,
        decompile_modules=None,
    ):
        """Initialize the Binary Ninja decompiler.

        Args:
            filepath: Path to the binary file to analyze
            log: Logger object (optional)
            timeout: Maximum time in seconds for analysis (default: 1200)
            exporters: List of exporters for the results (optional)
            index_prefix: Prefix for elastic index (optional)
            filetype: Type of the file (optional)

        """
        self.filepath = filepath
        self.log = log if log else setup_default_logger("BninjaDecompiler")
        self.BNINJA_TIMEOUT = timeout
        self.bv = None
        self.analysis_results = None
        self.errors = []
        self.exporters = exporters
        self.index_prefix = index_prefix
        self.filetype = filetype
        self.goresym = goresym
        self.decompile_modules = decompile_modules or {"all"}

        set_license(binaryninja)

        # Map to track instruction categorization
        mainthread.set_worker_thread_count(3)
        register_custom_analysis_options(binaryninja)

    def log_error(
        self, message, function_name, address, exception=None, error_location="unknown"
    ):
        """Log an error during processing."""
        error_msg = f"Error in function {function_name} at {address}: {message}"
        if exception:
            error_msg += f" - {str(exception)}"

        self.log.error(error_msg)

        # Add to errors list
        error = {
            "function_name": function_name,
            "function_address": str(address),
            "error_location": error_location,
            "error_message": message,
            "error_details": str(exception) if exception else "",
            "error_type": type(exception).__name__ if exception else "Unknown",
            "timestamp": int(time.time() * 1000),
        }
        self.errors.append(error)

    def __enter__(self):
        """Context manager entry point."""
        self.log.info(f"Opening binary file: {self.filepath}")
        binaryninja.BinaryViewType.add_binaryview_initial_analysis_completion_event(
            self.on_analysis_complete
        )

        #self.bv = binaryninja.load(self.filepath, update_analysis=False)
        self.bv = binaryninja.load(self.filepath, update_analysis=True)
        if self.bv is None:
            raise ValueError(f"Failed to open file: {self.filepath}")

        self.log.info("Waiting for analysis to complete...")

        self.log.debug(f"Binja analysis complete: {len(list(self.bv.functions))} functions")

        # set the architecture
        # todo: personalize this for other architectures
        self.arch = ArchitectureCreator("x86").get()

        # apply goresym
        if self.goresym is not None:
            self.__apply_goresym()
        return self

    def on_analysis_complete(self, bv):
        # Request an additional update after analysis is complete to ensure IL generation
        self.bv = bv
        self.bv.update_analysis()

        return

    def __apply_goresym(self):
        file = self.goresym
        data = None
        try:
            data = json.loads(open(file, 'r').read())
        except Exception as e:
            self.log_error(
                "Failed to open file from goresym: ",
                file,
                e,
                "analyze_binary",
            )

        if data is None:
            return

        self.bv.begin_undo_actions()
        if data.get('UserFunctions') is not None:
            user_functions = data['UserFunctions']
            for func in user_functions:
                try:
                    start = int(func['Start'])
                    name = func['FullName']
                    if self.bv.get_function_at(start) is None:
                        self.bv.create_user_function(start)

                    sym = Symbol(SymbolType.FunctionSymbol, start, name, name, name)
                    self.bv.define_user_symbol(sym)
                except Exception as e:
                    self.log.warning(f"Failed to apply GoReSym symbol for UserFunction {func.get('FullName', 'unknown')} at {func.get('Start', 'unknown')}: {e}")

        if data.get('StdFunctions') is not None:
            standard_functions = data['StdFunctions']
            for func in standard_functions:
                try:
                    start = int(func['Start'])
                    name = func['FullName']
                    if self.bv.get_function_at(start) is None:
                        self.bv.create_user_function(start)

                    sym = Symbol(SymbolType.FunctionSymbol, start, name, name, name)
                    self.bv.define_user_symbol(sym)
                except Exception as e:
                    self.log.warning(f"Failed to apply GoReSym symbol for StdFunction {func.get('FullName', 'unknown')} at {func.get('Start', 'unknown')}: {e}")

        self.bv.commit_undo_actions()
        return

    def __exit__(self, exc_type, exc_val, exc_tb):
        """Context manager exit point - clean up resources."""
        if self.bv:
            # Make sure to cancel any pending analysis
            # (if we have no pending analysis, binary ninja will log an error)

            # todo(@nicolo): investigate
            # if hasattr(self.bv, "abort_analysis"):
            #    self.bv.abort_analysis()
            self.bv.file.close()

        self.log.info("Cleanup completed successfully")
        return

    def tag(self):
        """Return the tag for this extractor."""
        return "DECOMPILED"

    def _module_selected(self, module_name):
        """Check if a decompiler sub-module is selected."""
        return "all" in self.decompile_modules or module_name in self.decompile_modules

    def analyze_binary(self):
        """Run Binary Ninja analysis and return results.

        Respects self.decompile_modules to selectively run/skip sub-modules:
        - strings: independent, skipped if not selected
        - decompilation: leaf module, skipped if not selected
        - disassembly: always runs (backbone — provides hash linkage for all others)
        - llil: leaf module, skipped if not selected
        - cfg: leaf module, skipped if not selected

        Only selected modules' results are appended to the results dict for DB insertion.
        Disassembly is always computed for linkage but only inserted when selected.
        """
        try:
            results = {
                "decompiled": [],
                "disassembled": [],
                "cfg": [],
                "llil": [],
                "errors": [],
                "strings": [],
                "mlil": []
            }

            run_all = "all" in self.decompile_modules
            run_strings = run_all or "strings" in self.decompile_modules
            run_decompilation = run_all or "decompilation" in self.decompile_modules
            run_disassembly = run_all or "disassembly" in self.decompile_modules
            run_llil = run_all or "llil" in self.decompile_modules
            run_cfg = run_all or "cfg" in self.decompile_modules

            # Determine if we need the per-function loop at all
            need_per_function = run_decompilation or run_disassembly or run_llil or run_cfg

            #functions_list = list(filter(is_not_ext_lib_function, self.bv.functions))
            functions_list = list(filter(is_lib_or_thunk, self.bv.functions))
            functions_list = list(filter(self.is_too_few_blocks, functions_list))

            # Strings extraction — independent of per-function analysis
            if run_strings:
                results["strings"] = StringAnalysis(self.bv, functions_list).analyze()

            if not need_per_function:
                return results

            for function in functions_list:
                try:
                    # Decompilation (HLIL) — leaf module, skip if not selected
                    hlil_json = self.extract_hlil(function) if run_decompilation else None

                    # Disassembly — always compute (provides hash linkage for others)
                    disass_json = self.extract_disasm(function)

                    # CFG — leaf module, skip if not selected
                    cfg_json = self.extract_cfg(function) if run_cfg else None

                    # LLIL — leaf module, skip if not selected
                    lowlevel_json = self.extract_lowlevel(function) if run_llil else None

                    # we run mlil only if we have cfg
                    mlil_json = self.extract_mediumlevel(function) if run_llil else None

                    # Calculate fuzzy hashes for disassembly using utils.hashes
                    if disass_json:
                        disass_no_addr = disass_json.get("disassembled_function_no_addresses", "")
                        disass_json["tlsh_disassembly"] = calculate_tlsh(disass_no_addr)

                    if hlil_json and disass_json:
                        hlil_json["disassembled_function_hash"] = disass_json[
                            "disassembled_function_hash"
                        ]
                        disass_json["decompiled_function_hash"] = hlil_json[
                            "decompiled_function_hash"
                        ]

                        results["decompiled"].append(hlil_json)
                        if run_disassembly:
                            results["disassembled"].append(disass_json)

                    elif hlil_json:
                        hlil_json["disassembled_function_hash"] = None
                        results["decompiled"].append(hlil_json)
                    elif disass_json:
                        disass_json["decompiled_function_hash"] = None
                        if run_disassembly:
                            results["disassembled"].append(disass_json)

                    # Add bi-directional linkage between LLIL and disassembly with fuzzy hashes
                    # LLIL fuzzy hashes (tlsh_llil) are already calculated in lowlevel_json
                    if lowlevel_json and disass_json:
                        # Add disassembly info to LLIL
                        lowlevel_json["disassembled_function_hash"] = disass_json["disassembled_function_hash"]
                        lowlevel_json["tlsh_disassembly"] = disass_json.get("tlsh_disassembly")

                        # Add LLIL fuzzy hashes to disassembly for easy export access
                        disass_json["tlsh_llil"] = lowlevel_json.get("tlsh_llil")
                        disass_json["minhash"] = lowlevel_json.get("minhash")

                    elif lowlevel_json:
                        lowlevel_json["disassembled_function_hash"] = None
                        lowlevel_json["tlsh_disassembly"] = None
                    elif disass_json:
                        # No LLIL available for this disassembly
                        disass_json["tlsh_llil"] = None
                        disass_json["minhash"] = None

                    if lowlevel_json:
                        results["llil"].append(lowlevel_json)
                        results["mlil"].append(mlil_json)

                    # Add CFG linkage with disassembled_function_hash
                    # Also add cyclomatic_complexity to disass_json for similarity metrics export
                    if cfg_json and disass_json:
                        cfg_json["disassembled_function_hash"] = disass_json["disassembled_function_hash"]
                        disass_json["cyclomatic_complexity"] = cfg_json.get("cyclomatic_complexity")
                        results["cfg"].append(cfg_json)
                    elif cfg_json:
                        cfg_json["disassembled_function_hash"] = None
                        results["cfg"].append(cfg_json)

                    # Ensure cyclomatic_complexity is set even if no cfg_json
                    if disass_json and "cyclomatic_complexity" not in disass_json:
                        disass_json["cyclomatic_complexity"] = None

                except Exception as e:
                    self.log_error(
                        "Failed to process function: ",
                        function.name,
                        function.start,
                        e,
                        "analyze_binary",
                    )

            return results

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

    def extract_mediumlevel(self, function):
        middle_level = MediumLevelAnalysis(function, self.bv, self.log)
        middle_level_result, errors = middle_level.analyze()

        for error in errors:
            self.errors.append(error)

        return middle_level_result


    def extract_lowlevel(self, function):
        low_level = LowLevelAnalysis(function, self.bv, self.log)
        disassembly_json, errors = low_level.analyze()

        for error in errors:
            self.errors.append(error)

        return disassembly_json

    def extract_cfg(self, function):
        try:
            llil = function.llil if hasattr(function, 'llil') else None
            cfg = CFGAnalysis(function, llil_function=llil).extract_function_cfg()
            return cfg
        except Exception as e:
            self.log_error(
                "Fatal error in CFG extraction",
                function.name,
                function.start,
                e,
                "extract_disassembly",
            )
            return None

    def extract_disasm(self, function):
        try:
            disass_analysis = DisassemblyAnalysis(
                self.arch, function, self.bv, self.log
            )

            # Create disassembly JSON
            disassembly_json, errors = disass_analysis.get_json()

            for error in errors:
                self.errors.append(error)

            return disassembly_json

        except Exception as e:
            self.log_error(
                "Fatal error in disassembly extraction",
                function.name,
                function.start,
                e,
                "extract_disassembly",
            )
            return None

    def extract_hlil(self, function):
        """Extract HLIL from a function."""
        try:
            # Access function.hlil directly - this will either return the HLIL or raise an exception
            # Removed hlil_if_available check as it was causing race conditions
            if function.hlil is None:
                return None

            if len(function.hlil.basic_blocks) == 0:
                return None

            # if function has one basic block, then compare the len of the instructions against minimum of our functions
            if len(function.hlil.basic_blocks) == 1:
                block = function.basic_blocks[0]
                if len(list(block.disassembly_text)) < self.MIN_FUNCTION_SIZE:
                    return None

            # Get decompiled code
            function_prototype = str(function)
            decompiled_code = str(function.hlil)
            if not decompiled_code or decompiled_code.strip() == "":
                self.log.warning(f"Empty decompilation result for {function.name}")
                return None

            callers = []
            for caller_site in function.caller_sites:
                if caller_site.hlil:
                    callers.append(str(caller_site.hlil))

            calls = []
            for call in function.call_sites:
                if call.hlil:
                    calls.append(str(call.hlil))

            analysis_score = ObfuscationScores(function.hlil)
            flattened_score = analysis_score.flattened_score()
            mba_score = analysis_score.MBA_score()

            if decompiled_code:
                # Create json object
                function_json = {
                    "decompiled_function_hash": calculate_sha256(decompiled_code),
                    "decompiled_function": decompiled_code,
                    "decompiled_function_name": function.name,
                    "decompiled_function_prototype": function_prototype,
                    "decompiled_function_address": function.start,
                    "function_type": FunctionTypeAnalysis(function)
                    .get_function_type()
                    .name,
                    "functions_caller": list(callers),
                    "functions_call": list(calls),
                    "flattened_score": flattened_score,
                    "mba_score": mba_score,
                }
                return function_json
            else:
                return None

        except Exception as e:
            self.log.warning(
                f"Failed to get HLIL for {function.name} at {function.start}: {str(e)}"
            )

        return None

    def extract(self) -> bool:
        """Extract and process all analysis results.

        Returns:
            bool: True if extraction was successful, False otherwise

        """
        self.log.info(f"Starting binary analysis on {self.filepath}")
        try:
            results = self.analyze_binary()
            if not results:
                self.log.error("Analysis failed to produce results")
                return False

            self.analysis_results = results
            self.log.info(
                f"Successfully analyzed binary: {len(results['decompiled'])} decompiled functions, "
                f"{len(results['disassembled'])} disassembled functions, "
                #f"{len(results['cfg'])} basic blocks, "
                f"{len(results['errors'])} errors"
            )
            return True

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

    def is_too_few_blocks(self, function):
        if function is None:
            return False

        if function.basic_blocks is None:
            return False

        # when binary ninja does not wait for the analysis, it creates function stubs where basic blocks array
        # is not populated yet. Therefore, we disable this heuristic.
        #if len(function.basic_blocks) == 0:
        #    return False

        # if function has one basic block, then compare the len of the instructions against minimum of our functions
        if len(function.basic_blocks) == 1:
            block = function.basic_blocks[0]
            if len(list(block.disassembly_text)) < self.MIN_FUNCTION_SIZE:
                return False

        return True

def is_lib_or_thunk(function):
    function_type = FunctionTypeAnalysis(function).get_function_type()
    return not (function_type == FunctionType.THUNK or function_type == FunctionType.EXTERNAL or function_type == FunctionType.LIBRARY)