Karim Bouzoubaa

37 papers A* 5C 5Misc 3Journal 9Unranked 14
YearRankTypeTitle / Venue / Authors
2024 conf
ICALP (2)
Ridouane Tachicart, Karim Bouzoubaa, Driss Namly
2022 J jnl
J. King Saud Univ. Comput. Inf. Sci.
Ridouane Tachicart, Karim Bouzoubaa
2021 conf
EACL (System Demonstrations)
Karim Bouzoubaa, Younes Jaafar, Driss Namly, Ridouane Tachicart, Rachida Tajmout, Hakima Khamar, Hamid Jaafar, Si Lhoussain Aouragh, Abdellah Yousfi
2021 J jnl
Commun. ACM
Kareem Darwish, Nizar Habash, Mourad Abbas, Hend S. Al-Khalifa, Hussein T. Al-Natsheh, Houda Bouamor, Karim Bouzoubaa, Violetta Cavalli-Sforza, Samhaa R. El-Beltagy, Wassim El-Hajj, Mustafa Jarrar, Hamdy Mubarak
2021 J jnl
Vietnam. J. Comput. Sci.
Ridouane Tachicart, Karim Bouzoubaa
2020 J jnl
CoRR
Kareem Darwish, Nizar Habash, Mourad Abbas, Hend S. Al-Khalifa, Hussein T. Al-Natsheh, Samhaa R. El-Beltagy, Houda Bouamor, Karim Bouzoubaa, Violetta Cavalli-Sforza, Wassim El-Hajj, Mustafa Jarrar, Hamdy Mubarak
2019 conf
ICCCI (2)
Ridouane Tachicart, Karim Bouzoubaa
2019 A* conf
ICALP
Driss Namly, Karim Bouzoubaa, Rachida Tajmout, Ali Laadimi
2019 A* conf
ICALP
Ridouane Tachicart, Karim Bouzoubaa
2018 A* ed.
ICALP
Abdelmonaime Lachkar, Karim Bouzoubaa, Azzeddine Mazroui, Abdelfettah Hamdani, Abdelhak Lekhouaja
2018 conf
CIST
Mohammed Nasri, Younes Jaafar, Karim Bouzoubaa
2018 conf
LOPAL
Abdelhamid El-Jihad, Driss Namly, fettah Hamdani, Karim Bouzoubaa
2018 conf
ACLING
Younes Jaafar, Karim Bouzoubaa
2017 A* conf
ICALP
Younes Jaafar, Karim Bouzoubaa
2017 A* conf
ICALP
Ridouane Tachicart, Karim Bouzoubaa, Si Lhoussain Aouragh, Hamid Jaafar
2017 J jnl
J. King Saud Univ. Comput. Inf. Sci.
Younes Jaafar, Driss Namly, Karim Bouzoubaa, Abdellah Yousfi
2017 conf
ACLING
Hind Saddiki, Violetta Cavalli-Sforza, Karim Bouzoubaa
2016 C conf
GWC
Yasser Regragui, Lahsen Abouenour, Fettoum Krieche, Karim Bouzoubaa, Paolo Rosso
2016 J jnl
Int. J. Speech Technol.
Younes Jaafar, Karim Bouzoubaa, Abdellah Yousfi, Rachida Tajmout, Hakima Khamar
2016 C conf
AICCSA
Driss Namly, Yasser Regragui, Karim Bouzoubaa
2016 conf
CIST
Ridouane Tachicart, Karim Bouzoubaa, Hamid Jaafar
2015 C conf
AICCSA
Hind Saddiki, Karim Bouzoubaa, Violetta Cavalli-Sforza
2014 conf
SITA
Ridouane Tachicart, Karim Bouzoubaa
2014 conf
SITA
Younes Jaafar, Karim Bouzoubaa
2014 J jnl
J. Intell. Fuzzy Syst.
Lahsen Abouenour, Mohammed Nasri, Karim Bouzoubaa, Adil Kabbaj, Paolo Rosso
2014 ch.
NLP of Semitic Languages
Yassine Benajiba, Paolo Rosso, Lahsen Abouenour, Omar Trigui, Karim Bouzoubaa, Lamia Hadrich Belguith
2013 C conf
AICCSA
Violetta Cavalli-Sforza, Hind Saddiki, Karim Bouzoubaa, Lahsen Abouenour, Mohamed Maamouri, Emily Goshey
2013 J jnl
Lang. Resour. Evaluation
Lahsen Abouenour, Karim Bouzoubaa, Paolo Rosso
2013 J jnl
Lang. Resour. Evaluation
Lahsen Abouenour, Karim Bouzoubaa, Paolo Rosso
2012 conf
CLEF (Online Working Notes/Labs/Workshop)
Lahsen Abouenour, Karim Bouzoubaa, Paolo Rosso
2011 Misc conf
ICCS
Mohammed Nasri, Adil Kabbaj, Karim Bouzoubaa
2010 C conf
KEOD
Lahsen Abouenour, Karim Bouzoubaa, Paolo Rosso
2009 conf
SEMITIC@EACL
Lahsen Abouenour, Karim Bouzoubaa, Paolo Rosso
2006 conf
IAT Workshops
Jamal Bentahar, Karim Bouzoubaa, Bernard Moulin
2006 Misc conf
ICCS
Adil Kabbaj, Karim Bouzoubaa, Khalid El Hachimi, Nabil Ourdani
2004 conf
AC
Karim Bouzoubaa, Jamal Bentahar, Bernard Moulin
1998 Misc conf
FLAIRS
Karim Bouzoubaa, Bernard Moulin
redb/extractors/ioc_extractor/ioc_extractor.py
← Index redb/extractors/ioc_extractor/ioc_extractor.py python
"""
IOC Extractor - Extractor class for extracting IOCs from decompilation results.

This extractor works with in-memory data from DecompileBinja, following the
standard Extractor pattern to support both ClickHouse and PrintExporter (dry-run).

Usage:
    # After DecompileBinja completes:
    ioc_extractor = IOCExtractorFromResults(
        analysis_results=decompiler.analysis_results,
        sha256=sha256,
        log=logger,
        exporters=exporters,
        index_prefix=index_prefix
    )
    ioc_extractor.export_data()
"""

import inspect
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, List, Dict, Optional

from redb.extractors.enum import Tag
from redb.extractors.database_exporters import DatabaseExporter

# Import the IOCScraper and related classes from standalone module
from redb.extractors.ioc_extractor.standalone_ioc_extractor import (
    IOCScraper,
    IOCType,
    SourceType,
    ExtractedIOC,
)
from typing import Set


class IOCExtractorFromResults:
    """
    Extracts IOCs from in-memory decompilation results.

    This follows a simplified Extractor pattern but doesn't inherit from Extractor
    since it doesn't read from a binary file - instead it takes already-processed
    analysis results from DecompileBinja.
    """

    def __init__(
        self,
        analysis_results: Dict[str, Any],
        sha256: str,
        log: Any,
        exporters: Optional[List[DatabaseExporter]] = None,
        index_prefix: Optional[str] = None,
        tld_file: Optional[Path] = None,
        suppress_types: Optional[Set[IOCType]] = None,
        js_context: bool = False,
    ):
        """
        Initialize IOC Extractor with analysis results.

        Args:
            analysis_results: Dict containing 'strings' and 'decompiled' lists from DecompileBinja
            sha256: Sample SHA256 hash
            log: Logger instance
            exporters: List of database exporters (ClickHouse, Print, etc.)
            index_prefix: Index prefix for database
            tld_file: Optional path to TLD list file
            js_context: When True, the underlying IOCScraper rejects FQDN
                candidates that match JS object-access syntax (see
                JS_FP_TLDS / JS_FP_SLDS). Set this for the JS pipeline only;
                APK suppresses FQDN entirely via suppress_types and binary
                callers leave it disabled.
        """
        self.log = log
        self.log.debug(f"Creating {self.__class__.__name__}")
        self.analysis_results = analysis_results
        self.sha256 = sha256
        self.exporters = exporters or []
        self.index_prefix = index_prefix
        self.scraper = IOCScraper(
            tld_file, suppress_types=suppress_types, js_context=js_context,
        )
        self.extracted_iocs: List[ExtractedIOC] = []

    def extract(self) -> List[ExtractedIOC]:
        """
        Extract IOCs from strings and decompiled functions in analysis_results.

        Returns:
            List of ExtractedIOC objects
        """
        self.log.debug(inspect.currentframe().f_code.co_name)
        self.extracted_iocs = []

        # Extract from strings
        strings_count = self._extract_from_strings()

        # Extract from decompiled functions
        functions_count = self._extract_from_decompiled()

        # Extract from text-based artefact surfaces (JS, PowerShell, etc.)
        text_count = self._extract_from_text()

        self.log.info(
            f"Extracted {len(self.extracted_iocs)} IOCs for {self.sha256[:16]}... "
            f"(strings: {strings_count}, functions: {functions_count}, "
            f"text: {text_count})"
        )

        return self.extracted_iocs

    def _extract_from_strings(self) -> int:
        """Extract IOCs from sample's strings."""
        count = 0
        strings = self.analysis_results.get("strings", [])

        for s in strings:
            string_value = s.get("string", "")
            string_offset = s.get("string_offset", 0)

            if isinstance(string_value, bytes):
                string_value = string_value.decode('utf-8', errors='replace')

            for ioc in self.scraper.scrape(string_value, SourceType.STRING, str(string_offset)):
                self.extracted_iocs.append(ioc)
                count += 1

        return count

    def _extract_from_decompiled(self) -> int:
        """Extract IOCs from sample's decompiled functions.

        Supports both Binja format (key: "decompiled", fields: "decompiled_function",
        "decompiled_function_hash", "function_type") and APK format (key:
        "decompiled_content", fields: "decompiled_method", "decompiled_method_hash",
        "method_type").
        """
        count = 0

        # Binja format
        decompiled = self.analysis_results.get("decompiled", [])
        for func in decompiled:
            func_type = func.get("function_type", "UNKNOWN")
            if func_type in ("LIBRARY", "THUNK"):
                continue

            func_content = func.get("decompiled_function", "")
            func_hash = func.get("decompiled_function_hash", "unknown")

            if isinstance(func_content, bytes):
                func_content = func_content.decode('utf-8', errors='replace')

            for ioc in self.scraper.scrape(func_content, SourceType.DECOMPILED_FUNCTION, func_hash):
                self.extracted_iocs.append(ioc)
                count += 1

        # APK format (decompiled_content with method-level fields)
        decompiled_content = self.analysis_results.get("decompiled_content", [])
        for func in decompiled_content:
            func_type = func.get("method_type", "UNKNOWN")
            if func_type in ("LIBRARY", "THUNK"):
                continue

            func_content = func.get("decompiled_method", "")
            func_hash = func.get("decompiled_method_hash", "unknown")

            if isinstance(func_content, bytes):
                func_content = func_content.decode('utf-8', errors='replace')

            for ioc in self.scraper.scrape(func_content, SourceType.DECOMPILED_FUNCTION, func_hash):
                self.extracted_iocs.append(ioc)
                count += 1

        return count

    def _extract_from_text(self) -> int:
        """Extract IOCs from text-based artefact surfaces.

        Walks `analysis_results["text_raw"]` and `analysis_results["text_normalized"]`,
        each a list of `{"content": str, "content_hash": str}` dicts. Each
        list is routed through its own SourceType (`TEXT_RAW` /
        `TEXT_NORMALIZED`) so analysts can distinguish IOCs that were already
        present in the raw source from those exposed only after normalisation
        (deobfuscation/beautification). Generic across text-based formats —
        used by JS today, intended for PowerShell, Python, email body,
        extracted PDF/Office text in the future.
        """
        count = 0

        for key, source_type in (
            ("text_raw", SourceType.TEXT_RAW),
            ("text_normalized", SourceType.TEXT_NORMALIZED),
        ):
            for entry in self.analysis_results.get(key, []):
                content = entry.get("content", "")
                content_hash = entry.get("content_hash", "unknown")

                if isinstance(content, bytes):
                    content = content.decode('utf-8', errors='replace')

                for ioc in self.scraper.scrape(content, source_type, content_hash):
                    self.extracted_iocs.append(ioc)
                    count += 1

        return count

    def prepare_export_data(self, exporter_type: str) -> Any:
        """
        Prepare data for specific export type.

        Returns tuple for ClickHouse or list of dicts for Print/Elasticsearch.
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        if not self.extracted_iocs:
            return None

        now = datetime.now(timezone.utc)

        if exporter_type == "ClickHouseExporter":
            data = [
                [
                    self.sha256,
                    ioc.ioc_type.value,
                    ioc.ioc_value,
                    ioc.source_type.value,
                    ioc.source_identifier,
                    now,
                ]
                for ioc in self.extracted_iocs
            ]

            column_names = [
                "sha256",
                "ioc_type",
                "ioc_value",
                "source_type",
                "source_identifier",
                "extracted_at",
            ]

            column_type_names = [
                "FixedString(64)",
                "Enum8('ipv4'=1, 'ipv6'=2, 'fqdn'=3, 'url'=4, 'email'=5, 'server'=6, "
                "'hash_md5'=10, 'hash_sha1'=11, 'hash_sha256'=12, 'cve'=20, 'cwe'=21, 'cpe'=22, "
                "'crypto_btc'=30, 'crypto_eth'=31, 'crypto_xrp'=32, 'crypto_bch'=33, "
                "'crypto_ada'=34, 'crypto_substrate'=35, 'path_linux'=40, 'path_windows'=41, "
                "'registry_key'=42, 'onion'=50)",
                "String",
                "Enum8('decompiled_function'=1, 'disassembled_function'=2, 'string'=3, "
                "'text_raw'=4, 'text_normalized'=5)",
                "String",
                "DateTime64(3, 'UTC')",
            ]

            return (data, column_names, column_type_names)

        else:
            # For PrintExporter and others - return list of dicts
            return [
                {
                    "sha256": self.sha256,
                    "ioc_type": ioc.ioc_type.value,
                    "ioc_value": ioc.ioc_value,
                    "source_type": ioc.source_type.value,
                    "source_identifier": ioc.source_identifier,
                    "extracted_at": now.isoformat(),
                }
                for ioc in self.extracted_iocs
            ]

    def get_clickhouse_table(self) -> str:
        """Return the ClickHouse table name for IOCs."""
        return "redb_iocs"

    def tag(self) -> str:
        """Return the tag for this extractor."""
        return Tag.IOC.value if hasattr(Tag, 'IOC') else "ioc"

    def export_data(self) -> bool:
        """
        Export extracted IOCs to all configured exporters.

        Returns:
            True if export succeeded, False if failed, None if no data
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        # First extract the IOCs
        extracted = self.extract()

        if not extracted:
            self.log.debug("No IOCs extracted, skipping export")
            return None

        success = True

        from redb.extractors.database_exporters import PrintExporter, ClickHouseExporter

        for exporter in self.exporters:
            try:
                if isinstance(exporter, PrintExporter):
                    # For PrintExporter, pass the list of dicts
                    export_data = self.prepare_export_data("PrintExporter")
                    success &= exporter.export(export_data)

                elif isinstance(exporter, ClickHouseExporter):
                    # For ClickHouse, pass tuple with table info
                    export_data = self.prepare_export_data("ClickHouseExporter")
                    if export_data:
                        success &= exporter.export(
                            export_data,
                            table=self.get_clickhouse_table(),
                            column_names=export_data[1],
                            column_type_names=export_data[2]
                        )

            except Exception as e:
                self.log.error(f"Error exporting IOCs to {exporter.__class__.__name__}: {e}")
                success = False

        return success