Manli Wu

15 papers C 1Journal 7Unranked 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
Inf. Manag.
Zhaohua Deng, Yuyao Tang, Manli Wu, Xing Zhang
2025 J jnl
Kybernetes
Zhaohua Deng, Rongyang Ma, Manli Wu, Richard Evans
2025 J jnl
Electron. Libr.
Xiaojuan Xu, Manli Wu, Zerui Zhao, Li Pan
2023 J jnl
Kybernetes
Manli Wu
2022 J jnl
CoRR
Yuyang Chen, Xiaoyu Cui, Yunjie Song, Manli Wu
2019 J jnl
Internet Res.
Manli Wu, Xiaojuan Xu, Lele Kang, J. Leon Zhao, Liang Liang
2019 conf
ASIST
Xiaojuan Xu, Manli Wu
2019 J jnl
J. Glob. Inf. Manag.
Manli Wu, Lele Kang, Yani Shi, J. Leon Zhao, Liang Liang
2018 conf
HICSS
Manli Wu, Chen Yang, Chuang Wang, J. Leon Zhao, Sisi Wu, Liang Liang
2018 conf
PACIS
Qiang Zhang, Manli Wu, J. Leon Zhao, Liang Liang
2017 C conf
ICIS
Manli Wu, Xunhua Guo, J. Leon Zhao, Liang Liang
2016 conf
HCI (21)
Manli Wu, Lele Kang, Xuan Li, J. Leon Zhao
2015 conf
HICSS
Manli Wu, J. Leon Zhao, Shuk Ying Ho, Liang Liang
2015 conf
PACIS
Manli Wu, Yonggui Wang, J. Leon Zhao, Liang Liang
2014 conf
PACIS
Ji Wu, Shaokun Fan, Manli Wu, J. Leon Zhao
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