Haitao Liu

32 papers Journal 27Unranked 5
YearRankTypeTitle / Venue / Authors
2025 conf
ROBIO
Guangxi Li, Zhizhen Ren, Qingpo Xu, Haitao Liu
2025 J jnl
IEEE Trans. Ind. Electron.
Mingli Wang, Juliang Xiao, Wei Zhao, Haitao Liu
2025 J jnl
Robotica
Zhuo Ma, Yingxue Wang, Rencheng Zheng, Haitao Liu, Jianbin Liu
2025 conf
ICIRA (1)
Wei Ma, Haitao Liu, Guofeng Wang, Juliang Xiao, Qingpo Xu, Tianren Zhao, Wei Han
2025 J jnl
Ind. Robot
Haitao Liu, Junfu Zhou, Guangxi Li, Juliang Xiao, Xucang Zheng
2025 J jnl
IEEE Trans. Instrum. Meas.
Wei Zhao, Zhikang Niu, Juliang Xiao, Sijiang Liu, Haitao Liu
2025 J jnl
Symmetry
Kai Cui, Qingpo Xu, Yabin Ding, Jiangping Mei, Ying He, Haitao Liu
2024 J jnl
Ind. Robot
Zaihua Luo, Juliang Xiao, Sijiang Liu, Mingli Wang, Wei Zhao, Haitao Liu
2024 J jnl
Biomed. Signal Process. Control.
Yunjiao Deng, Feng Gu, Daxing Zeng, Junyan Lu, Haitao Liu, Yulei Hou, Qinghua Zhang
2023 conf
ICIRA (3)
Yunjiao Deng, Feng Gu, Shuai Wang, Daxing Zeng, Junyan Lu, Haitao Liu, Yulei Hou, Qinghua Zhang
2023 J jnl
Robotics Comput. Integr. Manuf.
Juliang Xiao, Mingli Wang, Haitao Liu, Sijiang Liu, Huihui Zhao, Jiashuang Gao
2023 J jnl
Appl. Intell.
Xinwang Li, Juliang Xiao, Yu Cheng, Haitao Liu
2023 J jnl
Robotics Comput. Integr. Manuf.
Guangxi Li, Haitao Liu, Tian Huang, Jiale Han, Juliang Xiao
2023 J jnl
Robotics Comput. Integr. Manuf.
Qi Liu, Haitao Liu, Juliang Xiao, Wenjie Tian, Yue Ma, Bin Li
2023 J jnl
Ind. Robot
Wei Zhao, Juliang Xiao, Sijiang Liu, Saixiong Dou, Haitao Liu
2022 J jnl
J. Intell. Robotic Syst.
Saixiong Dou, Juliang Xiao, Wei Zhao, Hang Yuan, Haitao Liu
2022 J jnl
IEEE Trans. Robotics
Mingli Wang, Juliang Xiao, Sijiang Liu, Haitao Liu
2022 J jnl
Robotics Comput. Integr. Manuf.
Juliang Xiao, Sijiang Liu, Haitao Liu, Mingli Wang, Guangxi Li, Yunpeng Wang
2022 J jnl
Ind. Robot
Xinwang Li, Juliang Xiao, Wei Zhao, Haitao Liu, Guodong Wang
2022 J jnl
CoRR
Yugeng Huang, Haitao Liu, Tian Huang
2021 J jnl
Robotics Comput. Integr. Manuf.
Long Wu, Chenglin Dong, Guofeng Wang, Haitao Liu, Tian Huang
2021 conf
ICIRA (3)
Chenglin Dong, Haitao Liu, Longqi Cai, Lizhi Liu
2021 J jnl
Robotica
Manxin Wang, Qiusheng Chen, Haitao Liu, Tian Huang, Hutian Feng, Wenjie Tian
2021 J jnl
Ind. Robot
Juliang Xiao, Yunpeng Wang, Sijiang Liu, Yubo Sun, Haitao Liu, Tian Huang, Jian Xu
2021 J jnl
IEEE Robotics Autom. Lett.
Juliang Xiao, Saixiong Dou, Wei Zhao, Haitao Liu
2020 J jnl
Ind. Robot
Yubo Sun, Juliang Xiao, Haitao Liu, Tian Huang, Guodong Wang
2019 J jnl
Robotica
Tian Huang, Chenglin Dong, Haitao Liu, Tao Sun, Derek G. Chetwynd
2019 J jnl
IEEE Access
Fan Zeng, Juliang Xiao, Haitao Liu
2019 J jnl
Ind. Robot
Juliang Xiao, Fan Zeng, Qiulong Zhang, Haitao Liu
2017 conf
TE
Lili Li, Zhongxia Xiang, Haitao Liu, Yixin Shao, Junxia Zhang
2017 J jnl
IEEE Trans. Robotics
Haitao Liu, Tian Huang, Derek G. Chetwynd, Andrés Kecskeméthy
2011 J jnl
IEEE Trans. Robotics
Haitao Liu, Tian Huang, Derek G. Chetwynd
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