Xianglan Chen

30 papers A* 1A 3B 3C 3Journal 11Unranked 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
IEEE Trans. Computers
Zihan Wang, Lei Gong, Wenqi Lou, Teng Wang, Qianyu Cheng, Xianglan Chen, Chao Wang, Xuehai Zhou
2025 J jnl
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Yingxue Gao, Teng Wang, Yang Yang, Lei Gong, Xianglan Chen, Chao Wang, Xi Li, Xuehai Zhou
2025 J jnl
IEEE Trans. Computers
Yingxue Gao, Teng Wang, Lei Gong, Chao Wang, Dong Dai, Yang Yang, Xianglan Chen, Xi Li, Xuehai Zhou
2025 J jnl
IEEE Trans. Artif. Intell.
Yang Yang, Chao Wang, Lei Gong, Min Wu, Zhenghua Chen, Xiang Li, Xianglan Chen, Xuehai Zhou
2024 C conf
ICCD
Xiangjun Qu, Lei Gong, Wenqi Lou, Qianyu Cheng, Xianglan Chen, Chao Wang, Xuehai Zhou
2024 B conf
FPL
Zhendong Zheng, Qianyu Cheng, Teng Wang, Lei Gong, Xianglan Chen, Cheng Tang, Chao Wang, Xuehai Zhou
2024 C conf
ICCD
Zihan Wang, Lei Gong, Wenqi Lou, Qianyu Cheng, Xianglan Chen, Chao Wang, Xuehai Zhou
2023 J jnl
IEEE Trans. Computers
Lei Gong, Chao Wang, Haojun Xia, Xianglan Chen, Xi Li, Xuehai Zhou
2023 J jnl
Int. J. Hum. Comput. Interact.
Faizan Ali, Seden Dogan, Xianglan Chen, Cihan Cobanoglu, Moez Limayem
2021 B conf
IPEC
Yanmei Jia, Xianglan Chen
2021 A conf
DATE
Haojun Xia, Lei Gong, Chao Wang, Xianglan Chen, Xuehai Zhou
2019 conf
HPCC/SmartCity/DSS
Huihuang Yu, Zongwei Zhu, Xianglan Chen, Yuming Cheng, Yahui Hu, Xi Li
2019 J jnl
ACM Trans. Design Autom. Electr. Syst.
Bo Wan, Xi Li, Bo Zhang, Caixu Zhao, Xianglan Chen, Chao Wang, Xuehai Zhou
2019 A* conf
PLDI
Guangpu Li, Haopeng Liu, Xianglan Chen, Haryadi S. Gunawi, Shan Lu
2018 conf
ACM Great Lakes Symposium on VLSI
Yuming Cheng, Chao Wang, Yangyang Zhao, Xianglan Chen, Xuehai Zhou, Xi Li
2017 conf
ISPA/IUCC
Bo Wan, Xi Li, Bo Zhang, Kaiqi Zhou, Haizhao Luo, Chao Wang, Xianglan Chen, Xuehai Zhou
2017 conf
HPCC/SmartCity/DSS
Bo Wan, Haizhao Luo, Kaiqi Zhou, Xi Li, Chao Wang, Xianglan Chen, Xuehai Zhou
2017 conf
ISPA/IUCC
Zhen Wang, Zhinan Cheng, Xi Li, Chao Wang, Xianglan Chen, Xuehai Zhou
2017 conf
ACM TUR-C
Yu Zhang, Xianglan Chen, Xin An, Jianliang Lu, Xuejun Li, Xuehai Zhou
2017 C conf
APSEC
Bo Wan, Xi Li, Kaiqi Zhou, Haizhao Luo, Chao Wang, Xianglan Chen, Xuehai Zhou
2017 conf
ISPA/IUCC
Bo Wan, Xi Li, Haizhao Luo, Beilei Sun, Chao Wang, Xianglan Chen, Xuehai Zhou
2017 B conf
CCGrid
Jinhong Zhou, Chongchong Xu, Xianglan Chen, Chao Wang, Xuehai Zhou
2017 conf
ISPA/IUCC
Haizhao Luo, Xi Li, Bo Wan, Guixing Wu, Xianglan Chen, Chao Wang
2017 A conf
RTSS
Bo Wan, Xi Li, Haizhao Luo, Chao Wang, Xianglan Chen, Xuehai Zhou
2017 J jnl
计算机科学
Xi Li, Beilei Sun, Bo Wan, Xianglan Chen, Xuehai Zhou
2016 J jnl
Int. J. Parallel Program.
Huang Wang, Xianglan Chen, Huaping Chen
2016 J jnl
J. Syst. Archit.
Beilei Sun, Xi Li, Bo Wan, Chao Wang, Xuehai Zhou, Xianglan Chen
2016 conf
Trustcom/BigDataSE/ISPA
Youjun Xu, Xianglan Chen, Zhinan Cheng, Jiachen Song, Yuxiang Zhang
2015 J jnl
计算机科学
Xiaofei Li, Xianglan Chen, Jie Liu, Xi Li
2007 A conf
SIGCSE
Haifeng Liu, Xianglan Chen, Yuchang Gong
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