Hai Liu

77 papers A* 2A 2B 2Journal 56Unranked 15
YearRankTypeTitle / Venue / Authors
2026 J jnl
Neurocomputing
Hai Liu, Hao Zheng, Tingting Liu, Yu Song, Xiaolan Yang, Zhaoli Zhang
2026 J jnl
IEEE Internet Things J.
Tingting Liu, Zhibing Liu, Qiang Chen, Hai Liu, Zhaoli Zhang, Neal N. Xiong
2026 J jnl
Expert Syst. Appl.
Zhaoli Zhang, Jiahao Li, Hai Liu, Erqi Zhang, Tingting Liu, Minhong Wang
2026 J jnl
Neurocomputing
Meiyi Yang, Qianang Zhou, Hai Liu, You-Fu Li, Junlin Xiong
2026 J jnl
IEEE Trans. Circuits Syst. Video Technol.
Hai Liu, Shuang Zeng, Liqian Deng, Tingting Liu, Xionghua Liu, Zhaoli Zhang, You-Fu Li
2026 J jnl
IEEE Trans. Neural Networks Learn. Syst.
Hai Liu, Yu Song, Tingting Liu, Hao Zheng, Lin Chen, Zhaoli Zhang, Youfu Li
2026 J jnl
Pattern Recognit.
Hai Liu, Feifei Li, Zhibing Liu, Qiang Chen, Zhiyi Du, Tingting Liu, Zhaoli Zhang, You Fu Li
2026 J jnl
IEEE Trans. Multim.
Hai Liu, Qiang Chen, Zhibing Liu, Tingting Liu, Li Zhao, Zhaoli Zhang, You-Fu Li
2026 J jnl
IEEE Internet Things J.
Hai Liu, Yu Song, Tingting Liu, Lin Chen, Zhaoli Zhang, Xiaolan Yang, Neal N. Xiong
2025 J jnl
Digit. Signal Process.
Yi Deng, Jun Ma, Ziyi Wu, Wanhao Wang, Hai Liu
2025 J jnl
Neurocomputing
Tingting Liu, Minghong Wang, Bing Yang, Hai Liu, Shaoxin Yi
2025 J jnl
Neurocomputing
Shuang Zeng, Hai Liu, Tingting Liu, Qiuxia Liu, Minhong Wang, Bing Yang, Zhaoli Zhang
2025 J jnl
Br. J. Educ. Technol.
Erqi Zhang, Zhaoli Zhang, Hai Liu, Shuyun Han, Zengcan Xue
2025 J jnl
Neurocomputing
Hai Liu, Shijia Qian, Tingting Liu, Zelin Cao, Minhong Wang, Jianping Ju, Zhaoli Zhang
2025 J jnl
Appl. Intell.
Yi Deng, Jiawen Chen, Quan Xie, Dapeng Tan, Hai Liu
2025 J jnl
Appl. Intell.
Zengzhao Chen, Fumei Ma, Hai Liu, Wenkai Huang, Tingting Liu
2025 J jnl
Knowl. Based Syst.
Zengcan Xue, Zhaoli Zhang, Hai Liu, Zhifei Li, Shuyun Han, Erqi Zhang
2025 J jnl
Neurocomputing
Yuhan Liu, Yongjian Deng, Bochen Xie, Hai Liu, Zhen Yang, Youfu Li
2025 J jnl
Eng. Appl. Artif. Intell.
Haoxiang Ma, Yongjian Deng, Bochen Xie, Jian Liu, Hai Liu, Youfu Li, Zhen Yang
2025 J jnl
IEEE Trans. Multim.
Hai Liu, Cheng Zhang, Yongjian Deng, Bochen Xie, Tingting Liu, Youfu Li
2024 J jnl
IEEE Trans. Multim.
Hai Liu, Tingting Liu, Yu Chen, Zhaoli Zhang, You-Fu Li
2024 conf
ROBIO
Hai Liu, Qiang Chen, Zhibing Liu, Yongjian Deng, Zhaoli Zhang, You-Fu Li
2024 J jnl
Interact. Learn. Environ.
Shuyun Han, Zhaoli Zhang, Hai Liu, Weiliang Kong, Zengcan Xue, Taihe Cao, Jiangbo Shu
2024 J jnl
IEEE Trans. Ind. Informatics
Tingting Liu, Hai Liu, Bing Yang, Zhaoli Zhang
2024 J jnl
IEEE Trans. Ind. Informatics
Hai Liu, Qiyun Zhou, Cheng Zhang, Junyan Zhu, Tingting Liu, Zhaoli Zhang, Youfu Li
2024 J jnl
Sensors
Hui Li, Jiawen Li, Hai Liu, Tingting Liu, Qiang Chen, Xinge You
2023 J jnl
CoRR
Yongjian Deng, Hao Chen, Bochen Xie, Hai Liu, Youfu Li
2023 conf
ICDM (Workshops)
Linfeng Li, Hai Liu, Zhaoli Zhang
2023 conf
ICISE
Hai Liu, Jiawen Li, Li Zhao, Junya Si, Weixin Li, Dazhen Shen, Zixin Li, Tingting Liu
2023 J jnl
CoRR
Bochen Xie, Yongjian Deng, Zhanpeng Shao, Hai Liu, Qingsong Xu, Youfu Li
2023 conf
ICISE
Tingting Liu, Zixin Li, Li Zhao, Weixin Li, Junya Si, Hai Liu, Dazhen Shen, Jiawen Li
2023 J jnl
Expert Syst. Appl.
Zengcan Xue, Zhaoli Zhang, Hai Liu, Shuoqiu Yang, Shuyun Han
2023 J jnl
Expert Syst. Appl.
Qiuyu Zheng, Zengzhao Chen, Hai Liu, Yuanyuan Lu, Jiawen Li, Tingting Liu
2023 J jnl
IEEE Trans. Image Process.
Hai Liu, Cheng Zhang, Yongjian Deng, Tingting Liu, Zhaoli Zhang, Youfu Li
2023 A* conf
CVPR
Cheng Zhang, Hai Liu, Yongjian Deng, Bochen Xie, Youfu Li
2023 conf
ICISE
Li Zhao, Dazheng Shen, Tingting Liu, Zhuowei Wang, Weixin Li, Hai Liu, Junya Si, Jiawen Li, Zixin Li
2022 A* conf
CVPR
Yongjian Deng, Hao Chen, Hai Liu, Youfu Li
2022 J jnl
IEEE Trans. Ind. Informatics
Hai Liu, Tingting Liu, Zhaoli Zhang, Arun Kumar Sangaiah, Bing Yang, Youfu Li
2022 conf
ROBIO
Hai Liu, Cheng Zhang, Bochen Xie, Tingting Liu, Qingsong Xu, Youfu Li
2022 J jnl
IEEE Trans. Ind. Informatics
Hai Liu, Chao Zheng, Duantengchuan Li, Xiaoxuan Shen, Ke Lin, Jiazhang Wang, Zhen Zhang, Zhaoli Zhang, Neal N. Xiong
2022 conf
CRC
Bochen Xie, Yongjian Deng, Zhanpeng Shao, Hai Liu, Qingsong Xu, Youfu Li
2022 J jnl
Interact. Learn. Environ.
Zhaoli Zhang, Taihe Cao, Jiangbo Shu, Hai Liu
2022 J jnl
IEEE Trans. Neural Networks Learn. Syst.
Zhifei Li, Hai Liu, Zhaoli Zhang, Tingting Liu, Neal N. Xiong
2022 J jnl
IEEE Trans. Multim.
Hai Liu, Shuai Fang, Zhaoli Zhang, Duantengchuan Li, Ke Lin, Jiazhang Wang
2022 J jnl
IEEE Trans. Knowl. Data Eng.
Zhaoli Zhang, Zhifei Li, Hai Liu, Neal N. Xiong
2022 J jnl
Neurocomputing
Hai Liu, Chao Zheng, Duantengchuan Li, Zhaoli Zhang, Ke Lin, Xiaoxuan Shen, Neal N. Xiong, Jiazhang Wang
2022 J jnl
IEEE Robotics Autom. Lett.
Bochen Xie, Yongjian Deng, Zhanpeng Shao, Hai Liu, Youfu Li
2021 J jnl
Neurocomputing
Hai Liu, Hanwen Nie, Zhaoli Zhang, Youfu Li
2021 J jnl
Neurocomputing
Duantengchuan Li, Hai Liu, Zhaoli Zhang, Ke Lin, Shuai Fang, Zhifei Li, Neal N. Xiong
2021 J jnl
IEEE Trans. Knowl. Data Eng.
Xiaoxuan Shen, Baolin Yi, Hai Liu, Wei Zhang, Zhaoli Zhang, Sannyuya Liu, Naixue Xiong
2021 conf
TALE
Zengcan Xue, Hai Liu, Zhaoli Zhang, Shuoqiu Yang
2021 conf
TALE
Xiaonan Wu, Zengzhao Chen, Hai Liu
2021 J jnl
Neurocomputing
Zhifei Li, Hai Liu, Zhaoli Zhang, Tingting Liu, Jiangbo Shu
2021 J jnl
IEEE Trans. Instrum. Meas.
Meng Liu, Youfu Li, Hai Liu
2020 A conf
IROS
Meng Liu, Youfu Li, Hai Liu
2020 J jnl
IEEE Access
Meng Liu, Youfu Li, Hai Liu
2020 J jnl
IEEE Trans. Ind. Informatics
Tingting Liu, Hai Liu, Youfu Li, Zengzhao Chen, Zhaoli Zhang, Sannyuya Liu
2020 J jnl
Neurocomputing
Zhaoli Zhang, Chenghang Lai, Hai Liu, Youfu Li
2020 J jnl
Neurocomputing
Hai Liu, Xiang Wang, Wei Zhang, Zhaoli Zhang, Youfu Li
2019 A conf
IROS
Hai Liu, Youfu Li, Dan Su, Zhaoli Zhang, Sannyuya Liu, Tingting Liu
2019 J jnl
IEEE Trans. Ind. Informatics
Baolin Yi, Xiaoxuan Shen, Hai Liu, Zhaoli Zhang, Wei Zhang, Sannyuya Liu, Naixue Xiong
2018 J jnl
Multim. Syst.
Jiangbo Shu, Xiaoxuan Shen, Hai Liu, Baolin Yi, Zhaoli Zhang
2018 J jnl
IEEE Trans. Ind. Informatics
Tingting Liu, Hai Liu, Zengzhao Chen, Alan M. Lesgold
2018 conf
ICAIP
Tingting Liu, Zengzhao Chen, Hai Liu, Zhaoli Zhang, Yingying Chen
2017 J jnl
Circuits Syst. Signal Process.
Hai Liu, Luxin Yan, Tao Huang, Sanya Liu, Zhaoli Zhang
2016 conf
SKIMA
Baolin Yi, Xiaoxuan Shen, Zhaoli Zhang, Jiangbo Shu, Hai Liu
2016 conf
APSIPA
Tingting Liu, Zengzhao Chen, Hai Liu, Sanya Liu, Zhaoli Zhang, Taihe Cao
2015 conf
APSIPA
Hai Liu, Zhaoli Zhang, Sanya Liu, Jiangbo Shu, Zhi Liu
2015 B conf
ICIP
Hai Liu, Zhaoli Zhang, Sanya Liu, Tingting Liu, Yi Chang
2015 conf
ICHL
Jiangbo Shu, Beibei Wan, Jiaojiao Li, Zhaoli Zhang, Liang Wu, Hai Liu
2015 conf
SP/SPE
Hai Liu, Zhaoli Zhang, Sanya Liu, Jiangbo Shu, Tingting Liu
2014 J jnl
IEEE Geosci. Remote. Sens. Lett.
Zu Yan, Jie Ma, Jinwen Tian, Hai Liu, Jingang Yu, Yun Zhang
2014 J jnl
IEEE Geosci. Remote. Sens. Lett.
Yi Chang, Luxin Yan, Houzhang Fang, Hai Liu
2013 B conf
ICIP
Yi Chang, Houzhang Fang, Luxin Yan, Hai Liu
2013 J jnl
IEEE Trans. Instrum. Meas.
Hai Liu, Luxin Yan, Yi Chang, Houzhang Fang, Tianxu Zhang
2012 J jnl
Photonic Netw. Commun.
Yuan Zhan, Mengli Tang, Hai Liu, Minming Zhang, Deming Liu
2012 J jnl
IEEE Geosci. Remote. Sens. Lett.
Luxin Yan, Mingzhi Jin, Houzhang Fang, Hai Liu, Tianxu Zhang
redb/extractors/yara.py
← Index redb/extractors/yara.py python
"""
YARA Extractor - Scans binary files with YARA rules and stores matches in ClickHouse.

This extractor uses the yara-x library to scan samples against a collection of
YARA rules located in the 'yara/' folder at the project root.

Supports both:
- Pre-compiled rules (.yarac) for faster loading
- Source rules (.yar/.yara) compiled on-the-fly

Schema Design:
- yara_rules: Rule metadata stored once per unique rule (deduplicated by rule_id)
- yara_matches: Sample-rule matches with binary sha256 for efficiency
"""
import inspect
import json
import os
import re
import threading
import time
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple

import xxhash
import yara_x

from redb.extractors.enum import Tag
from redb.extractors.extractor import Extractor
from redb.models.dataclasses import YaraMatch, YaraRule


# Default compiled rules filename (can be overridden via YARA_COMPILED_RULES env var)
COMPILED_RULES_FILENAME = os.getenv("YARA_COMPILED_RULES", "compiled_rules.yarac")

# Default source collection name
DEFAULT_SOURCE_COLLECTION = os.getenv("YARA_SOURCE_COLLECTION", "default")


def canonicalize_rule(rule_text: str) -> str:
    """
    Canonicalize YARA rule text for consistent hashing.

    Strips comments and normalizes whitespace, but excludes metadata
    so rules with same logic but different metadata get the same ID.
    """
    # Strip single-line comments
    text = re.sub(r'//.*$', '', rule_text, flags=re.MULTILINE)
    # Strip multi-line comments
    text = re.sub(r'/\*.*?\*/', '', text, flags=re.DOTALL)
    # Strip meta section (keep only strings/condition)
    text = re.sub(r'meta\s*:\s*[^}]+(?=strings|condition|})', '', text, flags=re.DOTALL)
    # Normalize whitespace
    text = ' '.join(text.split())
    return text


def generate_rule_id(rule_text: str) -> int:
    """
    Generate a unique rule_id from canonicalized rule content.

    Returns:
        UInt64 hash of the canonical rule content
    """
    canonical = canonicalize_rule(rule_text)
    return xxhash.xxh64(canonical.encode('utf-8')).intdigest()


def sha256_hex_to_binary(hex_str: str) -> bytes:
    """Convert SHA256 hex string to binary (32 bytes)."""
    return bytes.fromhex(hex_str)


def sha256_binary_to_hex(binary: bytes) -> str:
    """Convert SHA256 binary (32 bytes) to hex string."""
    return binary.hex()


def parse_yara_rules(file_content: str) -> List[Dict[str, Any]]:
    """
    Parse individual YARA rules from file content.

    Handles files with multiple rules and extracts:
    - rule_name: The rule identifier
    - rule_tags: List of tags (from 'rule Name : tag1 tag2 {')
    - rule_meta: Dict of metadata key-value pairs
    - rule_text: Full rule source code

    Args:
        file_content: Raw content of a .yar/.yara file

    Returns:
        List of dicts, each containing rule_name, rule_tags, rule_meta, rule_text
    """
    rules = []

    # Pattern to match rule declarations: rule Name or rule Name : tags
    # We need to find rule boundaries by tracking braces
    rule_pattern = re.compile(
        r'(?:^|\n)\s*((?:private\s+|global\s+)*rule\s+(\w+)\s*(?::\s*([^{]*))?\s*\{)',
        re.MULTILINE
    )

    matches = list(rule_pattern.finditer(file_content))

    for i, match in enumerate(matches):
        rule_start = match.start(1)  # Start of 'rule ...'
        rule_name = match.group(2)
        tags_str = match.group(3) or ""
        rule_tags = [t.strip() for t in tags_str.split() if t.strip()]

        # Find the matching closing brace by counting braces
        brace_count = 0
        rule_end = match.end()
        in_string = False
        escape_next = False

        for j, char in enumerate(file_content[match.end() - 1:], start=match.end() - 1):
            if escape_next:
                escape_next = False
                continue
            if char == '\\':
                escape_next = True
                continue
            if char == '"' and not escape_next:
                in_string = not in_string
                continue
            if in_string:
                continue
            if char == '{':
                brace_count += 1
            elif char == '}':
                brace_count -= 1
                if brace_count == 0:
                    rule_end = j + 1
                    break

        rule_text = file_content[rule_start:rule_end].strip()

        # Extract metadata from rule
        meta = {}
        meta_match = re.search(
            r'meta\s*:\s*(.*?)(?=strings\s*:|condition\s*:|$)',
            rule_text,
            re.DOTALL
        )
        if meta_match:
            meta_text = meta_match.group(1)
            for line in meta_text.strip().split('\n'):
                if '=' in line:
                    key, _, value = line.partition('=')
                    key = key.strip()
                    value = value.strip().strip('"\'')
                    if key and not key.startswith('//'):
                        meta[key] = value

        rules.append({
            'rule_name': rule_name,
            'rule_tags': rule_tags,
            'rule_meta': meta,
            'rule_text': rule_text,
        })

    return rules


class YaraBatchInsertBuffer:
    """
    Thread-safe buffer for batching YARA match inserts.

    Collects matches from multiple samples and flushes to ClickHouse
    when batch_size is reached or flush_interval expires.
    """

    def __init__(
        self,
        exporter,
        index_prefix: str,
        batch_size: int = 1000,
        flush_interval: int = 30,
    ):
        self.exporter = exporter
        self.index_prefix = index_prefix
        self.batch_size = batch_size
        self.flush_interval = flush_interval

        self.matches_buffer: List[List] = []
        self.rules_buffer: Dict[int, List] = {}  # rule_id -> rule_data (deduplicated)
        self.lock = threading.Lock()
        self.last_flush = time.time()

        # Start background flush timer
        self._stop_timer = False
        self._timer_thread = threading.Thread(target=self._flush_timer, daemon=True)
        self._timer_thread.start()

    def add(self, sha256_binary: bytes, matches: List[Tuple], rules: Dict[int, List]) -> None:
        """
        Add matches and rules to buffer.

        Args:
            sha256_binary: Binary SHA256 (32 bytes)
            matches: List of match tuples (sha256_binary, rule_id, rule_name, scan_date, match_strings)
            rules: Dict of rule_id -> rule_data tuples
        """
        with self.lock:
            self.matches_buffer.extend(matches)
            # Merge rules (deduplicated by rule_id)
            for rule_id, rule_data in rules.items():
                if rule_id not in self.rules_buffer:
                    self.rules_buffer[rule_id] = rule_data

            if len(self.matches_buffer) >= self.batch_size:
                self._flush_locked()

    def _flush_locked(self) -> None:
        """Flush buffer (must hold lock)."""
        if not self.matches_buffer:
            return

        try:
            # Insert rules first (deduplicated)
            if self.rules_buffer:
                rules_data = list(self.rules_buffer.values())
                self.exporter.batch_insert(
                    table='yara_rules',
                    rows=rules_data,
                    column_names=[
                        'rule_id', 'rule_name', 'source_collection',
                        'ingested_at', 'rule_text', 'rule_meta', 'rule_tags'
                    ],
                    column_type_names=[
                        'UInt64', 'String', 'LowCardinality(String)',
                        "DateTime64(3, 'UTC')", 'String', 'JSON', 'Array(LowCardinality(String))'
                    ]
                )

            # Insert matches
            self.exporter.batch_insert(
                table='yara_matches',
                rows=self.matches_buffer,
                column_names=[
                    'sha256', 'rule_id', 'rule_name',
                    'scan_date', 'match_strings'
                ],
                column_type_names=[
                    'FixedString(32)', 'UInt64', 'LowCardinality(String)',
                    "DateTime64(3, 'UTC')", 'Array(String)'
                ]
            )

            print(f"[YARA] Flushed {len(self.matches_buffer)} matches and {len(self.rules_buffer)} rules")

        except Exception as e:
            print(f"[YARA] Error flushing batch: {e}")

        # Clear buffers
        self.matches_buffer = []
        self.rules_buffer = {}
        self.last_flush = time.time()

    def flush(self) -> None:
        """Public flush (acquires lock)."""
        with self.lock:
            self._flush_locked()

    def _flush_timer(self) -> None:
        """Background timer for periodic flushes."""
        while not self._stop_timer:
            time.sleep(5)  # Check every 5 seconds
            with self.lock:
                if time.time() - self.last_flush > self.flush_interval and self.matches_buffer:
                    self._flush_locked()

    def stop(self) -> None:
        """Stop the background timer and flush remaining data."""
        self._stop_timer = True
        self.flush()


class YaraExtractor(Extractor):
    """
    Extractor that scans binary files with YARA rules.

    The YARA rules are loaded from the 'yara/' folder at the project root.
    Each matching rule is stored in ClickHouse with its metadata.

    Supports pre-compiled rules for faster loading:
    - If 'yara/compiled_rules.yarac' exists, it will be loaded directly
    - Otherwise, all .yar/.yara files are compiled and cached in memory
    - Use YaraExtractor.compile_and_save() to pre-compile rules
    """

    # Class-level cache for compiled YARA rules
    _compiled_rules = None
    _rules_path = None

    def __init__(
        self,
        filepath: str,
        log: Any,
        exporters: Optional[List] = None,
        index_prefix: Optional[str] = None,
        known_benign: bool = False,
        known_malicious: bool = False,
    ):
        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            known_benign,
            known_malicious,
        )
        self.matches: List[YaraMatch] = []
        self.rules: Dict[str, YaraRule] = {}  # rule_name -> YaraRule (deduplicated)

    @classmethod
    def get_yara_rules_path(cls) -> Path:
        """Get the path to the YARA rules directory."""
        # Default to 'yara/' in project root
        project_root = Path(__file__).parent.parent.parent
        default_path = project_root / "yara"

        # Allow override via environment variable
        rules_path = os.getenv("YARA_RULES_PATH", str(default_path))
        return Path(rules_path)

    @classmethod
    def get_compiled_rules_path(cls) -> Path:
        """Get the path to the pre-compiled rules file."""
        return cls.get_yara_rules_path() / COMPILED_RULES_FILENAME

    @classmethod
    def load_compiled_rules(cls) -> Optional[yara_x.Rules]:
        """
        Load pre-compiled YARA rules from .yarac file.

        Returns:
            Compiled Rules object or None if file doesn't exist
        """
        compiled_path = cls.get_compiled_rules_path()
        if not compiled_path.exists():
            return None

        try:
            with open(compiled_path, "rb") as f:
                rules = yara_x.Rules.deserialize_from(f)
            # Only log in debug mode (non-prod) to avoid spamming in bulk processing
            if os.getenv("SERVER_ENV") != "prod":
                print(f"[DEBUG] Loaded pre-compiled YARA rules from {compiled_path}")
            return rules
        except Exception as e:
            print(f"[WARNING] Failed to load compiled rules from {compiled_path}: {e}")
            return None

    @classmethod
    def compile_rules_from_source(cls) -> Optional[yara_x.Rules]:
        """
        Compile all YARA rules from source .yar/.yara files.

        Returns:
            Compiled Rules object or None if no rules found
        """
        rules_path = cls.get_yara_rules_path()

        if not rules_path.exists():
            return None

        # Find all .yar and .yara files recursively
        rule_files = []
        for ext in ["*.yar", "*.yara"]:
            rule_files.extend(rules_path.rglob(ext))

        if not rule_files:
            return None

        print(f"[INFO] Compiling {len(rule_files)} YARA rule files from {rules_path}")

        # Compile all rules using yara-x compiler
        compiler = yara_x.Compiler()
        compiled_count = 0
        failed_count = 0

        for rule_file in rule_files:
            try:
                with open(rule_file, "r", encoding="utf-8") as f:
                    rule_content = f.read()
                # Use the relative path from rules_path as namespace
                namespace = str(rule_file.relative_to(rules_path).parent)
                if namespace == ".":
                    namespace = "default"
                compiler.new_namespace(namespace)
                compiler.add_source(rule_content)
                compiled_count += 1
            except Exception as e:
                # Log warning but continue with other rules
                print(f"[WARNING] Failed to compile YARA rule {rule_file}: {e}")
                failed_count += 1
                continue

        try:
            rules = compiler.build()
            print(f"[INFO] Successfully compiled {compiled_count} rule files ({failed_count} failed)")
            return rules
        except Exception as e:
            print(f"[ERROR] Failed to build YARA rules: {e}")
            return None

    @classmethod
    def compile_rules(cls, force_reload: bool = False) -> Optional[yara_x.Rules]:
        """
        Get compiled YARA rules, loading from cache, .yarac file, or compiling from source.

        Priority:
        1. Return cached rules if available
        2. Load pre-compiled .yarac file if it exists
        3. Compile from source .yar/.yara files

        Args:
            force_reload: If True, ignore cache and reload rules

        Returns:
            Compiled YARA rules or None if no rules found
        """
        rules_path = cls.get_yara_rules_path()

        # Return cached rules if available and path hasn't changed
        if (
            cls._compiled_rules is not None
            and cls._rules_path == rules_path
            and not force_reload
        ):
            return cls._compiled_rules

        # Try loading pre-compiled rules first
        rules = cls.load_compiled_rules()

        # If no pre-compiled rules, compile from source
        if rules is None:
            rules = cls.compile_rules_from_source()

        # Cache the rules
        if rules is not None:
            cls._compiled_rules = rules
            cls._rules_path = rules_path

        return rules

    @classmethod
    def compile_and_save(cls, output_path: Optional[Path] = None) -> bool:
        """
        Compile all YARA rules from source and save to a .yarac file.

        This is useful for pre-compiling rules for faster loading in production.

        Args:
            output_path: Path to save compiled rules (default: yara/compiled_rules.yarac)

        Returns:
            True if successful, False otherwise
        """
        if output_path is None:
            output_path = cls.get_compiled_rules_path()

        # Force compile from source
        rules = cls.compile_rules_from_source()
        if rules is None:
            print("[ERROR] No rules to compile")
            return False

        try:
            # Ensure parent directory exists
            output_path.parent.mkdir(parents=True, exist_ok=True)

            with open(output_path, "wb") as f:
                rules.serialize_into(f)

            print(f"[INFO] Saved compiled YARA rules to {output_path}")
            return True
        except Exception as e:
            print(f"[ERROR] Failed to save compiled rules: {e}")
            return False

    def _extract_yara_matches(self) -> Tuple[List[YaraMatch], Dict[str, YaraRule]]:
        """
        Scan the binary with compiled YARA rules.

        Returns:
            Tuple of (matches list, rules dict) for each matching rule
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        compiled_rules = self.compile_rules()
        if compiled_rules is None:
            self.log.warning("No YARA rules found or compiled")
            return [], {}

        matches = []
        rules = {}

        try:
            # Scan the binary data
            scan_results = compiled_rules.scan(self.binary)

            # Process each matching rule
            for rule in scan_results.matching_rules:
                rule_name = rule.identifier

                # Extract rule metadata and store rule (deduplicated by name)
                if rule_name not in rules:
                    meta = {}
                    for identifier, value in rule.metadata:
                        meta[identifier] = str(value)
                    rules[rule_name] = YaraRule(
                        rule_name=rule_name,
                        rule_tags=list(rule.tags),
                        rule_meta=meta,
                    )

                # Extract matched string identifiers
                matched_strings = []
                for pattern in rule.patterns:
                    for match in pattern.matches:
                        matched_strings.append(pattern.identifier)

                # Remove duplicates from matched strings
                matched_strings = list(set(matched_strings))

                yara_match = YaraMatch(
                    rule_name=rule_name,
                    match_strings=matched_strings,
                )
                matches.append(yara_match)

                self.log.debug(
                    f"YARA match: {rule_name} (tags: {list(rule.tags)})"
                )

        except Exception as e:
            self.log.error(f"Error scanning with YARA: {e}")
            return [], {}

        return matches, rules

    def extract(self) -> Optional[List[YaraMatch]]:
        """
        Extract YARA matches from the binary.

        Returns:
            List of YaraMatch objects or None on error
        """
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            self.matches, self.rules = self._extract_yara_matches()
            return self.matches if self.matches else None
        except Exception as e:
            self.log.error(f"Error extracting YARA matches: {e}")
            return None

    def tag(self) -> str:
        """Return the tag for this extractor."""
        return Tag.YARA.value

    def get_clickhouse_table(self) -> str:
        """Return the ClickHouse table name for YARA matches."""
        return "yara_matches"

    def get_clickhouse_tables(self) -> Dict[str, str]:
        """Return all ClickHouse table names for multi-table support."""
        return {
            'rules': 'yara_rules',
            'matches': 'yara_matches',
        }

    def prepare_export_data(self, exporter_type: str) -> Any:
        """
        Prepare data for export to the specified exporter type.

        Uses optimized normalized schema with two tables:
        - yara_rules: Rule metadata with rule_id (UInt64 hash)
        - yara_matches: Matches with binary sha256 (32 bytes) and rule_id

        Args:
            exporter_type: The type of exporter (e.g., 'ClickHouseExporter')

        Returns:
            Data formatted for the specified exporter
        """

        if exporter_type == "ClickHouseExporter":
            if not self.matches:
                return None

            current_time = datetime.now(timezone.utc)
            source_collection = DEFAULT_SOURCE_COLLECTION

            # Convert sha256 hex to binary (32 bytes)
            sha256_binary = sha256_hex_to_binary(self.sha256)

            # Build rules data from self.rules (deduplicated by rule_id)
            rules_data = {}  # rule_id -> rule_data
            for rule_name, rule in self.rules.items():
                rule_content = f"rule {rule_name} {{ }}"  # Simplified for now
                rule_id = generate_rule_id(rule_content)
                if rule_id not in rules_data:
                    rules_data[rule_id] = [
                        rule_id,
                        rule.rule_name,
                        source_collection,
                        current_time,  # ingested_at
                        "",  # rule_text (empty for now, populated during sync)
                        json.dumps(rule.rule_meta),
                        rule.rule_tags,
                    ]

            # Build matches data
            matches_data = []
            for match in self.matches:
                rule_content = f"rule {match.rule_name} {{ }}"
                rule_id = generate_rule_id(rule_content)

                matches_data.append([
                    sha256_binary,  # Binary sha256 (32 bytes)
                    rule_id,
                    match.rule_name,
                    current_time,  # scan_date
                    match.match_strings,
                ])

            return {
                'multi_table': True,
                'rules': {
                    'table': 'yara_rules',
                    'data': list(rules_data.values()),
                    'column_names': [
                        'rule_id',
                        'rule_name',
                        'source_collection',
                        'ingested_at',
                        'rule_text',
                        'rule_meta',
                        'rule_tags',
                    ],
                    'column_type_names': [
                        'UInt64',
                        'String',
                        'LowCardinality(String)',
                        "DateTime64(3, 'UTC')",
                        'String',
                        'JSON',
                        'Array(LowCardinality(String))',
                    ],
                },
                'matches': {
                    'table': 'yara_matches',
                    'data': matches_data,
                    'column_names': [
                        'sha256',
                        'rule_id',
                        'rule_name',
                        'scan_date',
                        'match_strings',
                    ],
                    'column_type_names': [
                        'FixedString(32)',  # Binary sha256
                        'UInt64',
                        'LowCardinality(String)',
                        "DateTime64(3, 'UTC')",
                        'Array(String)',
                    ],
                },
            }

        return None


def sync_rules_to_db(source_collection: str = None) -> bool:
    """
    Sync all YARA rules from source files to the database.

    This ensures all rules exist in yara_rules table before scanning begins.
    Should be run before batch scanning or in container initialization.

    Args:
        source_collection: Source collection name (default from env)

    Returns:
        True if successful, False otherwise
    """
    from redb import settings

    source_collection = source_collection or DEFAULT_SOURCE_COLLECTION
    rules_path = YaraExtractor.get_yara_rules_path()

    if not rules_path.exists():
        print(f"[ERROR] Rules path does not exist: {rules_path}")
        return False

    # Find all rule files
    rule_files = []
    for ext in ["*.yar", "*.yara"]:
        rule_files.extend(rules_path.rglob(ext))

    if not rule_files:
        print(f"[INFO] No rule files found in {rules_path}")
        return True

    print(f"[INFO] Syncing {len(rule_files)} rule files to database...")

    current_time = datetime.now(timezone.utc)
    rules_data = []
    total_rules = 0

    for rule_file in rule_files:
        try:
            with open(rule_file, "r", encoding="utf-8") as f:
                file_content = f.read()

            # Parse individual rules from file (handles multiple rules per file)
            parsed_rules = parse_yara_rules(file_content)

            for rule in parsed_rules:
                rule_id = generate_rule_id(rule['rule_text'])

                rules_data.append([
                    rule_id,
                    rule['rule_name'],
                    source_collection,
                    current_time,
                    rule['rule_text'],
                    json.dumps(rule['rule_meta']),
                    rule['rule_tags'],
                ])
                total_rules += 1

        except Exception as e:
            print(f"[WARNING] Failed to parse rule file {rule_file}: {e}")
            continue

    print(f"[INFO] Parsed {total_rules} individual rules from {len(rule_files)} files")

    if not rules_data:
        print("[INFO] No rules to sync")
        return True

    # Insert rules to database
    try:
        client = settings.create_clickhouse_client()
        table = "yara_rules"

        client.insert(
            table,
            rules_data,
            column_names=[
                'rule_id', 'rule_name', 'source_collection',
                'ingested_at', 'rule_text', 'rule_meta', 'rule_tags'
            ],
            column_type_names=[
                'UInt64', 'String', 'LowCardinality(String)',
                "DateTime64(3, 'UTC')", 'String', 'JSON', 'Array(LowCardinality(String))'
            ]
        )

        print(f"[INFO] Successfully synced {len(rules_data)} rules to {table}")
        client.close()
        return True

    except Exception as e:
        print(f"[ERROR] Failed to sync rules to database: {e}")
        return False


# CLI utility for pre-compiling rules and syncing
if __name__ == "__main__":
    import argparse

    parser = argparse.ArgumentParser(description="YARA Rules Management Utility")
    parser.add_argument(
        "--compile",
        action="store_true",
        help="Compile all YARA rules and save to .yarac file",
    )
    parser.add_argument(
        "--sync-rules",
        action="store_true",
        help="Sync all YARA rules to the database (run before batch scanning)",
    )
    parser.add_argument(
        "--output",
        type=str,
        help="Output path for compiled rules (default: yara/compiled_rules.yarac)",
    )
    parser.add_argument(
        "--rules-path",
        type=str,
        help="Path to YARA rules directory (default: yara/)",
    )
    parser.add_argument(
        "--source-collection",
        type=str,
        help="Source collection name for rules (default: from YARA_SOURCE_COLLECTION env)",
    )

    args = parser.parse_args()

    if args.rules_path:
        os.environ["YARA_RULES_PATH"] = args.rules_path

    if args.compile:
        output_path = Path(args.output) if args.output else None
        success = YaraExtractor.compile_and_save(output_path)
        if not success:
            exit(1)

    if args.sync_rules:
        success = sync_rules_to_db(args.source_collection)
        if not success:
            exit(1)

    if not args.compile and not args.sync_rules:
        parser.print_help()