Hans J. Johnson

55 papers B 17Journal 23Unranked 15
YearRankTypeTitle / Venue / Authors
2023 conf
ISBI
Michal Brzus, Aaron D. Boes, Joel Bruss, Hans J. Johnson
2023 B conf
Image Processing
Xing Yao, Ange Lou, Hao Li, Dewei Hu, Daiwei Lu, Han Liu, Jiacheng Wang, Zachary A. Stoebner, Hans J. Johnson, Jeffrey D. Long, Jane S. Paulsen, Ipek Oguz
2023 J jnl
Algorithms
Michal Brzus, Kevin Knoernschild, Jessica C. Sieren, Hans J. Johnson
2022 B conf
Image Processing
Hao Li, Qibang Zhu, Dewei Hu, Manasvi R. Gunnala, Hans J. Johnson, Omar Sherbini, Francesco Gavazzi, Russell D'Aiello, Adeline Vanderver, Jeffrey D. Long, Jane S. Paulsen, Ipek Oguz
2022 J jnl
CoRR
M. Jorge Cardoso, Wenqi Li, Richard Brown, Nic Ma, Eric Kerfoot, Yiheng Wang, Benjamin Murray, Andriy Myronenko, Can Zhao, Dong Yang, Vishwesh Nath, Yufan He, Ziyue Xu, Ali Hatamizadeh, Wentao Zhu, Yun Liu, Mingxin Zheng, Yucheng Tang, Isaac Yang, Michael Zephyr, Behrooz Hashemian, Sachidanand Alle, Mohammad Zalbagi Darestani, Charlie Budd, Marc Modat, Tom Vercauteren, Guotai Wang, Yiwen Li, Yipeng Hu, Yunguan Fu, Benjamin Gorman, Hans J. Johnson, Brad W. Genereaux, Barbaros S. Erdal, Vikash Gupta, Andres Diaz-Pinto, Andre Dourson, Lena Maier-Hein, Paul F. Jaeger, Michael Baumgartner, Jayashree Kalpathy-Cramer, Mona Flores, Justin S. Kirby, Lee A. D. Cooper, Holger R. Roth, Daguang Xu, David Bericat, Ralf Floca, S. Kevin Zhou, Haris Shuaib, Keyvan Farahani, Klaus H. Maier-Hein, Stephen R. Aylward, Prerna Dogra, Sébastien Ourselin, Andrew Feng
2022 B conf
Image Processing
Michal Brzus, Alexander B. Powers, Kevin Knoernschild, Jessica C. Sieren, Hans J. Johnson
2022 conf
MLCN@MICCAI
Hao Li, Han Liu, Dewei Hu, Jiacheng Wang, Hans J. Johnson, Omar Sherbini, Francesco Gavazzi, Russell D'Aiello, Adeline Vanderver, Jeffrey D. Long, Jane S. Paulsen, Ipek Oguz
2021 B conf
Image Processing
Hao Li, Huahong Zhang, Hans J. Johnson, Jeffrey D. Long, Jane S. Paulsen, Ipek Oguz
2021 B conf
Image Processing
Hao Li, Huahong Zhang, Hans J. Johnson, Jeffrey D. Long, Jane S. Paulsen, Ipek Oguz
2020 J jnl
CoRR
Eric S. Pahl, W. Nick Street, Hans J. Johnson, Alan I. Reed
2020 conf
MLCN/RNO-AI@MICCAI
Hao Li, Huahong Zhang, Dewei Hu, Hans J. Johnson, Jeffrey D. Long, Jane S. Paulsen, Ipek Oguz
2020 conf
MICCAI (7)
Kilian Hett, Rémi Giraud, Hans J. Johnson, Jane S. Paulsen, Jeffrey D. Long, Ipek Oguz
2020 conf
ISBI
Arjit Jain, Alexander Powers, Hans J. Johnson
2020 conf
ISBI
Kilian Hett, Hans J. Johnson, Pierrick Coupé, Jane S. Paulsen, Jeffrey D. Long, Ipek Oguz
2020 J jnl
CoRR
Kilian Hett, Hans J. Johnson, Pierrick Coupé, Jane S. Paulsen, Jeffrey D. Long, Ipek Oguz
2019 J jnl
J. Digit. Imaging
Ziv Yaniv, Bradley C. Lowekamp, Hans J. Johnson, Richard Beare
2019 conf
ABCD-NP@MICCAI
Leo Brueggeman, Tanner Koomar, Yongchao Huang, Brady Hoskins, Tien Tong, James Kent, Ethan Bahl, Charles E. Johnson, Alexander Powers, Douglas R. Langbehn, Jatin G. Vaidya, Hans J. Johnson, Jacob J. Michaelson
2018 B conf
IJCNN
Renjie Hu, Venous Roshdibenam, Hans J. Johnson, Emil Eirola, Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse
2018 J jnl
NeuroImage
Ali Ghayoor, Jatin G. Vaidya, Hans J. Johnson
2018 J jnl
J. Digit. Imaging
Ziv Yaniv, Bradley C. Lowekamp, Hans J. Johnson, Richard Beare
2018 J jnl
Brain Connect.
Flor A. Espinoza, Jessica A. Turner, Victor M. Vergara, Robyn L. Miller, Eva Mennigen, Jingyu Liu, Maria B. Misiura, Jennifer Ciarochi, Hans J. Johnson, Jeffrey D. Long, Henry Jeremy Bockholt, Vincent A. Magnotta, Jane S. Paulsen, Vince D. Calhoun
2017 conf
PETRA
Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Yoan Miché, Hans J. Johnson, Amaury Lendasse
2017 B conf
Image Processing
Sungmin Hong, James Fishbaugh, Morteza Rezanejad, Kaleem Siddiqi, Hans J. Johnson, Jane S. Paulsen, Eun Young Kim, Guido Gerig
2016 J jnl
Frontiers Neuroinformatics
Jessica L. Forbes, Regina E. Y. Kim, Jane S. Paulsen, Hans J. Johnson
2016 conf
ISBI
Prasanna Muralidharan, James Fishbaugh, Eun Young Kim, Hans J. Johnson, Jane S. Paulsen, Guido Gerig, P. Thomas Fletcher
2016 conf
Biomedical Applications in Molecular, Structural, and Functional Imaging
Mohammad Saleh Miri, Ali Ghayoor, Hans J. Johnson, Milan Sonka
2016 conf
CVPR Workshops
Wei Shao, Gary E. Christensen, Hans J. Johnson, Joo Hyun Song, Oguz C. Durumeric, Casey P. Johnson, Joseph J. Shaffer, Vincent A. Magnotta, Jess G. Fiedorowicz, John A. Wemmie
2016 B conf
Image Processing
Ali Ghayoor, Jane S. Paulsen, Regina E. Y. Kim, Hans J. Johnson
2015 conf
CLIP@MICCAI
Regina E. Y. Kim, Peg Nopoulos, Jane S. Paulsen, Hans J. Johnson
2015 J jnl
Frontiers Neuroinformatics
Brian B. Avants, Hans J. Johnson, Nicholas J. Tustison
2014 J jnl
NeuroImage
Daniel Kostro, Ahmed Abdulkadir, Alexandra Durr, Raymund Roos, Blair R. Leavitt, Hans J. Johnson, David M. Cash, Sarah J. Tabrizi, Rachael I. Scahill, Olaf Ronneberger, Stefan Klöppel
2014 J jnl
Frontiers Neuroinformatics
Ipek Oguz, Mahshid Farzinfar, Joy T. Matsui, François Budin, Zhexing Liu, Guido Gerig, Hans J. Johnson, Martin Andreas Styner
2014 conf
MICCAI (3)
Prasanna Muralidharan, James Fishbaugh, Hans J. Johnson, Stanley Durrleman, Jane S. Paulsen, Guido Gerig, P. Thomas Fletcher
2013 B conf
Image Processing
Ali Ghayoor, Jatin G. Vaidya, Hans J. Johnson
2013 J jnl
Frontiers Neuroinformatics
Eun Young Kim, Hans J. Johnson
2013 B conf
Image Processing
Audrey R. Verde, Jean-Baptiste Berger, Aditya Gupta, Mahshid Farzinfar, Adrien Kaiser, Vicki W. Chanon, Charlotte A. Boettiger, Hans J. Johnson, Joy T. Matsui, Anuja Sharma, Casey Goodlett, Yundi Shi, Hongtu Zhu, Guido Gerig, Sylvain Gouttard, Clement Vachet, Martin Styner
2013 J jnl
Frontiers Neuroinformatics
Audrey R. Verde, François Budin, Jean-Baptiste Berger, Aditya Gupta, Mahshid Farzinfar, Adrien Kaiser, Mihye Ahn, Hans J. Johnson, Joy T. Matsui, Heather Cody Hazlett, Anuja Sharma, Casey Goodlett, Yundi Shi, Sylvain Gouttard, Clement Vachet, Joseph Piven, Hongtu Zhu, Guido Gerig, Martin Andreas Styner
2012 conf
WBIR
Brian B. Avants, Nicholas J. Tustison, Gang Song, Baohua Wu, Michael Stauffer, Matthew McCormick, Hans J. Johnson, James C. Gee
2012 J jnl
Brain Connect.
Vincent Magnotta, Joy T. Matsui, Dawei Liu, Hans J. Johnson, Jeffrey D. Long, Bradley D. Bolster Jr., Bryon A. Mueller, Kelvin O. Lim, Susumu Mori, Karl G. Helmer, Jessica A. Turner, Sarah A. J. Reading, Mark J. Lowe, Elizabeth H. Aylward, Laura A. Flashman, Greg Bonett, Jane S. Paulsen
2011 J jnl
NeuroImage
Ronald Pierson, Hans J. Johnson, Gregory Harris, Helen Keefe, Jane S. Paulsen, Nancy Andreasen, Vincent Magnotta
2010 B conf
Image Processing
Eun Young Kim, Hans J. Johnson
2009 B conf
Image Processing
Ronald Pierson, Gregory Harris, Hans J. Johnson, Steve Dunn, Vincent A. Magnotta
2008 J jnl
NeuroImage
Stephanie Powell, Vincent Magnotta, Hans J. Johnson, Vamsi K. Jammalamadaka, Ronald Pierson, Nancy Andreasen
2006 B conf
Image Processing
Stephanie Powell, Vincent Magnotta, Hans J. Johnson, Nancy Andreasen
2006 J jnl
NeuroImage
Gary E. Christensen, Hans J. Johnson, Michael W. Vannier
2003 J jnl
J. Electronic Imaging
Gary E. Christensen, Hans J. Johnson
2003 J jnl
IEEE Trans. Medical Imaging
Pierre Hellier, Christian Barillot, Isabelle Corouge, Bernard Gibaud, Georges Le Goualher, D. Louis Collins, Alan C. Evans, Grégoire Malandain, Nicholas Ayache, Gary E. Christensen, Hans J. Johnson
2003 J jnl
NeuroImage
Vincent A. Magnotta, Henry Jeremy Bockholt, Hans J. Johnson, Gary E. Christensen, Nancy C. Andreasen
2002 J jnl
IEEE Trans. Medical Imaging
Hans J. Johnson, Gary E. Christensen
2001 J jnl
IEEE Trans. Medical Imaging
Gary E. Christensen, Hans J. Johnson
2001 B conf
Image Processing
Blake L. Carlson, Gary E. Christensen, Hans J. Johnson, Michael W. Vannier
2001 conf
IPMI
Hans J. Johnson, Gary E. Christensen
2000 B conf
Image Processing
Hans J. Johnson, Gary E. Christensen, Jeffrey L. Marsh, Michael W. Vannier
1999 B conf
Image Processing
Gary E. Christensen, Hans J. Johnson, Tron A. Darvann, Nuno V. Hermann, Jeffrey L. Marsh
1999 B conf
Image Processing
Gary E. Christensen, Hans J. Johnson, John W. Haller, Jenny Melloy, Michael W. Vannier, Jeffrey L. Marsh
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()