Ole Andreas Alsos

36 papers A* 2A 1B 2C 1Misc 3Journal 11Unranked 16
YearRankTypeTitle / Venue / Authors
2026 conf
HRI Companion
Vedran Simic, Eleftherios Papachristos, Ole Andreas Alsos, Taufik Akbar Sitompul
2026 J jnl
Int. J. Hum. Comput. Interact.
Yngve Dahl, Ole Andreas Alsos, Sofie Margrethe Bjørnå, Ingrid Medalen, Dag Svanæs
2026 A* conf
CHI
Felix-Marcel Petermann, Ole Andreas Alsos, Mina Saghafian, Erik Veitch, Grace Winifred Turner, Maria Letizia Potenza
2025 J jnl
Frontiers Virtual Real.
Attila Bekkvik Szentirmai, Ole Andreas Alsos, Anne Britt Torkildsby, Yavuz Inal
2025 J jnl
CoRR
Kim Alexander Christensen, Andreas Gudahl Tufte, Alexey Gusev, Rohan Sinha, Milan Ganai, Ole Andreas Alsos, Marco Pavone, Martin Steinert
2025 conf
INTERACT (1)
Felix-Marcel Petermann, Ole Andreas Alsos
2025 A* conf
CHI
Ole Andreas Alsos, Mina Saghafian, Erik Veitch, Taufik Akbar Sitompul, Felix Petermann, Eleftherios Papachristos
2025 conf
VRCAI
Henrik Viken Lied, Taufik Akbar Sitompul, Ole Andreas Alsos
2024 J jnl
Reliab. Eng. Syst. Saf.
Tingting Cheng, Erik Veitch, Ingrid Bouwer Utne, Marilia Abílio Ramos, Ali Mosleh, Ole Andreas Alsos, Bing Wu
2024 J jnl
Comput. Support. Cooperative Work.
Erik Veitch, Henrikke Dybvik, Martin Steinert, Ole Andreas Alsos
2024 J jnl
Frontiers Virtual Real.
Emanuel A. Lorenz, Andreas Bråten Støen, Magnus Lie Fridheim, Ole Andreas Alsos
2024 conf
HCI (14)
Attila Bekkvik Szentirmai, Yavuz Inal, Anne Britt Torkildsby, Ole Andreas Alsos
2023 conf
INTERACT Workshops (1)
Taufik Akbar Sitompul, Jooyoung Park, Ole Andreas Alsos
2023 A conf
Conference on Designing Interactive Systems
Vedran Simic, Ole Andreas Alsos
2023 B conf
SMC
Taufik Akbar Sitompul, Jooyoung Park, Ole Andreas Alsos
2022 J jnl
CoRR
Vilde B. Gjærum, Inga Strümke, Ole Andreas Alsos, Anastasios M. Lekkas
2021 J jnl
Int. J. Serious Games
Marikken Høiseth, Ole Andreas Alsos, Sindre Holme, Sondre Ek, Charlotte Tendenes Gabrielsen
2020 conf
HCI (2)
Kasper Rise, Ole Andreas Alsos
2020 conf
IDC (Extended Abstracts)
Marikken Høiseth, Sindre Holme, Sondre Ek, Charlotte Tendenes Gabrielsen, Ole Andreas Alsos
2020 conf
HCI (2)
Kasper Rise, Ole Andreas Alsos
2020 Misc conf
NordiCHI
Ole Andreas Alsos, Saara Kauppi
2015 C conf
ICEC
Anne Berit Kigen Bjering, Marikken Høiseth, Ole Andreas Alsos
2015 conf
Make2Learn@ICEC
Ole Andreas Alsos
2013 Misc conf
IDC
Marikken Høiseth, Michail N. Giannakos, Ole Andreas Alsos, Letizia Jaccheri, Jonas Asheim
2012 J jnl
Int. J. Medical Informatics
Ole Andreas Alsos, Anita Das, Dag Svanæs
2011 conf
INTERACT (4)
Ole Andreas Alsos, Dag Svanæs
2010 conf
I-UxSED
Ole Andreas Alsos
2010 conf
PervasiveHealth
Ole Andreas Alsos, Benjamin Dabelow
2010 J jnl
Int. J. Hum. Comput. Interact.
Yngve Dahl, Ole Andreas Alsos, Dag Svanæs
2010 J jnl
Int. J. Medical Informatics
Dag Svanæs, Ole Andreas Alsos, Yngve Dahl
2009 conf
HCI (1)
Yngve Dahl, Ole Andreas Alsos, Dag Svanæs
2009 B conf
ARES
Lillian Røstad, Ole Andreas Alsos
2008 conf
MIE
Ole Andreas Alsos
2008 conf
Business Process Management Workshops
Øystein Nytrø, Inger Dybdahl Sørby, Ole Andreas Alsos
2008 conf
MIE
Dag Svanæs, Anita Das, Ole Andreas Alsos
2008 Misc conf
NordiCHI
Ole Andreas Alsos, Yngve Dahl
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()