Cem Keskin

75 papers A* 25A 1B 1Journal 32Unranked 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Zhenyu Li, Sai Kumar Dwivedi, Filip Maric, Carlos Chacón, Nadine Bertsch, Filippo Arcadu, Tomas Hodan, Michael Ramamonjisoa, Peter Wonka, Amy Zhao, Robin Kips, Cem Keskin, Anastasia Tkach, Chenhongyi Yang
2025 A* conf
CVPR
Kefan Chen, Chaerin Min, Linguang Zhang, Shreyas Hampali, Cem Keskin, Srinath Sridhar
2025 J jnl
CoRR
Zhengdi Yu, Simone Foti, Linguang Zhang, Amy Zhao, Cem Keskin, Stefanos Zafeiriou, Tolga Birdal
2025 J jnl
CoRR
van Nguyen Nguyen, Christian Forster, Sindi Shkodrani, Vincent Lepetit, Bugra Tekin, Cem Keskin, Tomas Hodan
2025 J jnl
CoRR
Zicong Fan, Edoardo Remelli, David Dimond, Fadime Sener, Liuhao Ge, Bugra Tekin, Cem Keskin, Shreyas Hampali
2024 J jnl
CoRR
Chenhongyi Yang, Anastasia Tkach, Shreyas Hampali, Linguang Zhang, Elliot J. Crowley, Cem Keskin
2024 conf
ECCV (55)
Chenhongyi Yang, Anastasia Tkach, Shreyas Hampali, Linguang Zhang, Elliot J. Crowley, Cem Keskin
2024 J jnl
CoRR
Kefan Chen, Chaerin Min, Linguang Zhang, Shreyas Hampali, Cem Keskin, Srinath Sridhar
2024 conf
ECCV (26)
Evin Pinar Örnek, Yann Labbé, Bugra Tekin, Lingni Ma, Cem Keskin, Christian Forster, Tomas Hodan
2023 A* conf
CVPR
Takehiko Ohkawa, Kun He, Fadime Sener, Tomas Hodan, Luan Tran, Cem Keskin
2023 J jnl
CoRR
Takehiko Ohkawa, Kun He, Fadime Sener, Tomas Hodan, Luan Tran, Cem Keskin
2023 J jnl
CoRR
Evin Pinar Örnek, Yann Labbé, Bugra Tekin, Lingni Ma, Cem Keskin, Christian Forster, Tomas Hodan
2023 A* conf
CVPR
Shreyas Hampali, Tomas Hodan, Luan Tran, Lingni Ma, Cem Keskin, Vincent Lepetit
2023 A* conf
ICCV
Mathias Parger, Chengcheng Tang, Thomas Neff, Christopher D. Twigg, Cem Keskin, Robert Wang, Markus Steinberger
2023 A conf
WACV
Qi Feng, Kun He, He Wen, Cem Keskin, Yuting Ye
2023 A* conf
ICCV
Julian Tanke, Linguang Zhang, Amy Zhao, Chengcheng Tang, Yujun Cai, Lezi Wang, Po-Chen Wu, Juergen Gall, Cem Keskin
2022 A* conf
CVPR
Mathias Parger, Chengcheng Tang, Christopher D. Twigg, Cem Keskin, Robert Wang, Markus Steinberger
2022 J jnl
CoRR
Mathias Parger, Chengcheng Tang, Christopher D. Twigg, Cem Keskin, Robert Y. Wang, Markus Steinberger
2022 A* conf
AAAI
Utku Evci, Yani Ioannou, Cem Keskin, Yann N. Dauphin
2022 J jnl
CoRR
Shreyas Hampali, Tomas Hodan, Luan Tran, Lingni Ma, Cem Keskin, Vincent Lepetit
2022 J jnl
CoRR
Mathias Parger, Chengcheng Tang, Thomas Neff, Christopher D. Twigg, Cem Keskin, Robert Wang, Markus Steinberger
2022 A* conf
NeurIPS
Zhixuan Yu, Linguang Zhang, Yuanlu Xu, Chengcheng Tang, Luan Tran, Cem Keskin, Hyun Soo Park
2022 conf
ECCV (10)
Lin Huang, Tomas Hodan, Lingni Ma, Linguang Zhang, Luan Tran, Christopher D. Twigg, Po-Chen Wu, Junsong Yuan, Cem Keskin, Robert Wang
2022 J jnl
CoRR
Lin Huang, Tomas Hodan, Lingni Ma, Linguang Zhang, Luan Tran, Christopher D. Twigg, Po-Chen Wu, Junsong Yuan, Cem Keskin, Robert Wang
2022 A* conf
SIGGRAPH Asia
Shangchen Han, Po-Chen Wu, Yubo Zhang, Beibei Liu, Linguang Zhang, Zheng Wang, Weiguang Si, Peizhao Zhang, Yujun Cai, Tomas Hodan, Randi Cabezas, Luan Tran, Muzaffer Akbay, Tsz-Ho Yu, Cem Keskin, Robert Wang
2022 J jnl
CoRR
Shangchen Han, Po-Chen Wu, Yubo Zhang, Beibei Liu, Linguang Zhang, Zheng Wang, Weiguang Si, Peizhao Zhang, Yujun Cai, Tomas Hodan, Randi Cabezas, Luan Tran, Muzaffer Akbay, Tsz-Ho Yu, Cem Keskin, Robert Wang
2021 J jnl
CoRR
Qi Feng, Kun He, He Wen, Cem Keskin, Yuting Ye
2021 J jnl
CoRR
Albert Ryou, James Whitehead, Maksym Zhelyeznyakov, Paul Anderson, Cem Keskin, Michal Bajcsy, Arka Majumdar
2021 A* conf
CVPR
Feitong Tan, Danhang Tang, Mingsong Dou, Kaiwen Guo, Rohit Pandey, Cem Keskin, Ruofei Du, Deqing Sun, Sofien Bouaziz, Sean Ryan Fanello, Ping Tan, Yinda Zhang
2021 J jnl
CoRR
Feitong Tan, Danhang Tang, Mingsong Dou, Kaiwen Guo, Rohit Pandey, Cem Keskin, Ruofei Du, Deqing Sun, Sofien Bouaziz, Sean Ryan Fanello, Ping Tan, Yinda Zhang
2021 A* conf
ICCV
Zhang Chen, Yinda Zhang, Kyle Genova, Sean Ryan Fanello, Sofien Bouaziz, Christian Häne, Ruofei Du, Cem Keskin, Thomas A. Funkhouser, Danhang Tang
2021 J jnl
CoRR
Zhang Chen, Yinda Zhang, Kyle Genova, Sean Ryan Fanello, Sofien Bouaziz, Christian Häne, Ruofei Du, Cem Keskin, Thomas A. Funkhouser, Danhang Tang
2020 A* conf
CVPR
Danhang Tang, Saurabh Singh, Philip A. Chou, Christian Häne, Mingsong Dou, Sean Ryan Fanello, Jonathan Taylor, Philip Davidson, Onur G. Guleryuz, Yinda Zhang, Shahram Izadi, Andrea Tagliasacchi, Sofien Bouaziz, Cem Keskin
2020 J jnl
CoRR
Danhang Tang, Saurabh Singh, Philip A. Chou, Christian Häne, Mingsong Dou, Sean Ryan Fanello, Jonathan Taylor, Philip Davidson, Onur G. Guleryuz, Yinda Zhang, Shahram Izadi, Andrea Tagliasacchi, Sofien Bouaziz, Cem Keskin
2020 J jnl
CoRR
Utku Evci, Yani Andrew Ioannou, Cem Keskin, Yann N. Dauphin
2020 J jnl
CoRR
Hossam N. Isack, Christian Häne, Cem Keskin, Sofien Bouaziz, Yuri Boykov, Shahram Izadi, Sameh Khamis
2019 J jnl
IEEE Trans. Pattern Anal. Mach. Intell.
Danhang Tang, Qi Ye, Shanxin Yuan, Jonathan Taylor, Pushmeet Kohli, Cem Keskin, Tae-Kyun Kim, Jamie Shotton
2019 A* conf
CVPR
Rohit Pandey, Anastasia Tkach, Shuoran Yang, Pavel Pidlypenskyi, Jonathan Taylor, Ricardo Martin-Brualla, Andrea Tagliasacchi, George Papandreou, Philip Davidson, Cem Keskin, Shahram Izadi, Sean Ryan Fanello
2019 J jnl
CoRR
Rohit Pandey, Anastasia Tkach, Shuoran Yang, Pavel Pidlypenskyi, Jonathan Taylor, Ricardo Martin-Brualla, Andrea Tagliasacchi, George Papandreou, Philip Davidson, Cem Keskin, Shahram Izadi, Sean Ryan Fanello
2018 B conf
ICPR
Ufuk Can Biçici, Cem Keskin, Lale Akarun
2018 J jnl
CoRR
Ufuk Can Biçici, Cem Keskin, Lale Akarun
2018 J jnl
CoRR
Ricardo Martin-Brualla, Rohit Pandey, Shuoran Yang, Pavel Pidlypenskyi, Jonathan Taylor, Julien P. C. Valentin, Sameh Khamis, Philip Davidson, Anastasia Tkach, Peter Lincoln, Adarsh Kowdle, Christoph Rhemann, Dan B. Goldman, Cem Keskin, Steven M. Seitz, Shahram Izadi, Sean Ryan Fanello
2018 J jnl
ACM Trans. Graph.
Danhang Tang, Mingsong Dou, Peter Lincoln, Philip Davidson, Kaiwen Guo, Jonathan Taylor, Sean Ryan Fanello, Cem Keskin, Adarsh Kowdle, Sofien Bouaziz, Shahram Izadi, Andrea Tagliasacchi
2018 A* conf
NeurIPS
Cem Keskin, Shahram Izadi
2018 J jnl
CoRR
Cem Keskin, Shahram Izadi
2018 J jnl
ACM Trans. Graph.
Adarsh Kowdle, Christoph Rhemann, Sean Ryan Fanello, Andrea Tagliasacchi, Jonathan Taylor, Philip Davidson, Mingsong Dou, Kaiwen Guo, Cem Keskin, Sameh Khamis, David Kim, Danhang Tang, Vladimir Tankovich, Julien P. C. Valentin, Shahram Izadi
2017 J jnl
ACM Trans. Graph.
Jonathan Taylor, Vladimir Tankovich, Danhang Tang, Cem Keskin, David Kim, Philip Davidson, Adarsh Kowdle, Shahram Izadi
2017
Cem Keskin
2016 J jnl
ACM Trans. Graph.
Jonathan Taylor, Lucas Bordeaux, Thomas J. Cashman, Bob Corish, Cem Keskin, Toby Sharp, Eduardo Soto, David Sweeney, Julien P. C. Valentin, Benjamin Luff, Arran Topalian, Erroll Wood, Sameh Khamis, Pushmeet Kohli, Shahram Izadi, Richard Banks, Andrew W. Fitzgibbon, Jamie Shotton
2016 A* conf
UIST
Sergio Orts-Escolano, Christoph Rhemann, Sean Ryan Fanello, Wayne Chang, Adarsh Kowdle, Yury Degtyarev, David Kim, Philip Davidson, Sameh Khamis, Mingsong Dou, Vladimir Tankovich, Charles T. Loop, Qin Cai, Philip A. Chou, Sarah Mennicken, Julien P. C. Valentin, Vivek Pradeep, Shenlong Wang, Sing Bing Kang, Pushmeet Kohli, Yuliya Lutchyn, Cem Keskin, Shahram Izadi
2016 conf
3DV
Julien P. C. Valentin, Angela Dai, Matthias Nießner, Pushmeet Kohli, Philip H. S. Torr, Shahram Izadi, Cem Keskin
2016 J jnl
CoRR
Julien P. C. Valentin, Angela Dai, Matthias Nießner, Pushmeet Kohli, Philip H. S. Torr, Shahram Izadi, Cem Keskin
2015 A* conf
CHI
Toby Sharp, Cem Keskin, Duncan P. Robertson, Jonathan Taylor, Jamie Shotton, David Kim, Christoph Rhemann, Ido Leichter, Alon Vinnikov, Yichen Wei, Daniel Freedman, Pushmeet Kohli, Eyal Krupka, Andrew W. Fitzgibbon, Shahram Izadi
2015 A* conf
CVPR
Mohammad Rastegari, Cem Keskin, Pushmeet Kohli, Shahram Izadi
2015 A* conf
CVPR
Sameh Khamis, Jonathan Taylor, Jamie Shotton, Cem Keskin, Shahram Izadi, Andrew W. Fitzgibbon
2015 A* conf
ICCV
Danhang Tang, Jonathan Taylor, Pushmeet Kohli, Cem Keskin, Tae-Kyun Kim, Jamie Shotton
2014 A* conf
CHI
Mathieu Le Goc, Stuart Taylor, Shahram Izadi, Cem Keskin
2014 A* conf
CVPR
Sean Ryan Fanello, Cem Keskin, Pushmeet Kohli, Shahram Izadi, Jamie Shotton, Antonio Criminisi, Ugo Pattacini, Tim Paek
2014 A* conf
UIST
Jie Song, Gábor Sörös, Fabrizio Pece, Sean Ryan Fanello, Shahram Izadi, Cem Keskin, Otmar Hilliges
2014 J jnl
ACM Trans. Graph.
Sean Ryan Fanello, Cem Keskin, Shahram Izadi, Pushmeet Kohli, David Kim, David Sweeney, Antonio Criminisi, Jamie Shotton, Sing Bing Kang, Tim Paek
2014 conf
3DV
Vahid Kazemi, Cem Keskin, Jonathan Taylor, Pushmeet Kohli, Shahram Izadi
2014 A* conf
CHI
David Kim, Shahram Izadi, Jakub Dostal, Christoph Rhemann, Cem Keskin, Christopher Zach, Jamie Shotton, Timothy A. Large, Steven Bathiche, Matthias Nießner, D. Alex Butler, Sean Ryan Fanello, Vivek Pradeep
2014 A* conf
CHI
Stuart Taylor, Cem Keskin, Otmar Hilliges, Shahram Izadi, John Helmes
2014 A* conf
CVPR
Jonathan Taylor, Richard V. Stebbing, Varun Ramakrishna, Cem Keskin, Jamie Shotton, Shahram Izadi, Aaron Hertzmann, Andrew W. Fitzgibbon
2013 ch.
Consumer Depth Cameras for Computer Vision
Cem Keskin, Furkan Kiraç, Yunus Emre Kara, Lale Akarun
2012 conf
SIU
Cem Keskin, Furkan Kiraç, Yunus Emre Kara, Lale Akarun
2012 conf
SIU
Furkan Kiraç, Yunus Emre Kara, Cem Keskin, Lale Akarun
2012 conf
ECCV (6)
Cem Keskin, Furkan Kiraç, Yunus Emre Kara, Lale Akarun
2012 conf
CVPR Workshops
Cem Keskin, Furkan Kiraç, Yunus Emre Kara, Lale Akarun
2011 conf
HBU
Cem Keskin, Ali Taylan Cemgil, Lale Akarun
2011 ch.
Computer Analysis of Human Behavior
Cem Keskin, Oya Aran, Lale Akarun
2011 conf
ICCV Workshops
Cem Keskin, Furkan Kiraç, Yunus Emre Kara, Lale Akarun
2009 J jnl
Pattern Recognit. Lett.
Cem Keskin, Lale Akarun
2005 conf
EUSIPCO
Cem Keskin, Oya Aran, Lale Akarun
2005 conf
EUSIPCO
Oya Aran, Cem Keskin, Lale Akarun
redb/extractors/ioc_extractor/standalone_ioc_extractor.py
← Index redb/extractors/ioc_extractor/standalone_ioc_extractor.py python
#!/usr/bin/env python3
"""
Standalone IOC Extractor for REDB Analysis Pipeline

This is a single-file IOC extraction script that can be called from the
analysis backend after Binary Ninja processing completes.

Dependencies:
    - clickhouse-connect (pip install clickhouse-connect)
    - python-dotenv (pip install python-dotenv)
    - Python 3.9+

Usage:
    # Extract IOCs for a single sample (uses .env for ClickHouse connection)
    python standalone_ioc_extractor.py --sha256 <hash>

    # Specify custom .env file
    python standalone_ioc_extractor.py --sha256 <hash> --env-file /path/to/.env

    # Override connection settings
    python standalone_ioc_extractor.py --sha256 <hash> --host ch.example.com --port 8123

    # Force re-extraction (delete existing IOCs first)
    python standalone_ioc_extractor.py --sha256 <hash> --force

    # Programmatic usage:
    from standalone_ioc_extractor import IOCExtractor
    extractor = IOCExtractor()  # Uses .env by default
    ioc_count = extractor.extract_for_sample("sha256_hash_here")

Required files:
    - iana_tlds.txt: Place in same directory as this script, or specify with --tld-file
    - .env file with CLICKHOUSE_* variables (or pass connection params directly)

Environment variables (from .env):
    CLICKHOUSE_HOST (default: localhost)
    CLICKHOUSE_PORT (default: 8123)
    CLICKHOUSE_USER (default: default)
    CLICKHOUSE_PASSWORD (default: empty)
    CLICKHOUSE_DATABASE (default: redb)

Based on IOC scraper patterns from Synapse (https://github.com/vertexproject/synapse)
"""

import os
import re
import argparse
import ipaddress
import logging
from pathlib import Path
from datetime import datetime
from dataclasses import dataclass
from enum import Enum
from typing import List, Set, Tuple, Generator, Optional

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s [%(levelname)s] %(message)s',
    datefmt='%Y-%m-%d %H:%M:%S'
)
logger = logging.getLogger(__name__)


# =============================================================================
# Enums and Data Classes
# =============================================================================

class IOCType(str, Enum):
    """IOC types matching ClickHouse Enum8 values"""
    IPV4 = 'ipv4'
    IPV6 = 'ipv6'
    FQDN = 'fqdn'
    URL = 'url'
    EMAIL = 'email'
    SERVER = 'server'
    HASH_MD5 = 'hash_md5'
    HASH_SHA1 = 'hash_sha1'
    HASH_SHA256 = 'hash_sha256'
    CVE = 'cve'
    CWE = 'cwe'
    CPE = 'cpe'
    CRYPTO_BTC = 'crypto_btc'
    CRYPTO_ETH = 'crypto_eth'
    CRYPTO_XRP = 'crypto_xrp'
    CRYPTO_BCH = 'crypto_bch'
    CRYPTO_ADA = 'crypto_ada'
    CRYPTO_SUBSTRATE = 'crypto_substrate'
    PATH_LINUX = 'path_linux'
    PATH_WINDOWS = 'path_windows'
    REGISTRY_KEY = 'registry_key'
    ONION = 'onion'


class SourceType(str, Enum):
    """Source types matching ClickHouse Enum8 values"""
    DECOMPILED_FUNCTION = 'decompiled_function'
    DISASSEMBLED_FUNCTION = 'disassembled_function'
    STRING = 'string'
    # Universal text-based artefact surfaces (JS today; PowerShell, Python,
    # email, extracted PDF/Office text in the future). The frontend reads
    # `redb_basic_properties.filetype_magika` to render the right per-format
    # view, the same translation pattern APK uses for `decompiled_function`.
    TEXT_RAW = 'text_raw'
    TEXT_NORMALIZED = 'text_normalized'


@dataclass
class ExtractedIOC:
    """Represents an extracted IOC"""
    ioc_type: IOCType
    ioc_value: str
    source_type: SourceType
    source_identifier: str


# =============================================================================
# TLD Loading
# =============================================================================

def load_tld_list(tld_file: Optional[Path] = None) -> str:
    """Load TLD list and build regex alternation pattern."""
    if tld_file is None:
        tld_file = Path(__file__).parent / 'iana_tlds.txt'

    tlds = []
    try:
        with open(tld_file, 'r') as f:
            for line in f:
                line = line.strip().lower()
                if not line or line.startswith('#'):
                    continue
                tlds.append(line)
    except FileNotFoundError:
        logger.warning(f"TLD file not found at {tld_file}, using fallback list")
        tlds = ['com', 'net', 'org', 'edu', 'gov', 'mil', 'io', 'co', 'info',
                'biz', 'me', 'tv', 'cc', 'uk', 'de', 'fr', 'ru', 'cn', 'jp',
                'br', 'au', 'in', 'link', 'taxi']

    # Add special TLDs used in malware
    tlds.extend(['onion', 'bit', 'bazar'])
    tlds.sort(key=len, reverse=True)

    return '(?:' + '|'.join(re.escape(tld) for tld in tlds) + ')'


# =============================================================================
# Regex Patterns
# =============================================================================

# IPv4
IPV4_OCTET = r'(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)'
IPV4_PATTERN = re.compile(
    rf'(?<![0-9.])({IPV4_OCTET}\.{IPV4_OCTET}\.{IPV4_OCTET}\.{IPV4_OCTET})(?![0-9.])',
    re.ASCII
)

# IPv6
IPV6_PATTERN = re.compile(
    r'(?<![0-9a-fA-F:])('
    r'(?:[0-9a-fA-F]{1,4}:){7}[0-9a-fA-F]{1,4}|'
    r'(?:[0-9a-fA-F]{1,4}:){1,7}:|'
    r'(?:[0-9a-fA-F]{1,4}:){1,6}:[0-9a-fA-F]{1,4}|'
    r'(?:[0-9a-fA-F]{1,4}:){1,5}(?::[0-9a-fA-F]{1,4}){1,2}|'
    r'(?:[0-9a-fA-F]{1,4}:){1,4}(?::[0-9a-fA-F]{1,4}){1,3}|'
    r'(?:[0-9a-fA-F]{1,4}:){1,3}(?::[0-9a-fA-F]{1,4}){1,4}|'
    r'(?:[0-9a-fA-F]{1,4}:){1,2}(?::[0-9a-fA-F]{1,4}){1,5}|'
    r'[0-9a-fA-F]{1,4}:(?::[0-9a-fA-F]{1,4}){1,6}|'
    r':(?::[0-9a-fA-F]{1,4}){1,7}|'
    r'::(?:[fF]{4}:)?(?:' + IPV4_OCTET + r'\.){3}' + IPV4_OCTET + r'|'
    r'(?:[0-9a-fA-F]{1,4}:){1,4}:(?:' + IPV4_OCTET + r'\.){3}' + IPV4_OCTET +
    r')(?![0-9a-fA-F:])',
    re.ASCII
)

# URL
URL_SCHEMES = r'(?:https?|ftp|ftps|sftp|file|smb|ssh|telnet|ldap|ldaps)'
URL_PATTERN = re.compile(
    rf'({URL_SCHEMES}://[^\s<>\"\'\)\]\}},;]+)',
    re.IGNORECASE
)

# Defanging patterns
DEFANG_PATTERNS = [
    (re.compile(r'hxxps?://', re.IGNORECASE), lambda m: m.group().lower().replace('xx', 'tt')),
    (re.compile(r'\[\.?\]'), '.'),
    (re.compile(r'\[\s*dot\s*\]', re.IGNORECASE), '.'),
    (re.compile(r'\[\s*at\s*\]', re.IGNORECASE), '@'),
    (re.compile(r'\(\.\)'), '.'),
    (re.compile(r'\[:\]'), ':'),
]

# Email
EMAIL_PATTERN = re.compile(
    r'(?<![a-zA-Z0-9._%+-])([a-zA-Z0-9._%+-]{1,64}@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,})(?![a-zA-Z0-9_])',
    re.ASCII
)

# Server (IP:port)
SERVER_PATTERN = re.compile(
    rf'({IPV4_OCTET}\.{IPV4_OCTET}\.{IPV4_OCTET}\.{IPV4_OCTET}):(\d{{1,5}})',
    re.ASCII
)

# .onion
ONION_PATTERN = re.compile(
    r'(?<![a-zA-Z0-9.-])([a-z2-7]{16}(?:[a-z2-7]{40})?\.onion)(?![a-zA-Z0-9.-])',
    re.IGNORECASE
)

# Hashes
MD5_PATTERN = re.compile(r'(?<![A-Za-z0-9])([a-fA-F0-9]{32})(?![A-Za-z0-9])', re.ASCII)
SHA1_PATTERN = re.compile(r'(?<![A-Za-z0-9])([a-fA-F0-9]{40})(?![A-Za-z0-9])', re.ASCII)
SHA256_PATTERN = re.compile(r'(?<![A-Za-z0-9])([a-fA-F0-9]{64})(?![A-Za-z0-9])', re.ASCII)

# CVE/CWE/CPE
CVE_PATTERN = re.compile(
    r'(?i)(CVE[-\u2010\u2011\u2012\u2013\u2014\u2015](?:19|20)\d{2}[-\u2010\u2011\u2012\u2013\u2014\u2015]\d{4,7})',
    re.UNICODE
)
CWE_PATTERN = re.compile(r'(?i)(CWE-\d{1,8})')
CPE_PATTERN = re.compile(
    r'(cpe:2\.3:[aho\*\-](?::[a-zA-Z0-9\*\-._~%!$&\'()+,;=]*){10})',
    re.IGNORECASE
)

# Cryptocurrency
BASE58_CHARSET = r'a-zA-HJ-NP-Z0-9'
BECH32_CHARSET = r'qpzry9x8gf2tvdw0s3jn54khce6mua7l'

BTC_P2PKH_PATTERN = re.compile(rf'(?<![A-Za-z0-9])([1][{BASE58_CHARSET}]{{25,39}})(?![A-Za-z0-9])')
BTC_P2SH_PATTERN = re.compile(rf'(?<![A-Za-z0-9])(3[{BASE58_CHARSET}]{{33}})(?![A-Za-z0-9])')
BTC_BECH32_PATTERN = re.compile(
    rf'(?<![A-Za-z0-9])((bc|bcrt|tb)1[{BECH32_CHARSET}]{{3,71}})(?![A-Za-z0-9])',
    re.IGNORECASE
)
ETH_PATTERN = re.compile(r'(?<![A-Za-z0-9])(0x[A-Fa-f0-9]{40})(?![A-Fa-f0-9])')
XRP_PATTERN = re.compile(rf'(?<![A-Za-z0-9])([xr][{BASE58_CHARSET}]{{25,46}})(?![A-Za-z0-9])')
BCH_PATTERN = re.compile(
    rf'(?<![A-Za-z0-9])((bitcoincash|bchtest):[{BECH32_CHARSET}]{{42}})(?![A-Za-z0-9])',
    re.IGNORECASE
)
ADA_SHELLEY_PATTERN = re.compile(
    rf'(?<![A-Za-z0-9])(addr1[{BECH32_CHARSET}]{{53,}})(?![A-Za-z0-9])',
    re.IGNORECASE
)
ADA_BYRON_PATTERN = re.compile(
    rf'(?<![A-Za-z0-9])((DdzFF|Ae2td)[{BASE58_CHARSET}]{{54,99}})(?![A-Za-z0-9])'
)
SUBSTRATE_PATTERN = re.compile(
    rf'(?<![A-Za-z0-9])([1a-z][{BASE58_CHARSET}]{{46,47}})(?![A-Za-z0-9])'
)

# File paths
LINUX_PATH_PATTERN = re.compile(
    r'(?<![a-zA-Z0-9/])(/(?:bin|boot|dev|etc|home|lib|lib64|media|mnt|opt|proc|root|run|sbin|srv|sys|tmp|usr|var)/[^\s<>\"\'\)\]\}},;]{1,500})(?![a-zA-Z0-9/])'
)

# Windows path / registry key — both share separator and component grammar.
# Separator accepts 1 or 2 backslashes so paths embedded in source-code string
# literals (where `\` is escaped to `\\` — JS, JSON, PowerShell, etc.) match
# the same as runtime-form paths. `*` is permitted in components to capture
# wildcard patterns common in malware (e.g. C:\Users\*\AppData\Local\Temp).
#
# Two-tier component grammar:
#   _WIN_FIRST — strict (no whitespace, quote, separator, reserved-char) —
#     used as the first char of every segment so segments can't start with
#     a space or a quote that would let a path drift into prose
#   _WIN_INNER — permissive (allows internal whitespace) — used in the body
#     of *delimited* segments only (those followed by `\` or `\\`), so
#     `Program Files` matches between separators
# The final segment uses _WIN_FIRST throughout, so a path that runs into
# free text stops at the first whitespace instead of slurping the rest of
# the line. (e.g. "c:\users\admin\desktop and stuff" → "c:\users\admin\desktop".)
_WIN_SEP = r'\\{1,2}'
_WIN_FIRST = r"[^\\<>\"'`\?\|\s]"
# `_WIN_INNER` also excludes `:` to prevent two adjacent paths in free text
# from collapsing into one match — e.g. "From C:\one to D:\two" must not
# slurp ` to D:` into the body of segment 1. Colon-in-segment is rare in
# practice (only NTFS alternate data streams use it: `C:\file.txt:stream`).
_WIN_INNER = r"[^\\<>\"'`\?\|:]"
WINDOWS_PATH_PATTERN = re.compile(
    rf'(?<![a-zA-Z0-9\\])'
    rf'([a-zA-Z]:{_WIN_SEP}'
    rf'(?:{_WIN_FIRST}{_WIN_INNER}*{_WIN_SEP})*'
    rf'(?:{_WIN_FIRST}+)?'
    rf')(?![a-zA-Z0-9\\])',
    re.IGNORECASE
)
_REG_HIVE = (
    r'(?:HK(?:LM|CU|CR|U|CC|PD)'
    r'|HKEY_(?:LOCAL_MACHINE|CURRENT_USER|CLASSES_ROOT|USERS|CURRENT_CONFIG|PERFORMANCE_DATA))'
)
REGISTRY_KEY_PATTERN = re.compile(
    rf'(?<![A-Za-z0-9\\])'
    rf'({_REG_HIVE}{_WIN_SEP}'
    rf'(?:{_WIN_FIRST}{_WIN_INNER}*{_WIN_SEP})*'
    rf'{_WIN_FIRST}+'
    rf')(?![A-Za-z0-9\\])',
    re.IGNORECASE
)

# Exclusions
EXCLUDED_IPS = {
    '0.0.0.0', '127.0.0.1', '255.255.255.255',
    '1.0.0.0', '1.0.0.1', '1.1.1.1',
    '8.8.8.8', '8.8.4.4',
}
EXCLUDED_DOMAINS = {
    'example.com', 'example.org', 'example.net',
    'localhost', 'localhost.localdomain',
    'test.com', 'test.local',
}

# JS-context FQDN false-positive blocklists.
#
# When the scraper is constructed with `js_context=True`, FQDN candidates whose
# leftmost segment is in JS_FP_SLDS or whose TLD is in JS_FP_TLDS are rejected.
# Both lists target patterns that arise from JS object/property access syntax
# (`this.foo.bar`, `process.id`, `lib.so`, `Function.name`, ...) where the
# segment chain accidentally shape-matches a hostname. Without this filter
# typical samples produce ~80% FQDN false positives because new gTLDs include
# common JS property-name suffixes (`.name`, `.id`, `.so`, `.post`,
# `.services`, ...).
#
# Curated specifically for JS — APK suppresses FQDN entirely (smali class
# names produce orders-of-magnitude more dotted identifiers than JS source).
# Protocol prefixes (ftp, smtp, imap, pop3, http, https) are *not* in the SLD
# list so legitimate C2 hostnames like `ftp.evil.example.com` survive.
JS_FP_TLDS = frozenset({
    'name', 'id', 'so', 'post', 'services', 'tools', 'support',
    'today', 'email', 'page', 'site', 'click', 'link', 'tech',
    'systems', 'network',
})
JS_FP_SLDS = frozenset({
    # JS keywords / pseudo-globals
    'this', 'self', 'super', 'arguments', 'globalthis',
    # Common host objects
    'window', 'document', 'console', 'navigator', 'location', 'history',
    'screen', 'event',
    # Node / runtime globals
    'process', 'proc', 'module', 'exports', 'require', 'global', 'buffer',
    # Built-in constructors / prototypes that get used as property roots
    'function', 'func', 'object', 'array', 'string', 'number', 'boolean',
    'symbol', 'promise', 'map', 'set', 'date', 'regexp', 'error', 'json',
    'math', 'reflect', 'proxy', 'class', 'interface',
    # Framework / popular library roots
    'vue', 'react', 'angular', 'firebase', 'jquery', 'lodash', 'axios',
    'socket', 'express', 'fastify', 'koa', 'next', 'nuxt', 'svelte',
    'redux', 'mobx',
    # Browser-extension surfaces
    'chrome', 'browser', 'firefox', 'safari',
    # Generic code-shape identifiers that show up in malware-analysis text
    'system', 'lib', 'api', 'app', 'component', 'controller', 'service',
    'handler', 'manager', 'factory', 'builder', 'view', 'model', 'config',
    'option', 'param', 'arg', 'data', 'result', 'value', 'key', 'index',
    'count', 'size', 'length', 'type', 'kind', 'target', 'payload',
    'exploit', 'malware', 'sandbox', 'vm', 'thread', 'task', 'job',
    'worker', 'session', 'request', 'response', 'callback', 'listener',
    'observer', 'subscriber',
})


# =============================================================================
# IOC Scraper
# =============================================================================

class IOCScraper:
    """Scrapes IOCs from text content."""

    def __init__(
        self,
        tld_file: Optional[Path] = None,
        suppress_types: Optional[Set[IOCType]] = None,
        js_context: bool = False,
    ):
        self.tld_pattern = load_tld_list(tld_file)
        self.suppress_types: Set[IOCType] = suppress_types or set()
        # When True, FQDN validation additionally rejects candidates whose
        # leftmost segment is in JS_FP_SLDS or whose TLD is in JS_FP_TLDS, to
        # filter false positives from JS object-access syntax. Defaults to
        # False so non-JS callers behave identically to before.
        self.js_context: bool = js_context
        self.fqdn_pattern = re.compile(
            rf'(?<![a-zA-Z0-9_./:@\\-])([a-zA-Z0-9](?:[a-zA-Z0-9-]{{0,61}}[a-zA-Z0-9])?(?:\.[a-zA-Z0-9](?:[a-zA-Z0-9-]{{0,61}}[a-zA-Z0-9])?)*\.{self.tld_pattern})(?![a-zA-Z0-9_-])',
            re.IGNORECASE
        )

    def _defang_text(self, text: str) -> str:
        for pattern, replacement in DEFANG_PATTERNS:
            if callable(replacement):
                text = pattern.sub(replacement, text)
            else:
                text = pattern.sub(replacement, text)
        return text

    def _validate_ipv4(self, ip: str) -> bool:
        try:
            addr = ipaddress.IPv4Address(ip)
            if ip in EXCLUDED_IPS:
                return False
            if addr.is_private or addr.is_loopback or addr.is_reserved:
                return False
            return True
        except (ipaddress.AddressValueError, ValueError):
            return False

    def _validate_ipv6(self, ip: str) -> bool:
        try:
            addr = ipaddress.IPv6Address(ip)
            if addr.is_private or addr.is_loopback or addr.is_reserved:
                return False
            return True
        except (ipaddress.AddressValueError, ValueError):
            return False

    def _validate_hash(self, hash_value: str) -> bool:
        if len(set(hash_value.lower())) <= 2:
            return False
        if hash_value.lower() in {'0' * len(hash_value), 'f' * len(hash_value)}:
            return False
        return True

    def _validate_fqdn(self, fqdn: str) -> bool:
        fqdn_lower = fqdn.lower()
        if fqdn_lower in EXCLUDED_DOMAINS:
            return False
        parts = fqdn_lower.split('.')
        if all(part.isdigit() for part in parts[:-1]):
            return False
        # Reject FQDNs where the second-level domain is less than 3 characters
        # e.g. a.com, ab.com are rejected; abc.com and x.abc.com are accepted
        if len(parts) >= 2 and len(parts[-2]) < 3:
            return False
        # JS-context filter: reject candidates that are almost certainly JS
        # object-access syntax (`this.foo.bar`, `process.id`, `lib.so`,
        # `Component.name`) rather than real hostnames. The TLD check fires on
        # gTLDs that double as common JS property suffixes; the leftmost-
        # segment check fires on JS keywords / framework roots. Either one
        # alone is sufficient to reject. See JS_FP_TLDS / JS_FP_SLDS for the
        # rationale and the curated lists.
        if self.js_context:
            if parts[-1] in JS_FP_TLDS:
                return False
            if len(parts) >= 2 and parts[0] in JS_FP_SLDS:
                return False
        return True

    def _normalize_cve(self, cve: str) -> str:
        cve = re.sub(r'[\u2010\u2011\u2012\u2013\u2014\u2015]', '-', cve)
        return cve.upper()

    def scrape(
        self,
        text: str,
        source_type: SourceType,
        source_identifier: str
    ) -> Generator[ExtractedIOC, None, None]:
        """Scrape IOCs from text."""
        if not text:
            return

        text = self._defang_text(text)
        seen: Set[Tuple[IOCType, str]] = set()

        def emit(ioc_type: IOCType, value: str) -> Generator[ExtractedIOC, None, None]:
            key = (ioc_type, value.lower())
            if key not in seen:
                seen.add(key)
                yield ExtractedIOC(
                    ioc_type=ioc_type,
                    ioc_value=value,
                    source_type=source_type,
                    source_identifier=source_identifier
                )

        # URLs
        for match in URL_PATTERN.finditer(text):
            url = match.group(1).rstrip('.,;:')
            yield from emit(IOCType.URL, url)

        # Servers (IP:port)
        for match in SERVER_PATTERN.finditer(text):
            ip = match.group(1)
            port = int(match.group(2))
            if self._validate_ipv4(ip) and 1 <= port <= 65535:
                yield from emit(IOCType.SERVER, f"{ip}:{port}")

        # IPv4
        for match in IPV4_PATTERN.finditer(text):
            ip = match.group(1)
            if self._validate_ipv4(ip):
                yield from emit(IOCType.IPV4, ip)

        # IPv6
        for match in IPV6_PATTERN.finditer(text):
            ip = match.group(1)
            if self._validate_ipv6(ip):
                yield from emit(IOCType.IPV6, ip)

        # .onion
        for match in ONION_PATTERN.finditer(text):
            onion = match.group(1).lower()
            yield from emit(IOCType.ONION, onion)

        # FQDNs
        if IOCType.FQDN not in self.suppress_types:
            for match in self.fqdn_pattern.finditer(text):
                fqdn = match.group(1).lower()
                if self._validate_fqdn(fqdn) and not fqdn.endswith('.onion'):
                    yield from emit(IOCType.FQDN, fqdn)

        # Emails
        for match in EMAIL_PATTERN.finditer(text):
            email = match.group(1).lower()
            yield from emit(IOCType.EMAIL, email)

        # Hashes (SHA256 first)
        for match in SHA256_PATTERN.finditer(text):
            hash_val = match.group(1).lower()
            if self._validate_hash(hash_val):
                yield from emit(IOCType.HASH_SHA256, hash_val)

        for match in SHA1_PATTERN.finditer(text):
            hash_val = match.group(1).lower()
            if self._validate_hash(hash_val) and (IOCType.HASH_SHA256, hash_val) not in seen:
                yield from emit(IOCType.HASH_SHA1, hash_val)

        for match in MD5_PATTERN.finditer(text):
            hash_val = match.group(1).lower()
            if self._validate_hash(hash_val):
                if not any((IOCType.HASH_SHA1, h) in seen or (IOCType.HASH_SHA256, h) in seen
                           for h in [hash_val]):
                    yield from emit(IOCType.HASH_MD5, hash_val)

        # CVE/CWE/CPE
        for match in CVE_PATTERN.finditer(text):
            cve = self._normalize_cve(match.group(1))
            yield from emit(IOCType.CVE, cve)

        for match in CWE_PATTERN.finditer(text):
            cwe = match.group(1).upper()
            yield from emit(IOCType.CWE, cwe)

        for match in CPE_PATTERN.finditer(text):
            cpe = match.group(1).lower()
            yield from emit(IOCType.CPE, cpe)

        # Cryptocurrency
        for match in BTC_BECH32_PATTERN.finditer(text):
            addr = match.group(1).lower()
            yield from emit(IOCType.CRYPTO_BTC, addr)

        for match in BTC_P2PKH_PATTERN.finditer(text):
            yield from emit(IOCType.CRYPTO_BTC, match.group(1))

        for match in BTC_P2SH_PATTERN.finditer(text):
            yield from emit(IOCType.CRYPTO_BTC, match.group(1))

        for match in ETH_PATTERN.finditer(text):
            yield from emit(IOCType.CRYPTO_ETH, match.group(1).lower())

        for match in XRP_PATTERN.finditer(text):
            yield from emit(IOCType.CRYPTO_XRP, match.group(1))

        for match in BCH_PATTERN.finditer(text):
            yield from emit(IOCType.CRYPTO_BCH, match.group(1).lower())

        for match in ADA_SHELLEY_PATTERN.finditer(text):
            yield from emit(IOCType.CRYPTO_ADA, match.group(1).lower())

        for match in ADA_BYRON_PATTERN.finditer(text):
            yield from emit(IOCType.CRYPTO_ADA, match.group(1))

        for match in SUBSTRATE_PATTERN.finditer(text):
            addr = match.group(1)
            if any(c.isdigit() for c in addr) and len(addr) in (47, 48):
                yield from emit(IOCType.CRYPTO_SUBSTRATE, addr)

        # File paths
        for match in LINUX_PATH_PATTERN.finditer(text):
            path = match.group(1).rstrip('.,;:')
            yield from emit(IOCType.PATH_LINUX, path)

        for match in WINDOWS_PATH_PATTERN.finditer(text):
            # Normalise doubled backslashes (source-escaped form) to single so
            # `C:\\Users\\Public` and `C:\Users\Public` collapse to one IOC.
            path = match.group(1).rstrip('.,;:').replace('\\\\', '\\')
            yield from emit(IOCType.PATH_WINDOWS, path)

        # Windows registry keys — same normalisation as paths
        for match in REGISTRY_KEY_PATTERN.finditer(text):
            key = match.group(1).rstrip('.,;:').replace('\\\\', '\\')
            yield from emit(IOCType.REGISTRY_KEY, key)


# =============================================================================
# IOC Extractor (ClickHouse integration)
# =============================================================================

def load_env(env_file: Optional[Path] = None):
    """Load environment variables from .env file."""
    try:
        from dotenv import load_dotenv
    except ImportError:
        logger.warning("python-dotenv not installed, using environment variables only")
        return

    if env_file:
        load_dotenv(env_file)
    else:
        # Try common locations
        for path in [Path(".env"), Path(__file__).parent.parent.parent.parent / ".env"]:
            if path.exists():
                load_dotenv(path)
                logger.debug(f"Loaded environment from {path}")
                break


class IOCExtractor:
    """Extracts IOCs from ClickHouse data and stores results."""

    def __init__(
        self,
        host: Optional[str] = None,
        port: Optional[int] = None,
        user: Optional[str] = None,
        password: Optional[str] = None,
        database: Optional[str] = None,
        batch_size: int = 1000,
        tld_file: Optional[Path] = None,
        env_file: Optional[Path] = None,
        client=None
    ):
        """
        Initialize IOC Extractor.

        Connection parameters can be passed directly or loaded from environment:
            CLICKHOUSE_HOST, CLICKHOUSE_PORT, CLICKHOUSE_USER,
            CLICKHOUSE_PASSWORD, CLICKHOUSE_DATABASE

        Args:
            host: ClickHouse host (default: from env or localhost)
            port: ClickHouse port (default: from env or 8123)
            user: ClickHouse user (default: from env or default)
            password: ClickHouse password (default: from env or empty)
            database: ClickHouse database (default: from env or redb)
            batch_size: Batch size for processing
            tld_file: Path to TLD list file
            env_file: Path to .env file (default: auto-detect)
            client: Existing ClickHouse client (if provided, connection params are ignored)
        """
        # If existing client provided, use it directly
        if client is not None:
            self.client = client
            self.database = database or os.environ.get("CLICKHOUSE_DATABASE", "redb")
            logger.info(f"Using existing ClickHouse client, database={self.database}")
        else:
            # Create new connection
            try:
                import clickhouse_connect
            except ImportError:
                raise ImportError("clickhouse-connect is required. Install with: pip install clickhouse-connect")

            # Load .env file
            load_env(env_file)

            # Use passed values or fall back to environment variables
            host = host or os.environ.get("CLICKHOUSE_HOST", "localhost")
            port = port or int(os.environ.get("CLICKHOUSE_PORT", "8123"))
            user = user or os.environ.get("CLICKHOUSE_USER", "default")
            password = password if password is not None else os.environ.get("CLICKHOUSE_PASSWORD", "")
            database = database or os.environ.get("CLICKHOUSE_DATABASE", "redb")

            logger.info(f"Connecting to ClickHouse at {host}:{port}, database={database}")

            self.client = clickhouse_connect.get_client(
                host=host,
                port=port,
                username=user,
                password=password,
                database=database
            )
            self.database = database

        self.batch_size = batch_size
        self.scraper = IOCScraper(tld_file)
        self._insert_buffer: List[dict] = []

    def has_existing_iocs(self, sha256: str) -> bool:
        """Check if sample already has IOCs extracted."""
        result = self.client.query(
            f"SELECT 1 FROM {self.database}.redb_iocs WHERE sha256 = %(sha256)s LIMIT 1",
            parameters={"sha256": sha256}
        )
        return len(result.result_rows) > 0

    def delete_iocs_for_sample(self, sha256: str):
        """Delete existing IOCs for a sample."""
        self.client.command(
            f"ALTER TABLE {self.database}.redb_iocs DELETE WHERE sha256 = %(sha256)s",
            parameters={"sha256": sha256}
        )
        logger.info(f"Deleted existing IOCs for {sha256[:16]}...")

    def extract_for_sample(self, sha256: str, force: bool = False) -> int:
        """
        Extract IOCs for a single sample.

        Args:
            sha256: Sample SHA256 hash
            force: Delete existing IOCs and re-extract

        Returns:
            Number of IOCs extracted
        """
        if force:
            self.delete_iocs_for_sample(sha256)
        elif self.has_existing_iocs(sha256):
            logger.info(f"Skipping {sha256[:16]}... (already has IOCs)")
            return 0

        total_iocs = 0

        # Extract from strings
        strings_count = self._extract_from_strings(sha256)
        total_iocs += strings_count

        # Extract from decompiled functions
        functions_count = self._extract_from_decompiled(sha256)
        total_iocs += functions_count

        # Flush remaining buffer
        self._flush_buffer()

        logger.info(f"Extracted {total_iocs} IOCs for {sha256[:16]}... (strings: {strings_count}, functions: {functions_count})")
        return total_iocs

    def _extract_from_strings(self, sha256: str) -> int:
        """Extract IOCs from sample's strings."""
        count = 0
        offset = 0

        while True:
            result = self.client.query(
                f"""
                SELECT string, string_offset
                FROM {self.database}.code_binja_strings_by_binary
                WHERE sha256 = %(sha256)s
                ORDER BY string_offset
                LIMIT %(limit)s OFFSET %(offset)s
                """,
                parameters={"sha256": sha256, "limit": self.batch_size, "offset": offset}
            )

            if not result.result_rows:
                break

            for row in result.result_rows:
                string_value, string_offset = row
                if isinstance(string_value, bytes):
                    string_value = string_value.decode('utf-8', errors='replace')

                for ioc in self.scraper.scrape(string_value, SourceType.STRING, str(string_offset)):
                    self._buffer_insert(sha256, ioc)
                    count += 1

            offset += len(result.result_rows)

        return count

    def _extract_from_decompiled(self, sha256: str) -> int:
        """Extract IOCs from sample's decompiled functions."""
        count = 0

        # Get function hashes for this sample
        refs_result = self.client.query(
            f"""
            SELECT decompiled_function_hash
            FROM {self.database}.code_binja_decompiled_functions_references
            WHERE sha256 = %(sha256)s
            """,
            parameters={"sha256": sha256}
        )

        if not refs_result.result_rows:
            return 0

        function_hashes = [row[0] for row in refs_result.result_rows]
        if isinstance(function_hashes[0], bytes):
            function_hashes = [h.decode('utf-8') for h in function_hashes]

        # Process in batches
        for i in range(0, len(function_hashes), self.batch_size):
            batch_hashes = function_hashes[i:i + self.batch_size]

            # Get function content, excluding LIBRARY and THUNK types
            content_result = self.client.query(
                f"""
                SELECT decompiled_function_hash, decompiled_function
                FROM {self.database}.code_binja_decompiled_functions_content
                WHERE decompiled_function_hash IN %(hashes)s
                  AND function_type NOT IN ('LIBRARY', 'THUNK')
                """,
                parameters={"hashes": batch_hashes}
            )

            for row in content_result.result_rows:
                func_hash, func_content = row
                if isinstance(func_hash, bytes):
                    func_hash = func_hash.decode('utf-8')
                if isinstance(func_content, bytes):
                    func_content = func_content.decode('utf-8', errors='replace')

                for ioc in self.scraper.scrape(func_content, SourceType.DECOMPILED_FUNCTION, func_hash):
                    self._buffer_insert(sha256, ioc)
                    count += 1

        return count

    def _buffer_insert(self, sha256: str, ioc: ExtractedIOC):
        """Buffer an IOC for batch insert."""
        self._insert_buffer.append({
            "sha256": sha256,
            "ioc_type": ioc.ioc_type.value,
            "ioc_value": ioc.ioc_value,
            "source_type": ioc.source_type.value,
            "source_identifier": ioc.source_identifier,
            "extracted_at": datetime.utcnow()
        })

        if len(self._insert_buffer) >= self.batch_size:
            self._flush_buffer()

    def _flush_buffer(self):
        """Flush buffered IOCs to ClickHouse."""
        if not self._insert_buffer:
            return

        columns = ["sha256", "ioc_type", "ioc_value", "source_type", "source_identifier", "extracted_at"]
        data = [[row[col] for col in columns] for row in self._insert_buffer]

        self.client.insert(
            f"{self.database}.redb_iocs",
            data,
            column_names=columns
        )

        self._insert_buffer = []


# =============================================================================
# CLI
# =============================================================================

def main():
    parser = argparse.ArgumentParser(
        description="Extract IOCs from ClickHouse sample data",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog="""
Examples:
    # Extract IOCs for a sample (uses .env for connection)
    python standalone_ioc_extractor.py --sha256 abc123...

    # Force re-extraction
    python standalone_ioc_extractor.py --sha256 abc123... --force

    # Override connection settings from .env
    python standalone_ioc_extractor.py --sha256 abc123... --host ch.example.com

    # Use custom .env file
    python standalone_ioc_extractor.py --sha256 abc123... --env-file /path/to/.env
        """
    )
    parser.add_argument("--sha256", required=True, help="Sample SHA256 hash")
    parser.add_argument("--env-file", type=Path, help="Path to .env file (default: auto-detect)")
    parser.add_argument("--host", help="ClickHouse host (default: from .env or localhost)")
    parser.add_argument("--port", type=int, help="ClickHouse HTTP port (default: from .env or 8123)")
    parser.add_argument("--user", help="ClickHouse user (default: from .env or default)")
    parser.add_argument("--password", help="ClickHouse password (default: from .env or empty)")
    parser.add_argument("--database", help="ClickHouse database (default: from .env or redb)")
    parser.add_argument("--force", action="store_true", help="Force re-extraction (delete existing IOCs)")
    parser.add_argument("--tld-file", type=Path, help="Path to TLD list file (default: iana_tlds.txt in script directory)")
    parser.add_argument("--batch-size", type=int, default=1000, help="Batch size for processing (default: 1000)")

    args = parser.parse_args()

    extractor = IOCExtractor(
        host=args.host,
        port=args.port,
        user=args.user,
        password=args.password,
        database=args.database,
        batch_size=args.batch_size,
        tld_file=args.tld_file,
        env_file=args.env_file
    )

    ioc_count = extractor.extract_for_sample(args.sha256, force=args.force)
    print(f"Extracted {ioc_count} IOCs for {args.sha256[:16]}...")


if __name__ == "__main__":
    main()