198 lines
7.9 KiB
Python
198 lines
7.9 KiB
Python
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#!/usr/bin/env python
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# Elasticsearch Recon Ingestion Scripts (ERIS) - Developed by Acidvegas (https://git.acid.vegas/eris)
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# HTTPX Log File Ingestion:
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#
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# This script takes JSON formatted HTTPX logs and indexes them into Elasticsearch.
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#
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# Saving my "typical" HTTPX command here for reference to myself:
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# httpx -l zone.org.txt -t 200 -r nameservers.txt -sc -location -favicon -title -bp -td -ip -cname -mc 200 -stream -sd -j -o output.json -v
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import argparse
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import json
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import logging
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import os
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try:
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from elasticsearch import Elasticsearch, helpers
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except ImportError:
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raise ImportError('Missing required \'elasticsearch\' library. (pip install elasticsearch)')
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# Setting up logging
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', datefmt='%m/%d %I:%M:%S')
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class ElasticIndexer:
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def __init__(self, es_host: str, es_port: str, es_user: str, es_password: str, es_api_key: str, es_index: str, dry_run: bool = False, self_signed: bool = False):
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'''
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Initialize the Elastic Search indexer.
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:param es_host: Elasticsearch host
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:param es_port: Elasticsearch port
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:param es_user: Elasticsearch username
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:param es_password: Elasticsearch password
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:param es_api_key: Elasticsearch API Key
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:param es_index: Elasticsearch index name
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:param dry_run: If True, do not initialize Elasticsearch client
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:param self_signed: If True, do not verify SSL certificates
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'''
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self.dry_run = dry_run
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self.es = None
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self.es_index = es_index
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if not dry_run:
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if es_api_key:
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self.es = Elasticsearch([f'{es_host}:{es_port}'], headers={'Authorization': f'ApiKey {es_api_key}'}, verify_certs=self_signed, ssl_show_warn=self_signed)
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else:
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self.es = Elasticsearch([f'{es_host}:{es_port}'], basic_auth=(es_user, es_password), verify_certs=self_signed, ssl_show_warn=self_signed)
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def process_file(self, file_path: str, batch_size: int):
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'''
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Read and index HTTPX records in batches to Elasticsearch, handling large volumes efficiently.
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:param file_path: Path to the HTTPX log file
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:param batch_size: Number of records to process before indexing
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Example record:
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{
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"timestamp":"2024-01-14T13:08:15.117348474-05:00", # Rename to seen and remove milliseconds and offset
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"hash": {
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"body_md5":"4ae9394eb98233b482508cbda3b33a66",
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"body_mmh3":"-4111954",
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"body_sha256":"89e06e8374353469c65adb227b158b265641b424fba7ddb2c67eef0c4c1280d3",
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"body_simhash":"9814303593401624250",
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"header_md5":"980366deb2b2fb5df2ad861fc63e79ce",
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"header_mmh3":"-813072798",
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"header_sha256":"39aea75ad548e38b635421861641ad1919ed3b103b17a33c41e7ad46516f736d",
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"header_simhash":"10962523587435277678"
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},
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"port":"443",
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"url":"https://supernets.org",
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"input":"supernets.org", # rename to domain
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"title":"SuperNETs",
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"scheme":"https",
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"webserver":"nginx",
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"body_preview":"SUPERNETS Home About Contact Donate Docs Network IRC Git Invidious Jitsi LibreX Mastodon Matrix Sup",
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"content_type":"text/html",
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"method":"GET",
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"host":"51.89.151.158",
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"path":"/",
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"favicon":"-674048714",
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"favicon_path":"/i/favicon.png",
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"time":"592.907689ms",
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"a":[
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"51.89.151.158",
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"2001:41d0:801:2000::5ce9"
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],
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"tech":[
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"Bootstrap:4.0.0",
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"HSTS",
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"Nginx"
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],
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"words":436,
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"lines":79,
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"status_code":200,
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"content_length":4597,
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"failed":false,
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"knowledgebase":{
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"PageType":"nonerror",
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"pHash":0
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}
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}
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'''
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records = []
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with open(file_path, 'r') as file:
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for line in file:
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line = line.strip()
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if not line:
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continue
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record = json.loads(line)
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record['seen'] = record.pop('timestamp').split('.')[0] + 'Z' # Hacky solution to maintain ISO 8601 format without milliseconds or offsets
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record['domain'] = record.pop('input')
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del record['failed'], record['knowledgebase'], record['time']
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if self.dry_run:
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print(record)
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else:
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record = {'_index': self.es_index, '_source': record}
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records.append(record)
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if len(records) >= batch_size:
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success, _ = helpers.bulk(self.es, records)
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logging.info(f'Successfully indexed {success} records to {self.es_index}')
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records = []
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if records:
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success, _ = helpers.bulk(self.es, records)
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logging.info(f'Successfully indexed {success} records to {self.es_index}')
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def main():
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'''Main function when running this script directly.'''
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parser = argparse.ArgumentParser(description='Index data into Elasticsearch.')
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parser.add_argument('input_path', help='Path to the input file or directory')
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# General arguments
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parser.add_argument('--dry-run', action='store_true', help='Dry run (do not index records to Elasticsearch)')
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parser.add_argument('--batch_size', type=int, default=50000, help='Number of records to index in a batch')
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# Elasticsearch connection arguments
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parser.add_argument('--host', default='localhost', help='Elasticsearch host')
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parser.add_argument('--port', type=int, default=9200, help='Elasticsearch port')
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parser.add_argument('--user', default='elastic', help='Elasticsearch username')
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parser.add_argument('--password', default=os.getenv('ES_PASSWORD'), help='Elasticsearch password (if not provided, check environment variable ES_PASSWORD)')
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parser.add_argument('--api-key', help='Elasticsearch API Key for authentication')
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parser.add_argument('--self-signed', action='store_false', help='Elasticsearch is using self-signed certificates')
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# Elasticsearch indexing arguments
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parser.add_argument('--index', default='zone-files', help='Elasticsearch index name')
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parser.add_argument('--shards', type=int, default=1, help='Number of shards for the index')
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parser.add_argument('--replicas', type=int, default=1, help='Number of replicas for the index')
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args = parser.parse_args()
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if not os.path.exists(args.input_path):
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raise FileNotFoundError(f'Input file {args.input_path} does not exist')
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if not args.dry_run:
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if args.batch_size < 1:
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raise ValueError('Batch size must be greater than 0')
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if not args.host:
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raise ValueError('Missing required Elasticsearch argument: host')
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if not args.api_key and (not args.user or not args.password):
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raise ValueError('Missing required Elasticsearch argument: either user and password or apikey')
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edx = ElasticIndexer(args.host, args.port, args.user, args.password, args.api_key, args.index, args.dry_run, args.self_signed)
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if os.path.isfile(args.input_path):
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logging.info(f'Processing file: {args.input_path}')
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edx.process_file(args.input_path, args.batch_size)
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elif os.path.isdir(args.input_path):
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logging.info(f'Processing files in directory: {args.input_path}')
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for file in sorted(os.listdir(args.input_path)):
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file_path = os.path.join(args.input_path, file)
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if os.path.isfile(file_path):
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logging.info(f'Processing file: {file_path}')
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edx.process_file(file_path, args.batch_size)
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else:
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raise ValueError(f'Input path {args.input_path} is not a file or directory')
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if __name__ == '__main__':
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main()
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