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