eris/ingestors/ingest_massdns.py

344 lines
13 KiB
Python

#!/usr/bin/env python
# Elasticsearch Recon Ingestion Scripts (ERIS) - Developed by Acidvegas (https://git.acid.vegas/eris)
# Massdns Log File Ingestion:
#
# This script takes JSON formatted massdns logs and indexes them into Elasticsearch.
#
# Saving my "typical" massdns command here for reference to myself:
# python $HOME/massdns/scripts/ptr.py | massdns -r $HOME/massdns/nameservers.txt -t PTR --filter NOERROR -o J -w $HOME/massdns/ptr.json
import argparse
import logging
import os
import time
try:
from elasticsearch import Elasticsearch, helpers
import sniff_patch
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: int, es_user: str, es_password: str, es_api_key: str, es_index: str, dry_run: bool = False, self_signed: bool = False, retries: int = 10, timeout: int = 30):
'''
Initialize the Elastic Search indexer.
:param es_host: Elasticsearch host(s)
: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
:param retries: Number of times to retry indexing a batch before failing
:param timeout: Number of seconds to wait before retrying a batch
'''
self.dry_run = dry_run
self.es = None
self.es_index = es_index
if not dry_run:
es_config = {
'hosts': [f'{es_host}:{es_port}'],
'verify_certs': self_signed,
'ssl_show_warn': self_signed,
'request_timeout': timeout,
'max_retries': retries,
'retry_on_timeout': True,
'sniff_on_start': False,
'sniff_on_node_failure': True,
'min_delay_between_sniffing': 60
}
if es_api_key:
es_config['headers'] = {'Authorization': f'ApiKey {es_api_key}'}
else:
es_config['basic_auth'] = (es_user, es_password)
#self.es = Elasticsearch(**es_config)
self.es = sniff_patch.init_elasticsearch(**es_config)
def create_index(self, shards: int = 1, replicas: int = 1):
'''Create the Elasticsearch index with the defined mapping.'''
mapping = {
'settings': {
'number_of_shards': shards,
'number_of_replicas': replicas
},
'mappings': {
'properties': {
'ip': { 'type': 'ip' },
'name': { 'type': 'keyword' },
'record': { 'type': 'text', 'fields': { 'keyword': { 'type': 'keyword', 'ignore_above': 256 } } },
'seen': { 'type': 'date' }
}
}
}
if not self.es.indices.exists(index=self.es_index):
response = self.es.indices.create(index=self.es_index, body=mapping)
if response.get('acknowledged') and response.get('shards_acknowledged'):
logging.info(f'Index \'{self.es_index}\' successfully created.')
else:
raise Exception(f'Failed to create index. ({response})')
else:
logging.warning(f'Index \'{self.es_index}\' already exists.')
def get_cluster_size(self) -> int:
'''Get the number of nodes in the Elasticsearch cluster.'''
cluster_stats = self.es.cluster.stats()
number_of_nodes = cluster_stats['nodes']['count']['total']
return number_of_nodes
def process_file(self, file_path: str, watch: bool = False, chunk: dict = {}):
'''
Read and index PTR records in batches to Elasticsearch, handling large volumes efficiently.
:param file_path: Path to the PTR log file
:param batch_size: Number of records to process before indexing
Example PTR record:
0.6.229.47.in-addr.arpa. PTR 047-229-006-000.res.spectrum.com.
0.6.228.75.in-addr.arpa. PTR 0.sub-75-228-6.myvzw.com.
0.6.207.73.in-addr.arpa. PTR c-73-207-6-0.hsd1.ga.comcast.net.
0.6.212.173.in-addr.arpa. PTR 173-212-6-0.cpe.surry.net.
0.6.201.133.in-addr.arpa. PTR flh2-133-201-6-0.tky.mesh.ad.jp.
Will be indexed as:
{
"ip": "47.229.6.0",
"record": "047-229-006-000.res.spectrum.com.",
"seen": "2021-06-30T18:31:00Z"
}
'''
count = 0
records = []
with open(file_path, 'r') as file:
for line in (file := follow(file) if watch else file):
line = line.strip()
if not line:
continue
parts = line.split()
if len(parts) < 3:
raise ValueError(f'Invalid PTR record: {line}')
name, record_type, data = parts[0].rstrip('.'), parts[1], ' '.join(parts[2:]).rstrip('.')
if record_type != 'PTR':
continue
# Let's not index the PTR record if it's the same as the in-addr.arpa domain
if data == name:
continue
ip = '.'.join(name.replace('.in-addr.arpa', '').split('.')[::-1])
source = {
'ip': ip,
'record': data,
'seen': time.strftime('%Y-%m-%dT%H:%M:%SZ', time.gmtime())
}
if self.dry_run:
print(source)
else:
struct = {'_index': self.es_index, '_source': source}
records.append(struct)
count += 1
if len(records) >= chunk['batch']:
self.bulk_index(records, file_path, chunk, count)
records = []
if records:
self.bulk_index(records, file_path, chunk, count)
def bulk_index(self, documents: list, file_path: str, chunk: dict, count: int):
'''
Index a batch of documents to Elasticsearch.
:param documents: List of documents to index
:param file_path: Path to the file being indexed
:param count: Total number of records processed
'''
remaining_documents = documents
parallel_bulk_config = {
'client': self.es,
'chunk_size': chunk['size'],
'max_chunk_bytes': chunk['max_size'] * 1024 * 1024, # MB
'thread_count': chunk['threads'],
'queue_size': 2
}
while remaining_documents:
failed_documents = []
try:
for success, response in helpers.parallel_bulk(actions=remaining_documents, **parallel_bulk_config):
if not success:
failed_documents.append(response)
if not failed_documents:
ingested = parallel_bulk_config['chunk_size'] * parallel_bulk_config['thread_count']
logging.info(f'Successfully indexed {ingested:,} ({count:,} processed) records to {self.es_index} from {file_path}')
break
else:
logging.warning(f'Failed to index {len(failed_documents):,} failed documents! Retrying...')
remaining_documents = failed_documents
except Exception as e:
logging.error(f'Failed to index documents! ({e})')
time.sleep(30)
def follow(file) -> str:
'''
Generator function that yields new lines in a file in real time.
:param file: File object to read from
'''
file.seek(0,2) # Go to the end of the file
while True:
line = file.readline()
if not line:
time.sleep(0.1)
continue
yield line
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('--watch', action='store_true', help='Watch the input file for new lines and index them in real time')
# Elasticsearch 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='ptr-records', 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')
# Batch arguments (for fine tuning performance)
parser.add_argument('--batch-max', type=int, default=10, help='Maximum size in MB of a batch')
parser.add_argument('--batch-size', type=int, default=5000, help='Number of records to index in a batch')
parser.add_argument('--batch-threads', type=int, default=2, help='Number of threads to use when indexing in batches')
# NOTE: Using --batch-threads as 4 and --batch-size as 10000 means we will process 40,000 records per-node before indexing, so 3 nodes would process 120,000 records before indexing
# Elasticsearch retry arguments
parser.add_argument('--retries', type=int, default=10, help='Number of times to retry indexing a batch before failing')
parser.add_argument('--timeout', type=int, default=30, help='Number of seconds to wait before retrying a batch')
args = parser.parse_args()
if not os.path.exists(args.input_path):
raise FileNotFoundError(f'Input file {args.input_path} does not exist')
elif not os.path.isdir(args.input_path) and not os.path.isfile(args.input_path):
raise ValueError(f'Input path {args.input_path} is not a file or directory')
if not args.dry_run:
if args.batch_size < 1:
raise ValueError('Batch size must be greater than 0')
elif args.retries < 1:
raise ValueError('Number of retries must be greater than 0')
elif args.timeout < 5:
raise ValueError('Timeout must be greater than 4')
elif args.batch_max < 1:
raise ValueError('Batch max size must be greater than 0')
elif args.batch_threads < 1:
raise ValueError('Batch threads must be greater than 0')
elif not args.host:
raise ValueError('Missing required Elasticsearch argument: host')
elif not args.api_key and (not args.user or not args.password):
raise ValueError('Missing required Elasticsearch argument: either user and password or apikey')
elif args.shards < 1:
raise ValueError('Number of shards must be greater than 0')
elif args.replicas < 0:
raise ValueError('Number of replicas must be greater than 0')
edx = ElasticIndexer(args.host, args.port, args.user, args.password, args.api_key, args.index, args.dry_run, args.self_signed, args.retries, args.timeout)
if not args.dry_run:
time.sleep(5) # Delay to allow time for sniffing to complete
nodes = edx.get_cluster_size()
logging.info(f'Connected to {nodes:,} Elasticsearch node(s)')
edx.create_index(args.shards, args.replicas) # Create the index if it does not exist
chunk = {
'size': args.batch_size,
'max_size': args.batch_max * 1024 * 1024,
'threads': args.batch_threads
}
chunk['batch'] = nodes * (chunk['size'] * chunk['threads'])
else:
chunk = {} # Ugly hack to get this working...
if os.path.isfile(args.input_path):
logging.info(f'Processing file: {args.input_path}')
edx.process_file(args.input_path, args.watch, chunk)
elif os.path.isdir(args.input_path):
count = 1
total = len(os.listdir(args.input_path))
logging.info(f'Processing {total:,} 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'[{count:,}/{total:,}] Processing file: {file_path}')
edx.process_file(file_path, args.watch, chunk)
count += 1
else:
logging.warning(f'[{count:,}/{total:,}] Skipping non-file: {file_path}')
if __name__ == '__main__':
main()