eris/ingestors/ingest_zone.py

154 lines
5.6 KiB
Python

#!/usr/bin/env python
# Elasticsearch Recon Ingestion Scripts (ERIS) - Developed by Acidvegas (https://git.acid.vegas/eris)
# ingest_zone.py
import time
try:
import aiofiles
except ImportError:
raise ImportError('Missing required \'aiofiles\' library. (pip install aiofiles)')
default_index = 'dns-zones'
record_types = ('a','aaaa','caa','cdnskey','cds','cname','dnskey','ds','mx','naptr','ns','nsec','nsec3','nsec3param','ptr','rrsig','rp','sshfp','soa','srv','txt','type65534')
def construct_map() -> dict:
'''Construct the Elasticsearch index mapping for zone file records.'''
keyword_mapping = { 'type': 'text', 'fields': { 'keyword': { 'type': 'keyword', 'ignore_above': 256 } } }
mapping = {
'mappings': {
'properties': {
'domain': keyword_mapping,
'records': { 'properties': {} },
'seen': {'type': 'date'}
}
}
}
# Add record types to mapping dynamically to not clutter the code
for item in record_types:
if item in ('a','aaaa'):
mapping['mappings']['properties']['records']['properties'][item] = {
'properties': {
'data': { 'type': 'ip' },
'ttl': { 'type': 'integer' }
}
}
else:
mapping['mappings']['properties']['records']['properties'][item] = {
'properties': {
'data': keyword_mapping,
'ttl': { 'type': 'integer' }
}
}
return mapping
async def process_data(file_path: str):
'''
Read and process zone file records.
:param file_path: Path to the zone file
'''
domain_records = {}
last_domain = None
async with aiofiles.open(file_path, mode='r') as input_file:
async for line in input_file:
line = line.strip()
if line == '~eof': # Sentinel value to indicate the end of a process (Used with --watch with FIFO)
break
if not line or line.startswith(';'):
continue
parts = line.split()
if len(parts) < 5:
raise ValueError(f'Invalid line: {line}')
domain, ttl, record_class, record_type, data = parts[0].rstrip('.').lower(), parts[1], parts[2].lower(), parts[3].lower(), ' '.join(parts[4:])
if not ttl.isdigit():
raise ValueError(f'Invalid TTL: {ttl} with line: {line}')
ttl = int(ttl)
# Anomaly...Doubtful any CHAOS/HESIOD records will be found in zone files
if record_class != 'in':
raise ValueError(f'Unsupported record class: {record_class} with line: {line}')
# We do not want to collide with our current mapping (Again, this is an anomaly)
if record_type not in record_types:
raise ValueError(f'Unsupported record type: {record_type} with line: {line}')
# Little tidying up for specific record types (removing trailing dots, etc)
if record_type == 'nsec':
data = ' '.join([data.split()[0].rstrip('.'), *data.split()[1:]])
elif record_type == 'soa':
data = ' '.join([part.rstrip('.') if '.' in part else part for part in data.split()])
elif data.endswith('.'):
data = data.rstrip('.')
if domain != last_domain:
if last_domain:
struct = {
'domain' : last_domain,
'records' : domain_records[last_domain],
'seen' : time.strftime('%Y-%m-%dT%H:%M:%SZ', time.gmtime()) # Zone files do not contain a timestamp, so we use the current time
}
del domain_records[last_domain]
yield {'_id': domain, '_index': default_index, '_source': struct} # Set the ID to the domain name to allow the record to be reindexed if it exists.
last_domain = domain
domain_records[domain] = {}
if record_type not in domain_records[domain]:
domain_records[domain][record_type] = []
domain_records[domain][record_type].append({'ttl': ttl, 'data': data})
'''
Example record:
0so9l9nrl425q3tf7dkv1nmv2r3is6vm.vegas. 3600 in nsec3 1 1 100 332539EE7F95C32A 10MHUKG4FHIAVEFDOTF6NKU5KFCB2J3A NS DS RRSIG
0so9l9nrl425q3tf7dkv1nmv2r3is6vm.vegas. 3600 in rrsig NSEC3 8 2 3600 20240122151947 20240101141947 4125 vegas. hzIvQrZIxBSwRWyiHkb5M2W0R3ikNehv884nilkvTt9DaJSDzDUrCtqwQb3jh6+BesByBqfMQK+L2n9c//ZSmD5/iPqxmTPCuYIB9uBV2qSNSNXxCY7uUt5w7hKUS68SLwOSjaQ8GRME9WQJhY6gck0f8TT24enjXXRnQC8QitY=
1-800-flowers.vegas. 3600 in ns dns1.cscdns.net.
1-800-flowers.vegas. 3600 in ns dns2.cscdns.net.
100.vegas. 3600 in ns ns51.domaincontrol.com.
100.vegas. 3600 in ns ns52.domaincontrol.com.
1001.vegas. 3600 in ns ns11.waterrockdigital.com.
1001.vegas. 3600 in ns ns12.waterrockdigital.com.
Will be indexed as:
{
"_id" : "1001.vegas"
"_index" : "dns-zones",
"_source" : {
"domain" : "1001.vegas",
"records" : { # All records are stored in a single dictionary
"ns": [
{"ttl": 3600, "data": "ns11.waterrockdigital.com"},
{"ttl": 3600, "data": "ns12.waterrockdigital.com"}
]
},
"seen" : "2021-09-01T00:00:00Z" # Zulu time added upon indexing
}
}
'''
'''
Notes:
- How do we want to handle hashed NSEC3 records? Do we ignest them as they are, or crack the NSEC3 hashes first and ingest?
'''