The BAT Python package supports the processing and analysis of Bro data with Pandas, scikit-learn, and Spark
Data Analysis, Machine Learning, Bro, and You! (Video)
Bro already has a flexible, powerful scripting language why should I use BAT?
Offloading: Running complex tasks like statistics, state machines, machine learning, etc.. should be offloaded from Bro so that Bro can focus on the efficient processing of high volume network traffic.
Data Analysis: We have a large set of support classes that help bridge from raw Bro data to packages like Pandas, scikit-learn, and Spark. We also have example notebooks that show step-by-step how to get from here to there.
from bat import bro_log_reader
...
# Run the bro reader on a given log file
reader = bro_log_reader.BroLogReader('dhcp.log')
for row in reader.readrows():
pprint(row)
Output: Each row is a nice Python Dictionary with timestamps and types properly converted.
{'assigned_ip': '192.168.84.10',
'id.orig_h': '192.168.84.10',
'id.orig_p': 68,
'id.resp_h': '192.168.84.1',
'id.resp_p': 67,
'lease_time': datetime.timedelta(49710, 23000),
'mac': '00:20:18:eb:ca:54',
'trans_id': 495764278,
'ts': datetime.datetime(2012, 7, 20, 3, 14, 12, 219654),
'uid': 'CJsdG95nCNF1RXuN5'}
...
from bat.log_to_dataframe import LogToDataFrame
...
# Create a Pandas dataframe from a Bro log
bro_df = LogToDataFrame('/path/to/dns.log')
# Print out the head of the dataframe
print(bro_df.head())
Output: All the Bro log data is in a Pandas DataFrame with proper types and timestamp as the index
query id.orig_h id.orig_p id.resp_h
ts
2013-09-15 17:44:27.631940 guyspy.com 192.168.33.10 1030 4.2.2.3
2013-09-15 17:44:27.696869 www.guyspy.com 192.168.33.10 1030 4.2.2.3
2013-09-15 17:44:28.060639 devrubn8mli40.cloudfront.net 192.168.33.10 1030 4.2.2.3
2013-09-15 17:44:28.141795 d31qbv1cthcecs.cloudfront.net 192.168.33.10 1030 4.2.2.3
2013-09-15 17:44:28.422704 crl.entrust.net 192.168.33.10 1030 4.2.2.3
- Easy ingestion of any Bro Log into Python (dynamic tailing and log rotations are handled)
- Bro Logs to Pandas Dataframes and Scikit-Learn
- Dynamically monitor files.log and make VirusTotal Queries
- Dynamically monitor http.log and show 'uncommon' User Agents
- Running Yara Signatures on Extracted Files
- Checking x509 Certificates
- Anomaly Detection
- See BAT Examples for more details.
BAT enables the processing, analysis, and machine learning of realtime data coming from Bro.
- Bro to Scikit-Learn: Bro to Scikit
- Bro to Matplotlib: Bro to Plot
- Bro to Parquet to Spark: Bro->Parquet->Spark
- Bro to Kafka to Spark: Bro->Kafka->Spark
- Clustering: Picking K (or not): Clustering K Hyperparameter
- Anomaly Detection Exploration: Anomaly Detection
- Risky Domains Stats and Deployment: Risky Domains
$ pip install bat
- The DummyEncoder is based on Tom Augspurger's great PyData Chicago 2016 Talk