zat 0.3.4

Bro Analysis Tools

## Bro Analysis Tools (BAT) [](https://travis-ci.org/SuperCowPowers/bat) [](https://coveralls.io/github/SuperCowPowers/bat?branch=master) [](https://pypi.python.org/pypi/bat) [](https://choosealicense.com/licenses/apache-2.0)


The BAT Python package supports the processing and analysis of Bro data
with Pandas, scikit-learn, and Spark

## BroCon 2017 Presentation

Data Analysis, Machine Learning, Bro, and You!
([Video](https://www.youtube.com/watch?v=pG5lU9CLnIU))

## Why BAT?

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.

### Example: Pull in Bro Logs as Python Dictionaries

```python
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'}
...

### Example: Bro log to Pandas DataFrame (in one line of code)

```python
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
```

## More Examples

- 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](https://bat-tools.readthedocs.io/en/latest/examples.html)
for more details.

## Analysis Notebooks

BAT enables the processing, analysis, and machine learning of realtime
data coming from Bro.

- Bro to Scikit-Learn: [Bro to
Scikit](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Scikit_Learn.ipynb)
- Bro to Matplotlib: [Bro to
Plot](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Plot.ipynb)
- Bro to Parquet to Spark:
[Bro->Parquet->Spark](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Parquet_to_Spark.ipynb)
- Bro to Kafka to Spark:
[Bro->Kafka->Spark](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Bro_to_Kafka_to_Spark.ipynb)
- Clustering: Picking K (or not): [Clustering K
Hyperparameter](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Clustering_Picking_K.ipynb)
- Anomaly Detection Exploration: [Anomaly
Detection](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Anomaly_Detection.ipynb)
- Risky Domains Stats and Deployment: [Risky
Domains](https://nbviewer.jupyter.org/github/SuperCowPowers/bat/blob/master/notebooks/Risky_Domains.ipynb)

Install
-------

$ pip install bat

Documentation
-------------

[bat-tools.readthedocs.org](https://bat-tools.readthedocs.org/)

Thanks
------

- The DummyEncoder is based on Tom Augspurger's great PyData Chicago
2016 [Talk](https://youtu.be/KLPtEBokqQ0)

[](https://www.kitware.com)