A Python package to fake SOC (Security Operations Center) data
soc-faker is used to generate fake data for use by Security Operation Centers, Information security professionals, product teams, and many more.
soc-faker is compatible with Python 2.x and 3.x. You can install
pip as well as cloning this repository directly.
At the time of writing this document,
soc-faker has the ability to fake data for the following main categories. You can find specific details for each category by selecting the links below:
- Operating System
- User Agent
pip install soc-faker --user
Installing from source
git clone https://github.com/swimlane/soc-faker.git cd soc-faker python setup.py install
The following libraries are required and installed by soc-faker
requests==2.23.0 pendulum==2.1.2 ipaddress==1.0.23 bs4==0.0.1 lxml==4.5.1 xmltodict==0.12.0 netaddr==0.7.20 fire==0.3.1
soc-faker is a Python package that can be imported or be used via the command line utility to generate fake data related to security tools, products, and general data related to security.
After you have installed
soc-faker from source or using
pip you can import and instantiate it by doing the following:
from socfaker import SocFaker sc = SocFaker()
Once you have instantiated an instance of
soc-faker you can then access any of the different properties and methods avaialble based on your needs. If you would like to see soc-faker in action, then please see the bin/test.py script in the repository under the
bin folder for an example of all avaialble properties and methods.
Additionally, please read the documentation for more details about each avaialble property and method.
soc-faker is installed, it automatically creates a command-line utility for your use. This utility can be accessed by simply typing
soc-faker in your shell of choice.
soc-faker help type:
soc-faker # or soc-faker --help
You can access each property just like you can from the library, the only difference is you replace a
. between properties with a space. For example, if you wanted to get some randomly generated
hashes quickly you can run:
soc-faker file hashes
This will return the following to your shell:
md5: aa3150ac34ee6a5911e61ab6a5052a6d sha1: de5c15f64d979ed84bac340c334a63d94401059d sha256: 118a9f9de8f3dd6471ef113959485ecbaf66368dea16758eab4e22da182d0e9f
If you run into any issues, just type what you think is correct and the built-in help will guide you through all available groups, commands, etc. for each data point within
You can use the provided Dockerfile to get a development and testing environment up and running for
To use the
Dockerfile run, cd to this repositories directory and run:
docker build --force-rm -t socfaker .
Once it is built, then run the docker container:
docker run -p 7001:7001 -ti socfaker
Running this will call the test python file in bin\test.py. Modify this file for additional testing and development.
Running the tests
Tests within this project should cover all available properties and methods. As this project grows the tests will become more robust but for now we are testing that they exist and return outputs.
- carcass - Python packaging template
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
We use SemVer for versioning.
Please read CHANGELOG.md for details on features for a specific version of
- Josh Rickard - Initial work - MSAdministrator
- Nick Tausek
See also the list of contributors who participated in this project.
This project is licensed under the MIT License - see the LICENSE file for details
soc-faker is a Swimlane open-source project; we believe in giving back to the open-source community by sharing some of the projects we build for our application. Swimlane is an automated cyber security operations and incident response platform that enables cyber security teams to leverage threat intelligence, speed up incident response and automate security operations.
SecOps Hub is an open, product-agnostic, online community for security professionals to share ideas, use cases, best practices, and incident response strategies.
- This project utilizes data from the OSSEM project by hunters-forge
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