Skip to main content

MSTIC Notebooklets

Project description

Notebooklets

Notebooklets are reusable Jupyter notebook code patterns for InfoSec investigators and hunters.

Notebook Authoring issues

Notebook authors face several issues:

  • Code in one notebook cannot easily be reused in other notebooks
  • Code cannot easily be unit tested
  • Updating notebooks that have already been distributed to users is hard.

Notebooklets Goals

The goals for MSTIC notebooklets are:

  • Enable re-use of common notebook patterns
  • Allow unit testing of code blocks
  • Speed up authoring of new notebooks
  • Allow update of notebooklets code for fixes and enhancement
  • Support multiple data platforms

Installing

pip install msticnb

Usage

Import and initialize the notebooklets

import msticnb as nb
nb.init()

Run a Notebooklet

from msticnb.common import TimeSpan
tm_span = TimeSpan(period="7d")  # end defaults to utcnow()
host_summary = nb.nblts.azsent.host.HostSummary()
host_summary_rslt = host_summary.run(value="myhost", timespan=tm_span)

Get Help

nb.nblts.azsent.host.HostSummary.show_help()

and of course, standard Python help also works as expected

help(host_summary)
help(host_summary.run)

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

msticnb-0.0.1.tar.gz (34.5 kB view details)

Uploaded Source

Built Distribution

msticnb-0.0.1-py3-none-any.whl (47.9 kB view details)

Uploaded Python 3

File details

Details for the file msticnb-0.0.1.tar.gz.

File metadata

  • Download URL: msticnb-0.0.1.tar.gz
  • Upload date:
  • Size: 34.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1.post20200616 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.6.10

File hashes

Hashes for msticnb-0.0.1.tar.gz
Algorithm Hash digest
SHA256 a54fa7ccaefe02f8a154ba7aaf25ddc102955e1dae42005f347e97d30142f7c4
MD5 b842955fd5702e14a880557bc5120960
BLAKE2b-256 3cfe6afa30de00e9dc87baa47ccfcdff93729ebfb2b8f18ab2a445fa93078aca

See more details on using hashes here.

File details

Details for the file msticnb-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: msticnb-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 47.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.3.1.post20200616 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.6.10

File hashes

Hashes for msticnb-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 daae1bba23932d458f64c4d17c7c4c81331199b622c3bcfccca2209a9e277aec
MD5 bb56cbbd416b2c0ebd840a4b2ee43b58
BLAKE2b-256 b57fa7172db3ceb8a5265859a9c074656880b8cb1c71948bd2a3af6c88fca51b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page