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msticnb - Notebooklets for Jupyter Notebooks
============================================

# Notebooklets - msticnb
msticnb is a companion package to
[msticpy](https://msticpy.readthedocs.io/en/latest/). It is designed to
be used in Jupyter notebooks by security operations engineers and analysts,
to give them quick access to
common notebook patterns such as retrieving summary information about
a host or IP address.

Notebooklets are reusable Jupyter notebook code patterns for InfoSec investigators
and hunters.
<img src="https://github.com/microsoft/msticnb/blob/master/docs/source/_static/msticnb-browser.png"
alt="Notebooklet browser showing list of notebooklets and some
details of the user documentation for the selected notebooklet."
title="Notebooklet browser" height="300" />

The msticnb package uses functionality from the
[msticpy](https://github.com/microsoft/msticpy) package. Each notebooklet collects
together multiple msticpy and custom code functions to automate specific scenarios
related to InfoSec hunting and investigation.

Each notebooklet can be invoked and run with a couple of lines of code and replaces
what would be many code cells and hundreds of lines of code in a typical Jupyter
notebook.
Each notebooklet is equivalent to multiple cells and many lines of code
in a traditional notebook. You can import and run a notebooklet with two
lines of code (or even 1 line, if you are impatient). Typically, the input
parameters to a notebooklet will be an identifier (e.g. a host name) and
a time range (over which to query data). Some notebooklets (primarily
packaged analytics) will take a pandas DataFrame as input.

# Motivation for msticnb
## Jupyter notebook authoring issues
```python
import msticnb as nb
nb.init(query_provider="AzureSentinel")
host_summary = nb.nblts.azsent.host.HostSummary()
host_sum_rslt = host_summary.run(
value="Msticalertswin1", timespan=time_span
)
```

You can create your own notebooklets and use them in the same framework
as the ones already in the package.

---

Notebooklets
------------

### What are notebooklets?

Notebooklets are collections of notebook cells that implement some
useful reusable sequence. They are extensions of, and build upon the
msticpy package and are design to streamline authoring of Jupyter
notebooks for CyberSec hunters and investigators. The goal of
notebooklets is to replace repetitive and lengthy boilerplate code in
notebooks for common operations.

Some examples are:

- Get a host summary for a named host (IP address, cloud registration
information, recent alerts)
- Get account activity for an account (host and cloud logons and
failures, summary of recent activity)
- Triage alerts with Threat Intel data (prioritize your alerts by
correlating with Threat intel sources)

### Intended Audience

- Cyber security investigators and hunters using Jupyter notebooks for
their work
- Security Ops Center (SOC) engineers/SecDevOps building reusable
notebooks for SOC analysts

### Why did we create notebooklets?

- Notebook code can quickly become complex and lengthy:
- obscures the information you are trying to display
- can be intimidating to non-developers
- Code in notebook code cells is not easily re-useable:
- You can copy and paste but how do you sync changes back to the
original notebook?
- Difficult to discover code snippets in notebooks
- Notebook code is often fragile:
- Often not parameterized or modular
- Code blocks are frequently dependent on global values assigned
earlier
- Output data is not in any standard format
- Difficult to test

### Why aren\'t these part of msticpy?

- Msticpy aims to be platform-independent, whereas most if not all
notebooklets assume a data schema that is specific to their data
provider/SIEM.
- Msticpy is mostly for discrete functions such as data acquisition,
analysis and visualization. Msticnb implements common SOC scenarios
using this functionality.

### Traditional Notebook vs. one using a Notebooklets

Notebook authors face several issues:
The notebook on the left is using mostly inline code (occupying more
than 50% of the notebook). The one on the right is using a single
notebooklet with only 3 or 4 lines of code.

- 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.
<img src="https://github.com/microsoft/msticnb/blob/master/docs/source/_static/NBComparison.png"
alt="Comparing a standard notebook with one using a notebooklet.
The standard notebook on the left can require large amounts of code.
The notebook on the right uses just 3 lines of code."
title="With and without notebooklets" height="300" />

## Notebooklets Goals

The goals for MSTIC notebooklets are:
### Characteristics of Notebooklets

- Speed up authoring of new notebooks by aggregating a complex set of operations
in a single callable unit
- Enable re-use of common notebook patterns
- Allow unit testing of code blocks
- Allow update of notebooklets code for fixes and enhancement
- Support multiple data platforms
- They have one or small number of entry points/methods (typically a
\"run\" method)
- They are parametrizable (e.g. you can supply hostname, IP Address,
time range, etc.) and they may have runtime options to allow to skip
unwanted processing or include optional processing
- They can query, process or visualize data (or any combination)
- They return a package of results that can be used later in the
notebook
- The code can be imported into a notebook cell to be modified, if
needed.

# Installing
### Limitations

```bash
- They are normally specific to a data backend/SIEM since the data
schema and layout varies between SIEM vendors.
- Notebooklet code layout is typically more complex than standard
notebook code

---

Using Notebooklets
------------------

For a more detailed explanation of these steps and illustration of other
features see the [Notebooklets
notebook](https://github.com/microsoft/msticnb/blob/master/docs/notebooks/NotebookletsDemo.ipynb)

### Install the Package

```
pip install msticnb
```

# Usage
### Import and initialize

For detailed usage and examples see the [NotebookletDemo notebook](./docs/notebooks/NotebookletsDemo.ipynb)
<img src="https://github.com/microsoft/msticnb/blob/master/docs/source/_static/msticnb-import.png"
alt="Python statement to import msticnb - 'import msticnb as nb'"
title="Importing" height="300" />

### Import and initialize the notebooklets
The init method loads data drivers and data providers relevant to the
the chosen data platform.

```python
import msticnb as nb
nb.init()
<img src="https://github.com/microsoft/msticnb/blob/master/docs/source/_static/msticnb-init.png"
alt="Python statement to initialize msticnb -
nb.init('AzureSentinel')"
title="Initializing msticnb" height="300" />

```
### Pick a notebooklet to use

### Run a Notebooklet
You can pick a notebooklet from the commandline, using autocompletion.
You can also search for a notebooklet using keywords and text from the
notebooklet name and documentation.

```python
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)
```
The easiest way is using the nb.browse() method. This lists all of the
available notebooklets and displays documentation, usage information and
sample code snippet for each.

### Get Help
<img src="https://github.com/microsoft/msticnb/blob/master/docs/source/_static/msticnb-browser.png"
alt="Notebooklet browser showing list of notebooklets and some
details of the user documentation for the selected notebooklet."
title="Notebooklet browser" height="300" />

```python
nb.nblts.azsent.host.HostSummary.show_help()
```
### Instantiate the notebooklet and execute \"run\"

and of course, standard Python help also works as expected
```python
help(host_summary)
help(host_summary.run)
```
Notebooklets usually have a single `run` method, which is the entry
point for the notebooklet. A notebooklet might have additional methods
to do further drill-down, data retrieval, visualization or other
operations once the run method has completed. Run typically requires
parameters such as a host or account identifier and a time range over
which to perform the operations.

<img src="https://github.com/microsoft/msticnb/blob/master/docs/source/_static/msticnb-run-cell.png"
alt="Python code cell showing the creation of a notebooklet instance
from the WinHostevents notebooklet class. The notebooklet 'run'
method is called with parameters supplying the name of the host
and a time range."
title="Running a notebooklet" height="300" />

The notebooklet displays output directly to the notebook (although this
can be suppressed) - showing text, data tables and visualizations. This
data is all saved to a Results object. The data items are simple
properties of this results object, for example, DataFrames, plots, or
simple Python dictionaries. You can access these individually and you
can just display the results object using IPython display() or just
typing its name into and emtpy cell and running the cell.

<img src="https://github.com/microsoft/msticnb/blob/master/docs/source/_static/msticnb-run.png"
alt="The notebooklet displays output directly to th notebook.
The output includes styled tables, text headings and descriptions
and interactive timeline visualizations."
title="Running a notebooklet" height="300" />

### View extended help for a notebooklet

You can access detailed documentation from any notebooklet class or
instance using the show_help() method. This help includes a high-level
description and usage information (parameters, available methods,
options). It also describes the major output sections that will be
displayed and the the contents of the return results.

Note: the contents of this help are also displayed in the notebooklet browser
shown earlier.

<img src="https://github.com/microsoft/msticnb/blob/master/docs/source/_static/msticnb-help.png"
alt="The notebooklet help displays a description, parameter and other
usage information and available methods. It also describes the
major output sections and the contents of the return results."
title="Notebooklet help" height="300" />

Current Notebooklets
--------------------

### AccountSummary

Retrieves account summary for the selected account.

Main operations:

- Searches for matches for the account name in Active Directory,
Windows and Linux host logs.
- If one or more matches are found it will return a selection widget
that you can use to pick the account.
- Selecting the account displays a summary of recent activity and
retrieves any alerts and hunting bookmarks related to the account
- The alerts and bookmarks are browsable using the browse_alerts and
browse_bookmarks methods
- You can call the find_additional_data method to retrieve and display
more detailed activity information for the account.


### EnrichAlerts

Alert Enrichment Notebooklet Class.

Enriches Azure Sentinel alerts with Threat Intelligence data.

### HostLogonsSummary

Host Logons Summary Notebooklet class.

Queries and displays information about logons to a host including:

- Summary of successful logons
- Visualizations of logon event times
- Geolocation of remote logon sources
- Visualizations of various logon elements depending on host type
- Data on users with failed and successful logons

### HostSummary

HostSummary Notebooklet class.

Queries and displays information about a host including:

- IP address assignment
- Related alerts
- Related hunting/investigation bookmarks
- Azure subscription/resource data.

### WinHostEvents

Windows host Security Events Notebooklet class.

Queries and displays Windows Security Events including:

- All security events summary
- Extracting and displaying account management events
- Account management event timeline
- Optionally parsing packed event data into DataFrame columns

Process (4688) and Account Logon (4624, 4625) are not included in the
event types processed by this module.

### NetworkFlowSummary

Network Flow Summary Notebooklet class.

Queries network data and plots time lines for network traffic to/from a
host or IP address.

- Plot flows events by protocol and direction
- Plot flow count by protocol
- Display flow summary table
- Display flow summary by ASN
- Display results on map

### TemplateNB

# Contributing
Template Notebooklet class.

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.
A code template for creating additional notebooklets.

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.
See Also
--------

This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or
contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.
[msticpy documentation](https://msticpy.readthedocs.io/en/latest/)
20 changes: 20 additions & 0 deletions docs/Makefile
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# Minimal makefile for Sphinx documentation
#

# You can set these variables from the command line, and also
# from the environment for the first two.
SPHINXOPTS ?=
SPHINXBUILD ?= sphinx-build
SOURCEDIR = source
BUILDDIR = build

# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

.PHONY: help Makefile

# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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