Metadata-Version: 2.1
Name: msticnb
Version: 0.2.0
Summary: MSTIC Notebooklets
Home-page: https://github.com/microsoft/msticnb
Author: Ian Hellen
Author-email: ianhelle@microsoft.com
License: MIT License
Project-URL: Documentation, https://msticnb.readthedocs.io
Project-URL: Code, https://github.com/microsoft/msticnb
Description: # msticnb - Notebooklets for Jupyter Notebooks
        
        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.
        
        <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" />
        
        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.
        
        ```python
            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
        
        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.
        
        <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="500" />
        
        
        ### Characteristics of Notebooklets
        
        - 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.
        
        ### Limitations
        
        - 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
        
        ```bash
        pip install msticnb
        ```
        
        ### Import and initialize
        
        <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="70" />
        
        The init method loads data drivers and data providers relevant to the
        the chosen data platform.
        
        <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="70" />
        
        ### Pick a notebooklet to use
        
        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.
        
        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.
        
        <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="500" />
        
        ### Instantiate the notebooklet and execute \"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="100" />
        
        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="600" />
        
        ### 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="500" />
        
        ## 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 (e.g. host logons,
          Azure and Office 365 activity)
        
        ### EnrichAlerts
        
        Alert Enrichment Notebooklet Class.
        
        Enriches Azure Sentinel alerts with Threat Intelligence and other 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.
        
        ### IpAddressSummary
        
        Retrieves common data about an IP Address including:
        
        - Tries to determine IP address is external or internal (i.e. owned by the organization)
        - Azure Heartbeat, Network Analytics or VMComputer records
        - Geo-IP and Whois data
        - Threat intel reports
        - Related alerts and hunting bookmarks
        - Network flows involving IP address
        - Azure activity (e.g. sign-ins) originating from IP address
        
        ### 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
        
        Template Notebooklet class.
        
        A code template for creating additional notebooklets.
        
        ## See Also
        
        [msticpy documentation](https://msticpy.readthedocs.io/en/latest/)
        
Keywords: security,cybersecurity,infosec,jupyter,notebook,azure,sentinel
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Requires-Python: >=3.6
Description-Content-Type: text/markdown
