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Microsoft Threat Intelligence Python Security Tools.

msticpy is a library for InfoSec investigation and hunting in Jupyter Notebooks. It includes functionality to:

query log data from multiple sources
enrich the data with Threat Intelligence, geolocations and Azure resource data
extract Indicators of Activity (IoA) from logs and unpack encoded data
perform sophisticated analysis such as anomalous session detection and time series decomposition
visualize data using interactive timelines, process trees and multi-dimensional Morph Charts

It also includes some time-saving notebook tools such as widgets to set query time boundaries, select and display items from lists, and configure the notebook environment.

The msticpy package was initially developed to support Jupyter Notebooks authoring for Azure Sentinel. While Azure Sentinel is still a big focus of our work, we are extending the data query/acquisition components to pull log data from other sources (currently Splunk, Microsoft Defender for Endpoint and Microsoft Graph are supported but we are actively working on support for data from other SIEM platforms). Most of the components can also be used with data from any source. Pandas DataFrames are used as the ubiquitous input and output format of almost all components. There is also a data provider to make it easy to and process data from local CSV files and pickled DataFrames.

The package addresses three central needs for security investigators and hunters:

Acquiring and enriching data
Analyzing data
Visualizing data

We welcome feedback, bug reports, suggestions for new features and contributions.

Installing

For core install:

pip install msticpy

If you are using MSTICPy with Azure Sentinel you should install with the "azsentinel" extra package:

pip install msticpy[azsentinel]

or for the latest dev build

pip install git+https://github.com/microsoft/msticpy

Documentation

Full documentation is at ReadTheDocs

Sample notebooks for many of the modules are in the docs/notebooks folder and accompanying notebooks.

You can also browse through the sample notebooks referenced at the end of this document to see some of the functionality used in context. You can play with some of the package functions in this interactive demo on mybinder.org.

Log Data Acquisition

QueryProvider is an extensible query library targeting Azure Sentinel/Log Analytics, Splunk, OData and other log data sources. It also has special support for Mordor data sets and using local data.

Built-in parameterized queries allow complex queries to be run from a single function call. Add your own queries using a simple YAML schema.

Data Queries Notebook

Data Enrichment

Threat Intelligence providers

The TILookup class can lookup IoCs across multiple TI providers. built-in providers include AlienVault OTX, IBM XForce, VirusTotal and Azure Sentinel.

The input can be a single IoC observable or a pandas DataFrame containing multiple observables. Depending on the provider, you may require an account and an API key. Some providers also enforce throttling (especially for free tiers), which might affect performing bulk lookups.

TIProviders and TILookup Usage Notebook

GeoLocation Data

The GeoIP lookup classes allow you to match the geo-locations of IP addresses using either:

GeoLiteLookup - Maxmind Geolite (see https://www.maxmind.com)
IPStackLookup - IPStack (see https://ipstack.com)

GeoIP Lookup and GeoIP Notebook

Azure Resource Data, Storage and Azure Sentinel API

The AzureData module contains functionality for enriching data regarding Azure host details with additional host details exposed via the Azure API. The AzureSentinel module allows you to query incidents, retrieve detector and hunting queries. AzureBlogStorage lets you read and write data from blob storage.

Azure Resource APIs, Azure Sentinel APIs, Azure Storage

Security Analysis

This subpackage contains several modules helpful for working on security investigations and hunting:

Anomalous Sequence Detection

Detect unusual sequences of events in your Office, Active Directory or other log data. You can extract sessions (e.g. activity initiated by the same account) and identify and visualize unusual sequences of activity. For example, detecting an attacker setting a mail forwarding rule on someone's mailbox.

Anomalous Sessions and Anomalous Sequence Notebook

Time Series Analysis

Time series analysis allows you to identify unusual patterns in your log data taking into account normal seasonal variations (e.g. the regular ebb and flow of events over hours of the day, days of the week, etc.). Using both analysis and visualization highlights unusual traffic flows or event activity for any data set.

Time Series

Visualization

Event Timelines

Display any log events on an interactive timeline. Using the Bokeh Visualization Library the timeline control enables you to visualize one or more event streams, interactively zoom into specific time slots and view event details for plotted events.

Timeline and Timeline Notebook

Process Trees

The process tree functionality has two main components:

Process Tree creation - taking a process creation log from a host and building the parent-child relationships between processes in the data set.
Process Tree visualization - this takes the processed output displays an interactive process tree using Bokeh plots.

There are a set of utility functions to extract individual and partial trees from the processed data set.

Process Tree and Process Tree Notebook

Data Manipulation and Utility functions

Pivot Functions

Lets you use MSTICPy functionality in an "entity-centric" way. All functions, queries and lookups that relate to a particular entity type (e.g. Host, IpAddress, Url) are collected together as methods of that entity class. So, if you want to do things with an IP address, just load the IpAddress entity and browse its methods.

Pivot Functions and Pivot Functions Notebook

base64unpack

Base64 and archive (gz, zip, tar) extractor. It will try to identify any base64 encoded strings and try decode them. If the result looks like one of the supported archive types it will unpack the contents. The results of each decode/unpack are rechecked for further base64 content and up to a specified depth.

Base64 Decoding and Base64Unpack Notebook

iocextract

Uses regular expressions to look for Indicator of Compromise (IoC) patterns - IP Addresses, URLs, DNS domains, Hashes, file paths. Input can be a single string or a pandas dataframe.

IoC Extraction and IoCExtract Notebook

eventcluster (experimental)

This module is intended to be used to summarize large numbers of events into clusters of different patterns. High volume repeating events can often make it difficult to see unique and interesting items.

This is an unsupervised learning module implemented using SciKit Learn DBScan.

Event Clustering and Event Clustering Notebook

auditdextract

Module to load and decode Linux audit logs. It collapses messages sharing the same message ID into single events, decodes hex-encoded data fields and performs some event-specific formatting and normalization (e.g. for process start events it will re-assemble the process command line arguments into a single string).

syslog_utils

Module to support an investigation of a Linux host with only syslog logging enabled. This includes functions for collating host data, clustering logon events and detecting user sessions containing suspicious activity.

cmd_line

A module to support he detection of known malicious command line activity or suspicious patterns of command line activity.

domain_utils

A module to support investigation of domain names and URLs with functions to validate a domain name and screenshot a URL.

Notebook widgets

These are built from the Jupyter ipywidgets collection and group common functionality useful in InfoSec tasks such as list pickers, query time boundary settings and event display into an easy-to-use format.

More Notebooks on Azure Sentinel Notebooks GitHub

Azure Sentinel Notebooks

Example notebooks:

View directly on GitHub or copy and paste the link into nbviewer.org

Notebook examples with saved data

See the following notebooks for more examples of the use of this package in practice:

Windows Alert Investigation in GitHub or NbViewer
Office 365 Exploration in GitHub or NbViewer
Cross-Network Hunting in GitHubor NbViewer

Supported Platforms and Packages

msticpy is OS-independent
Requires Python 3.6 or later
See requirements.txt for more details and version requirements.

Contributing

For (brief) developer guidelines, see this wiki article Contributor Guidelines

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.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., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

Download Msticpy

More info

Hackerhubb.blogspot.com

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What is Bug Bounty ?

A bug bounty program, also called a vulnerability rewards program (VRP), is a crowdsourcing initiative that rewards individuals for discovering and reporting software bugs. Bug bounty programs are often initiated to supplement internal code audits and penetration tests as part of an organization's vulnerability management strategy.

Many software vendors and websites run bug bounty programs, paying out cash rewards to software security researchers and white hat hackers who report software vulnerabilities that have the potential to be exploited. Bug reports must document enough information for for the organization offering the bounty to be able to reproduce the vulnerability. Typically, payment amounts are commensurate with the size of the organization, the difficulty in hacking the system and how much impact on users a bug might have.

Mozilla paid out a $3,000 flat rate bounty for bugs that fit its criteria, while Facebook has given out as much as $20,000 for a single bug report. Google paid Chrome operating system bug reporters a combined $700,000 in 2012 and Microsoft paid UK researcher James Forshaw $100,000 for an attack vulnerability in Windows 8.1. In 2016, Apple announced rewards that max out at $200,000 for a flaw in the iOS secure boot firmware components and up to $50,000 for execution of arbitrary code with kernel privileges or unauthorized iCloud access.

While the use of ethical hackers to find bugs can be very effective, such programs can also be controversial. To limit potential risk, some organizations are offering closed bug bounty programs that require an invitation. Apple, for example, has limited bug bounty participation to few dozen researchers.

Related word

Are you tired of reading endless news stories about ethical hacking and not really knowing what that means? Let's change that!

This Post is for the people that:

Have No Experience With Cybersecurity (Ethical Hacking)
Have Limited Experience.
Those That Just Can't Get A Break

OK, let's dive into the post and suggest some ways that you can get ahead in Cybersecurity.

I receive many messages on how to become a hacker. "I'm a beginner in hacking, how should I start?" or "I want to be able to hack my friend's Facebook account" are some of the more frequent queries. Hacking is a skill. And you must remember that if you want to learn hacking solely for the fun of hacking into your friend's Facebook account or email, things will not work out for you. You should decide to learn hacking because of your fascination for technology and your desire to be an expert in computer systems. Its time to change the color of your hat 😀

I've had my good share of Hats. Black, white or sometimes a blackish shade of grey. The darker it gets, the more fun you have.

If you have no experience don't worry. We ALL had to start somewhere, and we ALL needed help to get where we are today. No one is an island and no one is born with all the necessary skills. Period.OK, so you have zero experience and limited skills…my advice in this instance is that you teach yourself some absolute fundamentals.

Let's get this party started.

What is hacking?

Hacking is identifying weakness and vulnerabilities of some system and gaining access with it.

Hacker gets unauthorized access by targeting system while ethical hacker have an official permission in a lawful and legitimate manner to assess the security posture of a target system(s)

There's some types of hackers, a bit of "terminology".
White hat — ethical hacker.
Black hat — classical hacker, get unauthorized access.
Grey hat — person who gets unauthorized access but reveals the weaknesses to the company.
Script kiddie — person with no technical skills just used pre-made tools.
Hacktivist — person who hacks for some idea and leaves some messages. For example strike against copyright.

Skills required to become ethical hacker.

Curosity anf exploration
Operating System
Fundamentals of Networking

*Note this sites

guitarz news

วันพุธที่ 31 พฤษภาคม พ.ศ. 2566

Msticpy - Microsoft Threat Intelligence Security Tools

Hackerhubb.blogspot.com

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$$$ Bug Bounty $$$

Related word

วันอังคารที่ 30 พฤษภาคม พ.ศ. 2566

How To Start | How To Become An Ethical Hacker

More info

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