Hacking on Medium
Web Application Penetration Testing eXtreme (WAPTX) Review

https://cdn-images-1.medium.com/max/884/1*ks97WY3zv9o53z1rsVgnUg.png
Why I did this course

Continue reading on Medium »

___________________________
@hacking_Attack
@Hacking_Video

Hacking on Medium
AArch 64 Bytes: Part 3 (Yet Another Upper)

https://cdn-images-1.medium.com/max/1280/1*Fvq5caqqhQunJGD_TEMBEA.png
For a complete table of contents of all the lessons please click below as it will give you a brief of each lesson in addition to the…

Continue reading on Medium »

___________________________
@hacking_Attack
@Hacking_Video

hacking: security in practice
Can anyone provide some guidance?

I’d like a bot that I could use to send mass messages with an account on discord. For an example, I would input my login info on the bot, type a message or image, and have it bomb the server threads with it.

submitted by /u/Icy-Bat3449
[link] [comments]

___________________________
@hacking_Attack
@Hacking_Video

hacking: security in practice
What in your opinion is a growing trend? What should people and organisations be paying attention to going forward?

Are there particular attack strategies we are seeing more of or something that is emerging thats hot right now?

submitted by /u/kai--zen
[link] [comments]

___________________________
@hacking_Attack
@Hacking_Video

hacking: security in practice
Scraping Chrome extension users

Folks, any way I can efficiently scrape the users [or at least those who left a review] for a Chrome extension? TIA

submitted by /u/ale6rbd
[link] [comments]

___________________________
@hacking_Attack
@Hacking_Video

Msticpy - Microsoft Threat Intelligence Security Tools
http://www.kitploit.com/2021/11/msticpy-microsoft-threat-intelligence.html

___________________________
@hacking_Attack
@Hacking_Video

Microsoft Threat Intelligence (https://www.kitploit.com/search/label/Threat%20Intelligence) Python Security Tools.msticpy is a library for InfoSec investigation and hunting in Jupyter Notebooks. It includes functionality to:query log data from multiple sourcesenrich the data with Threat Intelligence, geolocations and Azure resource dataextract Indicators of Activity (IoA) from logs and unpack encoded dataperform sophisticated analysis such as anomalous session detection and time series decompositionvisualize 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.

___________________________
@hacking_Attack
@Hacking_Video

The msticpy package was initially developed to support Jupyter Notebooks (https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/)authoring for Azure Sentinel (https://azure.microsoft.com/en-us/services/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 dataAnalyzing dataVisualizing dataWe welcome feedback, bug reports, suggestions for new features and contributions.
Installing
For core install:pip install msticpyIf you are using MSTICPy with Azure Sentinel you should install with the "azsentinel" extra package:pip install msticpy[azsentinel]or for the latest dev buildpip install git+https://github.com/microsoft/msticpy
Documentation
Full documentation is at ReadTheDocs (https://msticpy.readthedocs.io/en/latest/)Sample notebooks for many of the modules are in the docs/notebooks (https://github.com/microsoft/msticpy/blob/master/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 (https://github.com/OTRF/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 (https://github.com/microsoft/msticpy/blob/master/docs/notebooks/Data_Queries.ipynb)
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 (https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html)and TILookup Usage Notebook (https://github.com/microsoft/msticpy/blob/master/docs/notebooks/TIProviders.ipynb)
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 (https://www.maxmind.com/))IPStackLookup - IPStack (see https://ipstack.com (https://ipstack.com/))

___________________________
@hacking_Attack
@Hacking_Video

GeoIP Lookup (https://msticpy.readthedocs.io/en/latest/data_acquisition/GeoIPLookups.html)and GeoIP Notebook (https://github.com/microsoft/msticpy/blob/master/docs/notebooks/GeoIPLookups.ipynb)
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 (https://msticpy.readthedocs.io/en/latest/data_acquisition/AzureData.html), Azure Sentinel APIs (https://msticpy.readthedocs.io/en/latest/data_acquisition/AzureSentinel.html), Azure Storage (https://msticpy.readthedocs.io/en/latest/data_acquisition/AzureBlobStorage.html)
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 (https://www.kitploit.com/search/label/Active%20Directory) 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 (https://msticpy.readthedocs.io/en/latest/data_analysis/AnomalousSequence.html)and Anomalous Sequence Notebook (https://github.com/microsoft/msticpy/blob/master/docs/notebooks/AnomalousSequence.ipynb)
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.

___________________________
@hacking_Attack
@Hacking_Video

Time Series (https://msticpy.readthedocs.io/en/latest/visualization/TimeSeriesAnomalies.html)
Visualization

Event Timelines
Display any log events on an interactive timeline. Using the Bokeh (https://bokeh.org/)Visualization (https://www.kitploit.com/search/label/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.

___________________________
@hacking_Attack
@Hacking_Video

Timeline (https://msticpy.readthedocs.io/en/latest/visualization/EventTimeline.html)and Timeline Notebook (https://github.com/microsoft/msticpy/blob/master/docs/notebooks/EventTimeline.ipynb)
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.

___________________________
@hacking_Attack
@Hacking_Video

Process Tree (https://msticpy.readthedocs.io/en/latest/visualization/ProcessTree.html)and Process Tree Notebook (https://github.com/microsoft/msticpy/blob/master/docs/notebooks/ProcessTree.ipynb)
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 (https://msticpy.readthedocs.io/en/latest/data_analysis/PivotFunctions.html)and Pivot Functions Notebook (https://github.com/microsoft/msticpy/blob/master/docs/notebooks/PivotFunctions.ipynb)
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 (https://msticpy.readthedocs.io/en/latest/data_analysis/Base64Unpack.html)and Base64Unpack Notebook (https://github.com/microsoft/msticpy/blob/master/docs/notebooks/Base64Unpack.ipynb)
iocextract
Uses regular expressions (https://www.kitploit.com/search/label/Regular%20Expressions) 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 (https://msticpy.readthedocs.io/en/latest/data_analysis/IoCExtract.html)and IoCExtract Notebook (https://github.com/microsoft/msticpy/blob/master/docs/notebooks/IoCExtract.ipynb)
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.

___________________________
@hacking_Attack
@Hacking_Video