How to learn Hacking Part 2

Now that you have read the basics here at http://www.decisionstats.com/how-to-learn-to-be-a-hacker-easily/ (please do read this before reading the below)

 

Here is a list of tutorials that you should study (in order of ease)

1) LEARN BASICS – enough to get you a job maybe if that’s all you wanted.

http://www.offensive-security.com/metasploit-unleashed/Main_Page

2) READ SOME MORE-

Lena’s Reverse Engineering Tutorial-“Use Google.com  for finding the Tutorial

Lena’s Reverse Engineering tutorial. It includes 36 parts of individual cracking techniques and will teach you the basics of protection bypassing

01. Olly + assembler + patching a basic reverseme
02. Keyfiling the reverseme + assembler
03. Basic nag removal + header problems
04. Basic + aesthetic patching
05. Comparing on changes in cond jumps, animate over/in, breakpoints
06. “The plain stupid patching method”, searching for textstrings
07. Intermediate level patching, Kanal in PEiD
08. Debugging with W32Dasm, RVA, VA and offset, using LordPE as a hexeditor
09. Explaining the Visual Basic concept, introduction to SmartCheck and configuration
10. Continued reversing techniques in VB, use of decompilers and a basic anti-anti-trick
11. Intermediate patching using Olly’s “pane window”
12. Guiding a program by multiple patching.
13. The use of API’s in software, avoiding doublechecking tricks
14. More difficult schemes and an introduction to inline patching
15. How to study behaviour in the code, continued inlining using a pointer
16. Reversing using resources
17. Insights and practice in basic (self)keygenning
18. Diversion code, encryption/decryption, selfmodifying code and polymorphism
19. Debugger detected and anti-anti-techniques
20. Packers and protectors : an introduction
21. Imports rebuilding
22. API Redirection
23. Stolen bytes
24. Patching at runtime using loaders from lena151 original
25. Continued patching at runtime & unpacking armadillo standard protection
26. Machine specific loaders, unpacking & debugging armadillo
27. tElock + advanced patching
28. Bypassing & killing server checks
29. Killing & inlining a more difficult server check
30. SFX, Run Trace & more advanced string searching
31. Delphi in Olly & DeDe
32. Author tricks, HIEW & approaches in inline patching
33. The FPU, integrity checks & loader versus patcher
34. Reversing techniques in packed software & a S&R loader for ASProtect
35. Inlining inside polymorphic code
36. Keygenning

If you want more free training – hang around this website

http://www.owasp.org/index.php/Cheat_Sheets

OWASP Cheat Sheet Series

Draft OWASP Cheat Sheets

3) SPEND SOME MONEY on TRAINING

http://www.corelan-training.com/index.php/training/corelan-live/

Course overview

Module 1 – The x86 environment

  • System Architecture
  • Windows Memory Management
  • Registers
  • Introduction to Assembly
  • The stack

Module 2 – The exploit developer environment

  • Setting up the exploit developer lab
  • Using debuggers and debugger plugins to gather primitives

Module 3 – Saved Return Pointer Overwrite

  • Functions
  • Saved return pointer overwrites
  • Stack cookies

Module 4 – Abusing Structured Exception Handlers

  • Abusing exception handler overwrites
  • Bypassing Safeseh

Module 5 – Pointer smashing

  • Function pointers
  • Data/object pointers
  • vtable/virtual functions

Module 6 – Off-by-one and integer overflows

  • Off-by-one
  • Integer overflows

Module 7 – Limited buffers

  • Limited buffers, shellcode splitting

Module 8 – Reliability++ & reusability++

  • Finding and avoiding bad characters
  • Creative ways to deal with character set limitations

Module 9 – Fun with Unicode

  • Exploiting Unicode based overflows
  • Writing venetian alignment code
  • Creating and Using venetian shellcode

Module 10 – Heap Spraying Fundamentals

  • Heap Management and behaviour
  • Heap Spraying for Internet Explorer 6 and 7

Module 11 – Egg Hunters

  • Using and tweaking Egg hunters
  • Custom egghunters
  • Using Omelet egghunters
  • Egghunters in a WoW64 environment

Module 12 – Shellcoding

  • Building custom shellcode from scratch
  • Understanding existing shellcode
  • Writing portable shellcode
  • Bypassing Antivirus

Module 13 – Metasploit Exploit Modules

  • Writing exploits for the Metasploit Framework
  • Porting exploits to the Metasploit Framework

Module 14 – ASLR

  • Bypassing ASLR

Module 15 – W^X

  • Bypassing NX/DEP
  • Return Oriented Programming / Code Reuse (ROP) )

Module 16 – Advanced Heap Spraying

  • Heap Feng Shui & heaplib
  • Precise heap spraying in modern browsers (IE8 & IE9, Firefox 13)

Module 17 – Use After Free

  • Exploiting Use-After-Free conditions

Module 18 – Windows 8

  • Windows 8 Memory Protections and Bypass
TRAINING SCHEDULES AT

ALSO GET CERTIFIED http://www.offensive-security.com/information-security-training/penetration-testing-with-backtrack/ ($950 cost)

the syllabus is here at

http://www.offensive-security.com/documentation/penetration-testing-with-backtrack.pdf

4) HANG AROUND OTHER HACKERS

At http://attrition.org/attrition/

or The Noir  Hat Conferences-

http://blackhat.com/html/bh-us-12/training/bh-us-12-training_complete.html

or read this website

http://software-security.sans.org/developer-how-to/

5) GET A DEGREE

Yes it is possible

 

See http://web.jhu.edu/jhuisi/

The Johns Hopkins University Information Security Institute (JHUISI) is the University’s focal point for research and education in information security, assurance and privacy.

Scholarship Information

 

The Information Security Institute is now accepting applications for the Department of Defense’s Information Assurance Scholarship Program (IASP).  This scholarship includes full tuition, a living stipend, books and health insurance. In return each student recipient must work for a DoD agency at a competitive salary for six months for every semester funded. The scholarship is open to American citizens only.

http://web.jhu.edu/jhuisi/mssi/index.html

MASTER OF SCIENCE IN SECURITY INFORMATICS PROGRAM

The flagship educational experience offered by Johns Hopkins University in the area of information security and assurance is represented by the Master of Science in Security Informatics degree.  Over thirty courses are available in support of this unique and innovative graduate program.

———————————————————–

Disclaimer- I havent done any of these things- This is just a curated list from Quora  so I am open to feedback.

You use this at your own risk of conscience ,local legal jurisdictions and your own legal liability.

 

 

 

 

 

 

Google introduces Google Play

Some nice new features from the big G men from Mountain view. Google Play- for movies, games, apps, music and books. Nice to see entertainment is back on Google’s priority.

 

See this to read more

https://play.google.com/about/

When will I get Google Play?

About Google Play

Q: What is Google Play?
A: Google Play is a new digital content experience from Google where you can find your favorite music, movies, books, and Android apps and games. It’s your entertainment hub: you can access it from the web or from your Android device or even TV, and all your content is instantly available across all of these devices.

Q: What is your strategy with Google Play?
A: Our goal with Google Play is to bring together all your favorite content in one place that you can access across your devices. Specifically, digital content is fundamental to the mobile experience, so bringing all of this content together in one place for users makes the Android platform even more compelling. We’re also simplifying digital content for Google users – you can go to the Google Play website on your desktop and purchase and experience the latest movies, music and books. With Google Play, we’re giving you a simpler way to get your digital content.

Q: What will the experience be for users? What will happen to my existing account?
A: All content and apps in your existing account will remain in your account, but will transition to Google Play. On your device, the Android Market app icon will become the Google Play store icon. You’ll see “Play Store.” For the movies, books and music apps, you’ll begin to see Play versions of these as well, such as “Play Music,” and “Play Movies.”

Q: When will I get Google Play? What markets is this available in?
A: We’ll be rolling out Google Play globally starting today. On the web, Google Play will be live today. On devices, it will take a few days for the Android Market app to update to the Google Play Store app. The music, books and movies apps will also receive an update today.
Around the globe, Google Play will include Android apps and games. In countries where we have already launched music, books or movies, you will see those categories available in Google Play, too.

Q: I live outside the US. When will I get the books, music or movies verticals? I only see Android apps and games?
A: We want to bring different content categories to as many countries as possible. We’ve already launched movies and books in several countries outside the U.S. and will continue to do so overtime, but we don’t have a specific timeline to share.

Q: What types of content are available in my country?

  • Paid Apps: Available in these countries
  • Movies: Available in US, UK, Canada, and Japan
  • eBooks: Available in US, UK, Canada, and Australia
  • Music: Available in US

 

Q: Does this mean Google Music and the Google eBookstore will cease to exist? What about my account?
A: Both Google Music and the Google eBookstore are now part of Google Play. Your music and your books, including anything you bought, are still there, available to you in Google Play and accessible through your Google account.

Q: Where did my Google eBooks books go? Will I still have access to them?
A: Your books are now part of Google Play. Your books are still there, available to you in your Google Play library and accessible through your Google account.

Q: I don’t use an Android phone, can I still use Google Play?
A: Yes. Google Play is available on any computer with a modern browser at play.google.com. On the web, you can browse and buy books, movies and music. You can read books on the Google Play web reader, listen to music on your computer or watch movies online. Your digital content is all stored in the cloud, so you can access from anywhere using your Google Account.
We’ve also created ways to experience your music and books on other platforms such as the Google Books iOS app.

Q: Why do I not see Google Play yet on my device?
A: Please see our help center article on this here.

Q: How can I contact Google Play consumer support?
A: You can call or email our team here.

Book Review- Machine Learning for Hackers

This is review of the fashionably named book Machine Learning for Hackers by Drew Conway and John Myles White (O’Reilly ). The book is about hacking code in R.

 

The preface introduces the reader to the authors conception of what machine learning and hacking is all about. If the name of the book was machine learning for business analytsts or data miners, I am sure the content would have been unchanged though the popularity (and ambiguity) of the word hacker can often substitute for its usefulness. Indeed the many wise and learned Professors of statistics departments through out the civilized world would be mildly surprised and bemused by their day to day activities as hacking or teaching hackers. The book follows a case study and example based approach and uses the GGPLOT2 package within R programming almost to the point of ignoring any other native graphics system based in R. It can be quite useful for the aspiring reader who wishes to understand and join the booming market for skilled talent in statistical computing.

Chapter 1 has a very useful set of functions for data cleansing and formatting. It walks you through the basics of formatting based on dates and conditions, missing value and outlier treatment and using ggplot package in R for graphical analysis. The case study used is an Infochimps dataset with 60,000 recordings of UFO sightings. The case study is lucid, and done at a extremely helpful pace illustrating the powerful and flexible nature of R functions that can be used for data cleansing.The chapter mentions text editors and IDEs but fails to list them in a tabular format, while listing several other tables like Packages used in the book. It also jumps straight from installation instructions to functions in R without getting into the various kinds of data types within R or specifying where these can be referenced from. It thus assumes a higher level of basic programming understanding for the reader than the average R book.

Chapter 2 discusses data exploration, and has a very clear set of diagrams that explain the various data summary operations that are performed routinely. This is an innovative approach and will help students or newcomers to the field of data analysis. It introduces the reader to type determination functions, as well different kinds of encoding. The introduction to creating functions is quite elegant and simple , and numerical summary methods are explained adequately. While the chapter explains data exploration with the help of various histogram options in ggplot2 , it fails to create a more generic framework for data exploration or rules to assist the reader in visual data exploration in non standard data situations. While the examples are very helpful for a reader , there needs to be slightly more depth to step out of the example and into a framework for visual data exploration (or references for the same). A couple of case studies however elaborately explained cannot do justice to the vast field of data exploration and especially visual data exploration.

Chapter 3 discussed binary classification for the specific purpose for spam filtering using a dataset from SpamAssassin. It introduces the reader to the naïve Bayes classifier and the principles of text mining suing the tm package in R. Some of the example codes could have been better commented for easier readability in the book. Overall it is quite a easy tutorial for creating a naïve Bayes classifier even for beginners.

Chapter 4 discusses the issues in importance ranking and creating recommendation systems specifically in the case of ordering email messages into important and not important. It introduces the useful grepl, gsub, strsplit, strptime ,difftime and strtrim functions for parsing data. The chapter further introduces the reader to the concept of log (and affine) transformations in a lucid and clear way that can help even beginners learn this powerful transformation concept. Again the coding within this chapter is sparsely commented which can cause difficulties to people not used to learn reams of code. ( it may have been part of the code attached with the book, but I am reading an electronic book and I did not find an easy way to go back and forth between the code and the book). The readability of the chapters would be further enhanced by the use of flow charts explaining the path and process followed than overtly verbose textual descriptions running into multiple pages. The chapters are quite clearly written, but a helpful visual summary can help in both revising the concepts and elucidate the approach taken further.A suggestion for the authors could be to compile the list of useful functions they introduce in this book as a sort of reference card (or Ref Card) for R Hackers or atleast have a chapter wise summary of functions, datasets and packages used.

Chapter 5 discusses linear regression , and it is a surprising and not very good explanation of regression theory in the introduction to regression. However the chapter makes up in practical example what it oversimplifies in theory. The chapter on regression is not the finest chapter written in this otherwise excellent book. Part of this is because of relative lack of organization- correlation is explained after linear regression is explained. Once again the lack of a function summary and a process flow diagram hinders readability and a separate section on regression metrics that help make a regression result good or not so good could be a welcome addition. Functions introduced include lm.

Chapter 6 showcases Generalized Additive Model (GAM) and Polynomial Regression, including an introduction to singularity and of over-fitting. Functions included in this chapter are transform, and poly while the package glmnet is also used here. The chapter also introduces the reader formally to the concept of cross validation (though examples of cross validation had been introduced in earlier chapters) and regularization. Logistic regression is also introduced at the end in this chapter.

Chapter 7 is about optimization. It describes error metric in a very easy to understand way. It creates a grid by using nested loops for various values of intercept and slope of a regression equation and computing the sum of square of errors. It then describes the optim function in detail including how it works and it’s various parameters. It introduces the curve function. The chapter then describes ridge regression including definition and hyperparameter lamda. The use of optim function to optimize the error in regression is useful learning for the aspiring hacker. Lastly it describes a case study of breaking codes using the simplistic Caesar cipher, a lexical database and the Metropolis method. Functions introduced in this chapter include .Machine$double.eps .

Chapter 8 deals with Principal Component Analysis and unsupervised learning. It uses the ymd function from lubridate package to convert string to date objects, and the cast function from reshape package to further manipulate the structure of data. Using the princomp functions enables PCA in R.The case study creates a stock market index and compares the results with the Dow Jones index.

Chapter 9 deals with Multidimensional Scaling as well as clustering US senators on the basis of similarity in voting records on legislation .It showcases matrix multiplication using %*% and also the dist function to compute distance matrix.

Chapter 10 has the subject of K Nearest Neighbors for recommendation systems. Packages used include class ,reshape and and functions used include cor, function and log. It also demonstrates creating a custom kNN function for calculating Euclidean distance between center of centroids and data. The case study used is the R package recommendation contest on Kaggle. Overall a simplistic introduction to creating a recommendation system using K nearest neighbors, without getting into any of the prepackaged packages within R that deal with association analysis , clustering or recommendation systems.

Chapter 11 introduces the reader to social network analysis (and elements of graph theory) using the example of Erdos Number as an interesting example of social networks of mathematicians. The example of Social Graph API by Google for hacking are quite new and intriguing (though a bit obsolete by changes, and should be rectified in either the errata or next edition) . However there exists packages within R that should be atleast referenced or used within this chapter (like TwitteR package that use the Twitter API and ROauth package for other social networks). Packages used within this chapter include Rcurl, RJSONIO, and igraph packages of R and functions used include rbind and ifelse. It also introduces the reader to the advanced software Gephi. The last example is to build a recommendation engine for whom to follow in Twitter using R.

Chapter 12 is about model comparison and introduces the concept of Support Vector Machines. It uses the package e1071 and shows the svm function. It also introduces the concept of tuning hyper parameters within default algorithms . A small problem in understanding the concepts is the misalignment of diagram pages with the relevant code. It lastly concludes with using mean square error as a method for comparing models built with different algorithms.

 

Overall the book is a welcome addition in the library of books based on R programming language, and the refreshing nature of the flow of material and the practicality of it’s case studies make this a recommended addition to both academic and corporate business analysts trying to derive insights by hacking lots of heterogeneous data.

Have a look for yourself at-
http://shop.oreilly.com/product/0636920018483.do