Hardware Detection Tool

HDT (stands for Hardware Detection Tool) is a Syslinux com32 module that displays low-level information for any x86 compatible system. It provides both a command line interface and a semi-graphical menu mode for browsing.

anonimized run

The Amnesic Incognito Live System or Tails is a Debian based Linux distribution aimed at preserving privacy and anonymity.[1] Actually, it is the next iteration of development on the previous Gentoo based Incognito Linux distribution.[2] All its outgoing connections are forced to go through Tor,[3] and direct (non-anonymous) connections are blocked. The system is designed to be booted as a live CD or USB, and leaves no trace on the machine unless explicitly told to do so. The Tor Project has provided most of the financial support for development.[4]

Tails is a live system that aims at preserving your privacy and anonymity. It helps you to use the Internet anonymously almost anywhere you go and on any computer but leave no trace using unless you ask it explicitly.

It is a complete operating-system designed to be used from a DVD or a USB stick independently of the computer’s original operating system. It is Free Software and based on Debian GNU/Linux.

Tails comes with several built-in applications pre-configured with security in mind: web browser, instant messaging client, email client, office suite, image and sound editor, etc.

Continue reading “anonimized run”

cracking password hashes

Forgot your Windows admin password?

Reinstall? Oh no… But not any more…

  • This is a utility to reset the password of any user that has a valid local account on your Windows system.
  • Supports all Windows from NT3.5 to Win7, also 64 bit and also the Server versions (like 2003 and 2008)
  • You do not need to know the old password to set a new one.
  • It works offline, that is, you have to shutdown your computer and boot off a CD or USB disk to do the password reset.
  • Will detect and offer to unlock locked or disabled out user accounts!
  • There is also a registry editor and other registry utilities that works under linux/unix, and can be used for other things than password editing.

Windows stores its user information, including crypted versions of the passwords, in a file called ‘sam’, usually found in windowssystem32config. This file is a part of the registry, in a binary format previously undocumented, and not easily accessible. But thanks to a German(?) named B.D, I’ve now made a program that understands the registry.

This site provides CD and floppy images for end users to easily edit their forgotten passwords. But it also provides full source code and binary builds of the tools to allow others to use as they like for other purposes. Registry format documentation also available.

Latest release is 110511 (2011-05-11)

The following is available for download and information:


  • Some major! new features for people using the registry utilites, but not much changes to password reset.


  • New site, official URL is now: http://pogostick.net/~pnh/ntpasswd/
  • All releases still contains old mail address, please note NEW mailaddress is pnh@pogostick.net. Old mailaddress vil be invalid after January 1st 2010.
  • No new release, 2008-08-02 is still newest. Hope to release new early 2010.

A rainbow table is a precomputed table for reversing cryptographic hash functions, usually for cracking password hashes. Tables are usually used in recovering the plaintext password, up to a certain length consisting of a limited set of characters. It is a practical example of a space/time trade-off, using more computer processing time at the cost of less storage when calculating a hash on every attempt, or less processing time and more storage when compared to a simple lookup table with one entry per hash. Use of a key derivation function that employ a salt makes this attack infeasible.

Rainbow tables are an application of an earlier, simpler algorithm by Martin Hellman.[1]

Hash Sets are used in a data analysis technique called Hash Analysis, which uses the MD5, SHA1 and SHA256 hash of files to verify the files on a storage device. A hash uniquely identifies the contents of a file, regardless of filename and can be used to identify the presence of malicious, contraband, or incriminating files such as bootleg software, pornography and viruses. See this video of hash sets in use in OSForensics.

Rainbow tables are available for free from http://www.freerainbowtables.com/, approximately a 2.5TB (2500 GB) download.

The hash sets are available for free from the National Software Reference Library, approximately a 1.7GB download, and there is a OSForensics tutorial on how to convert them for use within OSForensics. Please note that conversion may take several days.

The hash sets and rainbow tables created by PassMark are also available from the OSForensics Download page.  We are not selling the tables, only the service of copying them onto a 3TB hard drive and shipping.

Any computer system that requires password authentication must contain a database of passwords, either hashed or in plaintext, and various methods of password storage exist. Because the tables are vulnerable to theft, storing the plaintext password is dangerous. Most databases therefore store a cryptographic hash of a user’s password in the database. In such a system, no one — including the authentication system — can determine what a user’s password is, simply by looking at the value stored in the database. Instead, when a user enters his or her password for authentication, it is hashed and that output is compared to the stored entry for that user (which was hashed before being stored). If the two hashes match, access is granted.

A thief who steals the (hashed) password table cannot merely enter the user’s (hashed) database entry to gain access since the authentication system would hash that a second time, producing a result which does not match the stored value, which was hashed only once. In order to learn a user’s password, the thief must reverse the hash to find a password which produces the hashed value. A good authentication system will make this process as difficult as possible by using a one-way hash function, that has a high ratio for the time to invert the function compared to the time to compute the function.

Rainbow tables are one tool that has been developed in an effort to derive a password by looking only at a hashed value.

Rainbow tables are not always needed, for there are simpler methods of hash reversal available. Brute-force attacks and dictionary attacks are the simplest methods available, however these are not adequate for systems that use large passwords, because of the difficulty of storing all the options available and searching through such a large database to perform a reverse-lookup of a hash.

To address this issue of scale, reverse lookup tables were generated that stored only a smaller selection of hashes that when reversed could generate long chains of passwords. Although the reverse lookup of a hash in a chained table takes more computational time, the lookup table itself can be much smaller, so hashes of longer passwords can be stored. Rainbow tables are a refinement of this chaining technique and provide a solution to a problem called chain collisions.

Ophcrack is a free Windows password cracker based on rainbow tables. It is a very efficient implementation of rainbow tables done by the inventors of the method. It comes with a Graphical User Interface and runs on multiple platforms.

The multi-platform password cracker Ophcrack is incredibly fast. How fast? It can crack the password “Fgpyyih804423” in 160 seconds. Most people would consider that password fairly secure. The Microsoft password strength checker rates it “strong”. The Geekwisdom password strength meter rates it “mediocre”.

Why is Ophcrack so fast? Because it uses Rainbow Tables.


  • » Runs on Windows, Linux/Unix, Mac OS X, …
  • » Cracks LM and NTLM hashes.
  • » Free tables available for Windows XP and Vista/7.
  • » Brute-force module for simple passwords.
  • » Audit mode and CSV export.
  • » Real-time graphs to analyze the passwords.
  • » LiveCD available to simplify the cracking.
  • » Dumps and loads hashes from encrypted SAM recovered from a Windows partition.
  • » Free and open source software (GPL).

Note that all rainbow tables have specific lengths and character sets they work in. Passwords that are too long, or contain a character not in the table’s character set, are completely immune to attack from that rainbow table.

Unfortunately, Windows servers are particularly vulnerable to rainbow table attack, due to unforgivably weak legacy Lan Manager hashes. I’m stunned that the legacy Lan Manager support “feature” is still enabled by default in Windows Server 2003. It’s highly advisable that you disable Lan Manager hashes, particularly on Windows servers which happen to store domain credentials for every single user. It’d be an awful shame to inconvenience all your Windows 98 users, but I think the increase in security is worth it.

I read that Windows Server 2008 will finally kill off LM hashes when it’s released next year. Windows Vista already removed support for these obsolete hashes on the desktop.

The Ophcrack tool isn’t very flexible. It doesn’t allow you to generate your own rainbow tables. For that, you’ll need to use the Project Rainbow Crack tools, which can be used to attack almost any character set and any hashing algorithm. But beware. There’s a reason rainbow table attacks have only emerged recently, as the price of 2 to 4 gigabytes of memory in a desktop machine have approached realistic levels. When I said massive, I meant it. Here are some generated rainbow table sizes for the more secure NT hash:

Character Set Length Table Size
ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!@#$%^&*()-_+= 14 24 GB
ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!@#$%^&*()-_+=~`[]{}|:;"'<>,.?/ 14 64 GB

A rainbow table attack is usually overkill for a desktop machine. If hackers have physical access to the machine, security is irrelevant. That’s rule number 3 in the 10 Immutable Laws of Computer Security. There are any number of tools that can reset passwords given physical access to the machine.

But when a remote hacker obtains a large list of hashed passwords from a server or database, we’re in trouble. There’s significant risk from a rainbow table attack. That’s why you should never rely on hashes alone– always add some salt to your hash so the resulting hash values are unique. Salting a hash sounds complicated (and vaguely delicious), but it’s quite simple. You prefix a unique value to the password before hashing it:

hash = md5('deliciously-salty-' + password)

If you’ve salted your password hashes, an attacker can’t use a rainbow table attack against you– the hash results from “password” and “deliciously-salty-password” won’t match. Unless your hacker somehow knows that all your hashes are “delicously-salty-” ones. Even then, he or she would have to generate a custom rainbow table specifically for you.

To begin, password storage 101: servers don’t usually store actual passwords. Instead, they hash the password, store the hash, and discard the password. The hash can verify a password from a login page, but can’t be reversed back to the text of the password. So when you inevitably lose your SQL password table, you haven’t exposed all the passwords; just the crappy ones.

Now let’s re-explain rainbow tables:

  1. take a “dictionary” —- say, of all combinations of alphanumerics less than 15 characters
  2. hash all of them
  3. burn the results onto a DVD.

You now have several hundred billion hash values that you can reverse back to text —- a “rainbow table”. To use,

  1. take your stolen table of hashes
  2. for each hash
  3. find it in the rainbow table.

If it’s there, you cracked it.



Here’s what you need to know about rainbow tables: no modern password scheme is vulnerable to them.

Rainbow tables are easy to beat. For each password, generate a random number (a nonce). Hash the password with the nonce, and store both the hash and the nonce. The server has enough information to verify passwords (the nonce is stored in the clear). But even with a small random value, say, 16 bits, rainbow tables are infeasible: there are now 65,536 “variants” of each hash, and instead of 300 billion rainbow table entries, you need quadrillions. The nonce in this scheme is called a “salt”.

Cool, huh? Yeah, and Unix crypt —- almost the lowest common denominator in security systems —- has had this feature since 1976. If this is news to you, you shouldn’t be designing password systems. Use someone else’s good one.



No, really. Use someone else’s password system. Don’t build your own.

Most of the industry’s worst security problems (like the famously bad LANMAN hash) happened because smart developers approached security code the same way they did the rest of their code. The difference between security code and application code is, when application code fails, you find out right away. When security code fails, you find out 4 years from now, when a DVD with all your customer’s credit card and CVV2 information starts circulating in Estonia.



Here’s a “state of the art” scheme from a recent blog post on rainbow tables and salts:

hash = md5('deliciously-salty-' + password)

There are at least two problems with this code. Yeah, the author doesn’t know what a salt is; “deliciously-salty-” is not a nonce (also, Jeff, your computer really doesn’t care if you seperate the password from the nonce with a dash; it’s a computer, not a 2nd grade teacher).

But there’s a much bigger problem with this code: the letters “md5”.

Two reasons.


You’re expecting me to go off on a rant about how there is no redeeming quality to justify using MD5 in 2007. That’s true (MD5 is broken; it’s too slow to use as a general purpose hash; etc). But that’s not the problem.


The problem is that MD5 is fast. So are its modern competitors, like SHA1 and SHA256. Speed is a design goal of a modern secure hash, because hashes are a building block of almost every cryptosystem, and usually get demand-executed on a per-packet or per-message basis.

Speed is exactly what you don’t want in a password hash function.

Modern password schemes are attacked with incremental password crackers.

Incremental crackers don’t precalculate all possible cracked passwords. They consider each password hash individually, and they feed their dictionary through the password hash function the same way your PHP login page would. Rainbow table crackers like Ophcrack use space to attack passwords; incremental crackers like John the Ripper, Crack, and LC5 work with time: statistics and compute.

The password attack game is scored in time taken to crack password X. With rainbow tables, that time depends on how big your table needs to be and how fast you can search it. With incremental crackers, the time depends on how fast you can make the password hash function run.

The better you can optimize your password hash function, the faster your password hash function gets, the weaker your scheme is. MD5 and SHA1, even conventional block ciphers like DES, are designed to be fast. MD5, SHA1, and DES are weak password hashes. On modern CPUs, raw crypto building blocks like DES and MD5 can be bitsliced, vectorized, and parallelized to make password searches lightning fast. Game-over FPGA implementations cost only hundreds of dollars.

Using raw hash functions to authenticate passwords is as naive as using unsalted hash functions. Don’t.



What is the state of the art here?


First, what your operating system already gives you: a password scheme “optimized” to be computationally expensive. The most famous of these is PHK’s FreeBSD MD5 scheme.

The difference between PHK’s scheme and the one you were about to use for your social shopping cart 2.0 application is simple. You were just going to run MD5 on a salt and a password and store the hash. PHK runs MD5 for thousands of iterations. That’s called “stretching”.

PHK’s MD5 scheme is straightforward to code and comes with Linux and BSD operating systems. If you have to choose between the PHP code you have now and PHK’s scheme, you choose PHK’s scheme or you fail your PCI audit. [â??]


The best simple answer is “adaptive hashing”, which Neils Provos and David Mazieres invented for OpenBSD in 1999. Their original scheme is called “bcrypt”, but the idea is more important than the algorithm.

There are three big differences between Provos-Mazieres and PHK’s scheme:

  1. Bcrypt was invented by two smart guys and PHK’s was only invented by one smart guy. That’s literally twice the smart.
  2. Bcrypt uses Blowfish instead of MD5. Blowfish is a block cipher with a notoriously expensive setup time. To optimize Blowfish to run much faster, you’d have to contribute a major advance to cryptography. We security practioners are all “betting people”, and we usually like to place our bets on the side that “demands major advances in cryptography”.
  3. Provos and Mazieres extended Blowfish. They call theirs “Eksblowfish”. Eksblowfish is pessimized: the setup time takes even longer than Blowfish. How long? Your call. You can make a single password trial take milliseconds, or you can make it take hours.

Why is bcrypt such a huge win? Think of the problem from two perspectives: the server, and the attacker.

First, the server: you get tens of thousands of logins per hour, or tens per second. Compared to the database hits and page refreshes and IO, the password check is negligable. You don’t care if password tests take twice as long, or even ten times as long, because password hashes aren’t in the 80/20 hot spot.

Now the attacker. This is easy. The attacker cares a lot if password tests take twice as long. If one password test takes twice as long, the total password cracking time takes twice as long.

Get it?

The major advantage of adaptive hashing is that you get to tune it. As computers get faster, the same block of code continues to produce passwords that are hard to crack.


Finally, as your attorney in this matter, I am required to inform you about SRP.

SRP is the Stanford Secure Remote Password protocol. It is a public key cryptosystem designed to securely store and validate passwords without storing them in the clear or transmitting them in the clear.

That design goal is cooler than it sounds, because there’s usually a tradeoff in designing password systems:

  1. You can store a hash of the password. Now if you lose the password database, you haven’t exposed the good passwords. However, you also don’t know the password cleartext, which means that to validate passwords, your customers need to send them to you in the clear.
  2. You can use a challenge-response scheme, where both sides use a math problem to prove to each other that they know the password, but neither side sends the password over the wire. These schemes are great, but they don’t work unless both sides have access to the cleartext password —- in other words, the server has to store them in the clear.

Most practitioners will select the hashing scheme. Both attacks —- stolen databases and phished passwords —- happen all the time. But stolen databases compromise more passwords.

SRP resolves the tradeoff. It’s an extension of Diffie-Hellman. The salient detail for this post: instead of storing a salted password hash, you store a “verifier”, which is a number raised to the (obviously very large) power of the password hash modulo N.

If you understand DH, SRP is just going to make sense to you. If you don’t, the Wikipedia will do a better job explaining it than I will. For the test next Wednesday, you need to know:

  • SRP is related to Diffie-Hellman.
  • SRP is a challenge-response protocol that lets a server prove you know your password without your password ever hitting the wire.
  • SRP doesn’t require you to store plaintext passwords; you store non-reversable cryptographic verifiers.
  • “Cracking” SRP verifiers quickly would involve a significant advancement to cryptography.
  • SRP is simple enough to run out of browser Javascript.

Awesome! Why aren’t you using SRP right now? I’ll give you three reasons:

  • SRP is patented.
  • To make it work securely in a browser, you have to feed the login page over SSL; otherwise, like Meebo, you wind up with a scheme that can be beaten by anyone who can phish a web page.
  • SRP is easy to fuck up, so the first N mainstream Rails or PHP or Pylons SRP implementations are going to be trivially bypassable for at least the first year after they’re deployed.



What have we learned?
We learned that if it’s 1975, you can set the ARPANet on fire with rainbow table attacks. If it’s 2007, and rainbow table attacks set you on fire, we learned that you should go back to 1975 and wait 30 years before trying to design a password hashing scheme.

We learned that if we had learned anything from this blog post, we should be consulting our friends and neighbors in the security field for help with our password schemes, because nobody is going to find the game-over bugs in our MD5 schemes until after my Mom’s credit card number is being traded out of a curbside stall in Tallinn, Estonia.

We learned that in a password hashing scheme, speed is the enemy. We learned that MD5 was designed for speed. So, we learned that MD5 is the enemy. Also Jeff Atwood and Richard Skrenta.

Finally, we learned that if we want to store passwords securely we have three reasonable options: PHK’s MD5 scheme, Provos-Maziere’s Bcrypt scheme, and SRP. We learned that the correct choice is Bcrypt.

The Rainbow Table Is Dead

Well ok, not really.  But you should not be securing hashes against rainbow tables anymore, you need to secure them against brute forcing.  Rainbow tables are still very effective for simple hashes (md5($password)), but just because an algorithm is hard to use for a rainbow table doesn’t mean that it is safe, because the rainbow table is dead…

What Is A Rainbow Table?

Generically, a rainbow table is nothing more than a time-storage trade-off.  Instead of recomputing a function every time you want to attack it, a rainbow table is generated by pre-computing a large number of input permutations to that function.  Then, given a result, it should be easy to look-up the result in a table to determine which input(s) generate it.  That way, you can effectively reverse a non-reversible function…

Applied to hashing (and in this particular context, password hashing), a rainbow table is generated by generating a large number of candidate passwords (typically random, but may be dictionary based as well), and storing the password->hash mapping in a database or data file.  Then simply look-up the hash that you have to get the plain text password that may have generated it.

The First Problem: Storage Space

For a rainbow table to be effective, it must have a lot of candidate passwords in it.  Let’s take a look at an MD5 rainbow table, and see how much storage space it will require.  Let’s also assume that it will be stored in MySQL with a char(10) column for the password, and binary(16) column for the hash (storing it in a binary format).  So each row will have approximately 26 bytes of data (not including any overhead).  And lets look at source passwords of all printable non-control ASCII characters (there are 77 of them).

Length Of Password Number Of Possibilities Size Of Table
4 characters 35,153,041 913 MB
5 characters 2,706,784,157 70 GB
6 characters 208,422,380,089 5.4 TB
7 characters 16,048,523,266,853 417 TB
8 characters 1,235,736,291,547,681 32 PB (PetaBytes, 10^15)

As you can see, the number of possibilities goes up quite fast as you support longer passwords. So that means for a rainbow table to be effective, it must actually reduce the number of possible candidates that it stores.  After all, who would want to download 32 Petabytes to crack a hash?  Sure, you could use a dictionary and permutations on the words to try to reduce the search space significantly without cutting down on effectiveness much (statistically speaking).  But that also means a much greater resistance to strong-but-short passwords.

The Second Problem: Hash Algorithms

Hash algorithms are designed with two things in mind: security and speed.  Their typical role is to create a MAC (message authentication code) for a document.  So by hashing the document, you can tell if the original document is the same as long as the generated hashes match.  So since they need to process a lot of data (potentially gigabytes or more), a key requirement is speed.  In fact, most modern “secure” algorithms are even faster than their predecessors on modern hardware (for example, sha256 is several times faster than md5 which is much older).

The faster the hash function is, the less reason there is to use a rainbow table.  After all, the rainbow table is just a time-storage trade-off (you’re reducing time by using more storage).  So since hash functions are only getting faster, the benefit of a rainbow table is diminished.

The Third Problem: Salts

Salts are a random token (usually used only once) that is combined with the password before hashing.  They are specifically used to prevent the use of a rainbow table.  Note that using a salt doesn’t directly prevent a rainbow table from being used, it just reduces its effectiveness.  It artificially increases the length of a password in the rainbow table (so to crack a 4 character password with a 4 character salt, you’d need to generate an 8 character rainbow table).  In practice, most usual lengths of salts are too big to generate a universal rainbow table (for a 32 character salt and 8 character password, the rainbow table would need to be 2.8*10^75 bytes).  So another method that attackers use is to steal the salt along with the hash, and then generate a new rainbow table for each salt.  That’s why it’s so important to use a unique salt for each stored password (it reduces the return on investment that the new rainbow table will provide).

Why Were They Popular?

Rainbow tables were popular for one key reason: Up until very recently, disk was significantly cheaper than CPU time.  It was easier to pre-compute the rainbow table (which can take a very long time) than to do hashes as needed.

The Reality Today

I know what you’re thinking…  “Isn’t disk space even cheaper today than it was a few years ago?”…  Yes it is.  But CPU time is even cheaper by several orders of magnitude.  In 2000, the cost of a hard drive was about $13 per gigabyte.  Today, the cost of a hard drive is about $0.10 per gigabyte.  That’s 2 orders of magnitude!  But if we look at a Pentium 3, it could achieve about 300 mflops (millions of floating point operations per second) for $825, for an average of $2.75 per mflop.  A modern Intel i7 can do about 107,000 mflops for $999, averaging about $0.0093 per mflop.  That’s a 4 order or magnitude difference!

But wait; we have a reasonably new contender!  Enter, the GPU.  A single Radeon HD 6990M can achieve approximately 1,600,000 mflops for about $700.  Computed down, that’s a whopping $0.00043 per mflop.  That’s about an order of magnitude less than the Intel i7, and 5 orders of magnitude less than the P3.  Not to mention the raw performance is 4 orders of magnitude greater!

How Many Hashes Per Second?

Well, there’s a password cracking tool called John the Ripper.  Currently, it can hash up to 514 million (DES crypt()) hashes per second (abbreviated mhps from here out) on a modern 4 core CPU (Intel x7550).  When using a more modern algorithm such as sha256, John the Ripper can do a rather measly 200,000 hashes per second.  At that rate it would take 3 minutes to generate a 4 character rainbow table.  Fast, but not fast enough for our purposes.

Now, let’s look at what a GPU can do.  Bitcoin currently uses 2 internal sha256 rounds to compute a single “hash”.  So when we look at the performance numbers they are reporting, we need to realize that’s for 2 sha256 hashes.  If we look at the fastest single card setup (an ATI 5970), it does over 860 million bitcoin hashes per second.  That’s over 1.720 billion sha256 hashes per second!  And a 3 card setup can hit almost 4.2 billion sha256 hashes per second.  So let’s take a look at our chart again, this time for a salted sha256 password:

Length Of Password Number Of Possibilities CPU GPU
4 characters 35,153,041 3 minutes 0.0083 seconds
5 characters 2,706,784,157 3.75 hours 0.64 seconds
6 characters 208,422,380,089 12 days 49 seconds
7 characters 16,048,523,266,853 2.5 years 1.06 hours
8 characters 1,235,736,291,547,681 195 years 3.4 days

So, for about $2100, we can have a set of 3 GPUs that can brute force any printable 8 character password possible in about 3.4 days. And that’s at the absolute worst case possible.  If we started to do intelligence things such as using a dictionary as the base for our search, we could likely find that password much, much faster.

The Other Benefit To Brute Forcing

The other benefit to brute forcing, is you invest practically nothing in the algorithm.  For a rainbow table you need to provide both cpu time to generate (a lot of it) and storage space (a lot of it). Not to mention thinks like disk seek time.  An average high end hard drive has a seek time of around 4ms.  So to merely read the data stored in a rainbow table for a 4 character password, you’re spending about 1/2 the time taken by the gpu just seeking in the database file.  Then, the computer needs to do a full scan of all of the data to search for the hash value.  So in the end, for a 4 character password, it’s likely cheaper in all accounts just to brute force it on a GPU than it is to generate a rainbow table.

A Word On Entropy

All of the numbers that I’ve used in this article are based off the assumption that password choice is fully random.  That’s the worst case situation.  That means that given n bits of data, it would take on average 2^(n-1) tries to have a 50% chance of guessing it.  So for a pure random 8 character password (printable characters), you’d need on average about 1.7 days on a GPU to brute force it.  Each character in our pure random password has about 6.26 bits of entropy (due to the 77 possible characters, instead of 256).  So an 8 character password has about 50 bits of entropy (and this is true, since 2^50 is about 10^15, which is what we calculated above).

But that’s not the way of the world.  The vast majority of passwords are user generated.  And user generated passwords tend to have significantly less entropy.  In fact, according to NIST (Appendix A), a 8 character password with symbols and numbers would only have about 18 bits of entropy.  It could be 24 bits if there existed both upper-case and lower-case characters.  But 2^24 is only about 16 million.  So notice that our 4 character random password is actually on average twice as strong as a user-selected 8 character password.  In the worst case, it would take the full 2^50 tries to guess a user selected 8 character password, so that’s the same.  But the 50% chance occurs much sooner at 2^23 than the random password at 2^49.

Speaking of entropy, we’re going to revisit the concept in another post soon (specifically about what a recent web-comic pontificated)…


The overall point is simple.  A rainbow table is a useful tool.  But it’s also an outdated tool that doesn’t mean nearly as much as it used to.  In the era of the cheap GPU, brute forcing is more than a possibility, it’s a fact.  Using an algorithm because it’s resistant to a rainbow table is not only obsolete, it bypasses the bigger problem.  You need to hash your passwords so that they are hard to brute force.  If they are hard to brute force, they will be hard to rainbow table as well.

Presently, there are about 3 algorithms for PHP that will provide adequate defense against brute forcing. BCrypt (called Blowfish in PHP’s docs), PBKDF2 and PHPASS‘s internal function (in order from strongest to weakest).  It’s worth noting that projects such as Drupal, PHPBB and WordPress have all implemented either PHPASS or a derivative thereof.  All of the algorithms accept a “work factor” which controls how much CPU time the algorithm takes.  By artificially slowing down the hash, brute forcing is made significantly harder (but not impossible).

Use an algorithm that has protections against brute forcing, as protecting against rainbow tables alone is a lost battle…

Posted by Anthony Ferrara at 8/16/2011 10:00:00 AM


Herramientas gratuitas para UML

Existen herramientas gratuitas de buena caliadad para UML. Tanto Netbeans como Eclipse soportan esta funcionalidad con el ciclo completo de desarrollo desde generación de código hasta reingenieria. Esto, claro, si se quiere trabajar en Java. En .Net no he encontrado este grado de funcionalidad en herramientas Open Source. Una opción de bajo costo, relativo a RUP y similares, es Visual UML. Visual Paradigm tiene una edición limitada sin costo, Smart Development Environment Community Edition for Visual Studio.

UML, ejemplo sencillo sobre Modelado de un Proyecto Introducción a UML

Zachman y los seis honestos de Kipling

I keep six honest serving-men

(They taught me all I knew)

Their names are What and Why and When And How and Where and Who

Uno de los dichos de mi buen amigo Ángel es sobre la gracia del gringo, ese gringo mítico de poderes de Comic, para tomar algún concepto del sentido común y convertirlo en un producto mercadeable. Un ejemplo interesante de esto es el marco de Zachman para arquitecturas empresariales. Todo un icono en la comunidad de arquitectura de datos. Se basa en el patrón de analizar problemas con una matriz de puntos a revisar. En el marco de Zachman las columnas corresponden a los seis interrogantes en ingles y las hileras a diferentes roles en el desarrollo de una aplicación empresarial. De este sencillo concepto Zachman desarrolla todo una teoría detallada de cómo documentar y administrar un proyecto de desarrollo de un sistema empresarial basado en un modelo entidad-relación.

WHAT’S WRONG WITH THE ZACHMAN FRAMEWORK? Extending the RUP with the Zachman Framework

Eclipse, herramienta universal – IDE abierto y extensible

Eclipse: una herramienta profesional al alcance de todos Pese a que Eclipse está escrito en su mayor parte en Java (salvo el núcleo) y que su uso más popular sea como un IDE para Java, Eclipse es neutral y adaptable a cualquier tipo de lenguaje, por ejemplo C/C++, Cobol, C#, XML, etc. La característica clave de Eclipse es la extensibilidad. Eclipse es una gran estructura formada por un núcleo y muchos plug-ins que van conformando la funcionalidad final. La forma en que los plug-ins interactúan es mediante interfaces o puntos de extensión; así, las nuevas aportaciones se integran sin dificultad ni conflictos.

Eclipse fue producto de una inversión de cuarenta millones de dólares de IBM en su desarrollo antes de ofrecerlo como un producto de código abierto al consorcio Eclipse.org que estaba compuesto inicialmente por Borland e IBM. IBM sigue dirigiendo el desarrollo de Eclipse a través de su subsidiaria OTI (Object Technologies International), creadora de Eclipse. OTI fue adquirida por IBM en 1996 y se consolidó como gran empresa de desarrollo de herramientas orientadas a objeto (O.O.) desde la popularidad del lenguaje Smalltalk. OTI era la división de IBM en la que se generaron los productos Visual Age, que marcaron el estándar de las herramientas de desarrollo Orientado a objetos. Muchos conceptos pioneros en Smalltalk fueron aplicados en Java, creando Visual Age for Java (VA4J). VA4J fue escrito en Smalltalk. Eclipse es una reescritura de VA4J en Java. La base para Eclipse es la Plataforma de cliente enriquecido (del Inglés Rich Client Platform RCP). Los siguientes componentes constituyen la plataforma de cliente enriquecido:

Plataforma principal – inicio de Eclipse, ejecución de plugins OSGi – una plataforma para integrar distribuciones. El Standard Widget Toolkit (SWT) – Un widget toolkit portable. JFace – manejo de archivos, manejo de texto, editores de texto El Workbench de Eclipse – vistas, editores, perspectivas, asistentes

Los widgets de Eclipse están implementados por un herramienta de widget para Java llamada SWT, a diferencia de la mayoría de las aplicaciones Java, que usan las opciones estándar Abstract Window Toolkit (AWT) o Swing. La interfaz de usuario de Eclipse también tiene una capa GUI intermedia llamada JFace, la cual simplifica la construcción de aplicaciones basada en SWT. El entorno integrado de desarrollo (IDE) de Eclipse emplea módulos (plug-in) para proporcionar toda su funcionalidad al frente de la plataforma de cliente rico, a diferencia de otros entornos monolí­ticos donde las funcionalidades están todas incluidas, las necesite el usuario o no. Este mecanismo de módulos es una plataforma ligera para componentes de software. Se provee soporte para Java y CVS en el SDK de Eclipse. En cuanto a las aplicaciones clientes, eclipse provee al programador con frameworks muy ricos para el desarrollo de aplicaciones gráficas, definición y manipulación de modelos de software, aplicaciones web, etc. Por ejemplo, GEF (Graphic Editing Framework – Framework para la edición gráfica) es un plugin de eclipse para el desarrollo de editores visuales que pueden ir desde procesadores de texto wysiwyg hasta editores de diagramas UML, interfaces gráficas para el usuario (GUI), etc. El SDK de Eclipse incluye las herramientas de desarrollo de Java, ofreciendo un IDE con un compilador de Java interno y un modelo completo de los archivos fuente de Java. Esto permite técnicas avanzadas de refactorización y análisis de código. El IDE también hace uso de un espacio de trabajo, en este caso un grupo de metadata en un espacio para archivos plano, permitiendo modificaciones externas a los archivos en tanto se refresque el espacio de trabajo correspondiente. Núcleo: su tarea es determinar cuales son los plug-ins disponibles en el directorio de plug-ins de Eclipse. Cada plug-in tiene un fichero XML manifest que lista los elementos que necesita de otros plug-ins así­ como los puntos de extensión que ofrece. Como la cantidad de plug-ins puede ser muy grande, solo se cargan los necesarios en el momento de ser utilizados con el objeto de minimizar el tiempo de arranque de Eclipse y recursos. Entorno de trabajo: maneja los recursos del usuario, organizados en uno o más proyectos. Cada proyecto corresponde a un directorio en el directorio de trabajo de Eclipse, y contienen archivos y carpetas. Interfaz de usuario: muestra los menús y herramientas, y se organiza en perspectivas que configuran los editores de código y las vistas. A diferencia de muchas aplicaciones escritas en Java, Eclipse tiene el aspecto y se comporta como una aplicación nativa. Esta programada SWT (Standard Widget Toolkit) y Jface (juego de herramientas construida sobre SWT), que emula los gráficos nativos de cada sistema operativo. Este ha sido un aspecto discutido sobre Eclipse, porque SWT debe ser portada a cada sistema operativo para interactuar con el sistema gráfico. En los proyectos de Java puede usarse AWT y Swing salvo cuando se desarrolle un plug-in para Eclipse. Para descargar Eclipse existen distribuciones con diferentes combinaciones de plug-ins dependiendo del uso que se le quiera dar a la herramienta. Un problema que se presenta con estas distribuciones es que en Windows XP el descompresor integrado a veces falla y es preferible usar un programa externo como 7-zip, WinZIP, o info-zip


¿Qué es Subversion?

Subversion es un sistema de control de versiones libre y de código fuente abierto. Es decir, Subversion maneja ficheros y directorios a través del tiempo. Hay un Árbol de archivos en un repositorio central. El repositorio es como un servidor de archivos ordinario, excepto que recuerda todos los cambios hechos a sus archivos y directorios. Esto permite recuperar versiones antiguas de datos o examinar el historial de cambios de los mismos. En este aspecto, mucha gente piensa en los sistemas de versiones como en una especie de máquina del tiempo.

Subversion proporciona:

Versionado de directorios
CVS solamente lleva el historial de archivos individuales, pero Subversion implementa un sistema de archivos versionado virtual que sigue los cambios sobre árboles de directorios completos a través del tiempo. Ambos, archivos y directorios, se encuentran bajo el control de versiones.
Verdadero historial de versiones
CVS está limitado al versionado de archivos. Operaciones como copiar y renombrar, las cuales pueden ocurrir sobre archivos, pero realmente son cambios al contenido del directorio en el que se encuentran, no son soportadas por CVS. Adicionalmente, en CVS no puede reemplazar un archivo versionado con algo nuevo que lleve el mismo nombre sin que el nuevo elemento herede el historial del archivo antiguo que quizás sea completamente distinto al anterior. Con Subversion, se puede añadir, borrar, copiar, y renombrar archivos y directorios. Cada fichero nuevo añadido comienza con un historial nuevo, limpio y completamente suyo.
Envíos atómicos
Una colección cualquiera de modificaciones o bien entra por completo al repositorio, o bien no lo hace en absoluto. Ésto permite a los desarrolladores construir y enviar los cambios como fragmentos lógicos e impide que ocurran problemas cuando sólo una parte de los cambios enviados lo hace con éxito.
Versionado de metadatos
Cada archivo o directorio tiene un conjunto de propiedades claves y sus valores asociado. Se puede crear y almacenar cualquier par arbitrario de clave/valor. Las propiedades son versionadas a través del tiempo, al igual que el contenido de los ficheros.
Elección de las capas de red
Subversion tiene una noción abstracta del acceso al repositorio, facilitando a las personas implementar nuevos mecanismos de red. Subversion puede conectarse al servidor HTTP Apache como un módulo de extensión. Ésto proporciona a Subversion una gran ventaja en estabilidad e interoperabilidad, y acceso instantáneo a las caracterí­sticas existentes que ofrece este servidor: autenticación, autorización, compresión de la conexión, etcétera. También tiene disponible un servidor de Subversion independiente, y más ligero. Este servidor habla un protocolo propio, el cual puede ser encaminado fácilmente a través de un túnel SSH.
La versión de default trabaja con apache 2.0 pero es posible bajar un versión para apache 2.2.4
Manipulación consistente de datos
Subversion expresa las diferencias del archivo usando un algoritmo de diferenciación binario, que funciona idénticamente con ficheros de texto (legibles para humanos) y ficheros binarios (ilegibles para humanos). Ambos tipos de ficheros son almacenados igualmente comprimidos en el repositorio, y las diferencias son transmitidas en ambas direcciones a través de la red.
Ramificación y etiquetado eficientes
El coste de ramificación y etiquetado no necesita ser proporcional al tamaño del proyecto. Subversion crea ramas y etiquetas simplemente copiando el proyecto, usando un mecanismo similar al enlace duro. De este modo estas operaciones toman solamente una cantidad de tiempo pequeña y constante.

Subversion almacena todos los datos versionados en un repositorio central. TortoiseSvn is un proyecto hermano que proporciona integración con Windows explorer. Vea Capítulo 6, Configuración del servidor para aprender acerca de los diferentes tipos de procesos servidor disponibles y cómo configurarlos. svnserver puede correr como un servicio de Windows. Para crear el servicio http://svn.haxx.se/dev/archive-2006-11/0348.shtmlhttp://httpd.apache.org/download.cgi



ASP.Net Security

tecnologias ASP.NetMake sure you are very familiar with the following terms:

  • Authentication. Positively identifying the clients of your application; clients might include end-users, services, processes or computers.
  • Authorization. Defining what authenticated clients are allowed to see and do within the application.
  • Secure Communications. Ensuring that messages remain private and unaltered as they cross networks.
  • Impersonation. This is the technique used by a server application to access resources on behalf of a client. The client’s security context is used for access checks performed by the server.
  • Delegation. An extended form of impersonation that allows a server process that is performing work on behalf of a client, to access resources on a remote computer. This capability is natively provided by Kerberos on Microsoft® Windows® 2000 and later operating systems. Conventional impersonation (for example, that provided by NTLM) allows only a single network hop. When NTLM impersonation is used, the one hop is used between the client and server computers, restricting the server to local resource access while impersonating.
  • Security Context. Security context is a generic term used to refer to the collection of security settings that affect the security-related behavior of a process or thread. The attributes from a process’ logon session and access token combine to form the security context of the process.
  • Identity. Identity refers to a characteristic of a user or service that can uniquely identify it. For example, this is often a display name, which often takes the form authority/user name.


There are a number of overarching principles that apply to the guidance. The following summarizes these principles:

  • Adopt the principle of least privilege. Processes that run script or execute code should run under a least privileged account to limit the potential damage that can be done if the process is compromised. If a malicious user manages to inject code into a server process, the privileges granted to that process determine to a large degree the types of operations the user is able to perform. Code that requires additional trust (and raised privileges) should be isolated within separate processes.The ASP.NET team made a conscious decision to run the ASP.NET account with least privileges.
  • Use defense in depth. Place check points within each of the layers and subsystems within your application. The check points are the gatekeepers that ensure that only authenticated and authorized users are able to access the next downstream layer.
  • Don’t trust user input. Applications should thoroughly validate all user input before performing operations with that input. The validation may include filtering out special characters. This preventive measure protects the application against accidental misuse or deliberate attacks by people who are attempting to inject malicious commands into the system. Common examples include SQL injection attacks, cross-site scripting attacks, and buffer overflow.
  • Use secure defaults. A common practice among developers is to use reduced security settings, simply to make an application work. If your application demands features that force you to reduce or change default security settings, test the effects and understand the implications before making the change.
  • Don’t rely on security by obscurity. Trying to hide secrets by using misleading variable names or storing them in odd file locations does not provide security. In a game of hide-and-seek, it’s better to use platform features or proven techniques for securing your data.
  • Check at the gate. You don’t always need to flow a user’s security context to the back end for authorization checks. Often, in a distributed system, this is not the best choice. Checking the client at the gate refers to authorizing the user at the first point of authentication (for example, within the Web application on the Web server), and determining which resources and operations (potentially provided by downstream services) the user should be allowed to access.If you design solid authentication and authorization strategies at the gate, you can circumvent the need to delegate the original caller’s security context all the way through to your application’s data tier.
  • Assume external systems are insecure. If you don’t own it, don’t assume security is taken care of for you.
  • Reduce surface area. Avoid exposing information that is not required. By doing so, you are potentially opening doors that can lead to additional vulnerabilities. Also, handle errors gracefully; don’t expose any more information than is required when returning an error message to the end user.
  • Fail to a secure mode. If your application fails, make sure it does not leave sensitive data unprotected. Also, do not provide too much detail in error messages; meaning don’t include details that could help an attacker exploit a vulnerability in your application. Write detailed error information to the Windows event log.
  • Remember you are only as secure as your weakest link. Security is a concern across all of your application tiers.
  • If you don’t use it, disable it. You can remove potential points of attack by disabling modules and components that your application does not require. For example, if your application doesn’t use output caching, then you should disable the ASP.NET output cache module. If a future security vulnerability is found in the module, your application is not threatened.

The following steps identify a process that will help you develop an authentication and authorization strategy for your application:

  1. Identify resources
  2. Choose an authorization strategy
  3. Choose the identities used for resource access
  4. Consider identity flow
  5. Choose an authentication approach
  6. Decide how to flow identity

Building Secure ASP.NET Applications: Authentication, Authorization, and Secure Communication

Natas; Crónica del virus mexicano

Tomado de http://vx.netlux.org/lib/agm00.html

En 1992 Little Loc se registro en Prodigy para buscar información sobre virii. Little Loc, alias James Gentile, a los 16 años habí­a escrito un virus mutante que se dispersaba rápidamente. El virus, Satan Bug, estaba escrito de manera que el proceso mismo de rastrear un disco en busca de infección infectaba todos los ejecutables en el mismo.

Satan Bug era el nombre de una teleserie de los 70s. ((Aunque Little Loc nunca vio la serie, vio el nombre en el TVguí­a y le gusto. )) El icono que inspiro la creación de Satan Bug fue el trabajo de Dark Avenger, ((un programador búlgaro de virus y su virus Eddie o Dark Avenger. Eddie usaba los mecanismos de rastreo de antivirus para infectar una maquina y gradualmente corrompí­a el disco duro del anfitrión. Una muerta lenta y dolorosa bajo las cuchillas del vengador tenebroso.))

Little Loc tenía talento natural para escribir virii, un arte que aprendió sin maestro directo ni entrenamiento formal en programación. ((Siguiendo el modelo de Eddie, Satan Bug atacaba el command shell al instalarse en memoria.)) Adicionalmente a los poderes del vengador tenebroso, Satan bug estaba encriptado y se escondí­a en la memoria del computador. Las características de encriptación estaban basadas en la ballena, un virus alemán. La ballena era una pesada navaja suiza de trucos para esconderse de los antivirus.

Little Loc publico el código fuente de Satan Bug en un boletín de noticias y se dedico activamente a diseminar su código. ((Su motivación era ser reconocido por su habilidad técnica.)) Eventualmente, en 1993, Satan Bug infecto las maquinas del servicio secreto en Washington D.C. y las saco de servicio por 3 dí­as. El servicio secreto siguió una línea de investigación con la hipótesis de que el virus era un esfuerzo deliberado para atacar maquinas del gobierno de Estados Unidos.

Little Loc cambió su nombre por Priest y escribió Jackal. ((Jackal fue escrito como un contraataque contra TBClean, un antivirus producido por la compañí­a holandesa Thunderbyte, del investigador de virus Frans Veldman.)) Un derivado de Jackal fue el Natas. En su espí­ritu de medida retaliatoria, Natas formatea el disco duro cuando detecta la presencia de TBClean.

Los mecanismos de detección de programas antivirus de Jackal los incluyo Priest en Natas (Satan al revés), que llego a la ciudad de México en la primavera de 1994.

De acuerdo a la tradición, un consultor que vendía servicios antivirus en la ciudad de México se encargo de propagarlo vigorosamente. Debido a ignorancia e incompetencia, adicionada con entusiasmo empresarial y poder de convocatoria, este pendejo con iniciativa logro difundir Natas en México tan rápido que la leyendo urbana lo ubica como un software de origen mexicano. Un script tragicómico digno del mejor guionista.

El consultor, al visitar los boletines de noticias dedicados a virii, contamino un diskette con Natas. ((El software que usaba detectaba el virus en programas, pero no en el sector MBR (Master Boot Record) del disco duro.)) El consultor iba con sus clientes, corrí­a su software de rastreo de su diskette infectado y detectaba la infección de Natas que el mismo provocaba. Alarmado corría a la siguiente maquina y repetía el proceso, infectando todas las maquinas del lugar. Inmediatamente iba a visitar a sus mejores clientes con la noticia de que había una epidemia de Natas y que más les valía rastrear sus maquinas, con el software que el traí­a, que podía detectar al Natas. Entonces procedía a infectar todas las maquinas y a continuar el proceso con el vecino de al lado. Seguramente penso que eso de Satan iba ne sero cuando despues de formatar las maquinas el virus resurguía de la nada. Espeluznante!

Natas llego a México del sur de California. El consultor era visitante frecuente de BBS en Santa Clarita que tenían el Natas y su código fuente en la revista 40Hex. El buen cuate bajo el virus sin entender que al diablo le puedes vender el alma, pero no pedirla de regreso. En mayo de 1994, un mes después, desesperadamente el consultor buscaba ayuda en los boletines de noticias.

Natas era un programa tí­pico de Priest. Estando en memoria, hace parecer que programas infectados no lo estaban. Copia una copia limpia de MBR y se la muestra al usuario para fintarlo de que todo estaba bien si lo revisa. Natas infectaba diskettes y utiliza el rastreo del antivirus para diseminarse.

Yo en lo personal tuve una experiencia similar a la del cuento. Tenia una Compaq Presario que me estaba dando problemas y solicite la vista de un técnico de Compaq para que revisara la maquina. El técnico se tuvo que retirar sin dar le servicio porque todos sus diskettes con utilerías de diagnostico estaban infectados con un virus.