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New Password Recovery Technique Uses CPU and GPU Together
BaCa writes to mention that a new hardware/software combination has been created by a company called ElcomSoft that will reportedly allow cryptography professionals to build cheap PCs that work like supercomputers for the specific task of retrieving lost passwords. Utilizing a combination of the CPU and the GPU the task of brute forcing a password may be reduced by as much as a factor of 25. "Until recently, graphic cards' GPUs couldn't be used for applications such as password recovery. Older graphics chips could only perform floating-point calculations, and most cryptography algorithms require fixed-point mathematics. Today's chips can process fixed-point calculations. And with as much as 1.5 Gb of onboard video memory and up to 128 processing units, these powerful GPU chips are much more effective than CPUs in performing many of these calculations."
So what, will hackers be able to use my computer to crack my password 25 times faster now?
now IT departments will require passwords to be 30 characters long, with at least 2 digits, at least 2 puncuation marks, mixed case, and use Unicode characters from at least 8 different international languages.
Table-ized A.I.
If brute force isn't working... you aren't using enough of it.
Weeks of coding saves hours of planning.
Oh wait, both.
Even people that believe in pre-destiny look both ways before crossing the street.
Pricing for these apps is pretty steep at $1,299 per machine license. Well, maybe not so steep if you consider how valuable it could be for you. It doesn't say if that has the GPU utilization with it yet or not.
Also, I wonder if they've investigated using SLI & CrossFire with these. That seems like something obvious to me but not included in the article. I'm unaware of their implementation but it sounds like it could be parallelized--and accross 2 or even 4 cards, that could get hilariously powerful.
My work here is dung.
"Password Recovery" sounds so much more benign than "Cracking Passwords".
Hello, Mr. Orwell. *wave*
I can now release the 12,000 monkeys I kidnapped for the task.
Table-ized A.I.
What seems to have been missed in the discussion so far is that this company is applying for a patent on their technique, which they claim is "revolutionary." I really hope that this doesn't get granted, as it would open a whole new realm of stupid patents for "X on a graphics card," which is about as stupid a patent as "X on the internet."
This project has been around for a long time: http://www.gpgpu.org/ Though I agree modern GPU's are even more useful for general purpose computing.
Petter Nordahl-Hagen's Offline NT Password & Registry Editor: http://home.eunet.no/~pnordahl/ntpasswd/
NOTE: Tested on: NT 3.51, NT 4 (all versions and SPs), Windows 2000 (all versions & SPs), Windows XP (all versions, also SP2), Windows Server 2003 (all SPs), Vindows Vista 32 and 64 bit.
I'm just wondering, should I take the summary as intentionally ironic (i.e. as if it had referred to an operating system "by a company called Microsoft"), or should I assume it was written by someone *fascinatingly* oblivious to the recent history of decryption software and the disputed legalities thereof? An informed, non-ironic summary would simply say, "...by ElcomSoft...", of course.
For any of you who may have been living under a rock (possibly on another planet), ElcomSoft is the company that was employing Dmitry Sklyarov, who was arrested in the US on DMCA charges when he'd come to present at a conference. Wikipedia has more.
Fail.
...allow cryptology professionals to build affordable PCs that will work like supercomputers when recovering lost passwords. Cut and pasted from "How to write with spin for dummies"Fail.
...will be incorporating this patent-pending technology into their entire family of enterprise password recovery applications. Corporate press release copy and paste == Fail.Numerous grammatical errors == Fail.
Add 1 letter and you've increased the time it takes to hack by 26x (although it's probably closer to 100x with punctuation and the like). So 25x is irrelevant. So is 250x. Only something that makes it non-exponential would really make a difference.
Cthon98> hey, if you type in your pw, it will show as stars
Cthon98> ********* see!
AzureDiamond> hunter2
AzureDiamond> doesnt look like stars to me
Cthon98> AzureDiamond> *******
Cthon98> thats what I see
AzureDiamond> oh, really?
Cthon98> Absolutely
AzureDiamond> you can go hunter2 my hunter2-ing hunter2
AzureDiamond> haha, does that look funny to you?
Cthon98> lol, yes. See, when YOU type hunter2, it shows to us as *******
AzureDiamond> thats neat, I didnt know IRC did that
Cthon98> yep, no matter how many times you type hunter2, it will show to us as ******
AzureDiamond> awesome!
AzureDiamond> wait, how do you know my pw?
Cthon98> er, I just copy pasted YOUR ******'s and it appears to YOU as hunter2 ause its your pw
AzureDiamond> oh, ok.
Why is the GPU a processor dedicated to nothing but "pretty graphics" so much more powerful than the central multi-purpose processor even at the things like number-crunching?
You need to rephrase your question, because it makes an incorrect assumption. Here:
Why is the GPU a processor dedicated to nothing but "pretty graphics" so much more powerful than the central multi-purpose processor especially at the things like number-crunching?
The answer is obvious if you think about it: those "pretty graphics" are a huge number crunching problem. That's all there is to it. GPU's, however, aren't very good at tasks that don't do exactly the same thing huge numbers of times. This is true of most applications. Including the applications that run on the PC to control what the GPU does in stuff like what the story's talking about.
Is it because the GPU engineers can completely redo the thing from scratch whenever they want to, whereas the CPU-designers are held back by the backwards-compatibility issues?
Partially. Modern GPUs have (I think -- I don't keep up to date) 256 bit wide memory interfaces, running at close to gigahertz speed. This means they can transfer to and from their memory at about 4 times the rate a PC can. This is possible because (1) graphics card manufacturers don't mind the types of memory they use changing on a virtually model-by-model basis and (2) they also don't mind being stuck with non-expandable memory that's soldered directly onto the card right next to the GPU.
It's also because GPU engineers can sacrifice a lot of the flexibility of a PC. So what if the pipeline stalls if all 32 threads aren't doing exactly the same thing at the same time? Most of the time, they will be.
Computer Science teaches, programmers aren't supposed to have to do "tricks" like this -- you code, and the translator (compiler or intepreter) will translate from your programming language to the hardware instructions.
So why did my CS course have a module where we learned how the hardware worked? About memory hierarchies? About SISD, SIMD and MIMD processors? Why does Knuth's The Art of Computer Programming, possibly the most important book ever written on CS, approach problems at an assembly language level? Why, in my CS course, did I learn two different kinds of assembly language (one CISC, one RISC)?
Because CS is concerned with a holistic view of computers. With the fact that they are machines for executing instructions, and what can be done with those instructions. With the fact that it may be more efficient not to specify that much detail, but also the fact that, from time to time, you do need to do that.