Nvidia’s Mental Ray high-performance 3D-rendering software has a vulnerability that could be exploited to compromise clusters of specialized computers called render farms, according to researchers from ReVuln.”There is a vulnerability affecting Nvidia mental ray (raysat) version 3.11.1.10, which allows a malicious user to load arbitrary DLLs on a victim system, thus an attacker can take control over a whole render farm by simply injecting a malicious remote library,” said Luigi Auriemma and Donato Ferrante, security researchers and founders of Malta-based vulnerability research ReVuln, Tuesday in a research paper.The Nvidia Mental Ray can use CUDA-enabled consumer or professional GPUs like the Nvidia GeForce, Quadro, and Tesla models for parallel rendering.It’s commonly used in the film industry for CGI (computer-generated imagery) effects, but also in industries that rely on computer-aided design (CAD).Mental Ray is available as a stand-alone application for Windows, Mac, and Linux that can be installed and used on dedicated render machines.

However, it is also integrated into third-party software like Autodesk 3ds Max, Autodesk Maya, Cinema 4D, and others.A render farm’s computing power varies depending on its size.Industrial Light & Magic, an American visual effects company, used a render farm with access to 5,700 processor cores when it worked on the Transformers 2 movie in 2009.On Windows, Nvidia Mental Ray runs as a system service and listens for incoming connections on port 7520, the ReVuln researchers said.bitcoin fbi auctionTo exploit the vulnerability, an attacker just needs to send a malicious packet to the affected systems from a compromised computer on the same network, they said.Post-exploitation scenarios could include using compromised render farms for password cracking or mining bitcoins, since both tasks can be distributed across many GPUs, the researchers said.An example of a malicious packet that triggers the vulnerability in the Mental Ray software was included in ReVuln’s research paper, but the company did not report the issue to Nvidia.ethereum gtx 1080

ReVuln discloses the vulnerabilities found by its researchers publicly or sells the information to third parties through a subscription-based vulnerability intelligence service.Nvidia did not immediately respond to a request for comment.To comment on this article and other PCWorld content, visit our Facebook page or our Twitter feed.coinbase litecoinNEXT POST Nvidia cards gained massive hashrate increase from the latest Cudaminer release (18 December 2013).bitcoin mutual fund indiaCUDA Core is the term Nvidia uses to call the shaders in its GPUs.litecoin miner shopThe Cudaminer is designed specifically for Nvidia GPU mining with Cuda accelerated mining application for Litecoin and Scrypt based altcoins.ethereum foundation members

There would be a noticeable speed increase compared to OpenCL based miners.Download Cudaminer-2013-12-18.zip (latest version as at 19 Jan 2014) or look for the latest version from the official link.Check your GPU Before going into the configuration, you would want to know which GPU that you have, so that you will find out the compute version that it is using.bitcoin mlm programIf you are not sure, you can install GPU-Z to find out.doge coin btc-eAlso make sure that you have the latest drivers installed for your Nvidia GPU.php bitcoin nodeYou can check this out at Nvidia’s download section.Compute version From your Nvidia GPU model, identify the compute version that the card is using, so that you would know which kernel prefix is suitable.Compute 1.0 G80, G92, G92b, G94, G94b GeForce GT 420*, GeForce 8800 Ultra, GeForce 8800 GTX, GeForce GT 340*, GeForce GT 330*, GeForce GT 320*, GeForce 315*, GeForce 310*, GeForce 9800 GT, GeForce 9600 GT, GeForce 9400GT, Quadro FX 5600, Quadro FX 4600, Quadro Plex 2100 S4, Tesla C870, Tesla D870, Tesla S870 Compute 1.1 G86, G84, G98, G96, G96b, G94, G94b, G92, G92b GeForce G110M, GeForce 9300M GS, GeForce 9200M GS, GeForce 9100M G, GeForce 8400M GT, GeForce G105M, Quadro FX 4700 X2, Quadro FX 3700, Quadro FX 1800, Quadro FX 1700, Quadro FX 580, Quadro FX 570, Quadro FX 470, Quadro FX 380, Quadro FX 370, Quadro FX 370 Low Profile, Quadro NVS 450, Quadro NVS 420, Quadro NVS 290, Quadro NVS 295, Quadro Plex 2100 D4, Quadro FX 3800M, Quadro FX 3700M, Quadro FX 3600M, Quadro FX 2800M, Quadro FX 2700M, Quadro FX 1700M, Quadro FX 1600M, Quadro FX 770M, Quadro FX 570M, Quadro FX 370M, Quadro FX 360M, Quadro NVS 320M, Quadro NVS 160M, Quadro NVS 150M, Quadro NVS 140M, Quadro NVS 135M, Quadro NVS 130M, Quadro NVS 450, Quadro NVS 420, Quadro NVS 295 Compute 1.2 GT218, GT216, GT215 GeForce GT 240, GeForce GT 220*, GeForce 210*, GeForce GTS 360M, GeForce GTS 350M, GeForce GT 335M, GeForce GT 330M, GeForce GT 325M, GeForce GT 240M, GeForce G210M, GeForce 310M, GeForce 305M, Quadro FX 380 Low Profile, NVIDIA NVS 300, Quadro FX 1800M, Quadro FX 880M, Quadro FX 380M, NVIDIA NVS 300, NVS 5100M, NVS 3100M, NVS 2100M Compute 1.3 GT200, GT200b GeForce GTX 280, GeForce GTX 275, GeForce GTX 260, Quadro FX 5800, Quadro FX 4800, Quadro FX 4800 for Mac, Quadro FX 3800, Quadro CX, Quadro Plex 2200 D2, Tesla C1060, Tesla S1070, Tesla M1060 Compute 2.0 GF100, GF110 GeForce GTX 590, GeForce GTX 580, GeForce GTX 570, GeForce GTX 480, GeForce GTX 470, GeForce GTX 465, GeForce GTX 480M, Quadro 6000, Quadro 5000, Quadro 4000, Quadro 4000 for Mac, Quadro Plex 7000, Quadro 5010M, Quadro 5000M, Tesla C2075, Tesla C2050/C2070, Tesla M2050/M2070/M2075/M2090 Compute 2.1 GF104, GF106 GF108，GF114, GF116, GF119 GeForce GTX 560 Ti, GeForce GTX 550 Ti, GeForce GTX 460, GeForce GTS 450, GeForce GTS 450*, GeForce GT 640 (GDDR3), GeForce GT 630, GeForce GT 620, GeForce GT 610, GeForce GT 520, GeForce GT 440, GeForce GT 440*, GeForce GT 430, GeForce GT 430*, GeForce GTX 675M, GeForce GTX 670M, GeForce GT 635M, GeForce GT 630M, GeForce GT 625M, GeForce GT 720M, GeForce GT 620M, GeForce 710M, GeForce 610M, GeForce GTX 580M, GeForce GTX 570M, GeForce GTX 560M, GeForce GT 555M, GeForce GT 550M, GeForce GT 540M, GeForce GT 525M, GeForce GT 520MX, GeForce GT 520M, GeForce GTX 485M, GeForce GTX 470M, GeForce GTX 460M, GeForce GT 445M, GeForce GT 435M, GeForce GT 420M, GeForce GT 415M, GeForce 710M, GeForce 410M, Quadro 2000, Quadro 2000D, Quadro 600, Quadro 410, Quadro 4000M, Quadro 3000M, Quadro 2000M, Quadro 1000M, NVS 5400M, NVS 5200M, NVS 4200M Compute 3.0 GK104, GK106, GK107 GeForce GTX 770, GeForce GTX 760, GeForce GTX 690, GeForce GTX 680, GeForce GTX 670, GeForce GTX 660 Ti, GeForce GTX 660, GeForce GTX 650 Ti BOOST, GeForce GTX 650 Ti, GeForce GTX 650, GeForce GTX 780M, GeForce GTX 770M, GeForce GTX 765M, GeForce GTX 760M, GeForce GTX 680MX, GeForce GTX 680M, GeForce GTX 675MX, GeForce GTX 670MX, GeForce GTX 660M, GeForce GT 750M, GeForce GT 650M, GeForce GT 745M, GeForce GT 645M, GeForce GT 740M, GeForce GT 730M, GeForce GT 640M, GeForce GT 640M LE, GeForce GT 735M, GeForce GT 730M, Quadro K5000, Quadro K4000, Quadro K2000, Quadro K2000D, Quadro K600, Quadro K500M, Tesla K10 Compute 3.5 GK110, GK208 GeForce GTX TITAN, GeForce GTX 780, GeForce GT 640 (GDDR5), Quadro K6000, Tesla K20 * – OEM-only products CUDA kernels do the computation.

Which one we select and in which configuration it is run greatly affects performance.CUDA kernel launch configurations are given as a character string, e.g.F16x2 prefix blocks x warps Available kernel prefixes are: L – Legacy cards (Compute 1.x) F – Fermi cards (Compute 2.x) S – Kepler cards (currently compiled for Compute 1.2) – formerly best for Kepler K – Kepler cards (Compute 3.0) – based on Dave Andersen’s work.Now best for Kepler.T – Titan, GTX 780 and GK208 based cards (Compute 3.5) X – Experimental kernel.Currently requires Compute 3.5 Examples: L27x3 is a launch configuration that works well on GTX 260 F28x4 is a launch configuration that works on Geforce GTX 460 K290x2 is a launch configuration that works on Geforce GTX 660Ti T30x16 is a launch configuration that works on GTX 780Ti.Cudaminer configuration Most of the time you can start mining without specifying any special options and let autotune select the best option for you like this: :3334 -O [WORKERNAME]:[PASSWORD] I will list the configuration for some Nvidia cards: GeForce GTX 560 Ti :3334 -O [WORKERNAME]:[PASSWORD] GeForce GTX 660 :3334 -O [WORKERNAME]:[PASSWORD] GeForce GTX 670 :3334 -O [WORKERNAME]:[PASSWORD] GeForce GTX 780 :3334 -O [WORKERNAME]:[PASSWORD] Update 2/3/2014 – Check out the latest update of cudaMiner with support for Maxwell architecture.