Offensive Tools and Techniques

In this article I go over a series of examples that illustrate different tools and techniques that are often used by both sides of the force! To exemplify it, I will follow the different attack stages and will use the intrusion kill chain as methodology. This methodology consist of seven stages. Reconnaissance, weaponization, delivery, exploitation, installation, C2 and action on objectives.

offensive-logoLet’s start with Recon! The goal here is to seek information about the target, normally a person. Targeting high profile individuals might be difficult because these individuals tend to have a personalized security group that looks after them. However, using different intelligence-gathering techniques such as searching information available in a variety of public information sources you can target other personnel. Due to the human nature, people succumb to social engineering techniques and several times they provide more information than is necessary. A starting point is to harvest metadata about the organization and personnel. Normally, companies do not know what metadata they are giving way. Metadata is a golden pot of information and information such as usernames, software versions, printers, email addresses and others can be retrieved using a tool such as FOCA Metadata Analysis Tool. You can see the presentation that was given by Chema Alonso and Jose Palazon Palatko in 2010 at Defcon 18 about FOCA 2.5.  At the end the attacker will use whatever works to gather as much information as possible about employee names, position in the hierarchy, friends and relatives, hobbies, etc.

Next step, weaponization and delivery! After getting as much information as possible and performing enough recon the attacker will choose the best method to perform the attack with his available resources. Nowadays, spear phishing techniques with attached documents are very dominant and probably a good choice as attack vector. The sophistication of how a document is weaponized and delivered might correlate with the amount of resources available to the attacker. In the example below I show how you could use Metasploit to easily create a word document with a malicious macro that when executed will connect back to the attacker system and establish a command and control channel. The payload uses HTTPS as communication channel but it uses a self-signed certificate and points to an IP address and not a domain. In organization of different sizes, many times the web filtering controls are tight and use different blocking techniques that might detect and stop this type of connection. However, the attacker can register a new domain or buy an expired domain ahead of time, create a simple and realistic web page and categorize the domain in a category such as Finance or Healthcare – these are normally allowed in web filtering products and probably the SSL wouldn’t be terminated and inspected. In addition, the attacker can buy a cheap SSL certificate and make this scenario much more realistic.  In addition, Metasploit just introduced an updated traffic obfuscation technique that will make harder for security products to detect it.

Before I continue with the different tools and techniques, is worth to mention that in this article I give several examples using the Metasploit Framework. For those of you who don’t know, Metasploit framework was originally created by the legendary H.D. Moore back in 2003. Originally coded in Perl and then ported to Ruby. In 2004, Metasploit Framework 2.0 was released and had less than 20 exploits and a similar number of payloads. Today, the free version of Metasploit framework has more than 1600 exploits and more than 400 payloads. In addition many other auxiliary modules, encoders and post exploitation modules are available. The modular framework of Metasploit makes it a fantastic tool to design, build and launch exploits.

So, the picture below illustrates how to use Metasploit to create a weaponized Word document. An alternative to this technique is to use PowerShell Empire. See this article from Matt Nelson.


Then, the word document can be customized and tailored to the target. To summarize, the attacker crafts a phishing email, either with a weaponized document or malicious link. This coupled with different social engineering techniques that appeal to human nature and exploit human vulnerabilities have good probability to make the attack a success. There is other factor that might impact the success of the campaign, which is the ability of the malicious email/link to circumvent the multitude of expensive filters that are layered throughout the network boundary and reach to the endpoint. If the email reaches the endpoint, you might have a well-intentioned employee making mistakes.  If these conditions are met, the attacker will establish a foothold inside the corporate network.

The picture below depicts the steps performed by the attacker to launch the Metasploit handler that will accept the beacon from the malicious document. Then, it shows the communication received and the established session.


Next step exploitation! With a foothold in the environment and an established communication channel the attacker will act quickly, stealthy and will probably try to find avenues to exploit other systems and achieve higher privileges.  Ruben Boonen who maintains and goes by the handler @FuzzySec has wrote a very comprehensive article where he describes the different techniques that could be used to escalate privileges on a Windows environment. Another great resource is the paper “Windows Services – All roads lead to SYSTEM” from Kostas Lintovois that exemplifies several ways in which misconfigured services could be compromised.  These techniques are very useful for attackers because in many organizations normal users don’t have admin rights. Admin rights are likely a goal that all attackers aim in an enterprise environment because it facilitates their job.

Many of the techniques written by Ruben and others have been materialized in the post-exploitation framework known as PowerSploit in a module called PowerUp.ps1 which has been originally written by Will Schroeder – a brilliant security researcher that in recent years released powerful tools -. PowerSploit contains a great library of modules and scripts that help in all phases of an attack life-cycle.  The PowerUp module facilitates the discovery of conditions that would allow an attacker to execute a technique that will lead him to get a privileged account. All this done using PowerShell and can be executed from within Meterpreter using the PowerShell extension that was written by OJ Reeves and incorporated into Metasploit  This means, that attacker can run PowerUp from within Metasploit. You can read more about PowerUp on Will Schroeder blog and also get PowerUp cheat sheet from here.

The picture below illustrates this scenario, where the attacker after getting a foothold in the environment – via phishing email – verifies that the account he is operating with doesn’t have enough privileges to run additional modules such as the powerful Mimikatz. Mimikatz is a post-exploitation tool written in C and developed by Benjamin Delphy. You can read more about many of its features on Sean Metcalf Unofficial Guide to Mimikatz and Command reference here and here. However, Meterpreter contains a PowerShell module that would allow the attacker to execute PowerShell commands. In this case the attacker can load the PowerShell module, execute the necessary commands to download the PowerUp from GitHub, a site owned by the attacker or other place and then perform the Invoke-AllChecks. At the time of this writing, the PowerUp module contains 14 checks.


In this case, as you could see in the image, the conditions necessary to perform DLL hijacking are found by PowerUp module. Essentially, the system contains a directory that any authenticated user can write to and this directory is part of the %PATH% environment variable. With this the attacker can leverage the DLL search order and obtain system privileges.  In this case PowerUp suggests to use “wlbsctrl.dll”. For this to work the Windows service “IKE and AuthIP IPsec Keying Modules” needs to be running but in enterprises where workstations have VPN clients installed this is quite common. This vulnerability was discovered in 2012 by the High-Tech Bridge Security Research Lab. It leverages the Windows service “IKE and AuthIP IPsec Keying Modules”, which during startup tries to load the “wlbsctrl.dll” DLL that doesn’t exist on default Windows installations. A great explanation about how this technique works and why the vulnerability exists was written by Parvez Anwar here.  Another resource about this topic is “DLL Hijacking Like a Boss!” presentation Jake Williams and an old article from the Corelan team here.

So, now that there is an avenue to explore, the next step is for the attacker to create a DLL that matches the architecture of the target system and has the name “wlbsctrl.dll”. This can be easily done with msfvenom. This utility is very popular to create one liners commands that will generate and encode a desired payload. Msfvenom was added to Metasploit in 2011 and combines the older Msfpayload and Msfencode commands in one utility. This is showing in the figure below.


Another way to leverage this technique is to use Write-HijackDll function available in the PowerUp.ps1 module. This function will create and drop the “wlbsctrl.dll” DLL into the writable path and when the service starts the DLL will load and will add a user to local administrators with a predefined password.

An important remark in regards to the usage of PowerShell is that on some environments the security might be tight and PowerShell execution might be blocked. However, in this cases the attacker could use other techniques and use other tools such as PowerOPS: PowerShell for Offensive Operations tool written by Portuculis Lab and inspired in the PowerShell Runspace Post Exploitation Toolkit written by Cn33liz.

After that, the attacker uploads the DLL to the desired folder, the attacker can force a reboot or wait for the system to be rebooted. When the system starts, the IKEEXT service will be started and the malicious DLL will be loaded, spawning a command and control channel back to the system owned by the attacker and with SYSTEM privileges. The picture below illustrates the upload of the malicious DLL to the folder that has weak permissions and is part of the %PATH% variable. Then it follows the command and control channel that is established due to the IKEEXT service being started. Due to the high privileges the attacker can then move on and start using the powerful Mimikatz module. To start he can obtain clear text credentials by using Kerberos command.


Now, the attacker is operating under a high privileged account! With that, the attacker can move on and find a way to establish a persistence mechanism and in parallel move laterally within the environment.

Next step, installation and C2! There are a multitude of clever techniques and tools used by attackers to accomplish a persistence mechanism but in this case I would give an example of using WMI combined with PowerShell using a payload crafted by Metasploit.

WMI has gained popularity among attacker in recent years. A good resource is the presentation that Matt Graeber gave on BlackHat 15 : Abusing Windows Management Instrumentation (WMI) to Build a Persistent, Asynchronous, and Fileless Backdoor. In addition, William Ballenthin, Matt Graeber and Claudiu Teodorescu have written a great paper about the usage of WMI for both offense and defense. Furthermore, you can read the paper WMI for Detection and Response from NCCIC/ICS-CERT.

So, to achieve persistence the attacker could use Windows Management Instrumentation (WMI). The WMI will be used as a vehicle to trigger a payload to run at a particular event. This event could be a specific schedule, an event that occurred at the OS level, such as login or one of the many events supported by WMI. The payload would leverage PowerShell to perform a technique known as Reflective DLL injection which will call back to the attacker system and inject the Metasploit Meterpreter – to read more about Reflective DLL injection read this article from Dan Staples and its references -. The communication occurs over HTTPS back to the domain owned by the attacker. In sum, the attacker will only use windows built-in functionality combined with Metasploit. This arrangement of different tools and techniques lead to more powerful attacks that are harder to detect. In addition this technique leverages in memory payload that doesn’t touch disk due to the fact that uses a PE loader in memory to load the DLL and not the traditional LoadLibraryA() method. The persistence mechanism is inside the WMI repository which is likely to be outside of the radar of many defenders.

Let’s see how the attacker can build this. To craft the payload the attacker could use msfvenom utility that is part of Metasploit framework. The following picture illustrates the use of msfvenom to create the Reflective DLL injection payload using PowerShell format.


Next step would be to weaponize this payload into a Managed Object Format (MOF) script.


Next the attacker will use the Managed Object Format (MOF) compiler, Mofcomp.exe on the target machine. This utility will parse a file containing MOF statements and adds the classes and class instances defined in the file to the WMI repository. A good article about MOF is “Playing with MOF files on Windows, for fun & profit” from Jérémy Brun-Nouvion. After that, a series of wmic.exe commands can be executed to view the contents of the different classes.


These commands are executed within the Meterpreter session that was established with the DLL hijacking technique. Then the attacker can cover his tracks and delete the malicious MOF script and move on. When the WMI event is triggered, the payload is invoked and a meterpreter session is established back to the system owned by the attacker. With this, the attacker has a persistence mechanism and is operating in the target environment with a privileged account.

Next, action on objectives! Lateral movement has been traditionally done using a variety of commands and tools such as net.exe, psexec.exe and wmic.exe. Nowadays, you can add PowerShell to the mix.. More specifically using the PowerView tool which was developed by William Schroeder and is part of PowerSploit tools and scripts. PowerView is an advanced active directory enumeration tool written in PowerShell that allows an attacker to gather extensive amount of information about a Windows enterprise environment. You can read more about the reason behind Powerview hereThis great write-up demonstrates several use cases for PowerView. Once again, we can load PowerView from within our Meterpreter sessions. In this case, the session has SYSTEM privileges and was obtained leveraging the WMI persistence but PowerView can run with a normal account.  The picture below exemplifies this step.


The list of functions available within PowerView is here and the cheat sheet here. The attacker starts enumerating different aspects of the Active Directory and the different systems just by leveraging PowerShell commands. To perform this he can leverage different techniques and modules within PowerView.  For a great summary you can see – once again – William Schroeder presentation given at Troopers 16 entitled “I have the power view”.

So, to start, the attacker can leverage the Kerberoasting technique. This technique pioneered by Tim Medin – I recommend you watch his presentation “Attacking Kerberos – Kicking the Guard God of Hades” – is brilliant and exploits the way Kerberos functions inside a Microsoft environment. This technique has been reorganized and adopted by PowerView and to run it is as simple as to list all user accounts in the active directory environment that have a SPN, request a Kerberos ticket and extract the crypto material. Then crack it offline to obtain clear text password. You can read more about it in this two articles written by William here and here. The below picture illustrates the Kerberoasting technique.


After obtaining the hash you could use John the Ripper to crack the password using as hash format the krb5tgs.

Another attack vector is to find accounts in the Active Directory that don’t require Kerberos preauthentication i.e., the PreAuthNotRequire attribute is enabled. This technique was pioneered by Geoff Janjua from Exumbra Operations and you can read the work he did in the article “Kerberos Party Tricks: Weaponizing Kerberos Protocol Flaws“. Essentially the technique consists on listing all accounts that have this attribute and request a Kerberos ticket for those accounts. This ticket contains crypto material that can be extracted and cracked offline. Once again this technique was adopted by PowerView and you can read more about it here.

Finally, if these techniques don’t work, then the attacker likely will move from system to system until he finds a system where he can obtain administrative privileges and move on until he finds a domain admin. This can be daunting task in large environments but once again William Schroeder coded the necessary steps into a series of PowerView modules that are coined with the Hunter word such as Invoke-UserHunter, Invoke-StealthUserHunter and many others that will facilitate the search for high value targets. You can view his presentation “I hunt sysadmins” to understand more what these modules do behind the scenes.  Justin Warner, one of the founders of PowerShell Empire, wrote a great article explaining how these modules works and went further by explaining a technique he named as derivative local admin. This technique was then automated by Andy Robbins which started in a proof-of-concept tool called PowerPath which leverages algorithms that are used to find the shortest path between two points. Andy then worked with Rohan Vazarkar and Will Schroeder  and their work culminated in the release of a tool called BloodHound. The tool was released as open source tool at DEF CON 24. Bottom line, using the different techniques and tools implemented by these brilliant folks the threat actor is likely to succeed obtaining a high privileged account.

Then, is matter of pivoting inside the enterprise environment using the obtained privileged accounts. For that the attacker can leverage the netsh.exe port forwarding feature or the Meterpreter port proxy command to pivot between internal systems. This technique is commonly used by attackers that want to use an internal system as pivot, allowing direct access to machines otherwise inaccessible from the attacking system. The command in the picture below illustrates this, where after configuring the port forwarding on the compromised system, the attacker can use wmic.exe to launch PowerShell on a remote system that will connect back to the attacker system and establish a meterpreter session.


From this moment, its a cycle. Enumerate weakness, exploit them, compromise the system, move further, repeat. This cycle goes on and on until the attacker meets his objectives. A great resource about the techniques that were shown and many others are listed in this article written by Raphael Mudge, the author of Cobalt Strike.

That’s it. With this we covered different tools and techniques that are used in the different attack stages and used nowadays by security professionals but as well by cyber criminals and APT groups. After this, I would ask, how would you detect, prevent and respond to each one of the steps outlined in this attack scenario?

Feel free to share your ideas in the comments below. Thanks for reading!

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Extract and use Indicators of Compromise from Security Reports

apt-reports-1Every now and then there is a new security report released and with it comes a a wealth  of information about different threat actors offering insight about the attacker’s tactics, techniques and procedures. For example, in this article I wrote back in 2014, you have a short summary about some of the reports that were released publicly throughout the year. These reports allow the security companies to advertise their capabilities but on the other hand they are a great resource for network defenders. Some reports are more structured than others and they might contain different technical data. Nonetheless, almost all of them have IOC’s (Indicators of compromise).

For those who never heard about indicators of compromise let me give a brief summary. IOC’s are pieces of information that can be used to search and identify compromised systems. These pieces of information have been around since ages but the security industry is now using them in a more structural and consistent fashion. All types of enterprises are moving from the traditional way of handling security incidents – Wait for an alert to come in and then respond to it – to a more proactive approach which consists in taking the necessary steps to hunt for evil in order to defend their networks. In this new strategy, the IOCs are a key technical component. When someone compromises a system, they leave evidence behind.  That evidence, artifact or remnant piece of information left by an attacker can be used to identify the intrusion, threat group or the malicious actor. Examples of IOCs are IP addresses, domain names, URLs, email addresses, file hashes, HTTP user agents, registry keys, a service configuration change, a file is deleted, etc. With this information one could sweep the network/endpoints and look for indicators that the system might have been compromised. For more background about it you can read Lenny Zeltzer summary. Will Gragido from RSA explained it well in is 3 parts blog herehere and here. Mandiant also has this and this great articles about it.

So, if almost all the reports published contain IOC’s, is there a central place that contains all reports that were released by the different security organizations? Kiran Bandla created a repository on GitHub named APTnotes where he does exactly that. He maintains a list of all security reports released by the different vendors – “APTnotes is a repository of publicly-available papers and blogs (sorted by year) related to malicious campaigns/activity/software that have been associated with vendor-defined APT (Advanced Persistent Threat) groups and/or tool-sets.” Kiran, among other methods relies on the community who share with him when a report X or Y was released and he adds it to the APTnotes repository. The list of reports is available in CSV and JSON format.

So, what can you do with all this reports? How can we as network defenders use this information?

Three example use cases.  The first use case is more likely and common, where the other two might be more common in larger organizations with higher budget and bigger security appetite.

  • An organization that has a Security Operations Center in place could use the IOC’s to augment their existing monitoring and detection capabilities.
  • An organization that has in-house CSIRT capabilities could leverage the IOC’s in a proactive manner in order to have a higher probability of discovering something bad and, as such, reduce the business impact that a security incident might have in the organization.
  • An organization that has a Cyber Threat Intelligence capability in-house, could collect, process, exploit and analyze these reports. Then disseminate actionable information to the threat intelligence consumers throughout the organization.

In a simple manner, the process for the first scenario would look something like the following diagram:


How would this work in practical terms? Normally, you could split the IOC’s in host based or network based. For example, a DNS name or IP addresses will be more effective to search across your network infrastructure. However, a Registry Key or a MD5 will be more likely to be searched across the endpoint.

For this article, I will focus on MD5’s. Some reports offer file hashes using SHA-1 or SHA-256 but not many organizations have the capability to search for this. MD5 is more common. Noteworthy that the value of MD5 hashes about a malicious file might be considered low.  A great article about the value of IOC’s and TTP’s was written back in 2014 from David Bianco title The Pyramid of Pain. Following that there is an article from Harlan Carvey with additional thoughts about it. Another point to take into consideration about the MD5’s from the reports is that some might be from legitimate files due to the usage of DLL hijacking or they are windows built-in commands used by threat actors. In addition is likely that malware used by the different threat actors is only used once and you might not see a MD5 hash a second time. Nonetheless, the MD5’s is a starting point.

So, how can we collect the reports, extract the IOC’s and convert them and use them?

First you can use a python script to download all the reports in a central place separated per year. Then you can use the tool IOC parser written by Armin Buescher. This tool will be able to parse PDF reports and extract IOC’s into CSV format. From here you can extract the relevant IOC’s. For this example, I want to extract the MD5’s and then use IOC writer to create IOC’s in OpenIOC 1.0/1.1  format which could be used with a tool such as Redline.  IOC writer is a python library written by William Gibb that allows you to manipulate IOC’s in OpenIOC 1.1 and 1.0 format and was released on BlackHat 2013.

The steps necessary to perform this are illustrated below – for sure there are  other better ways to perform this but this was a quick way to do the job -.


With this we created a series of files with  .ioc extension that can be further edited with the ioc_writer Python library. However, not many tools support OpenIOC, so you might just use the MD5’s and feed that into whatever tool or format you are using. You can download below the excel with all the MD5’s separated per year.  If you use them, please bare in mind you might have false positives and you will need to go back to the csv files to understand from which report did the MD5 came from. For example I  already removed half dozen of MD5’s that are legitimate files but seen in the reports, and also the MD5 for an empty file “d41d8cd98f00b204e9800998ecf8427e”

That’t it, with this you can create a custom IOC set that contain MD5’s of different tools, malware families and files that was compiled by extracting the MD5’s from the public reports about targeted attacks. From here you can start building more complex IOC’s with different artifacts based on a specific report or threat actor. Maybe you get lucky and you find evil on your network!

The year 2010 contains 81 unique MD5’s.
The year 2011 contains 96 unique MD5’s.
The year 2012 contains 718 unique MD5’s.
The year 2013 contains 2149 unique MD5’s
The year 2014 contains 1306 unique MD5’s
The year 2015 contains 1553 unique MD5’s
The year 2016 contains 1173 unique MD5’s

Excel : md5-aptnotes-2010-2016


Blockchain & Brainwallet cracking

img_1293The blockchain is the underlying technology that enables the bitcoin cryptocurrency to exist. A foundational component of this technology is its complex cryptosystem. The blockchain cryptosystem relies on public key algorithms based on Elliptic Curve and message digest functions like SHA-256 and RIPEMD-160. When you create a bitcoin wallet, under the hood you are creating an Elliptic Curve key pair based on Secp256k1 curves. The key pair has a private key and a public key. The private key is the one you keep secret and allows you to sign transactions. For example, when you send bitcoins to someone, you are signing this transaction with your private key and then you announce it to the network. The miners will pick up your transaction and verify that the transaction signature is valid and broadcast to the network until enough miners have validated the transaction and thus achieving consensus. The checks and balances of the Blockchain ledger are updated and when consensus is achieved, your transaction is written in “digital stone”.

On the other hand, the public key is the one used to create your bitcoin wallet address. The public key allows you to receive bitcoins. However, your bitcoin wallet address is not your raw Elliptic Curve public key There are additional steps performed in order to create an address. First, a digital representation of your public key is computed using SHA-256 followed by RIPEMD-160. Second, a byte with network id is prepended to this string. Third, a checksum of this string is computed by performing SHA-256 twice. From these results the first 4 bytes are appended to the string produced in second step. This string is encoded in Base58 and this is your bitcoin wallet address. The picture below illustrates this steps in a non-automated way.


There are many forms to store your bitcoins as well as to create wallets. One of the early methods to create bitcoin wallets was known as brain wallets. Unfortunately, this user-friendly method allowed you to enter a password or passphrase which was then hashed using an algorithm such as SHA-256 and used as seed to generate your private key. Due to its popularity and easy usage, many Brain wallets were used in the last few years with weak passwords or passphrases, transforming the Blockchain wallet address hashes in password or passphrases representation of your private key. This weak way of generating your private key allowed attackers to steal your bitcoins just by doing password cracking against the hashes stored in the Blockchain.

Although, this attack has been known for years,  it only got widely known recently due to the work made by Ryan Castellucci. Ryan’s released on 7th August 2015 at DEFCON 23 the results of his work cracking brain wallets in conjunction with a tool called BrainFlayer : A proof-of-concept cracker for cryptocurrency brain wallets and other low entropy key algorithms. You can view Ryan’s talk here.  Two months after Ryans’ initial release of BrainFlayer, he released a faster version. This was the result of the work done by Nicolas Courtois, Guangyang Song from
International Association for Cryptologic Research (IACR), University College London, and Ryan’s to optimize the speed of computing secp256k1 bitcoin elliptic curve. This has been detailed in the paper Speed Optimizations in Bitcoin Key Recovery Attacks.  Furthermore, this year at the Financial Cryptography and Data Security conference, Marie Vasek presented another article The Bitcoin Brain Dain: A Short Paper on the Use and Abuse of Bitcoin Brain Wallets. This paper published the results of evaluating 300 billion passwords against Blockchain hashes and their findings about 884 brain wallets that had funds at a given time, suggesting they might have been drained by active attackers.

So, how do you perform such attack?

The attempt to recover a password just by knowing its encrypted representation can be made mainly using three techniques. Dictionary attacks, which is the fastest method and consists of comparing the dictionary word with the password hash. Another method is the brute force attack, which is the most powerful one but the time it takes to recover the password might render the attack unfeasible. This is of course dependable on the complexity of the password and the chosen algorithm. Finally, there is the hybrid technique which consists of combining words in a dictionary with word mangling rules.

With that being said let’s go over the steps needed to perform this attack against the Blockchain hash160 hashes using a dictionary. This is done in 6 steps:

  • Bootstrap the Blockchain.
  • Parse the Blockchain by running Blockparser and get allBalances.
  • Extract hash160 strings.
  • Create a Bloomfilter.
  • Run BrainFlayer with your favorite dictionary.
  • Use Addressgen to generate key pair.

First step is to bootstrap the blockchain. To perform this, we need to download, install and run the bitcoin software on a system connected to the Internet. The system then becomes a node and part of the peer-to-peer blockchain network. The first task performed by the node is to download the entire database of records i.e., the public transaction ledger and verify it using the transaction engine. In other words, the node downloads the entire blockchain and verifies the validity of all blocks by performing a series of checks   This needs a lot of bandwidth and computing power. As I write this the Blockchain size is 90.633 Gb and contains 438556 blocks. The data contains every transaction that has been made in the blockchain since the genesis block was created on the 3rd of January 2009 at 18:15:05 GMT. To download the entire Blockchain, took me more than 72 hours . The image below illustrates the steps needed to perform the download, installation and running the bitcoin software.


Then, the picture below illustrates the steps needed to perform the configuration and running the bitcoin software. You can view the progress by executing the getblockchaininfo command and check the number of blocks that have been already downloaded.


After downloading the entire Blockchain we move into the second step. Parse the Blockchain.  The tool to perform this heavy lifting exercise is called Blockparser and is a powerful utility, open source, written in C++ that was created by Znort987. The tool doesn’t seem to be maintained anymore but is still able to perform its work. When blockparser performs the parsing, it creates and keeps the index in RAM which means with the current size of the blockchain you need enough RAM to be able to parse it in reasonable amount of time. The tool can perform various task but for this exercise we are interested in the allBalances command. To perform the parsing, I used a system with 64 GB ram and the process was smooth. I tried it on a system with 32Gb and stopped it due to the heavy swapping that was happening. The allBalances produced a 30Gb text file. The image below exemplifies these steps.


Third step is to extract the hash160 addresses from the allBalances. We are interested in the hash160 because this field contains the representation of the Bitcoin public key. Below you can see the output of allBalances.


Forth step, we create a bloom filter with the tool hex2blf which is part of the brainflayer toolkit. We also need to create a binary file containing all the hashes sorted in order to be used with the bloom filter. This will reduce the false positives.

Fifth step, we launch brainflayer using our favorite dictionary against the bloom filter file we generated in the previous step. If there is a match you will see the password or passphrase and the corresponding hash. In the output of cracked password you could see C or U in the second column. This is to indicate if the key is Compressed or Uncompressed. In the below image you can see these steps.


Sixth step and last step is to create the Elyptic Curve key pair using the known password or passphrase. This can be done using the tool Addressgen created by sarchar. Addressgen is a utility written in Python 3 to generate private keys and their corresponding addresses using secp256k1. This utility will allow you to generate the ECDSA key pair which can be used to take over the wallet.


Financial gain is a significant incentive to have people performing all kinds of activities in order to attempt to steal your coins. If you are interested in attacks against the Blockchain I would suggest looking at the different papers created by the professor Dr. Nicolas Courtois and available on his website. On a different note, there are other researchers that are brute forcing the entire bitcoin private key keyspace in order to find private keys for addresses that have funds. There is one project that has the code name Large Bitcoin Collider which is a distributed effort with a pool where people can contribute computing power. The thread on Bitcointalk forum is quite interesting and the author has the following aim for this project: “allow the Bitcoin community to actually have a better shot at risk assessment of this threat vector. Right now, the math says the danger is negligible. Should there at some point be evidence or indication of the contrary, then it’s still better to have a project like this for analysis/experimentation of this concrete attack vector”. The author also writes that the project is a derivative of brainflayer and supervanitygen. Moreover, brainflayer can also perform brute force attack, sequentially against the entire private key space. This would be unfeasible to perform in a reasonable time frame but better to view the talk “Stealoing Bitcoin with Math – HOPE XI” given by Fillippo Valsorda and Ryan’s where among other things they show how quick brain wallets get drained, attacks against newer Brainwallet implementations and other attacks against Eliptic Curve Digital Signature Algorithm (ECDSA).


Mastering Bitcoin – Unlocking Digital Cryptocurrencies by Andreas M. Antonopoulos

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RIG Exploit Kit Analysis – Part 3

Over the course of the last two articles (part 1 & part 2), I analyzed a recent drive-by-download campaign that was delivering the RIG Exploit Kit . In this article, I will complete the analysis by looking at the shellcode that is executed when the exploit code is successful.  As mentioned in the previous articles, each one of the two exploits has shellcode that is used to run malicious code in the victims system. The shellcode objective is the same across the exploits: Download, decrypt and execute the malware.

In part 1, when analyzing the JavaScript that was extracted from the RIG landing page we see that at the end there was a function that contained a hex string of 2505 bytes. This is the shellcode for the exploit CVE-2013-2551.  In a similar way but to exploit  CVE-2015-5122 on the second stage Flash file, inside the DefineBinaryData tag 3, one of the decrypted strings contained a hex string of 2828 bytes.

So, how can we analyze this shellcode and determine what it does?

You can copy the shellcode and create a skeletal executable that can then be analyzed using a debugger or a dissassembler. First, the shellcode needs to be converted into hex notation (\x). This can be done by coping the shellcode string into a file and then running the following Perl one liner “$cat shellcode | perl -pe ‘s/(..)/\\x$1/g’ >shellcode.hex”. Then generate the skeletal shellcode executable with script written by Mario Villa and later tweaked by Anand Sastry.  The command is “$ –s shellcode shellcode.exe”. The result is a windows executable for the x86 platform that can be loaded into a debugger.  Another way to convert shellcode is to use the converter tool from

Next step is to load the generated executable into OllyDbg. Stepping through the code one can see that the shellcode contains a deobfuscation routine. In this case, the shellcode author is using a XOR operation with key 0x84. After looping through the routine, the decoded shellcode shows a one liner command line.


After completing the XOR de-obfuscation routine the shellcode has to be able to dynamically resolve the Windows API’s in order to make the necessary system calls on the environment where is being executed. To make system calls the shellcode needs to know the memory address of the DLL that exports the required function. Popular API calls among shellcode writers are LoadLibraryandGetProcAddress. These are common functions that are used frequently because they are available in the Kernel32.dll which is almost certainly loaded into every Windows operating system.  The author can then get the address of any user mode API call made.

Therefore, the first step of the shellcode is to locate the base address of the memory image of Kernel32.dll. It then needs to scan its export table to locate the address of the functions needed.

How does the shellcode locate the Kernel32.dll? On 32-bit systems, the malware authors use a well-known technique that takes advantage of a structure that resides in memory and is available for all processes. The Process Environment Block (PEB). This structure among other things contains linked lists with information about the DLLs that have been loaded into memory. How do we access this structure? A pointer exists to the PEB that resides insider another structure known as the Threat Information Block (TIB) which is always located at the FS segment register and can be identified as FS:[0x30](Zeltser, L.). Given the memory address of the PEB the shellcode author can then browse through the different PEB linked lists such as the InLoadOrderModuleList which contains the list of DLL’s that have been loaded by the process in load order. The third element of this list corresponds to the Kernel32.dll.  The code can then retrieve the base address of the DLL. This technique was pioneered by one of the members of the well-known and prominent virus and worm coder group 29A and written in volume 6 of their e-zine in 2002. The figure below shows a snippet of the shellcode that contains the different sequence of assembly instructions in order for the code to find the Kernel32.dll.


The next step is to retrieve the address of the required function. This can be obtained by navigating through the Export Directory Table of the DLL. In order to find the right API there is a comparison made by the shellcode against a string. When it matches, it fetches its location and proceeds.  This technique was pioneered and is well described in the paper “Win32 Assembly Components” written in 2002 by The Last Stage of Delirium Research Group (LSD). Finally, the code invokes the desired API. In this case, the shellcode uses the CreateProcessA API where it will spawn a new process that will carry out the command line specified in the command line string.


This command will launch a new instance of the Windows command interpreter, navigate to the users %tmp% folder and then redirect a set of JavaScript  commands to a file. Finally it will invoke Windows Script Host and launch this JavaScript file with two parameters. One is the decryption key and the other is the URL from where to fetch the malicious payload. Essentially this shellcode is a downloader. The full command is shown in the figure below.


If the exploits are sucessfull and the shellcode is executed then the payload is downloaded. In this case the payload is variant of Locy ransomware and a user in Windows 7 box would see the User Account Control dialog box popping up asking to run it.


That’s it! We now have a better understanding how this variant of the RIG Exploit Kit works and what it does and how. All stages of the RIG Exploit Kit enforce different protection mechanisms that slow down analysis, prevent code reuse and evade detection. It begins with multiple layers of obfuscated JavaScript using junk code and string encoding that hides the code logic and launches a browser exploit. Then it goes further by having multiple layers of encrypted Flash files with obfuscated ActionScript. The ActionScript is then responsible to invoke an exploit with encoded shellcode that downloads encrypted payload. In addition, the modular backend framework allows the threat actors to use different distribution mechanisms to reach victims globally. Based on this modular backend different filtering rules are enforced and different payloads can be delivered based on the victim Geolocation, browser and operating system. This complexity makes these threats a very interesting case study and difficult to defend against. Against these capable and dynamic threats, no single solution is enough. The best strategy for defending against this type of attacks is to understand them and to use a defense in depth strategy – multiple security controls at different layers.


SANS FOR610: Reverse-Engineering Malware: Malware Analysis Tools and Techniques
Neutrino Exploit Kit Analysis and Threat Indicators

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RIG Exploit Kit Analysis – Part 2

Continuing with the analysis of the RIG exploit kit, let’s start where we left off and understand the part that contains the malicious Adobe Flash file. We saw, in the last post, that the RIG exploit kit landing page contains heavily obfuscated and encoded JavaScript. One of the things the JavaScript code does is verifying if the browser is vulnerable to CVE-2013-2551. If it is, it will launch an exploit followed by shellcode, as we saw in the last post. If the browser is not vulnerable, it continues and the browser is instructed to download a malicious Flash file. The HTTP request made to fetch the Flash file is made to the domain As you could see in the figure below, the HTTP answer is of content type x-shockwave-flash and the data downloaded starts with CWS (characters ‘C’,’W’,’S’ or bytes 0x43, 0x57, 0x53). This is the signature for a compressed Flash file.


Next  step of our analysis? Analyze this Flash file.  Before we start let’s go over some overview about Flash. There are two main reasons why Flash is an attractive target for malware authors. One is because of its presence in every modern endpoint and available across different browsers and content displayers. The other is due to its features and capabilities.

Let’s go over some of the features. Adobe Flash supports the scripting language known as ActionScript. The ActionScript is interpreted by the Adobe ActionScript Virtual Machine (AVM). Current Flash versions support two different versions of the ActionScript scripting language. The Action Script (AS2) and the ActionScript 3 (AS3) that are interpreted by different AVM’s. The AS3 appeared in 2006 with Adobe Flash player 9 and uses AVM2. The creation of a Flash file consists in compiling ActionScript code into byte code and then packaging that byte code into a SWF container. The combination of the complex SWF file format and the powerful AS3 makes Adobe Flash an attractive attack surface. For example, SWF files contain containers called tag’s that could be used to store ActionScript code or data. This is an ideal place for exploit writers and malware authors to conceal their intentions and to use it as vehicle for launching attacks against client side vulnerabilities. Furthermore, both AS2 and AS3 have the capability to load SWF embedded files at runtime that are stored inside tags using the loadMovie and Loader class respectively. AS3 even goes further by allowing referencing objects from one SWF to another SWF. As stated by Wressnegger et al., in the paper “Analyzing and Detecting Flash-based Malware using Lightweight Multi-Path Exploration ” this allows sophisticated capabilities that can leverage encrypted payloads, polymorphism and runtime packers .

Now, let’s go over the analysis and dissection of the Flash file. This is achieved using a combination of dynamic and static analysis. First, we look at the file capabilities and functionality by looking at its metadata. The command line tool Exiftool created by Phill Harvey can display the metadata included in the analyzed file. In this case, it shows that it takes advantage of the Action Script 3.0 functionality.  Information that is more comprehensive is available with the usage of the swfdump.exe tool that is part of the Adobe Flex SDK, which displays the different components of the Flash file. The output of swfdump displays that the SWF file contains the DoABC and DefineBinaryData tags.  This suggests the usage of ActionScript 3.0 and binary data containing other elements that might contain malicious code executed at runtime.

Second, we will go deeper and dissect the SWF file. Open source tools to dissect SWF files exist such as Flare and Flasm written by Igor Kogan. Regrettably, they do not support ActionScript 3.  Another option is the Adobe SWF Investigator. This tool was created by Peleus Uhley and released as open source by Adobe Labs. The tool can analyze and disassemble ActionScript 2 (AS2), ActionScript 3 (AS3) SWFs and include many other features. Unfortunately, sometimes the tool is unable to parse the SWF file in case has been packed using commercial tools like secureSWF and DoSWF.

One good alternative is to use JPEXS Flash File Decompiler (FFDec). FFDec is a powerful, feature rich and open source flash decompiler built in Java and originally written by Jindra Petřík. One key feature of FFDec is that it includes an Action Script debugger that can be used to add breakpoints to allow you to step into or over the code. Another feature is that it shows the decompiled ActionScript and its respective p-code.

One popular tool among Flash malware writers is doSWF. doSWF is a commercial product used to protect the intellectual property of different businesses that use Adobe Flash technology and want to prevent others copying it. Malware authors take advantage of this and use it for their own purposes. This tool can enforce different protections to the code level in order to defeat the decompiler. In addition to the different protections done to the code logic, doSWF can perform literal strings encryption using RC4 or AES. Also, it can be used to wrap an encrypted SWF inside another SWF file using the encrypted loader function.  The decryption occurs at runtime and the decrypted file is loaded into memory.

Opening the SWF file using FFDec and observing its structure using Action Script you can see the different strings referencing doSWF which is an indication that the file has been obfuscated using doSWF. FFDec has a P-Code deobfuscation feature that can restore the control flow, remove traps and remove dead code. In addition, there is a plugin that can help rename invalid identifiers.  The figure below shows a snippet of the ActionScript code after it has been deobfuscated by FFDec.


As seen in other Exploit Kits such as Angler and Neutrino, the first flash file is only used as carrier and malicious code such as exploit code or more Flash files are encrypted and obfuscated inside this first stage flash file.. The goal here is to perform static analysis of the Action Script code and determine what is happening behind the scenes. Normally, the DefineBinaryData contains further Flash files or exploit code but you need to understand the code and get the encryption keys in order to extract the data. Because my strengths are not in programming I tried to overcome this step before rolling up my sleeves and spending hours trying to understand the Action Script code like I did for Neutrino with the help of some friends. One way to carve the data is to use the Action Script debugger available in FFDec.  Essentially, setting a breakpoint in the LoadBytes() method. Then running the Flash file and then when the breakpoint is triggered, use the FFDec Search SWF in memory plugin in order to find SWF files inside the FFDec process memory address space. But for this sample I used SULO.

During Black Hat USA 2014, Timo Hirvonen presented a novel tool to perform dynamic analysis of malicious Flash files. He released an open source tool named SULO. This tool uses the Intel Pin framework to perform binary instrumentation in order to analyze Flash files dynamically. This method enables automated unpacking of embedded Flash files that are either obfuscated or encrypted using commercial tools like secureSWF and DoSWF.  The code is available for download on F-Secure GitHub repository ( and it should be compiled with Visual Studio 2010. The compilation process creates a .DLL file that can be used in conjunction with Intel Pin Kit for Visual Studio 2010. There are however limitations in the versions of Adobe Flash Player supported by SULO. At the time of writing only Flash versions and are supported. Nonetheless, one can use SULO with the aim to extract the packed Flash file in a simple and automated manner. In this case, I used the stand alone Flash player flashplayer11_1r102_62_win_sa_32bit.exe.

When using SULO to analyze the Flash file, the second stage Flash file is extracted automatically. The command shown in figure below will run and extract the packed SWF file.


In this particular case, SULO manages to extract 2 SWF files. So, the next step is to analyze these second stage SWF files. Once again, using FFDec and observing its structure and Action Script code. The second stage Flash files are interesting because one contains the code and the other makes extensive use of DefineBinaryData tag’s to store encrypted data.  As a starting point, the analysis steps here are the same. Invoke the P-Code deobfuscation feature in order to restore the control flow, remove traps and remove dead code. In addition, the plugin to rename invalid identifiers was executed. After performing these two steps, the Action Script code is more readable.

In this post I won’t bother you with the details about the Action Script code. Nonetheless, one thing to mention about the code is that if you follow the site and the amazing work done by Kaffeine on hunting down, analyzing and documenting Exploit Kits you might have noticed that he calls this version of RIG “RIG-v Neutrino-ish“. The reason might be due to the usage of the RC4 key to decrypt the payload and also the similarities in the way the Flash files are encoded and obfuscated.

Anyhow, understanding the code is important but is also important to understand what the Flash file is hiding from us. In a nutshell, one of the second stage Flash files contain several defineBinaryTags which contain encrypted strings that are used throughout the code in the other second stage Flash file. The data can be obtained by decrypting the data using RC4 keys that are also inside the defineBinaryTags. The figure below ilustrates this.


In summary DefineBinaryData tag 2 contains an array of one 16-byte RC4 key. DefineBinaryData tag 1 contains 19 (0x13) RC4-encrypted strings. The first dword contains the total number of strings. Then each string starts with a dword that contains the size of the string, followed by the RC4-encrypted data.

The DefineBinaryData tag 3 contains an array of three 16-byte RC4 keys. DefineBinaryData tag 4 contains 6 (0x06) RC4-encrypted strings. The first dword contains the total number of strings. Then each string starts with a dword that contains the size of the string, followed by the RC4-encrypted data. The RC4 decryption routine uses the 3 RC4 keys iteratively across the 19 strings.

The decrypted strings are used on different parts of the code. One of the strings is relevant because it contains shellcode that is nearly identical to the one seen in the JavaScript exploit inside the landing page.

Based on the decrypted strings it seems the Flash contains code to exploit CVE-2015-5122. This exploit has a CVSS score of 10 and is known as Adobe Flash ActionScript 3 opaque Background Use-After-Free Vulnerability. This exploit was found as a result of the public disclosure of the Hacking Team leak. In a matter of hours, the exploit was incorporated in the Angler Exploit Kit.

… and with a so lengthy post, that’s it for today. In the following post I will cover how to analyze the Shellcode to understand what is done behind the scenes when one of the exploits is successfully triggered.

First stage Flash file MD5: d11c936fecc72e44416dde49a570beb5
Second stage Flash file MD5: 574353ed63276009bc5d456da82ba7c1
Second stage Flash file MD5: e638fa878b6ea20fa8253d79b989fd7e

Neutrino Exploit Kit Analysis and Threat Indicators

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