Some of the most insidious threats that Darktrace finds use self-modifying technology to hide their presence on the network. These attacks can dynamically change their threat signatures, automatically extract data, and spread without a human controller.
Recently, we discovered anomalous activity on the network of a major US university. After investigation, we found that the anomaly was the ‘Smoke Malware Loader’ which employs numerous techniques to evade internal security. Most notably, the malware generates fake traffic to hide its presence.
Darktrace observed the initial infection when three anomalous executables were transferred over plain text. The malware did not match any known threat signatures, allowing it to bypass the network’s perimeter controls.
C1ulyq1wLrMBs6LG00 on Thu Sep 8, 13:19:01
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The connections originated from a suspicious external domain that the company had never communicated with before:
Both the anomalous download and the beaconing activity represented major deviations from the unique ‘pattern of life’ learned by the Enterprise Immune System.
Although the payload circumvented the network’s perimeter security, the company also had an alternate security system monitoring network flow. This tool raised an alert when the download occurred, but it was deemed a ‘false positive’ because the malware proceeded to install new, previously unknown versions of the executable to the Windows registry.
After the self-modifying modules were uploaded to the company device, a large number of HTTP POST requests were sent against /smk/log.php to the following domains:
The malware attempted to transfer data to these external destinations, but to hide its tracks, the remote machine replied with a fake 404 error code. These connections were deemed highly anomalous by Darktrace’s AI algorithms.
Since the payload was designed to be compatible with the password grabber module2 – which is often deployed side-by-side with Smoke Malware Loader – the data attempting to leave the network likely contained user credentials and passwords.
In conjunction with the initial transfer, another anomalous file was then delivered to a different device. This activity indicated that the threat actor was likely attempting to move laterally across the network:
hxxp://cdn.che[.]moe/izgmcx.exe (connection UID: CGH6uV3G5tdKSNY800) to 10.1.105.117 on Mon Sep 12 at 08:02:03.
Darktrace detected each anomaly in real time as the situation developed. By using AI algorithms to continuously learn normal behavior, Darktrace was able to monitor the malware’s changing threat signature.
Traditional security tools – no matter how advanced – are incapable of detecting such sophisticated threats. Legacy controls rely on rules and signatures, and these threats are specifically designed to bypass rules and signatures.
Darktrace’s real-time threat detection allowed the university’s security team to quarantine the infected devices before the malware could burrow deeper into the network, and before the attacker could use the passwords to further compromise the network. Darktrace then assisted the security team as they remediated the situation and changed their security protocols and passwords.
Justin is one of the US’s leading cyber intelligence experts, and holds the position of Director for Cyber Intelligence & Analytics at Darktrace. His insights on cyber security and artificial intelligence have been widely reported in leading media outlets, including the Wall Street Journal, CNN, The Washington Post, and VICELAND. With over 10 years of experience in cyber defense, Justin has supported various elements in the US intelligence community, holding mission-critical security roles with Lockheed Martin, Northrop Grumman Mission Systems and Abraxas. Justin is also a highly-skilled technical specialist, and works with Darktrace’s strategic global customers on threat analysis, defensive cyber operations, protecting IoT, and machine learning.
The ‘ransomware’ attack sweeping the globe is yet another demonstration of the decreasing usefulness of the traditional cyber defense approaches. Businesses cannot rely on patching vulnerabilities fast enough, and a NotPetya patch would only protect you against yesterday’s attack but will not be able to stop tomorrow’s.
An interesting difference to last month’s WannaCry attack is that it could spread from victim to new victim directly over the internet. Whilst this one can also spread quickly within organizations, Petya (or NotPetya) has not spread across the internet. The good news is that if you haven’t been affected yet, it is unlikely you will be.
At first glance, this might look like conventional ransomware, but it has emerged that the system for paying the criminals and decrypting data doesn’t work. This means that regardless of whether monetization was the original motive or not, it will feel like sabotage from the victims’ perspective.
Questions regarding whether the attack was a targeted one or not are in this case legitimate, as the initial deployment was via poisoning legitimate accountancy software heavily used in Ukraine and Ukrainian city websites. A majority of businesses affected would have been operating in the Ukraine area, or connected to them via their supply chain.
How many more warnings do we need that relying on stopping attacks seen in the past just isn’t enough? The latest advances in AI mean that autonomous technology can now detect and fight back against any in-progress threats within a company network, buying the security teams time to investigate.
In our tests, Darktrace has confirmed the ability to autonomously respond to NotPetya, neutralizing the threat in seconds. Enterprise Immune System technology works because it doesn’t rely on rules or signatures. It takes defensive action before humans have time to react, and is the only realistic way that security teams will scale to the increased speed and diversity of future attacks.
Dave is the Director of Technology at Darktrace, overseeing the mathematics and engineering teams and project strategies. With over 19 years of experience at the forefront of government intelligence operations, Dave has worked across UK intelligence agencies GCHQ and MI5, where he was responsible for delivering mission-critical infrastructure services, including replacing and securing entire global networks, the development of operational internet capabilities and the management of critical disaster recovery incidents. He acts as an advisor to cyber security start-ups and growth-stage companies from the UK Government’s Cyber Security Accelerator and CyLon. His insights on AI and the future of cyber security are also regularly featured in the UK media. He holds a first-class degree in Computer Science and Software Engineering from the University of Birmingham.