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Ransomware: a correlation between infection vectors and victims

Doina Cosovan (Security Scorecard), Cătălin Liță (Security Scorecard), Jue Mo (Security Scorecard) & Ryan Sherstobitoff (Security Scorecard)
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Ransomware attacks have increased exponentially recently. Some companies have even started to buy insurance against ransomware attacks.

Unlike in the past, nowadays it is not as easy to hide the fact that you’ve been breached, especially if the breach is a result of a ransomware infection or leads to a ransomware infection.

This happens because the attackers of more than 20 different ransomware families started to threaten to publicly expose the data belonging to companies unwilling to pay the ransom. Most of the attackers use Tor domains to disclose the identity of the companies they’ve infected as well as to upload files they’ve stolen before starting the encryption process.

In this paper we analyse the techniques that get companies infected with ransomware in an attempt to find a way to figure out if an entity is a potential future ransomware victim and what can it do to minimize the chances of getting hit.

Ransomware infects systems through other malware families or exploit kits, vulnerable services, spam campaigns, and so on. By correlating the victims of these malware families and exploit kits, the entities running these vulnerable services, as well as the entities that have poor email hygiene with the victims of ransomware attacks, we can estimate the risk those exposures added to the probability of ransomware infection.

There are two ways of collecting victims of ransomware attacks. Non-paying victims can be collected by crawling Tor websites maintained by the attackers while both paying and non-paying victims can be collected by sinkholing ransomware families which use multiple command-and-control domains and don’t register all of them.

For the ransomware families for which we can gather both paying and non-paying victims as a result of having information from both the attacker’s website and our sinkholes, we can derive the percentage of paying victims.

And even if a company doesn’t get infected with ransomware, a third-party entity, such as a supplier of that company, can get infected with ransomware, thus allowing the attackers access to the same data the company shared with the third party. The initial company can later be blackmailed against making that data public to competitors – as happened with Apple recently. Therefore, it is also important for a company to monitor its third-party entities for how vulnerable they are in order to protect themselves.

Got a question about this presentation? To get in touch with the speakers, contact them by email on [email protected], [email protected], [email protected] and [email protected].
Doina Cosovan
Security Scorecard

Doina spent five years as a malware researcher at Bitdefender, learning about malware and security. During that period, she reverse engineered, analysed, added detection for malware and collaborated with the communications team to publish over 50 blog posts about her findings on Hot for Security and Bitdefender Labs. Doina is now a malware researcher at Security Scorecard, a global cybersecurity ratings firm that continuously monitors the security posture of millions of companies. Her role is focused on implementing proof of concepts and creating ways of non-intrusively gathering malware-related signals. She researches cybersecurity topics like malware packers, command-and-control communication protocols, analysis of malware families, web injects, adware, and machine learning for malware detection. Doina is a frequent speaker at cyber industry conferences like Virus Bulletin, CARO and AVAR. She has also published papers in the Journal of Computer Virology and Hacking Techniques and International Conference on Artificial Neural Networks.

Cătălin Liță
Security Scorecard

Cătălin Valeriu Liță received a Bachelor's degree in computer science from the Technical University Gheorghe Asachi, Romania, Iasi, Faculty of Automatics and Computer Science. He has a Master's degree in information security from the Alexandru Ioan Cuza University of Iași, Faculty of Computer Science, a Master's degree in business administration from the Alexandru Ioan Cuza University of Iași, Faculty of Economics and Business Administration, and a Ph.D. in computer science from the Faculty of Computer Science. He has presented at CARO and Virus Bulletin conferences. Prior to joining Security Scorecard he worked for nine years in Bitdefender's anti-malware team.

Jue Mo
Security Scorecard

Jue Mo earned a Ph.D. degree in biomedical engineering from the University of Florida. She entered the data science world to explore her passion for pattern recognition and statistical analysis. She joined Security Scorecard in 2016 as a data scientist. Her role is focused on evaluating data accuracy/quality and building risk models on security observations.

Ryan Sherstobitoff
Security Scorecard

Ryan specializes in threat intelligence in the Asia Pacific Region, where he conducts cutting-edge research into new adversarial techniques and adapts those to better monitor the threat landscape. He formerly led intelligence teams at McAfee, where he managed the US strategic response for new and emerging threats. Ryan is widely recognized as a security & cloud computing expert throughout the country.