In order to mount an effective defense, information about likely adversaries, as well as their techniques, tactics and procedures is needed. This so-called cyber threat intelligence helps an organization to better understand its threat profile. Next to this understanding, specialized feeds of indicators about these threats downloaded into a firewall or intrusion detection system allow for a timely reaction to emerging threats. These feeds however only provide an actual benefit if they are of high quality. In other words, if they provide relevant, complete information in a timely manner. Incorrect and incomplete information may even cause harm, for example if it leads an organization to block legitimate clients or if the information is too unspecific and results in an excessive amount of collateral damage. In this paper, we evaluate the quality of 17 open source cyber threat intelligence feeds over a period of 14 months, and 7 additional feeds over 7 months. Our analysis shows that the majority of indicators are active for at least 20 days before they are listed. Additionally, we have found that many list have biases towards certain countries. Finally, we also show that blocking listed IP addresses can yield large amounts of collateral damage.

Since the release of a browser-based cryptominer by Coinhive in 2017, the easy use of these miners has skyrocketed illicit cryptomining in 2017 and continued in 2018. This method of monetizing websites attracted website owners, as well as criminals seeking new ways to earn a profit. In this paper, we perform two large studies into the world of cryptojacking, focused on organized cryptomining and the spread of cryptojacking on the Internet. We have identified 204 cryptojacking campaigns, an order of magnitude more than previous work, which indicates that these campaigns are heavily underestimated by previous studies. We discovered that criminals have chosen third-party software - such as WordPress - as their new method for spreading cryptojacking infections efficiently. With a novel method of using NetFlow data we estimated the popularity of mining applications, which showed that while Coinhive has a larger installation base, CoinImp WebSocket proxies were digesting significantly more traffic in the second half of 2018. After crawling a random sample of 49M domains, ~20% of the Internet, we conclude that cryptojacking is present on 0.011% of all domains and that adult content is the most prevalent category of websites affected.

The release of an efficient browser-based cryptominer, as introduced by Coinhive in 2017, has quickly spread throughout the web either as a new source of revenue for websites or exploited within the context of hacks and malicious advertisements. Several studies have analyzed the Alexa Top 1M and found 380 - 3,200 [5, 15, 18, 30, 31] (0.038% - 0.32%) to be actively mining, with an estimated $41,000 per month revenue for the top 10 perpetrators [18]. While placing a cryptominer on a popular website supplies considerable returns from its visitors' web browsers, it only generates revenue while a client is visiting the page. Even though large popular websites attract millions of visitors, the relatively low number of exploiting websites limits the total revenue that can be made. In this paper, we report on a new attack vector that drastically overshadows all existing cryptojacking activity discovered to date. Through a firmware vulnerability in MikroTik routers, cyber criminals are able to rewrite outgoing user traffic and embed cryptomining code in every outgoing web connection. Thus, every web page visited by any user behind an infected router would mine to profit the criminals. Based on NetFlows recorded in a Tier 1 network, semiweekly crawls and telescope traffic, we followed their activities over a period of 10 months, and report on the modus operandi and coordinating infrastructure of the perpetrators, which were during this period in control of up to 1.4M routers, approximately 70% of all MikroTik devices deployed worldwide. We observed different levels of sophistication among adversaries, ranging from individual installations to campaigns involving large numbers of routers. Our results show that cryptojacking through MITM attacks is highly lucrative, a factor of 30 more than previous attack vectors.