Advanced Persistent Threats (APTs) are sophisticated and long-lived attacks that are often backed by nationstates. Despite the security community’s efforts to design and deploy specialized systems to combat them, APTs have remained prevalent while persisting undetected for significantly more time than commodity cyber threats. In this paper, we measure this difference by conducting the first longitudinal analysis of APT infrastructure by shedding light on the lifecycle of their domain names. To enable this study, we build Atropos, a novel measurement methodology that automatically and accurately labels DNS records of APT domain names, enabling us to understand their lifecycle and gain a more comprehensive and contextualized infrastructure picture than the one that is shared in public reports. Using the comprehensive infrastructure view that Atropos provides, we study 405 APT actors over a period spanning a decade and unveil several novel findings regarding their utilization of network infrastructure that have practical implications. We find that APT actors provision their IPs to their domain names 317 days on average before an attack is publicly reported. Furthermore, $73.6 \%$ of the APT IPs that are part of the attack infrastructure no longer point to their domains at the time of first public disclosure, highlighting that researchers and security practitioners need to consider historic DNS data in order to get a more comprehensive and accurate picture when training network detection, investigation, or attribution systems. Organizations that are more sensitive to APT attacks will need to retain network logs for at least 19 to 25 months in order to have higher probabilities of discovering whether they have been a target of an APT attack. Finally, we provide evidence that APT actors re-use hosting providers, deploy APT network infrastructure close to their intended attack targets, and increasingly utilize more cloud-fronting. These findings are important because they can guide future threat detection and attribution works.

This work explores authoritative DNS (AuthDNS) as a new measurement perspective for studying the large-scale epidemiology of the malware ecosystem—when and where infections occur, and what infrastructure spreads and controls malware. Utilizing an AuthDNS dataset from a top registrar, we observe malware heterogeneity (202 families), global infrastructure (399,830 IPs in 151 countries) and infection (40,937 querying Autonomous Systems (ASes)) visibility, as well as breadth of temporal coverage (2017–2021). This combination of factors enables an extensive analysis of the malware ecosystem that reinforces prior work on malware infrastructure and also contributes new perspectives on malware infection distribution and lifecycle. We find that malware families re-use infrastructure, especially in cloud hosting countries, but contrary to prior work, we do not detect targeting of clients by countries or industry sector. Furthermore, our 4-year lifecycle analysis of diverse malware families shows that infection analysis is temporally sensitive: over 90% of ASes first query a malicious domain after public detection, and a median of 38.6% ASes only query after domain expiration or takedown. To fit AuthDNS into the broader context of malware research, we conclude with a comparison of experimental vantage points on four qualitative aspects and discuss their advantages and limitations. Ultimately, we establish AuthDNS as a unique measurement perspective capable of measuring global malware infections.

Over the past decade, many innovations have been achieved with respect to improving the responsiveness of highly-trafficked servers. These innovations are fueled by a desire to support complex and data-rich web applications while consuming minimal resources. One of the chief advancements has been the emergence of the asynchronous web server architecture, which is built from the ground up for scalability. While this architecture can offer a significant boost in performance over classic forking servers, it does so at the cost of abandoning memory space isolation between client interactions. This shift in design, that delegates the handling of many unrelated requests within the same process, enables powerful and covert data-oriented attacks that rival complete web server takeover - without ever hijacking the control flow of the server application. To demonstrate the severity of this threat, we present a technique for identifying security-critical web server data by tracing memory accesses committed by the program in generating responses to client requests. We further develop a framework for performing live memory analysis of a running server in order to understand how low-level memory structures can be corrupted for malicious intent. A fundamental goal of our work is to assess the realism of such data-oriented attacks in terms of the types of memory errors that can be leveraged to perform them, and to understand the prominence of these errors in real-world web servers. Our case study on a leading asynchronous architecture, namely Nginx, shows how dataoriented attacks allow an adversary to re-configure an Nginx instance on the fly in order to degrade or disable services (e.g., error reporting, security headers like HSTS, access control), steal sensitive information, as well as distribute arbitrary web content to unsuspecting clients - all by manipulating only a few bytes in memory. Our empirical findings on the susceptibility of modern asynchronous web servers to two wellknown CVEs show that the damage could be severe. To address this threat, we also discuss several potential mitigations. Taken as a whole, our work tells a cautionary tale regarding the risks of blindly pushing forward with performance optimizations.

Domain squatting is a common adversarial practice where attackers register domain names that are purposefully similar to popular domains. In this work, we study a specific type of domain squatting called "combosquatting," in which attackers register domains that combine a popular trademark with one or more phrases (e.g., betterfacebook[.]com, youtube-live[.]com). We perform the first large-scale, empirical study of combosquatting by analyzing more than 468 billion DNS records - collected from passive and active DNS data sources over almost six years. We find that almost 60% of abusive combosquatting domains live for more than 1,000 days, and even worse, we observe increased activity associated with combosquatting year over year. Moreover, we show that combosquatting is used to perform a spectrum of different types of abuse including phishing, social engineering, affiliate abuse, trademark abuse, and even advanced persistent threats. Our results suggest that combosquatting is a real problem that requires increased scrutiny by the security community.