Secure TLS server authentication depends on reliable trust anchors. The fault intolerant design of today's system---where a single compromised trust anchor can impersonate nearly all web entities---necessitates the careful assessment of each trust anchor found in a root store. In this work, we present a first look at the root store ecosystem that underlies the accelerating deployment of TLS. Our broad collection of TLS user agents, libraries, and operating systems reveals a surprisingly condensed root store ecosystem, with nearly all user agents ultimately deriving their roots from one of three root programs: Apple, Microsoft, and NSS. This inverted pyramid structure further magnifies the importance of judicious root store management by these foundational root programs.

Developers are increasingly deploying web applications which require real-time bidirectional updates, a use case which does not naturally align with the traditional client-server architecture of the web. Many solutions have arisen to address this need over the preceding decades, including HTTP polling, Server-Sent Events, and WebSockets. This paper investigates this ecosystem and reports on the prevalence, benefits, and drawbacks of these technologies, with a particular focus on the adoption of WebSockets. We crawl the Tranco Top 1 Million websites to build a dataset for studying real-time updates in the wild. We find that HTTP Polling remains significantly more common than WebSockets, and WebSocket adoption appears to have stagnated in the past two to three years. We investigate some of the possible reasons for this decrease in the rate of adoption, and we contrast the adoption process to that of other web technologies. Our findings further suggest that even when WebSockets are employed, the prescribed best practices for securing them are often disregarded. The dataset is made available in the hopes that it may help inform the development of future real-time solutions for the web.

Uniform Resource Locators (URLs) unambiguously specify host identity on the web. URLs are syntactically complex, and although software can accurately parse identity from URLs, users are frequently exposed to URLs and expected to do the same. Unfortunately, incorrect assessment of identity from a URL can expose users to attacks, such as typosquatting and phishing. Our work studies how well users can correctly determine the host identity of real URLs from common services and obfuscated "look-alike" URLs. We observe that participants employ a wide range of URL parsing strategies, and can identify real URLs 93% of time. However, only 40% of obfuscated URLs were identified correctly. These mistakes highlighted several ways in which URLs were confusing to users and why their existing URL parsing strategies fall short. We conclude with future research directions for reliably conveying website identity to users.

The success of cloud computing has shown that the cost and convenience benefits of outsourcing infrastructure, platform, and software resources outweigh concerns about confidentiality. Still, many businesses and individuals resist moving private data to cloud providers due to intellectual property and privacy reasons. A recent wave of hardware virtualization technologies aims to alleviate these concerns by offering encrypted virtualization features that support data confidentiality of guest virtual machines (e.g., by transparently encrypting memory) even when running on top untrusted hypervisors. We introduce two new attacks that can breach the confidentiality of protected enclaves. First, we show how a cloud adversary can judiciously inspect the general purpose registers to unmask the computation that passes through them. Specifically, we demonstrate a set of attacks that can precisely infer the executed instructions and eventually capture sensitive data given only indirect access to the CPU state as observed via the general purpose registers. Second, we show that even under a more restrictive environment - where access to the general purpose registers is no longer available - we can apply a different inference attack to recover the structure of an unknown, running, application as a stepping stone towards application fingerprinting. We demonstrate the practicality of these inference attacks by showing how an adversary can identify different applications and even distinguish between versions of the same application and the compiler used, recover data transferred over TLS connections within the encrypted guest, retrieve the contents of sensitive data as it is being read from disk by the guest, and inject arbitrary data within the guest. Taken as a whole, these attacks serve as a cautionary tale of what can go wrong when the state of registers (e.g., in AMD's SEV) and application performance data (e.g. in AMD's SEV-ES) are left unprotected. The latter is the first known attack that was designed to specifically target SEV-ES.

In-browser cryptojacking is a form of resource abuse that leverages end-users' machines to mine cryptocurrency without obtaining the users' consent. In this paper, we design, implement, and evaluate Outguard, an automated cryptojacking detection system. We construct a large ground-truth dataset, extract several features using an instrumented web browser, and ultimately select seven distinctive features that are used to build an SVM classification model. Outguardachieves a 97.9% TPR and 1.1% FPR and is reasonably tolerant to adversarial evasions. We utilized Outguardin the wild by deploying it across the Alexa Top 1M websites and found 6,302 cryptojacking sites, of which 3,600 are new detections that were absent from the training data. These cryptojacking sites paint a broad picture of the cryptojacking ecosystem, with particular emphasis on the prevalence of cryptojacking websites and the shared infrastructure that provides clues to the operators behind the cryptojacking phenomenon.

Certificate Authorities (CAs) regularly make mechanical errors when issuing certificates. To quantify these errors, we introduce ZLint, a certificate linter that codifies the policies set forth by the CA/Browser Forum Baseline Requirements and RFC 5280 that can be tested in isolation. We run ZLint on browser-trusted certificates in Censys and systematically analyze how well CAs construct certificates. We find that the number errors has drastically reduced since 2012. In 2017, only 0.02% of certificates have errors. However, this is largely due to a handful of large authorities that consistently issue correct certificates. There remains a long tail of small authorities that regularly issue non-conformant certificates. We further find that issuing certificates with errors is correlated with other types of mismanagement and for large authorities, browser action. Drawing on our analysis, we conclude with a discussion on how the community can best use lint data to identify authorities with worrisome organizational practices and ensure long-term health of the Web PKI.

Over the past 20 years, websites have grown increasingly complex and interconnected. In 2016, only a negligible number of sites are dependency free, and over 90% of sites rely on external content. In this paper, we investigate the current state of web dependencies and explore two security challenges associated with the increasing reliance on external services: (1) the expanded attack surface associated with serving unknown, implicitly trusted third-party content, and (2) how the increased set of external dependencies impacts HTTPS adoption. We hope that by shedding light on these issues, we can encourage developers to consider the security risks associated with serving third-party content and prompt service providers to more widely deploy HTTPS.

Industrial control systems have become ubiquitous, enabling the remote, electronic control of physical equipment and sensors. Originally designed to operate on closed networks, the protocols used by these devices have no built-in security. However, despite this, an alarming number of systems are connected to the public Internet and an attacker who finds a device often can cause catastrophic damage to physical infrastructure. We consider two aspects of ICS security in this work: (1) what devices have been inadvertently exposed on the public Internet, and (2) who is searching for vulnerable systems. First, we implement five common SCADA protocols in ZMap and conduct a survey of the public IPv4 address space finding more than 60K publicly accessible systems. Second, we use a large network telescope and high-interaction honeypots to find and profile actors searching for devices. We hope that our findings can both motivate and inform future work on securing industrial control systems.

Deterministic record-replay has many useful applications, ranging from fault tolerance and forensics to reproducing and diagnosing bugs. When choosing a record-replay solution, the system admin-istrator must choose a priori how comprehensively to record the execution and at what abstraction level to record it. Unfortunately, these choices may not match well with how the recording is eventu-ally used. A recording may contain too little information to support the end use of replay, or it may contain more sensitive information than is allowed to be shown to the end user of replay. Similarly, fixing the abstraction level at the time of recording often leads to a semantic mismatch with the end use of replay. This paper describes how to remedy these problems by adding customizable replay stages to create special-purpose logs for the end users of replay. Our system, called Crosscut, allows replay logs to be “sliced ” along time and abstraction boundaries. Using this approach, users can create slices that include only the processes, applications, or components of interest, excluding parts that handle sensitive data. Users can also retarget the abstraction level of the replay log to higher-level platforms, such as Perl or Valgrind. Exe-cution can then be augmented with additional analysis code at re-play time, without disturbing the replayed components in the slice. Crosscut thus uses replay itself to transform logs into a more effi-cient, secure, and usable form for replay-based applications. Our current Crosscut prototype builds on VMware Worksta-tion’s record-replay capabilities, and supports a variety of differ-ent replay environments. We show how Crosscut can create slices of only the parts of the computation of interest and thereby avoid leaking sensitive information, and we show how to retarget the ab-straction level of the log to enable more convenient use during re-play debugging.

History indicates that the security community commonly takes a divide-and-conquer approach to battling malware threats: identify the essential and inalienable components of an attack, then develop detection and prevention techniques that directly target one or more of the essential components. This abstraction is evident in much of the literature for buffer overflow attacks including, for instance, stack protection and NOP sled detection. It comes as no surprise then that we approach shellcode detection and prevention in a similar fashion. However, the common belief that components of polymorphic shellcode (e.g., the decoder) cannot reliably be hidden suggests a more implicit and broader assumption that continues to drive contemporary research: namely, that valid and complete representations of shellcode are fundamentally different in structure than benign payloads. While the first tenet of this assumption is philosophically undeniable (i.e., a string of bytes is either shellcode or it is not), truth of the latter claim is less obvious if there exist encoding techniques capable of producing shellcode with features nearly indistinguishable from non-executable content. In this paper, we challenge the assumption that shellcode must conform to superficial and discernible representations. Specifically, we demonstrate a technique for automatically producing English Shellcode, transforming arbitrary shellcode into a representation that is superficially similar to English prose. The shellcode is completely self-contained---i.e., it does not require an external loader and executes as valid IA32 code)---and can typically be generated in under an hour on commodity hardware. Our primary objective in this paper is to promote discussion and stimulate new ideas for thinking ahead about preventive measures for tackling evolutions in code-injection attacks.

While keystream reuse in stream ciphers and one-time pads has been a well known problem for several decades, the risk to real systems has been underappreciated. Previous techniques have relied on being able to accurately guess words and phrases that appear in one of the plaintext messages, making it far easier to claim that "an attacker would never be able to do that." In this paper, we show how an adversary can automatically recover messages encrypted under the same keystream if only the type of each message is known (e.g. an HTML page in English). Our method, which is related to HMMs, recovers the most probable plaintext of this type by using a statistical language model and a dynamic programming algorithm. It produces up to 99% accuracy on realistic data and can process ciphertexts at 200ms per byte on a $2,000 PC. To further demonstrate the practical effectiveness of the method, we show that our tool can recover documents encrypted by Microsoft Word 2002 [22].