Secure dynamic code generation against spraying

DCG (Dynamic Code Generation) technologies have found widely applications in the Web 2.0 era, Dion Blazakis recently presented a Flash JIT-Spraying attack against Adobe Flash Player that easily circumvented DEP and ASLR protection mechanisms built in modern operating systems. We have generalized and extended JIT Spraying into DCG Spraying. Based our analyses on this abstract model of DCG Spraying, we have found that all mainstream DCG implementations (Java/ JavaScript/ Flash/ .Net/ SilverLight) are vulnerable against DCG Spraying attack, and none of the existing ad hoc defenses such as compilation optimization, random NOP padding and constant splitting provides effective protection. Furthermore, we propose a new protection method, INSeRT, which combines randomization of intrinsic elements of machine instructions and randomly planted special trapping snippets. INSeRT practically renders the 'sprayed code' ineffective, while alerts the host program of ongoing attacking attempts. We implemented a prototype of INSeRT on the V8 JavaScript engine, and the performance overhead is less than 5%, which should be acceptable in practical application.EI

Adaptive just-in-time code diversification

We present a method to regenerate diversified code dynamically in a Java bytecode JIT compiler, and to update the diversification frequently during the execution of the program. This way, we can significantly reduce the time frame in which attackers can let a program leak useful address space information and subsequently use the leaked information in memory exploits. A proof of concept implementation is evaluated, showing that even though code is recompiled frequently, we can achieved smaller overheads than the previous state of the art, which generated diversity only once during the whole execution of a program

Between Worlds: Securing Mixed JavaScript/ActionScript Multi-Party Web Content

Mixed Flash and JavaScript content has become increasingly prevalent; its purveyance of dynamic features unique to each platform has popularized it for myriad Web development projects. Although Flash and JavaScript security has been examined extensively, the security of untrusted content that combines both has received considerably less attention. This article considers this fusion in detail, outlining several practical scenarios that threaten the security of Web applications. The severity of these attacks warrants the development of new techniques that address the security of Flash-JavaScript content considered as a whole, in contrast to prior solutions that have examined Flash or JavaScript security individually. Toward this end, the article presents FlashJaX, a cross-platform solution that enforces fine-grained, history-based policies that span both Flash and JavaScript. Using in-lined reference monitoring, FlashJaX safely embeds untrusted JavaScript and Flash content in Web pages without modifying browser clients or using special plug-ins. The architecture of FlashJaX, its design and implementation, and a detailed security analysis are exposited. Experiments with advertisements from popular ad networks demonstrate that FlashJaX is transparent to policy-compliant advertisement content, yet blocks many common attack vectors that exploit the fusion of these Web platforms

Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks

Malware still constitutes a major threat in the cybersecurity landscape, also due to the widespread use of infection vectors such as documents. These infection vectors hide embedded malicious code to the victim users, facilitating the use of social engineering techniques to infect their machines. Research showed that machine-learning algorithms provide effective detection mechanisms against such threats, but the existence of an arms race in adversarial settings has recently challenged such systems. In this work, we focus on malware embedded in PDF files as a representative case of such an arms race. We start by providing a comprehensive taxonomy of the different approaches used to generate PDF malware, and of the corresponding learning-based detection systems. We then categorize threats specifically targeted against learning-based PDF malware detectors, using a well-established framework in the field of adversarial machine learning. This framework allows us to categorize known vulnerabilities of learning-based PDF malware detectors and to identify novel attacks that may threaten such systems, along with the potential defense mechanisms that can mitigate the impact of such threats. We conclude the paper by discussing how such findings highlight promising research directions towards tackling the more general challenge of designing robust malware detectors in adversarial settings

Using HTML5 to Prevent Detection of Drive-by-Download Web Malware

The web is experiencing an explosive growth in the last years. New technologies are introduced at a very fast-pace with the aim of narrowing the gap between web-based applications and traditional desktop applications. The results are web applications that look and feel almost like desktop applications while retaining the advantages of being originated from the web. However, these advancements come at a price. The same technologies used to build responsive, pleasant and fully-featured web applications, can also be used to write web malware able to escape detection systems. In this article we present new obfuscation techniques, based on some of the features of the upcoming HTML5 standard, which can be used to deceive malware detection systems. The proposed techniques have been experimented on a reference set of obfuscated malware. Our results show that the malware rewritten using our obfuscation techniques go undetected while being analyzed by a large number of detection systems. The same detection systems were able to correctly identify the same malware in its original unobfuscated form. We also provide some hints about how the existing malware detection systems can be modified in order to cope with these new techniques.Comment: This is the pre-peer reviewed version of the article: \emph{Using HTML5 to Prevent Detection of Drive-by-Download Web Malware}, which has been published in final form at \url{http://dx.doi.org/10.1002/sec.1077}. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archivin

Binary Exploitation in Industrial Control Systems: Past, Present and Future

Despite being a decades-old problem, binary exploitation still remains a serious issue in computer security. It is mainly due to the prevalence of memory corruption errors in programs written with notoriously unsafe but yet indispensable programming languages like C and C++. For the past 30 years, the nip-and-tuck battle in memory between attackers and defenders has been getting more technical, versatile, and automated. With raised bar for exploitation in common information technology (IT) systems owing to hardened mitigation techniques, and with unintentionally opened doors into industrial control systems (ICS) due to the proliferation of industrial internet of things (IIoT), we argue that we will see an increased number of cyber attacks leveraging binary exploitation on ICS in the near future. However, while this topic generates a very rich and abundant body of research in common IT systems, there is a lack of systematic study targeting this topic in ICS. The present work aims at filling this gap and serves as a comprehensive walkthrough of binary exploitation in ICS. Apart from providing an analysis of the past cyber attacks leveraging binary exploitation on ICS and the ongoing attack surface transition, we give a review of the attack techniques and mitigation techniques on both general-purpose computers and embedded devices. At the end, we conclude this work by stressing the importance of network-based intrusion detection, considering the dominance of resource-constrained real-time embedded devices, low-end embedded devices in ICS, and the limited ability to deploy arbitrary defense mechanism directly on these devices

Practical Control-Flow Integrity

Control-Flow Integrity (CFI) is effective at defending against prevalent control-flow hijacking attacks. CFI extracts a control-flow graph (CFG) for a given program and instruments the program to respect the CFG. Specifically, checks are inserted before indirect branch instructions. Before these instructions are executed during runtime, the checks consult the CFG to ensure that the indirect branch is allowed to reach the intended target. Hence, any sort of control-flow hijacking would be prevented.However, CFI traditionally suffered from several problems that thwarted its practicality. The first problem is about precise CFG generation. CFI’s security squarely relies on the CFG, therefore the more precise the CFG is, the more security CFI improves, but precise CFG generation was considered hard. The second problem is modularity, or support for dynamic linking. When two CFI modules are linked together dynamically, their CFGs also need to be merged. However, the merge process has to be thread-safe to avoid concurrency issues. The third problem is efficiency. CFI instrumentation adds extra instructions to programs, so it is critical to minimize the performance impact of the CFI checks. Fourth, interoperability is required for CFI solutions to enable gradual adoption in practice, which means that CFI-instrumented modules can be linked with uninstrumented modules without breaking the program.In this dissertation, we propose several practical solutions to the above problems. To generate a precise CFG, we compile the program being protected using a modified compilation toolchain, which can propagate source-level information such as type information to the binary level. At runtime, such information is gathered to generate a relatively precise CFG. On top of this CFG, we further instrument the code so that only if a function’s address is dynamically taken can it be reachable. This approach results in lazily computed per-input CFGs, which provide better precision. To address modularity, we design a lightweight Software Transactional Memory (STM) algorithm to synchronize accesses to the CFG’s data structure at runtime. To minimize the performance overhead, we optimize the CFG representation and access operations so that no heavy buslockinginstructions are needed. For interoperability, we consider addresses in uninstrumented modules as special targets and make the CFI instrumentation aware of them. Finally, we propose a new architecture for Just-In-Time compilers to adopt our proposed CFI schemes

User-Behavior Based Detection of Infection Onset

A major vector of computer infection is through exploiting software or design flaws in networked applications such as the browser. Malicious code can be fetched and executed on a victim’s machine without the user’s permission, as in drive-by download (DBD) attacks. In this paper, we describe a new tool called DeWare for detecting the onset of infection delivered through vulnerable applications. DeWare explores and enforces causal relationships between computer-related human behaviors and system properties, such as file-system access and process execution. Our tool can be used to provide real time protection of a personal computer, as well as for diagnosing and evaluating untrusted websites for forensic purposes. Besides the concrete DBD detection solution, we also formally define causal relationships between user actions and system events on a host. Identifying and enforcing correct causal relationships have important applications in realizing advanced and secure operating systems. We perform extensive experimental evaluation, including a user study with 21 participants, thousands of legitimate websites (for testing false alarms), as well as 84 malicious websites in the wild. Our results show that DeWare is able to correctly distinguish legitimate download events from unauthorized system events with a low false positive rate (< 1%)