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Dynamic Hooks Dynamic Hooks: Hiding Control Flow Changes within Non-Control Data Sebastian Vogl, Technische Universität München; Robert Gawlik and Behrad Garmany, Ruhr-University Bochum; Thomas Kittel, Jonas Pfoh, and Claudia Eckert, Technische Universität München; Thorsten Holz, Ruhr-University Bochum https://www.usenix.org/conference/usenixsecurity14/technical-sessions/presentation/vogl This paper is included in the Proceedings of the 23rd USENIX Security Symposium. August 20–22, 2014 • San Diego, CA ISBN 978-1-931971-15-7 Open access to the Proceedings of the 23rd USENIX Security Symposium is sponsored by USENIX Dynamic Hooks: Hiding Control Flow Changes within Non-Control Data † † Sebastian Vogl∗, Robert Gawlik , Behrad Garmany , Thomas Kittel∗, † Jonas Pfoh∗, Claudia Eckert∗, Thorsten Holz ∗Technische Universität München †Horst Görtz Institute for IT-Security, Ruhr-University Bochum Abstract 1 Introduction Over the last decade, the sophistication and technical Generally speaking, malicious code leverages hooks level of malicious software (malware) has increased dra- within a system to divert the control flow. Without them, matically. In the early 2000s, we saw malware such as an attacker is blind to the events occurring in the sys- the I Love You [29] and Blaster worms [3] that gener- tem, rendering her unable to perform malicious activities ally operated in user space with very little in the way (e.g., hiding of files or capturing of keystrokes). How- of defensive mechanisms. In contrast, we nowadays see ever, while hooks are an integral part of modern attacks, complex kernel level malware such as Stuxnet, Duqu, and they are at the same time one of their biggest weaknesses: Flame [6] that show an increase in sophistication in the Even the most sophisticated attack can be easily identi- target of their attack, the exploitation methods used to fied if one of its hooks is found. In spite of this fact, deliver them, and their ability to evade detection. By tar- hooking mechanisms have remained almost unchanged geting kernel space, modern malware effectively runs at over the last years and still rely on the persistent mod- the same privilege level as the operating system (OS), ification of code or control data to divert the control enabling it to attack and modify any part of the system flow. As a consequence, hooks represent an abnormal- including the kernel itself. In addition, malware can take ity within the system that is permanently evident and can advantage of stealth techniques that were originally only in many cases easily be detected as the hook detection used by kernel rootkits to hide itself deep within the sys- mechanisms of recent years amply demonstrated. tem. This makes the detection of malware increasingly In this paper, we propose a novel hooking concept that difficult, especially as malware continues to evolve, en- we refer to as dynamic hooking. Instead of modifying abling it to stay one step ahead of the defenders. Cur- persistent control data permanently, this hooking mech- rently, one the most sophisticated methods employed is anisms targets transient control data such as return ad- data-only malware [16,41]. dresses at run-time. The hook itself will thereby reside However, even very sophisticated malware such as within non-control data and remains hidden until it is data-only malware has an Achilles’ heel: in general, mal- triggered. As a result, there is no evident connection be- ware needs to intercept events within the system to be tween the hook and the actual control flow change, which able to fulfill its purpose [27, 44]. Without this capabil- enables dynamic hooks to successfully evade existing de- ity, malware would be unable to react to events or pro- tection mechanisms. To realize this idea, dynamic hooks vide fundamental functionality such as key logging and make use of exploitation techniques to trigger vulner- file hiding, which would severely limit its possibilities. abilities at run-time. Due to this approach, dynamic Event interception, however, requires malware to divert hooks cannot only be used to arbitrarily modify the con- the control flow of the infected system at run-time. To trol flow, but can also be applied to conduct non-control achieve this, malware must install hooks in the system data attacks, which makes them more powerful than their that facilitate the required control flow transfer on be- predecessors. We implemented a prototype that makes half of the malware whenever the desired event occurs. uses of static program slicing and symbolic execution to While malware might manage to hide itself, these hooks automatically extract paths for dynamic hooks that can represent an abnormality that will be permanently visible then be used by a human expert for their realization. To within the system and thus lends itself well to becoming demonstrate this, we used the output provided by our the basis of detection mechanisms. This insight led to prototype to implement concrete examples of dynamic a wide range of research that enable the monitoring of hooks for both modern Linux and Windows kernels. malware hooking behavior for the purpose of signature USENIX Association 23rd USENIX Security Symposium 813 generation [47] or detecting malware based on control thereby provides detailed information about each jump flow modifications [15, 20, 43]. condition in the path and the actual vulnerability in an Although existing systems are not yet able to de- intuitive format, which makes the output suitable for ex- tect all hooks that are placed by malware, the remain- ploit generation frameworks or a human expert. We used ing possibilities for malware to install hooks are con- this prototype to automatically identify dynamic hooks stantly dwindling. Hooks that are based on code mod- for recent Linux and Windows kernels. Additionally, ifications are usually no longer an option, since changes we implemented proof of concepts (POCs) of dynamic to code areas can be easily detected due to their static na- hooks that demonstrate how they can be used in prac- ture. This leaves attackers only with the option of data tice to intercept events such as system calls or to imple- hooks [43,47], but even here the options are increasingly ment backdoors. This proves that the suggested hooking restricted by modern detection mechanisms. The reason mechanism is not only powerful, but also realistic. for this development is that, in contrast to malware where In summary, we make the following contributions: one can observe a constant evolution of techniques and mechanisms used, hooking techniques have not signifi- We present a novel hooking concept called dynamic • cantly changed over the course of recent years. hooking that targets transient control data at run- In this paper, we present a novel hooking concept that time instead of persistent control-data. This ap- we refer to as dynamic hooking. In contrast to existing proach bypasses existing hook detection techniques hooking mechanisms which persistently modify control proposed in the last few years. data, our hooking approach targets transient control data We show how dynamic hooks for OS kernels can be such as return addresses at run-time. As a consequence, • the resulting control flow change that is introduced by automatically found by leveraging binary analysis the hook only becomes visible when the hook is actu- techniques and implemented a prototype. ally triggered. This significantly complicates the detec- We provide detailed POC implementations of dy- • tion of dynamic hooks as security mechanisms can no namic hooks for both Linux and Windows kernels longer focus on persistent control data, but must also that demonstrate their capabilities and possibilities. take transient control data into account. What is even more, the hook itself will thereby reside in non-control data, which is much more difficult to analyze and ver- 2 Technical Background ify [4,15] when compared to control data that traditional hooks target. Despite the fact that dynamic hooks reside Before presenting our approach to realize dynamic purely in non-control data, they are able to reliably inter- hooks, we first review background information that is cept the execution flow of functions similar to traditional essential for the understanding of the remainder of the hooks. Furthermore, they can be used in pure data-only paper. We begin by defining important terms and then attacks, which are by themselves a realistic and danger- discuss why malware in general requires hooks within ous threat [3, 5]. Thus they are not only harder to detect, the system to function. Finally, we cover existing hook- but also more powerful than their predecessors. ing mechanisms and their countermeasures. To provide these capabilities, dynamic hooks modify data in such a way that they will trigger vulnerabilities at 2.1 Definitions run-time. Through this approach, they are able to arbi- trarily modify the control flow, while the hook itself only We first introduce important terms that we will use consists of the data that triggers and exploits the vulner- throughout the paper. In particular, we highlight the dif- ability. This makes them quite similar to traditional ex- ferences between control data and non-control data as ploitation techniques with the exception that they target well as transient and permanent control data. applications that are already controlled by the attacker. Due to this fact, the attack surface for dynamic hooks is Control data and non-control data. Control data much broader compared to traditional exploitation, since specifies the target location of a branch instruction. By an attacker can not only attack external functions, but changing control data, an attacker can arbitrarily change also internal functions. the control flow of an application. Examples of control Furthermore, dynamic hooks can be obtained automat- data are return addresses and function pointers. ically in a manner comparable to automated exploit gen- In contrast, non-control data never contains the target eration [2].
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