Master of Science

thesisSystem administrators use application-level knowledge to identify anomalies in virtual appliances (VAs) and to recover from them. This process can be automated through an anomaly detection and recovery system. In this thesis, we claim that application-level policies defined over kernel-level application state can be effective for automatically detecting and mitigating the effects of malicious software in VAs. By combining user-defined application-level policies, virtual machine introspection (VMI), expert systems, and kernel-based state management techniques for anomaly detection and recovery, we are able to provide a favorable environment for the execution of applications in VAs. We use policies to specify the desired state of the VA based on an administrator's application-level knowledge. By using VMI we are able to generate a snapshot that represents the true internal state of the VA. An expert system evaluates the snapshot and identifies any violations. Potential violations include the execution of an irrelevant application, an unauthorized process, or an unfavorable environment configuration. The expert system also reasons about appropriate recovery strategies for each of the violations detected. The recovery strategy decided by the expert system is carried out by recovery tools so that the VA can be restored to an acceptable state. We evaluate the effectiveness of this approach for anomaly detection and repair by using it to detect and recover from the actions of different types malicious software targeting a web server VA. The system is shown to be effective in guarding the VA against the actions of a kernel-exploit kit, a kernel rootkit, a user-space rootkit, and an application malware. For each of these attacks, the recovery component was able to restore the VA to an acceptable state. Although, the recovery actions carried out did not remove the malicious software, they substantially mitigated the harmful effects of the malicious software

Hypervisor-Based Active Data Protection for Integrity and Confidentiality Of Dynamically Allocated Memory in Windows Kernel

One of the main issues in the OS security is providing trusted code execution in an untrusted environment. During executing, kernel-mode drivers dynamically allocate memory to store and process their data: Windows core kernel structures, users’ private information, and sensitive data of third-party drivers. All this data can be tampered with by kernel-mode malware. Attacks on Windows-based computers can cause not just hiding a malware driver, process privilege escalation, and stealing private data but also failures of industrial CNC machines. Windows built-in security and existing approaches do not provide the integrity and confidentiality of the allocated memory of third-party drivers. The proposed hypervisor-based system (AllMemPro) protects allocated data from being modified or stolen. AllMemPro prevents access to even 1 byte of allocated data, adapts for newly allocated memory in real time, and protects the driver without its source code. AllMemPro works well on newest Windows 10 1709 x64

Covert Android Rootkit Detection: Evaluating Linux Kernel Level Rootkits on the Android Operating System

This research developed kernel level rootkits for Android mobile devices designed to avoid traditional detection methods. The rootkits use system call hooking to insert new handler functions that remove the presence of infection data. The effectiveness of the rootkit is measured with respect to its stealth against detection methods and behavior performance benchmarks. Detection method testing confirms that while detectable with proven tools, system call hooking detection is not built-in or currently available in the Google Play Android App Store. Performance behavior benchmarking showed that system call hooking affects the completion time of the targeted system calls. However, this delay\u27s magnitude may not be noticeable by users. The rootkits implemented targets Android 4.0 on the emulator available from the Android Open Source Project (AOSP) and the Samsung Galaxy Nexus. The rootkits are compiled against both Linux kernel 2.6 and 3.0, respectively. This research shows the Android\u27s Linux kernel is vulnerable to system call hooking and additional measures should be implemented before handling sensitive data with Android

Bridging the detection gap: a study on a behavior-based approach using malware techniques

In recent years the intensity and complexity of cyber attacks have increased at a rapid rate. The cost of these attacks on U.S. based companies is in the billions of dollars, including the loss of intellectual property and reputation. Novel and diverse approaches are needed to mitigate the cost of a security breach, and bridge the gap between malware detection and a security breach. This thesis focuses on the short term need to mitigate the impact of undetected shellcodes that cause security breaches. The thesis\u27s approach focuses on the agents driving the attacks, capturing their actions, in order to piece together the attacks for forensics purposes, as well as to better understand the opponent. The work presented in this thesis employs models of normal operating system behavior to detect access to the operating system\u27s shell interface. It also utilizes malware techniques to avoid detection and subsequent termination of the monitoring system, as well as dynamic shellcode execution methodologies in the testing of the thesis\u27 modules to implement a monitoring system --Document

NoSEBrEaK - Attacking Honeynets

It is usually assumed that Honeynets are hard to detect and that attempts to detect or disable them can be unconditionally monitored. We scrutinize this assumption and demonstrate a method how a host in a honeynet can be completely controlled by an attacker without any substantial logging taking place

Detecting kernel rootkits

Kernel rootkits are a special category of malware that are deployed directly in the kernel and hence have unmitigated reign over the functionalities of the kernel itself. We seek to detect such rootkits that are deployed in the real world by first observing how the majority of kernel rootkits operate. To this end, comparable to how rootkits function in the real world, we write our own kernel rootkit that manipulates the network driver, thus giving us control over all packets sent into the network. We then implement a mechanism to thwart the attacks of such rootkits by noticing that a large number of the rootkits deployed today rely heavily on the redirection of function pointers within the kernel. By overwriting the desired function pointer to its own function, a rootkit can perform a proverbial man-in-the-middle attack. Our goal is not just the detection of kernel rootkits, but also to levy as little an impact on system performance as possible. Hence our technique is to leverage existing kernel functionalities (in the case of Linux) such as kprobes to identify potential attack scenarios from within the sytem rather than from outside it (such as a VMM). We hope to introduce real-world security in devices where performance and resource constraints are tantamount to security considerations