Retrofitting Security in COTS Software with Binary Rewriting

We present a practical tool for inserting security features against low-level software attacks into third-party, proprietary or otherwise binary-only software. We are motivated by the inability of software users to select and use low-overhead protection schemes when source code is unavailable to them, by the lack of information as to what (if any) security mechanisms software producers have used in their toolchains, and the high overhead and inaccuracy of solutions that treat software as a black box. Our approach is based on SecondWrite, an advanced binary rewriter that operates without need for debugging information or other assist. Using SecondWrite, we insert a variety of defenses into program binaries. Although the defenses are generally well known, they have not generally been used together because they are implemented by different (non-integrated) tools. We are also the first to demonstrate the use of such mechanisms in the absence of source code availability. We experimentally evaluate the effectiveness and performance impact of our approach. We show that it stops all variants of low-level software attacks at a very low performance overhead, without impacting original program functionality

Multitenancy - Security Risks and Countermeasures

Security within the cloud is of paramount importance as the interest and indeed utilization of cloud computing increase. Multitenancy in particular introduces unique security risks to cloud computing as a result of more than one tenant utilizing the same physical computer hardware and sharing the same software and data. The purpose of this paper is to explore the specific risks in cloud computing due to Multitenancy and the measures that can be taken to mitigate those risks.Security within the cloud is of paramount importance as the interest and indeed utilization of cloud computing increase. Multitenancy in particular introduces unique security risks to cloud computing as a result of more than one tenant utilizing the same physical computer hardware and sharing the same software and data. The purpose of this paper is to explore the specific risks in cloud computing due to Multitenancy and the measures that can be taken to mitigate those risks

Detection of repetitive and irregular hypercall attacks from guest virtual machines to Xen hypervisor

Virtualization is critical to the infrastructure of cloud computing environment and other online services. Hypercall interface is provided by hypervisor to offer privileged requests by the guest domains. Attackers may use this interface to send malicious hypercalls. In the reported work, repetitive hypercall attacks and sending hypercalls within irregular sequences to Xen hypervisor were analyzed, and finally, an intrusion detection system (IDS) is proposed to detect these attacks. The proposed system is placed in the host domain (Dom0). Monitoring hypercalls traffic the system operates based on the identification of irregular behaviors in hypercalls sent from guest domains to hypervisor. Later on, the association rule algorithm is applied on the collected data within a fixed time window, and a set of thresholds for maximum number of all types of the hypercalls is extracted. The results from the implementation of the proposed system show 91% true positive rate

Investigating Emerging Security Threats in Clouds and Data Centers

Data centers have been growing rapidly in recent years to meet the surging demand of cloud services. However, the expanding scale of a data center also brings new security threats. This dissertation studies emerging security issues in clouds and data centers from different aspects, including low-level cooling infrastructures and different virtualization techniques such as container and virtual machine (VM). We first unveil a new vulnerability called reduced cooling redundancy that might be exploited to launch thermal attacks, resulting in severely worsened thermal conditions in a data center. Such a vulnerability is caused by the wide adoption of aggressive cooling energy saving policies. We conduct thermal measurements and uncover effective thermal attack vectors at the server, rack, and data center levels. We also present damage assessments of thermal attacks. Our results demonstrate that thermal attacks can negatively impact the thermal conditions and reliability of victim servers, significantly raise the cooling cost, and even lead to cooling failures. Finally, we propose effective defenses to mitigate thermal attacks. We then perform a systematic study to understand the security implications of the information leakage in multi-tenancy container cloud services. Due to the incomplete implementation of system resource isolation mechanisms in the Linux kernel, a spectrum of system-wide host information is exposed to the containers, including host-system state information and individual process execution information. By exploiting such leaked host information, malicious adversaries can easily launch advanced attacks that can seriously affect the reliability of cloud services. Additionally, we discuss the root causes of the containers\u27 information leakage and propose a two-stage defense approach. The experimental results show that our defense is effective and incurs trivial performance overhead. Finally, we investigate security issues in the existing VM live migration approaches, especially the post-copy approach. While the entire live migration process relies upon reliable TCP connectivity for the transfer of the VM state, we demonstrate that the loss of TCP reliability leads to VM live migration failure. By intentionally aborting the TCP connection, attackers can cause unrecoverable memory inconsistency for post-copy, significantly increase service downtime, and degrade the running VM\u27s performance. From the offensive side, we present detailed techniques to reset the migration connection under heavy networking traffic. From the defensive side, we also propose effective protection to secure the live migration procedure

TREDIS – A Trusted Full-Fledged SGX-Enabled REDIS Solution

Currently, offloading storage and processing capacity to cloud servers is a growing trend among web-enabled services managing big datasets. This happens because high storage capacity and powerful processors are expensive, whilst cloud services provide cheaper, ongoing, elastic, and reliable solutions. The problem with this cloud-based out sourced solutions are that they are highly accessible through the Internet, which is good, but therefore can be considerably exposed to attacks, out of users’ control. By exploring subtle vulnerabilities present in cloud-enabled applications, management functions, op erating systems and hypervisors, an attacker may compromise the supported systems, thus compromising the privacy of sensitive user data hosted and managed in it. These attacks can be motivated by malicious purposes such as espionage, blackmail, identity theft, or harassment. A solution to this problem is processing data without exposing it to untrusted components, such as vulnerable OS components, which might be compromised by an attacker. In this thesis, we do a research on existent technologies capable of enabling appli cations to trusted environments, in order to adopt such approaches to our solution as a way to help deploy unmodified applications on top of Intel-SGX, with overheads com parable to applications designed to use this kind of technology, and also conducting an experimental evaluation to better understand how they impact our system. Thus, we present TREDIS - a Trusted Full-Fledged REDIS Key-Value Store solution, implemented as a full-fledged solution to be offered as a Trusted Cloud-enabled Platform as a Service, which includes the possibility to support a secure REDIS-cluster architecture supported by docker-virtualized services running in SGX-enabled instances, with operations run ning on always-encrypted in-memory datasets.A transição de suporte de aplicações com armazenamento e processamento em servidores cloud é uma tendência que tem vindo a aumentar, principalmente quando se precisam de gerir grandes conjuntos de dados. Comparativamente a soluções com licenciamento privado, as soluções de computação e armazenamento de dados em nuvens de serviços são capazes de oferecer opções mais baratas, de alta disponibilidade, elásticas e relativa mente confiáveis. Estas soluções fornecidas por terceiros são facilmente acessíveis através da Internet, sendo operadas em regime de outsourcing da sua operação, o que é bom, mas que por isso ficam consideravelmente expostos a ataques e fora do controle dos utiliza dores em relação às reais condições de confiabilidade, segurança e privacidade de dados. Ao explorar subtilmente vulnerabilidades presentes nas aplicações, funções de sistemas operativos (SOs), bibliotecas de virtualização de serviços de SOs ou hipervisores, um ata cante pode comprometer os sistemas e quebrar a privacidade de dados sensíveis. Estes ataques podem ser motivados por fins maliciosos como espionagem, chantagem, roubo de identidade ou assédio e podem ser desencadeados por intrusões (a partir de atacantes externos) ou por ações maliciosas ou incorretas de atacantes internos (podendo estes atuar com privilégios de administradores de sistemas). Uma solução para este problema passa por armazenar e processar a informação sem que existam exposições face a componentes não confiáveis. Nesta dissertação estudamos e avaliamos experimentalmente diversas tecnologias que permitem a execução de aplicações com isolamento em ambientes de execução confiá vel suportados em hardware Intel-SGX, de modo a perceber melhor como funcionam e como adaptá-las à nossa solução. Para isso, realizámos uma avaliação focada na utilização dessas tecnologias com virtualização em contentores isolados executando em hardware confiável, que usámos na concepção da nossa solução. Posto isto, apresentamos a nossa solução TREDIS - um sistema Key-Value Store confiável baseado em tecnologia REDIS, com garantias de integridade da execução e de privacidade de dados, concebida para ser usada como uma "Plataforma como Serviço"para gestão e armazenamento resiliente de dados na nuvem. Isto inclui a possibilidade de suportar uma arquitetura segura com garantias de resiliência semelhantes à arquitetura de replicação em cluster na solução original REDIS, mas em que os motores de execução de nós e a proteção de memória do cluster é baseado em contentores docker isolados e virtualizados em instâncias SGX, sendo os dados mantidos sempre cifrados em memória

Comparative Analysis of Malware Behavior in Hardware and Virtual Sandboxes

openMalicious software, or malware, continues to be a pervasive threat to computer systems and networks worldwide. As malware constantly evolves and becomes more sophisticated, it is crucial to develop effective methods for its detection and analysis. Sandboxing technology has emerged as a valuable tool in the field of cybersecurity, allowing researchers to safely execute and observe malware behavior in controlled environments. This thesis presents a comprehensive investigation into the behavior of malware samples when executed in both hardware and virtual sandboxes. The primary objective is to assess the effectiveness of hardware sandboxing in capturing and analyzing malware behaviors compared to traditional virtual sandboxes. The research methodology involves the execution of various malware samples in both hardware and virtual sandboxes, followed by the analysis of key parameters, including memory changes, file system logs, and network traffic. By comparing the results obtained from the two sandboxing approaches, this study aims to provide insights into the advantages and limitations of each method. Furthermore, the research delves into the potential evasion techniques employed by malware to bypass detection in either sandboxing environment. Identifying such evasion strategies is vital for enhancing the overall security posture and developing more robust defense mechanisms against evolving malware threats. The findings of this research contribute to the field of cybersecurity by shedding light on the strengths and weaknesses of hardware and virtual sandboxes for malware analysis. Ultimately, this work serves as a valuable resource for security practitioners and researchers seeking to improve malware detection and analysis techniques in the ever-evolving landscape of cybersecurity threats.Malicious software, or malware, continues to be a pervasive threat to computer systems and networks worldwide. As malware constantly evolves and becomes more sophisticated, it is crucial to develop effective methods for its detection and analysis. Sandboxing technology has emerged as a valuable tool in the field of cybersecurity, allowing researchers to safely execute and observe malware behavior in controlled environments. This thesis presents a comprehensive investigation into the behavior of malware samples when executed in both hardware and virtual sandboxes. The primary objective is to assess the effectiveness of hardware sandboxing in capturing and analyzing malware behaviors compared to traditional virtual sandboxes. The research methodology involves the execution of various malware samples in both hardware and virtual sandboxes, followed by the analysis of key parameters, including memory changes, file system logs, and network traffic. By comparing the results obtained from the two sandboxing approaches, this study aims to provide insights into the advantages and limitations of each method. Furthermore, the research delves into the potential evasion techniques employed by malware to bypass detection in either sandboxing environment. Identifying such evasion strategies is vital for enhancing the overall security posture and developing more robust defense mechanisms against evolving malware threats. The findings of this research contribute to the field of cybersecurity by shedding light on the strengths and weaknesses of hardware and virtual sandboxes for malware analysis. Ultimately, this work serves as a valuable resource for security practitioners and researchers seeking to improve malware detection and analysis techniques in the ever-evolving landscape of cybersecurity threats

Nature-inspired survivability: Prey-inspired survivability countermeasures for cloud computing security challenges

As cloud computing environments become complex, adversaries have become highly sophisticated and unpredictable. Moreover, they can easily increase attack power and persist longer before detection. Uncertain malicious actions, latent risks, Unobserved or Unobservable risks (UUURs) characterise this new threat domain. This thesis proposes prey-inspired survivability to address unpredictable security challenges borne out of UUURs. While survivability is a well-addressed phenomenon in non-extinct prey animals, applying prey survivability to cloud computing directly is challenging due to contradicting end goals. How to manage evolving survivability goals and requirements under contradicting environmental conditions adds to the challenges. To address these challenges, this thesis proposes a holistic taxonomy which integrate multiple and disparate perspectives of cloud security challenges. In addition, it proposes the TRIZ (Teorija Rezbenija Izobretatelskib Zadach) to derive prey-inspired solutions through resolving contradiction. First, it develops a 3-step process to facilitate interdomain transfer of concepts from nature to cloud. Moreover, TRIZ’s generic approach suggests specific solutions for cloud computing survivability. Then, the thesis presents the conceptual prey-inspired cloud computing survivability framework (Pi-CCSF), built upon TRIZ derived solutions. The framework run-time is pushed to the user-space to support evolving survivability design goals. Furthermore, a target-based decision-making technique (TBDM) is proposed to manage survivability decisions. To evaluate the prey-inspired survivability concept, Pi-CCSF simulator is developed and implemented. Evaluation results shows that escalating survivability actions improve the vitality of vulnerable and compromised virtual machines (VMs) by 5% and dramatically improve their overall survivability. Hypothesis testing conclusively supports the hypothesis that the escalation mechanisms can be applied to enhance the survivability of cloud computing systems. Numeric analysis of TBDM shows that by considering survivability preferences and attitudes (these directly impacts survivability actions), the TBDM method brings unpredictable survivability information closer to decision processes. This enables efficient execution of variable escalating survivability actions, which enables the Pi-CCSF’s decision system (DS) to focus upon decisions that achieve survivability outcomes under unpredictability imposed by UUUR