PentestGPT: An LLM-empowered Automatic Penetration Testing Tool

Penetration testing, a crucial industrial practice for ensuring system security, has traditionally resisted automation due to the extensive expertise required by human professionals. Large Language Models (LLMs) have shown significant advancements in various domains, and their emergent abilities suggest their potential to revolutionize industries. In this research, we evaluate the performance of LLMs on real-world penetration testing tasks using a robust benchmark created from test machines with platforms. Our findings reveal that while LLMs demonstrate proficiency in specific sub-tasks within the penetration testing process, such as using testing tools, interpreting outputs, and proposing subsequent actions, they also encounter difficulties maintaining an integrated understanding of the overall testing scenario. In response to these insights, we introduce PentestGPT, an LLM-empowered automatic penetration testing tool that leverages the abundant domain knowledge inherent in LLMs. PentestGPT is meticulously designed with three self-interacting modules, each addressing individual sub-tasks of penetration testing, to mitigate the challenges related to context loss. Our evaluation shows that PentestGPT not only outperforms LLMs with a task-completion increase of 228.6\% compared to the \gptthree model among the benchmark targets but also proves effective in tackling real-world penetration testing challenges. Having been open-sourced on GitHub, PentestGPT has garnered over 4,700 stars and fostered active community engagement, attesting to its value and impact in both the academic and industrial spheres

Impact of Design Patterns on Code Quality in Blockchain-based Applications

Blockchain or Distributed Ledger Technology (DLT) introduces a new computing paradigm that is viewed by experts as a disruptive and revolutionary technology. While bitcoin is the most well-known successful application of blockchain technology, many other applications and sectors could successfully utilize the power of blockchain. The potential applications of blockchain beyond finance and banking encouraged many organizations to integrate and adopt blockchain into existing or new software systems. Integrating and using any new computing paradigm is expected to affect the best practice and design principles of building software systems. Emerging blockchain-based applications require careful attention to many functional and nonfunctional requirements. One common practice in software engineering to handle potential pitfalls in software systems is using design patterns. Design patterns have been long used in software development to optimize the quality of software being developed. This research aims to determine the level of adoption of design patterns blockchain applications and their usefulness by analyzing the quality of the source code. This is achieved in a two-step process. Firstly, the quality of publicly available blockchain-based applications developed with design patterns is compared with applications without design patterns. In the next step, two versions of a blockchain-based application for cheque clearance are developed, with and without design patterns, and their quality and vulnerability to attacks are compared

Architecture Supporting Computational Trust Formation

Trust is a concept that has been used in computing to support better decision making. For example, trust can be used in access control. Trust can also be used to support service selection. Although certain elements of trust such as reputation has gained widespread acceptance, a general model of trust has so far not seen widespread usage. This is due to the challenges of implementing a general trust model. In this thesis, a middleware based approach is proposed to address the implementation challenges. The thesis proposes a general trust model known as computational trust. Computational trust is based on research in social psychology. An individual’s computational trust is formed with the support of the proposed computational trust architecture. The architecture consists of a middleware and middleware clients. The middleware can be viewed as a representation of the individual that shares its knowledge with all the middleware clients. Each application uses its own middleware client to form computational trust for its decision making needs. Computational trust formation can be adapted to changing circumstances. The thesis also proposed algorithms for computational trust formation. Experiments, evaluations and scenarios are also presented to demonstrate the feasibility of the middleware based approach to computational trust formation

Attack Taxonomy Methodology Applied to Web Services

With the rapid evolution of attack techniques and attacker targets, companies and researchers question the applicability and effectiveness of security taxonomies. Although the attack taxonomies allow us to propose a classification scheme, they are easily rendered useless by the generation of new attacks. Due to its distributed and open nature, web services give rise to new security challenges. The purpose of this study is to apply a methodology for categorizing and updating attacks prior to the continuous creation and evolution of new attack schemes on web services. Also, in this research, we collected thirty-three (33) types of attacks classified into five (5) categories, such as brute force, spoofing, flooding, denial-of-services, and injection attacks, in order to obtain the state of the art of vulnerabilities against web services. Finally, the attack taxonomy is applied to a web service, modeling through attack trees. The use of this methodology allows us to prevent future attacks applied to many technologies, not only web services.Con la rápida evolución de las técnicas de ataque y los objetivos de los atacantes, las empresas y los investigadores cuestionan la aplicabilidad y eficacia de las taxonomías de seguridad. Si bien las taxonomías de ataque nos permiten proponer un esquema de clasificación, son fácilmente inutilizadas por la generación de nuevos ataques. Debido a su naturaleza distribuida y abierta, los servicios web plantean nuevos desafíos de seguridad. El propósito de este estudio es aplicar una metodología para categorizar y actualizar ataques previos a la continua creación y evolución de nuevos esquemas de ataque a servicios web. Asimismo, en esta investigación recolectamos treinta y tres (33) tipos de ataques clasificados en cinco (5) categorías, tales como fuerza bruta, suplantación de identidad, inundación, denegación de servicios y ataques de inyección, con el fin de obtener el estado del arte de las vulnerabilidades contra servicios web. Finalmente, se aplica la taxonomía de ataque a un servicio web, modelado a través de árboles de ataque. El uso de esta metodología nos permite prevenir futuros ataques aplicados a muchas tecnologías, no solo a servicios web

Novel Attacks and Defenses in the Userland of Android

In the last decade, mobile devices have spread rapidly, becoming more and more part of our everyday lives; this is due to their feature-richness, mobility, and affordable price. At the time of writing, Android is the leader of the market among operating systems, with a share of 76% and two and a half billion active Android devices around the world. Given that such small devices contain a massive amount of our private and sensitive information, the economic interests in the mobile ecosystem skyrocketed. For this reason, not only legitimate apps running on mobile environments have increased dramatically, but also malicious apps have also been on a steady rise. On the one hand, developers of mobile operating systems learned from security mistakes of the past, and they made significant strides in blocking those threats right from the start. On the other hand, these high-security levels did not deter attackers. In this thesis, I present my research contribution about the most meaningful attack and defense scenarios in the userland of the modern Android operating system. I have emphasized "userland'' because attack and defense solutions presented in this thesis are executing in the userspace of the operating system, due to the fact that Android is slightly different from traditional operating systems. After the necessary technical background, I show my solution, RmPerm, in order to enable Android users to better protect their privacy by selectively removing permissions from any app on any Android version. This operation does not require any modification to the underlying operating system because we repack the original application. Then, using again repackaging, I have developed Obfuscapk; it is a black-box obfuscation tool that can work with every Android app and offers a free solution with advanced state of the art obfuscation techniques -- especially the ones used by malware authors. Subsequently, I present a machine learning-based technique that focuses on the identification of malware in resource-constrained devices such as Android smartphones. This technique has a very low resource footprint and does not rely on resources outside the protected device. Afterward, I show how it is possible to mount a phishing attack -- the historically preferred attack vector -- by exploiting two recent Android features, initially introduced in the name of convenience. Although a technical solution to this problem certainly exists, it is not solvable from a single entity, and there is the need for a push from the entire community. But sometimes, even though there exists a solution to a well-known vulnerability, developers do not take proper precautions. In the end, I discuss the Frame Confusion vulnerability; it is often present in hybrid apps, and it was discovered some years ago, but I show how it is still widespread. I proposed a methodology, implemented in the FCDroid tool, for systematically detecting the Frame Confusion vulnerability in hybrid Android apps. The results of an extensive analysis carried out through FCDroid on a set of the most downloaded apps from the Google Play Store prove that 6.63% (i.e., 1637/24675) of hybrid apps are potentially vulnerable to Frame Confusion. The impact of such results on the Android users' community is estimated in 250.000.000 installations of vulnerable apps

The importance to manage data protection in the right way: Problems and solutions

Information and communication technology (ICT) has made remarkable impact on the society, especially on companies and organizations. The use of computers, databases, servers, and other technologies has made an evolution on the way of storing, processing, and transferring data. However, companies access and share their data on internet or intranet, thus there is a critical need to protect this data from destructive forces and from the unwanted actions of unauthorized users. This thesis groups a set of solutions proposed, from a company point of view, to reach the goal of \u201cManaging data protection\u201d. The work presented in this thesis represents a set of security solutions, which focuses on the management of data protection taking into account both the organizational and technological side. The work achieved can be divided into set of goals that are obtained particularly from the needs of the research community. This thesis handles the issue of managing data protection in a systematic way, through proposing a Data protection management approach, aiming to protect the data from both the organizational and the technological side, which was inspired by the ISO 27001 requirements. An Information Security Management System (ISMS) is then presented implementing this approach, an ISMS consists of the policies, procedures, guidelines, and associated resources and activities, collectively managed by an organization, in the pursuit of protecting its information assets. An ISMS is a systematic approach for establishing, implementing, operating, monitoring, reviewing, maintaining and improving an organization\u2019s information security to achieve business objectives, The goal of ISMS is to minimize risk and ensure continuity by pro-actively limiting the impact of a security breach. To be well-prepared to the potential threats that could occur to an organization, it is important to adopt an ISMS that helps in managing the data protection process, and in saving time and effort, minimizes cost of any loss. After that, a comprehensive framework is designed for the security risk management of Cyber Physical Systems (CPSs), this framework represents the strategy used to manage the security risk management, and it falls inside the ISMS as a security strategy. Traditional IT risk assessment methods can do the job (security risk management for a CPS); however, and because of the characteristics of a CPS, it is more efficient to adopt a solution that is wider than a method that addresses the type, functionalities and complexity of a CPS. Therefore, there is a critical need to follow a solution that breaks the restriction to a traditional risk assessment method, and so a high-level framework is proposed, it encompasses wider set of procedures and gives a great attention to the cybersecurity of these systems, which consequently leads to the safety of the physical world. In addition, inside the ISMS, another part of the work takes place, suggesting the guidelines to select an applicable Security Incident and Event Management (SIEM) solution. It also proposes an approach that aims to support companies seeking to adopt SIEM systems into their environments, suggesting suitable answers to preferred requirements that are believed to be valuable prerequisites a SIEM system should have; and to suggest criteria to judge SIEM systems using an evaluation process composed of quantitative and qualitative methods. This approach, unlike others, is customer driven which means that customer needs are taken into account when following the whole approach, specifically when defining the requirements and then evaluating the suppliers\u2019 solutions. At the end, a research activity was carried out aiming classify web attacks on the network level, since any information about the attackers might be helpful and worth a lot to the cyber security analysts. And so, using network statistical fingerprints and machine learning techniques, a two-layers classification system is designed to detect the type of the web attack and the type of software used by the attackers