XSS pattern for attack modeling in testing

Security issues of web applications are still a current topic of interest especially when considering the consequences of unintended behaviour. Such services might handle sensitive data about several thousands or millions of users. Hence, exploiting services or other undesired effects that cause harm on users has to be avoided. Therefore, for software developers of such applications one of the major tasks in providing security is to embed testing methodologies into the software development cycle, thus minimizing the subsequent damage resulting in debugging and time intensive upgrading. Model-based testing evolved as one of the methodologies which offer several theoretical and practical approaches in testing the system under test (SUT) that combine several input generation strategies like mutation testing, using of concrete and symbolic execution etc. by putting the emphasis on specification of the model of an application. In this work we propose an approach that makes use of an attack pattern model in form of a UML state machine for test case generation and execution. The paper also discusses the current implementation of our attack pattern testing tool using a XSS attack pattern and demonstrates the execution in a case study.

Application stress testing applies the concept of computer network penetration testing to software applications. Since software applications may be attacked - from inside or outside a protected network boundary - they are threatened by actions and conditions which cause delays, disruptions, or failures. Stress testing exposes software systems to simulated cyber attacks, revealing potential weaknesses and vulnerabilities in their implementation. By using such testing, these internal weaknesses and vulnerabilities can be discovered earlier in the software development life cycle, corrected prior to deployment, and lead to improved software quality. Application stress testing is a process and software prototype for verifying the quality of software applications under severe operating conditions. Since stress testing is rarely - if at all - performed today, the possibility of deploying critical software systems that have been stress tested provides a much stronger indication of their ability to withstand cyber attacks. Many possible attack vectors against critical software can be verified as true threats and mitigated prior to deployment. This improves software quality and serves as a tremendous risk reduction for critical software systems used in government and commercial enterprises. The software prototype models and verifies failure conditions of a system under test (SUT). The SUT is first executed in a virtual environment and its normal operational modes are observed. A normal behavior model is generated in order to predict failure conditions based on attack models and external SUT interfaces. Using off-the-shelf software tools, the predictions are verified in the virtual environment by stressing the executing SUT with attacks against the SUT. Results are presented to testers and system developers for dispensation or mitigation.

This paper contributes an analysis of possible pitfalls of automated test execution and provides an novel approach for TTCN-3 test system to manage and recover from errors occurred in the System Under Test (SUT) during test execution. The research problem addressed in this paper is how to facilitate recovery of distributed test system to recover from cascading errors caused by software faults in the SUT. This research problem is addressed by applying the software fault tolerance techniques in the implementation of the testing environment. Provided solutions for error recovery and management are derived from the software fault tolerance research work carried out during last decades. The presented approach is validated in a prototype TTCN-3 test environment supporting testing of distributed communication systems.

State-based testing (SBT) is known as deriving test cases from state machines and examining the dynamic behaviour of the system. It helps to identify various types of state-based faults within a system under test (SUT). For SBT, test cases are generated from state chart diagrams based on various coverage criteria such as All Transition, Round Trip Path, All Transition Pair, All Transition Pair with length 2, All Transition Pair with length 3, All Transition Pair of length 4 and Full Predicate. This article discuses a number of coverage criteria at the design level to find out various types of state-based faults in SBT. First, the intermediate graph is generated from a state chart diagram using an XML parser. The graph is traversed based on the given coverage criteria to generate a sequence of test cases. Then, mutation testing and sneak-path testing are applied on the generated test cases to check the effectiveness of the generated test suite. These two are common methods for checking the effectiveness of test cases. Mutation testing helps in the number of seeded errors covered whereas sneak-path testing basically helps to examine the unspecified behavior of the system. In round trip path (RTP), it is not possible to cover all paths. All transition is not an adequate level of fault detection with more execution time compared to all transition pair (ATP) with length 4 (LN4). In the discussion, ATP with LN4 is the best among all coverage criteria. SBT can able to detect various state-based faults-incorrect transition, missing transition, missing or incorrect event, missing or incorrect action, extra missing or corrupt state, which are difficult to detect in code-based testing. Most of these state-based faults can be avoided, if the testing is conducted at the early phase of design.

Clinical decision support (CDS) software requires regular maintenance and development. CDS software can be very complex and can have several different performance parameters that need to be considered in development and maintenance cycles. Stakeholders in management and software development need a shared and mutually agreed on framework to prioritize the development and maintenance of CDS software. The prioritization matrix, a quality improvement tool, was used to prioritize triage algorithms at Ask Mayo Clinic, a national triage call center. Key elements used in the priority matrix were the frequency of algorithm use, potential safety impact of the algorithm, algorithm length, overall agreement between software recommendation and triage nurse, and asymmetry of nurse overrides of the software recommendation. This methodology also bridges the language gap between software developers and management and gives management the ability to customize how software maintenance and development cycles are prioritized.

Regression testing as an essential activity in software development that has changed requirements. In practice, regression testing requires a lot of time so that an optimal strategy is needed. One approach that can be used to speed up execution time is the Regression Test Selection (RTS) approach. Currently, practitioners and academics have started to think about developing tools to optimize the process of implementing regression testing. Among them, STARTS and Ekstazi are the most popular regression testing tools among academics in running test case selection algorithms. This article discusses the comparison of the capabilities of the STARTS and Ekstazi features by using feature parameter evaluation. Both tools were tested with the same input data in the form of System Under Test (SUT) and test cases. The parameters used in the tool comparisons are platform technology, test case selection, functionality, usability and performance efficiency, the advantages, and disadvantages of the tool. he results of the trial show the differences and similarities between the features of STARTS and Ekstazi, so that it can be used by practitioners to take advantage of tools in the implementation of regression testing that suit their needs. In addition, experimental results show that the use of Ekstazi is more precise in sorting out important test cases and is more efficient, when compared to STARTS and regression testing with retest all.

In software security testing, fuzz testing and symbolic execution are two main testing techniques. Fuzz testing finds program bugs by executing the target program with random inputs it generates while monitoring the execution for abnormal behaviors. Though fuzz testing is able to explore deep into a program's state space efficiently, it usually cannot guarantee the code coverage ratio in many situations. Symbolic execution treats a program's input as symbols and executes the program with such symbolic input. Symbolic execution tries to explore the whole state space of a program by analyzing all of the program's paths. Symbolic execution always guarantees the code coverage ratio in theory, but for real programs it has many problems such as path explosion. Our new method, hybrid fuzz testing, combines the benefits of fuzz testing and symbolic execution. Symbolic execution will start to work and to generate new program input when fuzz testing cannot increase the code coverage ratio. The experiment result implies that our hybrid fuzz testing method can obviously increase the code coverage ratio efficiently in reasonable resources using.

This work focuses on the validation of attack pattern mining in the context of Industrial Control System (ICS) security. A comprehensive security assessment of an ICS requires the generation of a variety of attack patterns. For this purpose, we have proposed a data-driven technique to generate attack patterns for an ICS. The proposed technique has been used to generate 117,960 attack patterns from data from a water treatment plant. These attack patterns were used to launch attacks on the operational testbed that typically lasted 2 to 4 minutes. Interestingly, some 2-minute attacks impacted the plant, while some attacks of 3 or 4 minutes duration had no observable effect. This suggests that even short-lived attacks can significantly impact operational plants. The proposed technique and the effectiveness of the patterns generated in moving the plant to an anomalous state are valuable when assessing the quality of Intrusion Detection Systems for physical plants. In this work, we present a detailed case study to validate the attack patterns.

We present the Chained Attacks approach, an automated model-based approach to test the security of web applications that does not require a background in formal methods. Starting from a set of HTTP conversations and a configuration file providing the testing surface and purpose, a model of the System Under Test (SUT) is generated and input, along with the web attacker model we defined, to a model checker acting as test oracle. The HTTP conversations, payload libraries, and a mapping created while generating the model aid the concretization of the test cases, allowing for their execution on the SUT's implementation. We applied our approach to a real-life case study and we were able to find a combination of different attacks representing the concrete chained attack performed by a bug bounty hunter.

In this paper we present some theoretical and experimental issues related to organizational and cognitive models of the design and use of new information technologies in an industrial software development/maintenance environment. The approach attempts to reconcile, from a unified viewpoint, some results obtained through CEC and company funded research projects. It is our opinion that a large amount of “enterprise knowledge” should be captured both in terms of human expertise and skills, and in terms of system and domain knowledge acquired or produced during software system development. Varied and distributed expertise as well as shared workspaces and resources will pose further constraints on the way service organizations will evolve in the near future. An “enterprise knowledge communication network” can well constitute a learning infrastructure embodying organizational principles as well as decision support tools which are important for engaging and sustaining successful learning. Understanding and thus modelling organizational learning as a continuously interactive process which influences the decision-making behaviour as well as the service-oriented behaviour and providing it with intelligent support software tools, can result in the workplace of the future, where specialisation is valued and innovation encouraged.

Welcome to the International Conference on Software and Systems Process (ICSSP) held in Zurich, Switzerland, on June 2nd and 3rd, 2012. Having grown from a Software Process Workshop in 2005 to the International Conference on Software Process (ICSP) in 2007, and finally to the International Conference on Software and Systems Process (ICSSP) in 2011, this conference series has established its place in the software engineering community as a respected conference focusing on research and practice related to software and systems development process. Software and software systems development use processes as one major means for achieving and ensuring the quality of the final product. This leads to specific challenges regarding software processes such as simplicity, adaptability, standard conformance, the coordination of multiple domains and lifecycles, etc. Processes from other domains (e.g., health care, manufacturing, business, aerospace, automotive systems, and others) face similar challenges. Yet, they share interesting similarities with and differences to software processes. The question is: How can we in the software domain learn from other domains to meet our software process engineering challenges? The ICSSP conferences hence connect the traditional software and systems process community with outside views and insights, broadening its scope of software development processes to system development and explicitly including processes of other domains such as health care, business, and manufacturing. By sharing process development theories and practices from such domains, ICSSP 2012 is investigating novel solutions to today's process challenges. Correspondingly, the main theme of ICSSP 2012 is Beyond Software and Software Systems Processes, signaling our goal of learning from domains other than the traditional software process community.

We present results for the "Impact Project Focus Area" on the topic of symbolic execution as used in software testing. Symbolic execution is a program analysis technique introduced in the 70s that has received renewed interest in recent years, due to algorithmic advances and increased availability of computational power and constraint solving technology. We review classical symbolic execution and some modern extensions such as generalized symbolic execution and dynamic test generation. We also give a preliminary assessment of the use in academia, research labs, and industry. © 2011 ACM.

Symbolic execution based test-patterns generation algorithm for hardware Trojan detection

In a software system, most of the runtime failures may come to light only during test execution, and this may have a very high cost. To help address this problem, a symbolic execution engine called RTEHunter, which has been developed at the Department of Software Engineering at the University of Szeged, is able to detect runtime errors (such as null pointer dereference, bad array indexing, division by zero) in Java programs without actually running the program in a real-life environment. Applying the theory of symbolic execution, RTEHunter builds a tree, called a symbolic execution tree, composed of all the possible execution paths of the program. RTEHunter detects runtime issues by traversing the symbolic execution tree and if a certain condition is fulfilled the engine reports an issue. However, as the number of execution paths increases exponentially with the number of branching points, the exploration of the whole symbolic execution tree becomes impossible in practice. To overcome this problem, different kinds of constraints can be set up over the tree. E.g. the number of symbolic states, the depth of the execution tree, or the time consumption could be restricted. Our goal in this study is to find the optimal parametrization of RTEHunter in terms of the maximum number of states, maximum depth of the symbolic execution tree and search strategy in order to find more runtime issues in a shorter time. Results on three open-source Java systems demonstrate that more runtime issues can be detected in the 0 to 60 basic block-depth levels than in deeper ones within the same time frame. We also developed two novel search strategies for traversing the tree based on the number of null pointer references in the program and on linear regression that performs better than the default depth-first search strategy.

This work introduces a model-based approach for minimization of test costs for interactive systems. Results known from state-based conformance testing and graph theory are used and extended to construct algorithms for test case generation and selection to cover the behavioral model of the system under test (SUT). The test case selection on the basis of the established model is ruled by an adequacy criterion, which provides a measure of how effective a given set of test cases is in terms of its potential to reveal faults. The approach is specification-oriented; i.e., the underlying model represents the system behavior interacting with the user's actions, that are viewed here as events.