Although the security testing of Web systems can be automated by generating crafted inputs, solutions to automate the test oracle, i.e., vulnerability detection, remain difficult to apply in practice. Specifically, though previous work has demonstrated the potential of metamorphic testing—security failures can be determined by metamorphic relations that turn valid inputs into malicious inputs—metamorphic relations are typically executed on a large set of inputs, which is time-consuming and thus makes metamorphic testing impractical. We propose AIM, an approach that automatically selects inputs to reduce testing costs while preserving vulnerability detection capabilities. AIM includes a clustering-based black-box approach, to identify similar inputs based on their security properties. It also relies on a novel genetic algorithm to efficiently select diverse inputs while minimizing their total cost. Further, it contains a problem-reduction component to reduce the search space and speed up the minimization process. We evaluated the effectiveness of AIM on two well-known Web systems, Jenkins and Joomla, with documented vulnerabilities. We compared AIM's results with four baselines involving standard search approaches. Overall, AIM reduced metamorphic testing time by 84% for Jenkins and 82% for Joomla, while preserving the same level of vulnerability detection. Furthermore, AIM significantly outperformed all the considered baselines regarding vulnerability coverage.

Security testing aims at verifying that the software meets its security properties. In modern Web systems, however, this often entails the verification of the outputs generated when exercising the system with a very large set of inputs. Full automation is thus required to lower costs and increase the effectiveness of security testing. Unfortunately, to achieve such automation, in addition to strategies for automatically deriving test inputs, we need to address the oracle problem, which refers to the challenge, given an input for a system, of distinguishing correct from incorrect behavior (e.g., the response to be received after a specific HTTP GET request). In this paper, we propose Metamorphic Security Testing for Web-interactions (MST-wi), a metamorphic testing approach that integrates test input generation strategies inspired by mutational fuzzing and alleviates the oracle problem in security testing. It enables engineers to specify metamorphic relations (MRs) that capture many security properties of Web systems. To facilitate the specification of such MRs, we provide a domain-specific language accompanied by an Eclipse editor.MST-wiautomatically collects the input data and transforms the MRs into executable Java code to automatically perform security testing. It automatically tests Web systems to detect vulnerabilities based on the relations and collected data. We provide a catalog of 76 system-agnostic MRs to automate security testing in Web systems. It covers 39% of the OWASP security testing activities not automated by state-of-the-art techniques; further, our MRs can automatically discover 102 different types of vulnerabilities, which correspond to 45% of the vulnerabilities due to violations of security design principles according to the MITRE CWE database. We also define guidelines that enable test engineers to improve the testability of the system under test with respect to our approach. We evaluatedMST-wieffectiveness and scalability with two well-known Web systems (i.e., Jenkins and Joomla). It automatically detected 85% of their vulnerabilities and showed a high specificity (99.81% of the generated inputs do not lead to a false positive); our findings include a new security vulnerability detected in Jenkins. Finally, our results demonstrate that the approach scale, thus enabling automated security testing overnight.