Helmholtz Center for Information Security
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ProfilIoT: A Machine Learning Approach for IoT Device Identification Based on Network Traffic Analysis (Poster)
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An Automata-Theoretic Approach to Modeling Systems and Specifications over Infinite Data
No full textData-parameterized systems model finite state systems over an infinite data domain. VLTL is an extension of LTL that uses variables in order to specify properties of computations over infinite data, and as such VLTL is suitable for specifying properties of data-parameterized systems. We present Alternating Variable Büchi Word Automata (AVBWs), a new model of automata over infinite alphabets, capable of modeling a significant fragment of VLTL. While alternating and non-deterministic Büchi automata over finite alphabets have the same expressive power, we show that this is not the case for infinite data domains, as we prove that AVBWs are strictly stronger than the previously defined Non-deterministic Variable Büchi Word Automata (NVBWs). However, while the emptiness problem is easy for NVBWs, it is undecidable for AVBWs. We present an algorithm for translating AVBWs to NVBWs in cases where such a translation is possible. Additionally, we characterize the structure of AVBWs that can be translated to NVBWs with our algorithm, and identify fragments of VLTL for which a direct NVBW construction exists. Since the emptiness problem is crucial in the automata-theoretic approach to model checking, our results give rise to a model-checking algorithm for a rich fragment of VLTL and systems over infinite data domains
Deemon: Detecting CSRF with Dynamic Analysis and Property Graphs
Get PDFCross-Site Request Forgery (CSRF) vulnerabilities are a severe class of web vulnerabilities that have received only marginal attention from the research and security testing communities. While most of the effort has been spent on countermeasures and detection of XSS and SQLi, to date, the detection of CSRF vulnerabilities is still performed predominantly manually.
In this paper, we present Deemon, to the best of our knowledge, the first automated security testing framework to discover CSRF vulnerabilities. Our approach is based on a new modeling paradigm which captures multiple aspects of web applications, including execution traces, data flows, and architecture tiers in a unified, comprehensive property graph. We present the paradigm and show how a concrete model can be built automatically using dynamic traces. Then, using graph traversals, we mine for potentially vulnerable operations. Using the information captured in the model, our approach then automatically creates and conducts security tests, to practically validate the found CSRF issues. We evaluate the effectiveness of Deemon with 10 popular open source web applications. Our experiments uncovered 14 previously unknown CSRF vulnerabilities that can be exploited, for instance, to take over user accounts or entire websites
