Kostas Drakonakis (FORTH), Sotiris Ioannidis (Technical University of Crete), Jason Polakis (University of Illinois at Chicago)

Black-box web vulnerability scanners are invaluable for security researchers and practitioners. Despite recent approaches tackling emph{some} of the inherent limitations of scanners, many have not sufficiently evolved alongside web browsers and applications, and often lack the capabilities for handling the inherent challenges of navigating and interacting with modern web applications. Instead of building an alternative scanner that could naturally only incorporate a limited set of the wide range of vulnerability-finding capabilities offered by the multitude of existing scanners, in this paper we propose an entirely different strategy. We present ReScan, a emph{scanner-agnostic} middleware framework that emph{transparently} enhances scanners' capabilities by mediating their interaction with web applications in a realistic and robust manner, using an orchestrated, fully-fledged modern browser. In essence, our framework can be used in conjunction with emph{any} vulnerability scanner, thus allowing users to benefit from the capabilities of existing and future scanners. Our extensible and modular framework includes a collection of enhancement techniques that address limitations and obstacles commonly faced by state-of-the-art scanners. Our experimental evaluation demonstrates that despite the considerable (and expected) overhead introduced by a fully-fledged browser, our framework significantly improves the code coverage achieved by popular scanners (168% on average), resulting in a 66% and 161% increase in the number of reflected and stored XSS vulnerabilities detected, respectively.

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Lightning Community Shout-Outs to:

(1) Jonathan Petit, Secure ML Performance Benchmark (Qualcomm) (2) David Balenson, The Road to Future Automotive Research Datasets: PIVOT Project and Community Workshop (USC Information Sciences Institute) (3) Jeremy Daily, CyberX Challenge Events (Colorado State University) (4) Mert D. Pesé, DETROIT: Data Collection, Translation and Sharing for Rapid Vehicular App Development (Clemson University) (5) Ning…

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Hope of Delivery: Extracting User Locations From Mobile Instant...

Theodor Schnitzler (Research Center Trustworthy Data Science and Security, TU Dortmund, and Ruhr-Universität Bochum), Katharina Kohls (Radboud University), Evangelos Bitsikas (Northeastern University and New York University Abu Dhabi), Christina Pöpper (New York University Abu Dhabi)

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Measuring Messengers: Analyzing Infrastructures and Message Timings to Extract...

Theodor Schnitzler (Research Center Trustworthy Data Science and Security, TU Dortmund, and Ruhr-Universität Bochum)

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RAI2: Responsible Identity Audit Governing the Artificial Intelligence

Tian Dong (Shanghai Jiao Tong University), Shaofeng Li (Shanghai Jiao Tong University), Guoxing Chen (Shanghai Jiao Tong University), Minhui Xue (CSIRO's Data61), Haojin Zhu (Shanghai Jiao Tong University), Zhen Liu (Shanghai Jiao Tong University)

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