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.

View More Papers

Do Privacy Labels Answer Users' Privacy Questions?

Shikun Zhang, Norman Sadeh (Carnegie Mellon University)

Read More

Faster Secure Comparisons with Offline Phase for Efficient Private...

Florian Kerschbaum (University of Waterloo), Erik-Oliver Blass (Airbus), Rasoul Akhavan Mahdavi (University of Waterloo)

Read More

PPA: Preference Profiling Attack Against Federated Learning

Chunyi Zhou (Nanjing University of Science and Technology), Yansong Gao (Nanjing University of Science and Technology), Anmin Fu (Nanjing University of Science and Technology), Kai Chen (Chinese Academy of Science), Zhiyang Dai (Nanjing University of Science and Technology), Zhi Zhang (CSIRO's Data61), Minhui Xue (CSIRO's Data61), Yuqing Zhang (University of Chinese Academy of Science)

Read More