Cem Topcuoglu (Northeastern University), Kaan Onarlioglu (Akamai Technologies), Bahruz Jabiyev (Northeastern University), Engin Kirda (Northeastern University)

Web server fingerprinting is a common activity in vulnerability management and security testing, with network scanners offering the capability for over two decades. All known fingerprinting techniques are designed for probing a single, isolated web server. However, the modern Internet is made up of complex layered architectures, where chains of CDNs, reverse proxies, and cloud services front origin servers. That renders existing fingerprinting tools and techniques utterly ineffective.

We present the first methodology that can fingerprint servers in a multi-layer architecture, by leveraging the HTTP processing discrepancies between layers. This technique is capable of detecting both the server technologies involved and their correct ordering. It is theoretically extendable to any number of layers, any server technology, deployed in any order, but of course within practical constraints. We then address those practical considerations and present a concrete implementation of the scheme in a tool called Untangle, empirically demonstrating its ability to fingerprint 3-layer architectures with high accuracy.

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Decentralized Information-Flow Control for ROS2

Nishit V. Pandya (Indian Institute of Science Bangalore), Himanshu Kumar (Indian Institute of Science Bangalore), Gokulnath M. Pillai (Indian Institute of Science Bangalore), Vinod Ganapathy (Indian Institute of Science Bangalore)

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ShapFuzz: Efficient Fuzzing via Shapley-Guided Byte Selection

Kunpeng Zhang (Shenzhen International Graduate School, Tsinghua University), Xiaogang Zhu (Swinburne University of Technology), Xi Xiao (Shenzhen International Graduate School, Tsinghua University), Minhui Xue (CSIRO's Data61), Chao Zhang (Tsinghua University), Sheng Wen (Swinburne University of Technology)

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BGP-iSec: Improved Security of Internet Routing Against Post-ROV Attacks

Cameron Morris (University of Connecticut), Amir Herzberg (University of Connecticut), Bing Wang (University of Connecticut), Samuel Secondo (University of Connecticut)

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