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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Private Aggregate Queries to Untrusted Databases

Syed Mahbub Hafiz (University of California, Davis), Chitrabhanu Gupta (University of California, Davis), Warren Wnuck (University of California, Davis), Brijesh Vora (University of California, Davis), Chen-Nee Chuah (University of California, Davis)

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PANDORA: Jailbreak GPTs by Retrieval Augmented Generation Poisoning

Gelei Deng, Yi Liu (Nanyang Technological University), Yuekang Li (The University of New South Wales), Wang Kailong(Huazhong University of Science and Technology), Tianwei Zhang, Yang Liu (Nanyang Technological University)

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Transforming Raw Authentication Logs into Interpretable Events

Seth Hastings, Tyler Moore, Corey Bolger, Philip Schumway (University of Tulsa)

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AutoWatch: Learning Driver Behavior with Graphs for Auto Theft...

Paul Agbaje, Abraham Mookhoek, Afia Anjum, Arkajyoti Mitra (University of Texas at Arlington), Mert D. Pesé (Clemson University), Habeeb Olufowobi (University of Texas at Arlington)

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