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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Chloe Fortuna (STR), JT Paasch (STR), Sam Lasser (Draper), Philip Zucker (Draper), Chris Casinghino (Jane Street), Cody Roux (AWS)

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Programmer's Perception of Sensitive Information in Code

Xinyao Ma, Ambarish Aniruddha Gurjar, Anesu Christopher Chaora, Tatiana R Ringenberg, L. Jean Camp (Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington)

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Attributions for ML-based ICS Anomaly Detection: From Theory to...

Clement Fung (Carnegie Mellon University), Eric Zeng (Carnegie Mellon University), Lujo Bauer (Carnegie Mellon University)

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TinyML meets IoBT against Sensor Hacking

Raushan Kumar Singh (IIT Ropar), Sudeepta Mishra (IIT Ropar)

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