Tony Nasr (Concordia University), Sadegh Torabi (George Mason University), Elias Bou-Harb (University of Texas at San Antonio), Claude Fachkha (University of Dubai), Chadi Assi (Concordia University)

Electric Vehicle Charging Management Systems (EVCMS) are a collection of specialized software that allow users to remotely operate Electric Vehicle Charging Stations (EVCS). With the increasing number of deployed EVCS to support the growing global EV fleet, the number of EVCMS are consequently growing, which introduces a new attack surface. In this paper, we propose a novel multi-stage framework, ChargePrint, to discover Internet-connected EVCMS and investigate their security posture. ChargePrint leverages identifiers extracted from a small seed of EVCMS to extend the capabilities of device search engines through iterative fingerprinting and a combination of classification and clustering approaches. Using initial seeds from 1,800 discovered hosts that deployed 9 distinct EVCMS, we identified 27,439 online EVCS instrumented by 44 unique EVCMS. Consequently, our in-depth security analysis highlights the insecurity of the deployed EVCMS by uncovering 120 0-day vulnerabilities, which shed light on the feasibility of cyber attacks against the EVCS, its users, and the connected power grid. Finally, while we recommend countermeasures to mitigate future threats, we contribute to the security of the EVCS ecosystem by conducting a Coordinated Vulnerability Disclosure (CVD) effort with system developers/vendors who acknowledged and assigned the discovered vulnerabilities more than 20 CVE-IDs.

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Ankit Gangwal (IIIT Hyderabad), Aakash Jain (IIIT Hyderabad) and Mauro Conti (University of Padua)

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Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

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Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)