5GDescrambler: Locating, Descrambling, and Decoding 5G Scheduling Information (Long Version)

Tracking users in 5G NR has recently been successfully demonstrated by exploiting various side-channels. This allows for identification of individuals, classification of user activity in real time as well as tracking by fingerprinting, affecting billions of users with a 5G subscription and...

Towards Operator-Empowered Vulnerability Hotfixing for 5G Radio Access Networks

Cellular protocol vulnerabilities can remain exploitable for months or years while standards bodies, vendors, and mobile network operators MNOs coordinate permanent fixes. We present Buckler, a framework that enables an MNO to deploy temporary, local, and reversible hotfixes in its radio access...

Slice-Aware Spoofing Detection in 5G Networks Using Lightweight Machine Learning

The increasing virtualization of fifth generation 5G networks expands the attack surface of the user plane, making spoofing a persistent threat to slice integrity and service reliability. This study presents a slice-aware lightweight machine-learning framework for detecting spoofing attacks withi...

LTESniffer - An Open-source LTE Downlink/Uplink Eavesdropper

LTESniffer is An Open-source LTE Downlink/Uplink Eavesdropper It first decodes the Physical Downlink Control Channel PDCCH to obtain the Downlink Control Informations DCIs and Radio Network Temporary Identifiers RNTIs of all active users. Using decoded DCIs and RNTIs, LTESniffer further decodes t...