FIDO2 is a popular technology for single-factor and second-factor authentication. It is specified in an open standard including the WebAuthn and CTAP application layer protocols. We focus on CTAP which allows the communication between FIDO2 clients and authenticators. No prior work explored the CTAP Authenticator API which is a critical protocol-level attack surface as it deals with credential creation, deletion, and management. We address this gap by presenting the first security and privacy evaluation of the CTAP Authenticator API. We uncover two classes of CTAP protocol-level attacks we call CTRAPS.The client impersonation (CI) attacks exploit the lack of client authentication to tamper with FIDO2 authenticators. They include zero-click attacks capable of deleting FIDO2 credentials, including passkeys, without user interaction. The API confusion (AC) attacks abuse the lack of protocol API enforcements and confound FIDO2 authenticators, clients, and users into calling unwanted CTAP APIs while thinking they are calling legitimate ones. For example, a victim thinks is authenticating to a website, when they are deleting their credentials. The CTRAPS attacks are conducted either in proximity or remotely and are effective regardless of the underlying CTAP transport (USB, NFC, or BLE).We detail the eight vulnerabilities in the CTAP specification enabling the CTRAPS attacks. Seven of them are novel and include unauthenticated CTAP clients and trackable FIDO2 credentials. We release CTRAPS, an original toolkit to analyze CTAP and conduct the CTRAPS attacks. We confirm the attacks’ feasibility by exploiting six popular authenticators, including a FIPS-certified one, from Yubico, Feitian, SoloKeys, and Google, and ten widely used relying parties, such as Microsoft, Apple, GitHub, and Facebook. We discuss eight backward-compliant countermeasures to fix the attacks and their root causes. We responsibly disclosed our findings to the FIDO Alliance and the affected vendors.

Xiaomi is the market leader in the electric scooter (e-scooter) segment, with millions of active users. It provides several e-scooter models and Mi Home, a mobile application for Android and iOS to manage and control an e-scooter. Mi Home and the e-scooter interact via Bluetooth Low Energy (BLE). No prior research evaluated the security of this communication channel, as it employs security protocols proprietary to Xiaomi. Exploiting these protocols results in severe security, privacy, and safety issues, e.g., an attacker could steal an e-scooter or prevent the owner from controlling it. In this work, we fill this research gap by performing the first security evaluation on all proprietary wireless protocols deployed to Xiaomi e-scooters from 2016 to 2021. We identify and reverse-engineer four of them, each having ad-hoc Pairing and Session phases. We develop four attacks exploiting these protocols at the architectural level, and we call them Malicious Pairing (MP) and Session Downgrade (SD). Both attacks can be performed from proximity, if the attacker's machine is within BLE range of the target e-scooter, or remotely, via a malicious application co-located with Mi Home. An adversary can utilize MP and SD to steal a password-protected and software-locked e-scooter, or to prevent a victim from accessing it via Mi Home. We isolate six attack root causes, including the lack of authentication while pairing, and the improper enforcement of the e-scooter password. We open-source the E-Spoofer toolkit. Our toolkit automates the MP and SD attacks, and includes a reverse-engineering module for future research. We empirically confirm the effectiveness of our attacks by exploiting three e-scooters (i.e., M365, Essential, and Mi 3), embedding five BLE subsystem boards and eight BLE firmware versions that support all four Xiaomi protocols. We design and evaluate two practical countermeasures that address our impactful attacks and their root causes, and we release them as part of E-Spoofer. We responsibly disclosed our findings to Xiaomi.

Automated contact tracing is a key solution to control the spread of airborne transmittable diseases: it traces contacts among individuals in order to alert people about their potential risk of being infected. The current SARS-CoV-2 pandemic put a heavy strain on the healthcare system of many countries. Governments chose different approaches to face the spread of the virus and the contact tracing apps were considered the most effective ones. In particular, by leveraging on the Bluetooth Low-Energy technology, mobile apps allow to achieve a privacy-preserving contact tracing of citizens. While researchers proposed several contact tracing approaches, each government developed its own national contact tracing app.