Mathy Vanhoef

2papers

2 Papers

4.7CRApr 3
Open Challenges for Secure and Scalable Wi-Fi Connectivity in Rural Areas

Philip Virgil Berrer Astillo, Jayasree Sengupta, Mathy Vanhoef

Providing reliable, affordable, and secure Internet connectivity in rural areas remains a major challenge. Pay-for-use Wi-Fi hotspots are emerging as a scalable solution to provide affordable Internet access in underserved and rural regions. Despite their growing adoption, their security properties remain largely unexplored. In this paper, we present a security analysis of these hotspot ecosystems based on Wi-Fi surveys and practical attack validation. We first perform a Wi-Fi survey conducted in two countries, namely the Philippines and India, to understand the deployment and adoption of such systems in practice. Our results suggest that Piso-WiFi pay-to-use hotspots are particularly widespread in rural regions of the Philippines, and that India's PM-WANI initiative is slowly gaining traction. We then perform a security assessment of these deployments and demonstrate two practical attacks: hijacking another user's paid connection; and rogue hotspots. We analyze the root causes of these vulnerabilities, introduce threat models tailored to pay-for-use hotspot deployments, and outline practical security improvements, including a secure caching architecture. Our findings highlight security challenges in emerging rural connectivity infrastructure and provide directions toward more secure and scalable deployments.

CRJun 4, 2021
The Closer You Look, The More You Learn: A Grey-box Approach to Protocol State Machine Learning

Chris McMahon Stone, Sam L. Thomas, Mathy Vanhoef et al.

In this paper, we propose a new approach to infer state machine models from protocol implementations. Our method, STATEINSPECTOR, learns protocol states by using novel program analyses to combine observations of run-time memory and I/O. It requires no access to source code and only lightweight execution monitoring of the implementation under test. We demonstrate and evaluate STATEINSPECTOR's effectiveness on numerous TLS and WPA/2 implementations. In the process, we show STATEINSPECTOR enables deeper state discovery, increased learning efficiency, and more insightful post-mortem analyses than existing approaches. Further to improved learning, our method led us to discover several concerning deviations from the standards and a high impact vulnerability in a prominent Wi-Fi implementation.