What You Trust Is Insecure: Demystifying How Developers (Mis)Use Trusted Execution Environments in Practice
Trusted Execution Environments (TEEs), such as Intel SGX and ARM TrustZone, provide isolated regions of CPU and memory for secure computation and are increasingly used to protect sensitive data and code across diverse application domains. However, little is known about how developers actually use TEEs in practice. This paper presents the first large-scale empirical study of real-world TEE applications. We collected and analyzed 241 open-source projects from GitHub that utilize the two most widely-adopted TEEs, Intel SGX and ARM TrustZone. By combining manual inspection with customized static analysis scripts, we examined their adoption contexts, usage patterns, and development practices across three phases. First, we categorized the projects into 8 application domains and identified trends in TEE adoption over time. We found that the dominant use case is IoT device security (30%), which contrasts sharply with prior academic focus on blockchain and cryptographic systems (7%), while AI model protection (12%) is rapidly emerging as a growing domain. Second, we analyzed how TEEs are integrated into software and observed that 32.4% of the projects reimplement cryptographic functionalities instead of using official SDK APIs, suggesting that current SDKs may have limited usability and portability to meet developers’ practical needs. Third, we examined security practices through manual inspection and found that 25.3% (61 of 241) of the projects exhibit insecure coding behaviors when using TEEs, such as hardcoded secrets and missing input validation, which undermine their intended security guarantees. Our findings have important implications for improving the usability of TEE SDKs and supporting developers in trusted software development.
Wed 18 MarDisplayed time zone: Athens change
14:00 - 15:30 | Session 2B - Security, Vulnerabilities, and MisusesResearch Track / Industrial Track at Megaron Beta Chair(s): Minhaz F. Zibran Idaho State University | ||
14:00 15mTalk | What You Trust Is Insecure: Demystifying How Developers (Mis)Use Trusted Execution Environments in Practice Research Track Yuqing Niu , Jieke Shi Singapore Management University, Ruidong Han Singapore Management University, Ye Liu Singapore Management University, Chengyan Ma Singapore Management University, Yunbo Lyu Singapore Management University, David Lo Singapore Management University Pre-print | ||
14:15 15mTalk | From Patterns to Precision: LLM-Guided Detection of Signature Verification Flaws in Smart Contracts Research Track | ||
14:30 15mTalk | SeBERTis: A Framework for Producing Classifiers of Security-Related Issue Reports Research Track Sogol Masoumzadeh Mcgill University, Yufei Li McGill University, Shane McIntosh University of Waterloo, Daniel Varro Linköping University / McGill University, Lili Wei McGill University | ||
14:45 15mTalk | MLmisFinder: A Specification and Detection Approach of Machine Learning Service Misuses Research Track Hadil Ben Amor Ecole de Technologie Supérieure, Niruthiha Selvanayagam Ecole de Technologie Supérieure, Manel Abdellatif École de Technologie Supérieure, Taher A. Ghaleb Trent University, Naouel Moha École de Technologie Supérieure (ETS) | ||
15:00 15mTalk | VulTerminator: Bringing Back Template-Based Automated Repair for Fixing Java Vulnerabilities Research Track Quang-Cuong Bui Hamburg University of Technology, Emanuele Iannone Hamburg University of Technology, Riccardo Scandariato Hamburg University of Technology Pre-print | ||
15:15 15mTalk | From Legacy Designs to Vulnerability Fixes: Understanding SAST Adoption in Non-Technological Companies Industrial Track Luis Henrique Vieira Amaral University of Brasília, Brazil, Michael Schlichtig Heinz Nixdorf Institut, Paderborn University, Wagner Emanuel , Joilton Almeida de Jesus , Carine Ferreira , Jérôme Kempf , Rodrigo Bonifácio Informatics Center - CIn/UFPE and Computer Science Department / University of Brasília, Eric Bodden Heinz Nixdorf Institute at Paderborn University & Fraunhofer IEM, Laerte Peotta University of Brasília, Brazil, Gustavo Pinto Zup Innovation & UFPA, Márcio Ribeiro Federal University of Alagoas, Brazil | ||