Okara: Detection and Attribution of TLS Man-in-the-Middle Vulnerabilities in Android Apps with Foundation Models

• URL: http://arxiv.org/abs/2601.22770v1
• Date: Fri, 30 Jan 2026 09:49:09 GMT
• Title: Okara: Detection and Attribution of TLS Man-in-the-Middle Vulnerabilities in Android Apps with Foundation Models
• Authors: Haoyun Yang, Ronghong Huang, Yong Fang, Beizeng Zhang, Junpu Guo, Zhanyu Wu, Xianghang Mi,
• Abstract summary: Transport Layer Security (TLS) is fundamental to secure online communication.<n>Man-in-the-Middle (MitM) attacks remain a pervasive threat in Android apps.<n>We present Okara, a framework that automates the detection and attribution of MitM Vulnerabilities.
• Score: 3.9807330903947378
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Transport Layer Security (TLS) is fundamental to secure online communication, yet vulnerabilities in certificate validation that enable Man-in-the-Middle (MitM) attacks remain a pervasive threat in Android apps. Existing detection tools are hampered by low-coverage UI interaction, costly instrumentation, and a lack of scalable root-cause analysis. We present Okara, a framework that leverages foundation models to automate the detection and deep attribution of TLS MitM Vulnerabilities (TMVs). Okara's detection component, TMV-Hunter, employs foundation model-driven GUI agents to achieve high-coverage app interaction, enabling efficient vulnerability discovery at scale. Deploying TMV-Hunter on 37,349 apps from Google Play and a third-party store revealed 8,374 (22.42%) vulnerable apps. Our measurement shows these vulnerabilities are widespread across all popularity levels, affect critical functionalities like authentication and code delivery, and are highly persistent with a median vulnerable lifespan of over 1,300 days. Okara's attribution component, TMV-ORCA, combines dynamic instrumentation with a novel LLM-based classifier to locate and categorize vulnerable code according to a comprehensive new taxonomy. This analysis attributes 41% of vulnerabilities to third-party libraries and identifies recurring insecure patterns, such as empty trust managers and flawed hostname verification. We have initiated a large-scale responsible disclosure effort and will release our tools and datasets to support further research and mitigation.

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