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1. Why Does Your Data Leak? Uncovering the Data Leakage in Cloud from Mobile Apps

   https://doi.org/10.1109/SP.2019.00009  

   Zuo, Chaoshun; Lin, Zhiqiang; Zhang, Yinqian (May 2019, 2019 IEEE Symposium on Security and Privacy)

   Increasingly, more and more mobile applications (apps for short) are using the cloud as the back-end, in particular the cloud APIs, for data storage, data analytics, message notification, and monitoring. Unfortunately, we have recently witnessed massive data leaks from the cloud, ranging from personally identifiable information to corporate secrets. In this paper, we seek to understand why such significant leaks occur and design tools to automatically identify them. To our surprise, our study reveals that lack of authentication, misuse of various keys (e.g., normal user keys and superuser keys) in authentication, or misconfiguration of user permissions in authorization are the root causes. Then, we design a set of automated program analysis techniques including obfuscation-resilient cloud API identification and string value analysis, and implement them in a tool called LeakScope to identify the potential data leakage vulnerabilities from mobile apps based on how the cloud APIs are used. Our evaluation with over 1.6 million mobile apps from the Google Play Store has uncovered 15, 098 app servers managed by mainstream cloud providers such as Amazon, Google, and Microsoft that are subject to data leakage attacks. We have made responsible disclosure to each of the cloud service providers, and they have all confirmed the vulnerabilities we have identified and are actively working with the mobile app developers to patch their vulnerable services. 

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2. Why Does Your Data Leak? Uncovering the Data Leakage in Cloud from Mobile Apps

   Zuo, Chaoshun; Lin, Zhiqiang; Zhang, Yinqian (January 2019, IEEE Symposium on Security and Privacy)

   Increasingly, more and more mobile applications (apps for short) are using the cloud as the back-end, in particular the cloud APIs, for data storage, data analytics, message notification, and monitoring. Unfortunately, we have recently witnessed massive data leaks from the cloud, ranging from personally identifiable information to corporate secrets. In this paper, we seek to understand why such significant leaks occur and design tools to automatically identify them. To our surprise, our study reveals that lack of authentication, misuse of various keys (e.g., normal user keys and superuser keys) in authentication, or misconfiguration of user permissions in authorization are the root causes. Then, we design a set of automated program analysis techniques including obfuscation-resilient cloud API identification and string value analysis, and implement them in a tool called LeakScope to identify the potential data leakage vulnerabilities from mobile apps based on how the cloud APIs are used. Our evaluation with over 1.6 million mobile apps from the Google Play Store has uncovered 15, 098 app servers managed by mainstream cloud providers such as Amazon, Google, and Microsoft that are subject to data leakage attacks. We have made responsible disclosure to each of the cloud service providers, and they have all confirmed the vulnerabilities we have identified and are actively working with the mobile app developers to patch their vulnerable services. 

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3. Understanding the Hidden Cost of Software Vulnerabilities: Measurements and Predictions

   https://doi.org/10.1007%2F978-3-030-01701-9_21  

   Anwar, Afsah; Khormali, Aminollah; Nyang, DaeHun; Mohaisen, Aziz (August 2018, International Conference on Security and Privacy in Communication Systems)

   Vulnerabilities have a detrimental effect on end-users and enterprises, both direct and indirect; including loss of private data, intellectual property, the competitive edge, performance, etc. Despite the growing software industry and a push towards a digital economy, enterprises are increasingly considering security as an added cost, which makes it necessary for those enterprises to see a tangible incentive in adopting security. Furthermore, despite data breach laws that are in place, prior studies have suggested that only 4% of reported data breach incidents have resulted in litigation in federal courts, showing the limited legal ramifications of security breaches and vulnerabilities. In this paper, we study the hidden cost of software vulnerabilities reported in the National Vulnerability Database (NVD) through stock price analysis. Towards this goal, we perform a high-fidelity data augmentation to ensure data reliability and to estimate vulnerability disclosure dates as a baseline for estimating the implication of software vulnerabilities. We further build a model for stock price prediction using the NARX Neural Network model to estimate the effect of vulnerability disclosure on the stock price. Compared to prior work, which relies on linear regression models, our approach is shown to provide better accuracy. Our analysis also shows that the effect of vulnerabilities on vendors varies, and greatly depends on the specific software industry. Whereas some industries are shown statistically to be affected negatively by the release of software vulnerabilities, even when those vulnerabilities are not broadly covered by the media, some others were not affected at all. 

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4. Open Source Vulnerability Notification

   https://doi.org/10.1007/978-3-030-20883-7_2  

   Carlson, Brandon; Leach, Kevin; Marinov, Darko; Nagappan, Meiyappan; Prakash, Atul (May 2019, Bordeleau F., Sillitti A., Meirelles P., Lenarduzzi V. (eds) Open Source Systems. OSS 2019. IFIP Advances in Information and Communication Technology)

   The use of third-party libraries to manage software complexity can expose open source software projects to vulnerabilities. However, project owners do not currently have a standard way to enable private disclosure of potential security vulnerabilities. This neglect may be caused in part by having no template to follow for disclosing such vulnerabilities. We analyzed 600 GitHub projects to determine how many projects contained a vulnerable dependency and whether the projects had a process in place to privately communicate security issues. We found that 385 out of 600 open source Java projects contained at least one vulnerable dependency, and only 13 of those 385 projects had a security vulnerability reporting process. That is, 96.6% of the projects with a vulnerability did not have a security notification process in place to allow for private disclosure. In determining whether the projects even had contact information publicly available, we found that 19.8% had no contact information publicly available, let alone a security vulnerability reporting process. We suggest two methods to allow for community members to privately disclose potential security vulnerabilities. 

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5. Plug-N-Pwned: Comprehensive Vulnerability Analysis of OBD-II Dongles as A New Over-the-Air Attack Surface in Automotive IoT

   Wen, Haohuang; Chen, Qi Alfred; Lin, Zhiqiang (January 2020, USENIX Security Symposium)

   null (Ed.)

   With the growing trend of the Internet of Things, a large number of wireless OBD-II dongles are developed, which can be simply plugged into vehicles to enable remote functions such as sophisticated vehicle control and status monitoring. However, since these dongles are directly connected with in-vehicle networks, they may open a new over-the-air attack surface for vehicles. In this paper, we conduct the first comprehensive security analysis on all wireless OBD-II dongles available on Amazon in the US in February 2019, which were 77 in total. To systematically perform the analysis, we design and implement an automated tool DONGLESCOPE that dynamically tests these dongles from all possible attack stages on a real automobile. With DONGLESCOPE, we have identified 5 different types of vulnerabilities, with 4 being newly discovered. Our results reveal that each of the 77 dongles exposes at least two types of these vulnerabilities, which indicates a widespread vulnerability exposure among wireless OBD-II dongles on the market today. To demonstrate the severity, we further construct 4 classes of concrete attacks with a variety of practical implications such as privacy leakage, property theft, and even safety threat. We also discuss the root causes and feasible countermeasures, and have made corresponding responsible disclosure. 

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