As the default package manager for Node.js, npm has become one of the largest package management systems in the world. To facilitate dependency management for developers, npm supports a special type of dependency, Peer Dependency, whose installation and usage differ from regular dependencies. However, conflicts between peer dependencies can trap the npm client into infinite loops, leading to resource exhaustion and system crashes. We name this problem PeerSpin. Although PeerSpin poses a severe risk to ecosystems, it was overlooked by previous studies, and its impacts have not been explored. To bridge this gap, this paper conducts the first in-depth study to understand and detect PeerSpin in the npm ecosystem. First, by systematically analyzing the npm dependency resolution, we identify the root cause of PeerSpin and characterize two peer dependency patterns to guide detection. Second, we propose a novel technique called Node-Replacement-Conflict based PeerSpin Detection, which leverages the state of the directory tree during dependency resolution to achieve accurate and efficient PeerSpin detection. Based on this technique, we developed a tool called PeerChecker to detect PeerSpin. Finally, we apply PeerChecker to the entire npm ecosystem and find that 5,662 packages, totaling 72,968 versions, suffer from PeerSpin. Until now, we have selected 100 problematic packages to report and received 28 confirmations. We also open source all PeerSpin analysis implementations, tools, and data sets to the public to help the community detect PeerSpin issues and enhance the reliability of the npm ecosystem.

Linux kernel introduces the memory control group (memcg) to account and confine memory usage at the process-level. Due to its flexibility and efficiency, memcg has been widely adopted by container platforms and has become a fundamental technique. While being critical, memory accounting is prone to missing-account bugs due to the diverse memory accounting interfaces and the massive amount of allocation/free paths. To our knowledge, there is still no systematic analysis against the memory missing-account problem, with respect to its security impacts, detection, etc.