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With the rise in threats against the software supply chain, developer integrated development environments (IDEs) present an attractive target for attackers. For example, researchers have found extensions for Visual Studio Code (VS Code) that start web servers and can be exploited via JavaScript executing in a web browser on the developer's host. This paper seeks to systematically understand the landscape of vulnerabilities in VS Code's extension marketplace. We identify a set of four sources of untrusted input and three code targets that can be used for code injection and file integrity attacks and use them to design taint analysis rules in CodeQL. We then perform an ecosystem-level analysis of the VS Code extension marketplace, studying 25,402 extensions that contain code. Our results show that while vulnerabilities are not pervasive, they exist and impact millions of users. Specifically, we find 21 extensions with verified proof of concept exploits of code injection attacks impacting a total of over 6 million installations. Through this study, we demonstrate the need for greater attention to the security of IDE extensions. 

Millions of software projects leverage automated workflows, like GitHub Actions, for performing common build and deploy tasks. While GitHub Actions have greatly improved the software build process for developers, they pose significant risks to the software supply chain by adding more dependencies and code complexity that may introduce security bugs. This paper presents ARGUS, the first static taint analysis system for identifying code injection vulnerabilities in GitHub Actions. We used ARGUS to perform a large-scale evaluation on 2,778,483 Workflows referencing 31,725 Actions and discovered critical code injection vulnerabilities in 4,307 Workflows and 80 Actions. We also directly compared ARGUS to two existing pattern-based GitHub Actions vulnerability scanners, demonstrating that our system exhibits a marked improvement in terms of vulnerability detection, with a discovery rate more than seven times (7x) higher than the state-of-the-art approaches. These results demonstrate that command injection vulnerabilities in the GitHub Actions ecosystem are not only pervasive but also require taint analysis to be detected. 

Millions of software projects leverage automated workflows, like GitHub Actions, for performing common build and deploy tasks. While GitHub Actions have greatly improved the software build process for developers, they pose significant risks to the software supply chain by adding more dependencies and code complexity that may introduce security bugs. This paper presents ARGUS, the first static taint analysis system for identifying code injection vulnerabilities in GitHub Actions. We used ARGUS to perform a large-scale evaluation on 2,778,483 Workflows referencing 31,725 Actions and discovered critical code injection vulnerabilities in 4,307 Workflows and 80 Actions. We also directly compared ARGUS to two existing pattern-based GitHub Actions vulnerability scanners, demonstrating that our system exhibits a marked improvement in terms of vulnerability detection, with a discovery rate more than seven times (7x) higher than the state-of-the-art approaches. These results demonstrate that command injection vulnerabilities in the GitHub Actions ecosystem are pervasive and require taint analysis to be detected. 

Continuous integration and deployment (CI/CD) has revolutionized software development and maintenance. Commercial CI/CD platforms provide services for specifying and running CI/CD actions. However, they present a security risk in their own right, given their privileged access to secrets, infrastructure, and ability to fetch and execute arbitrary code. In this paper, we study the security of the newly popular GitHub CI platform. We first identify four fundamental security properties that must hold for any CI/CD system: Admittance Control, Execution Control, Code Control, and Access to Secrets. We then examine if GitHub CI enforces these properties in comparison with the other five popular CI/CD platforms. We perform a comprehensive analysis of 447,238 workflows spanning 213,854 GitHub repositories. We made several disturbing observations. Our analysis shows that 99.8% of workflows are overprivileged and have read-write access (instead of read-only) to the repository. In addition, 23.7% of workflows are triggerable by a pull_request and use code from the underlying repository. An attacker can exploit these workflows and execute arbitrary code as part of the workflow. Due to the modular nature of workflows, we find that 99.7% of repositories in our dataset execute some externally developed plugin, called "Actions" , for various purposes. We found that 97% of repositories execute at least one Action that does not originate with a verified creator, and 18% of repositories in our dataset execute at least one Action with missing security updates. These represent potential attack vectors that can be used to compromise the execution of workflows, consequently leading to supply chain attacks. This work highlights the systemic risks inherent in CI/CD platforms like GitHub CI; we also present our own Github action, GWChecker, which functions as an early warning system for bad practices that violate the identified security properties.