NodeMedic: End-to-end analysis of Node.js vulnerabilities with provenance graphs

• Main Authors: CASSEL, Darion, WONG, Wai Tuck, JIA, Limin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Analysis tools; Code execution; Command injections; Constraint-based; Tree-based; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/8094; https://ink.library.smu.edu.sg/context/sis_research/article/9097/viewcontent/nodemedic_eurosp23_av.pdf
• Institution: Singapore Management University

Packages in the Node.js ecosystem often suffer from serious vulnerabilities such as arbitrary command injection and code execution. Existing taint analysis tools fall short in providing an end-to-end infrastructure for automatically detecting and triaging these vulnerabilities.We develop NodeMedic, an end-to-end analysis infrastructure that automates test driver creation, performs precise yet scalable dynamic taint propagation via algorithmically tuned propagation policies, and exposes taint provenance information as a provenance graph. Using provenance graphs we develop two post-detection analyses: automated constraint-based exploit synthesis to confirm vulnerabilities; Attack-defense-tree-based rating of flow exploitability.We demonstrate the effectiveness of NodeMedic through a large-scale evaluation of 10,000 Node.js packages. Our evaluation uncovers 155 vulnerabilities, of which 152 are previously undisclosed, and 108 were confirmed with automatically synthesized exploits. We have open-sourced NodeMedic and a suite of 589 taint precision unit tests.