Ruian Duan (Georgia Institute of Technology), Omar Alrawi (Georgia Institute of Technology), Ranjita Pai Kasturi (Georgia Institute of Technology), Ryan Elder (Georgia Institute of Technology), Brendan Saltaformaggio (Georgia Institute of Technology), Wenke Lee (Georgia Institute of Technology)

Package managers have become a vital part of the modern software development process. They allow developers to reuse third-party code, share their own code, minimize their codebase, and simplify the build process. However, recent reports showed that package managers have been abused by attackers to distribute malware, posing significant security risks to developers and end-users. For example, eslint-scope, a package with millions of weekly downloads in Npm, was compromised to steal credentials from developers. To understand the security gaps and the misplaced trust that make recent supply chain attacks possible, we propose a comparative framework to qualitatively assess the functional and security features of package managers for interpreted languages. Based on qualitative assessment, we apply well-known program analysis techniques such as metadata, static, and dynamic analysis to study registry abuse. Our initial efforts found 339 new malicious packages that we reported to the registries for removal. The package manager maintainers confirmed 278 (82%) from the 339 reported packages where three of them had more than 100,000 downloads. For these packages we were issued official CVE numbers to help expedite the removal of these packages from infected victims. We outline the challenges of tailoring program analysis tools to interpreted languages and release our pipeline as a reference point for the community to build on and help in securing the software supply chain.

View More Papers

PyPANDA: Taming the PANDAmonium of Whole System Dynamic Analysis

Luke Craig, Tim Leek (MIT Lincoln Laboratory), Andrew Fasano, Tiemoko Ballo (MIT Lincoln Laboratory, Northeastern University), Brendan Dolan-Gavitt (New York University), William Robertson (Northeastern University)

Read More

KUBO: Precise and Scalable Detection of User-triggerable Undefined Behavior...

Changming Liu (Northeastern University), Yaohui Chen (Facebook Inc.), Long Lu (Northeastern University)

Read More

QPEP: An Actionable Approach to Secure and Performant Broadband...

James Pavur (Oxford University), Martin Strohmeier (armasuisse), Vincent Lenders (armasuisse), Ivan Martinovic (Oxford University)

Read More

TASE: Reducing Latency of Symbolic Execution with Transactional Memory

Adam Humphries (University of North Carolina), Kartik Cating-Subramanian (University of Colorado), Michael K. Reiter (Duke University)

Read More