# The Hitchhiker's Guide to Malicious Third-Party Dependencies

arXiv: https://arxiv.org/abs/2307.09087 · HTML: https://mlsanity.com/paper/2307.09087/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jul 2023.

## Built on by (most cited first, 2 of 2)

- [Setup Complete, Now You Are Compromised: Weaponizing Setup Instructions Against AI Coding Agents](https://mlsanity.com/paper/2607.15143/) (2026)
- [One Detector Fits All: Robust and Adaptive Detection of Malicious Packages from PyPI to Enterprises](https://mlsanity.com/paper/2512.04338/) (2025)

## Abstract (arXiv)

The increasing popularity of certain programming languages has spurred the creation of ecosystem-specific package repositories and package managers. Such repositories (e.g., npm, PyPI) serve as public databases that users can query to retrieve packages for various functionalities, whereas package managers automatically handle dependency resolution and package installation on the client side. These mechanisms enhance software modularization and accelerate implementation. However, they have become a target for malicious actors seeking to propagate malware on a large scale. In this work, we show how attackers can leverage capabilities of popular package managers and languages to achieve arbitrary code execution on victim machines, thereby realizing open-source software supply chain attacks. Based on the analysis of 7 ecosystems, we identify 3 install-time and 4 runtime techniques, and we provide recommendations describing how to reduce the risk when consuming third-party dependencies. We will provide proof-of-concepts that demonstrate the identified techniques. Furthermore, we describe evasion strategies employed by attackers to circumvent detection mechanisms.