Killing Two Birds with One Stone: Malicious Package Detection in NPM and PyPI using a Single Model of Malicious Behavior Sequence

TL;DR

This paper introduces Cerebro, a unified model leveraging behavior sequences and BERT to detect malicious packages across NPM and PyPI, effectively identifying new threats and improving detection accuracy.

Contribution

The paper presents a novel multi-lingual, sequence-based malicious package detection model that unifies knowledge from different ecosystems using a behavior abstraction and BERT.

Findings

Successfully detected 306 new malicious packages in PyPI.

Identified 196 new malicious packages in NPM.

Received 385 thank you letters from package registry teams.

Abstract

Open-source software (OSS) supply chain enlarges the attack surface, which makes package registries attractive targets for attacks. Recently, package registries NPM and PyPI have been flooded with malicious packages. The effectiveness of existing malicious NPM and PyPI package detection approaches is hindered by two challenges. The first challenge is how to leverage the knowledge of malicious packages from different ecosystems in a unified way such that multi-lingual malicious package detection can be feasible. The second challenge is how to model malicious behavior in a sequential way such that maliciousness can be precisely captured. To address the two challenges, we propose and implement Cerebro to detect malicious packages in NPM and PyPI. We curate a feature set based on a high-level abstraction of malicious behavior to enable multi-lingual knowledge fusing. We organize extracted features into a behavior sequence to model sequential malicious behavior. We fine-tune the BERT model to understand the semantics of malicious behavior. Extensive evaluation has demonstrated the effectiveness of Cerebro over the state-of-the-art as well as the practically acceptable efficiency. Cerebro has successfully detected 306 and 196 new malicious packages in PyPI and NPM, and received 385 thank letters from the official PyPI and NPM teams.