Open Access

ARTICLE

DAVS: Dockerfile Analysis for Container Image Vulnerability Scanning

Thien-Phuc Doan, Souhwan Jung^*

1 School of Electronic Engineering, Soongsil University, Seoul, 06978, Korea

* Corresponding Author: Souhwan Jung. Email:

(This article belongs to the Special Issue: Security and Privacy Issues in Systems and Networks Beyond 5G)

Computers, Materials & Continua 2022, 72(1), 1699-1711. https://doi.org/10.32604/cmc.2022.025096

Received 11 November 2021; Accepted 31 December 2021; Issue published 24 February 2022

Abstract

Container technology plays an essential role in many Information and Communications Technology (ICT) systems. However, containers face a diversity of threats caused by vulnerable packages within container images. Previous vulnerability scanning solutions for container images are inadequate. These solutions entirely depend on the information extracted from package managers. As a result, packages installed directly from the source code compilation, or packages downloaded from the repository, etc., are ignored. We introduce DAVS–A Dockerfile analysis-based vulnerability scanning framework for OCI-based container images to deal with the limitations of existing solutions. DAVS performs static analysis using file extraction based on Dockerfile information to obtain the list of Potentially Vulnerable Files (PVFs). The PVFs are then scanned to figure out the vulnerabilities in the target container image. The experimental shows the outperform of DAVS on detecting Common Vulnerabilities and Exposures (CVE) of 10 known vulnerable images compared to Clair– the most popular container image scanning project. Moreover, DAVS found that 68% of real-world container images are vulnerable from different image registries.

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Keywords

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