Security Smells in Ansible and Chef Scripts: A Replication Study

TL;DR

This study empirically investigates security smells in Ansible and Chef scripts, revealing their prevalence and proposing a static analysis tool to help practitioners identify and mitigate security vulnerabilities in infrastructure as code scripts.

Contribution

It introduces SLAC, a static analysis tool for detecting security smells in Ansible and Chef scripts, and provides empirical data on the occurrence of these smells in real-world repositories.

Findings

Security smells are common in Ansible and Chef scripts.

SLAC identified 46,600 security smell occurrences, including hard-coded passwords.

Two new security smells were discovered: missing default in case statement and no integrity check.

Abstract

Context: Security smells are recurring coding patterns that are indicative of security weakness, and require further inspection. As infrastructure as code (IaC) scripts, such as Ansible and Chef scripts, are used to provision cloud-based servers and systems at scale, security smells in IaC scripts could be used to enable malicious users to exploit vulnerabilities in the provisioned systems. Goal: The goal of this paper is to help practitioners avoid insecure coding practices while developing infrastructure as code scripts through an empirical study of security smells in Ansible and Chef scripts. Methodology: We conduct a replication study where we apply qualitative analysis with 1,956 IaC scripts to identify security smells for IaC scripts written in two languages: Ansible and Chef. We construct a static analysis tool called Security Linter for Ansible and Chef scripts (SLAC) to automatically identify security smells in 50,323 scripts collected from 813 open source software repositories. We also submit bug reports for 1,000 randomly-selected smell occurrences. Results: We identify two security smells not reported in prior work: missing default in case statement and no integrity check. By applying SLAC we identify 46,600 occurrences of security smells that include 7,849 hard-coded passwords. We observe agreement for 65 of the responded 94 bug reports, which suggests the relevance of security smells for Ansible and Chef scripts amongst practitioners. Conclusion: We observe security smells to be prevalent in Ansible and Chef scripts, similar to that of the Puppet scripts. We recommend practitioners to rigorously inspect the presence of the identified security smells in Ansible and Chef scripts using (i) code review, and (ii) static analysis tools.