Tracking Security Smell Diffusion Patterns in Ansible Playbooks Using Metadata
Peer-Reviewed Research PaperAbstract
Infrastructure as Code (IaC) platforms lack mechanisms for detecting security smell diffusion, a challenge stemming from the absence of repository relationships. We present a similarity-based methodology combining content and structure metrics to identify repository clones. Validated against Ansible Galaxy repositories that have GitHub fork data, our approach achieved 99.6%–99.8% accuracy to detect forks. Analysis of Ansible Galaxy repositories across three popular technologies revealed 38.4%–54.1% share code overlap, creating vulnerability propagation pathways. Security analysis identified CWE-477 and CWE-546 as most prevalent, with CVE-2017-7550 (CVSS 9.8 - Critical) propagating from a popular repository version with 2.7 million downloads. Fork metadata absence causes users to download repositories with induced security smells at 100x higher rates than platforms with visible fork relationships. A survey of 24 IaC tools confirmed none provide cross-repository comparison capabilities, demonstrating a gap in repository relationship tracking within the IaC supply chain. Our work addresses this gap by providing a systematic approach to detect clones and track security diffusion in environments lacking fork metadata.
Key Focus Areas
- Supply chain attack detection in IaC
- Metadata analysis for security
- Ansible security smells identification
- Dependency relationship analysis
- Repository clone detection