[Paper] Compliance as Code: A Study of Linux Distributions and Beyond

Source: arXiv - 2603.01520v1

Overview

The paper Compliance as Code: A Study of Linux Distributions and Beyond investigates how compliance requirements—traditionally expressed in legal or policy documents—can be turned into executable code that automatically checks whether a system meets those rules. By analysing more than 1,500 compliance rules across 14 releases of five major Linux distributions, the authors show both the promise and the current gaps of this “compliance‑as‑code” approach, especially in the context of the upcoming European Cyber Resilience Act (CRA).

Key Contributions

• Large‑scale empirical dataset – 1,500+ unique compliance rules covering 14 Linux distribution releases from five vendors.
• Coverage analysis – Demonstrates uneven rule coverage across vendors and identifies 24 distinct control families from over 10 standards bodies (government, standards organizations, NGOs).
• Rule‑rationale vs. code similarity – Finds that while textual rationales differ widely, the accompanying code snippets exhibit measurable similarity, hinting at reusable patterns.
• Mapping to the Cyber Resilience Act – Shows that most rules can be aligned with CRA’s essential cybersecurity requirements, though author agreement on exact mappings is modest.
• Evidence for continuous updating – Highlights the need for an evolving compliance‑as‑code repository to stay current with regulatory changes.

Methodology

1. Data collection – The authors harvested compliance rules from an open‑source “Compliance as Code” project that targets Linux distributions. Each rule includes a short rationale and a code snippet (typically a shell script or Ansible playbook).
2. Vendor & release selection – Four major Linux vendors (e.g., Debian, Ubuntu, Red Hat, SUSE) plus a fifth community‑driven distro were examined across multiple release versions, yielding 14 distinct OS snapshots.
3. Quantitative analysis –
   • Coverage: Counted how many rules each vendor implements.
   • Textual similarity: Applied basic statistical tests (e.g., cosine similarity on TF‑IDF vectors) to compare rationales.
   • Code similarity: Used token‑based similarity metrics to detect common patterns in the snippets.
4. Control mapping – Manually linked each rule to the relevant CRA security requirement, then measured inter‑author agreement (Cohen’s κ).
5. Cross‑standard comparison – Identified which external standards (e.g., NIST, ISO 27001, CIS Benchmarks) the rules originated from.

Results & Findings

• Uneven vendor support – Some vendors (e.g., Red Hat) implement >80 % of the rule set, while others cover <50 %.
• Rationale diversity – Statistical tests reveal no significant similarity among the textual explanations, suggesting each vendor writes its own justification.
• Code reuse – Approximately 30 % of snippets share a common structure (e.g., checking file permissions, verifying package signatures), indicating potential for shared libraries or modules.
• Broad standard footprint – The 24 covered controls span regulations from the U.S. NIST 800‑53, the EU’s GDPR‑related guidelines, to industry‑specific CIS Benchmarks.
• CRA alignment – Most rules map to CRA’s “essential security requirements,” but inter‑author agreement on specific mappings is only moderate (κ ≈ 0.45), underscoring the subjective nature of interpretation.
• Update necessity – The modest agreement and the evolving regulatory landscape imply that the compliance‑as‑code repository must be continuously curated.

Practical Implications

• Automated compliance pipelines – DevOps teams can embed the examined rule set into CI/CD workflows (e.g., using Ansible, Chef, or custom scripts) to catch non‑compliant configurations before they ship.
• Vendor‑agnostic security baselines – By identifying common code patterns, organizations can build a shared “security-as-code” library that works across multiple Linux flavors, reducing duplication of effort.
• Preparing for the Cyber Resilience Act – Since the CRA will treat operating systems as part of a network‑connected product’s compliance scope, manufacturers can leverage the study’s mapping to pre‑emptively certify their Linux‑based components.
• Policy‑to‑code translation tools – The observed gap between textual rationales and code suggests an opportunity for tooling that automatically generates skeleton compliance checks from policy documents.
• Community‑driven maintenance – The need for ongoing updates makes a collaborative, open‑source governance model (similar to the OpenSCAP project) a practical way to keep the rule set current with new regulations.

Limitations & Future Work

• Scope limited to Linux – The study does not cover other OS families (e.g., Windows, BSD) or container runtimes, which may behave differently under compliance‑as‑code regimes.
• Manual mapping bias – The CRA alignment relied on author judgment; higher inter‑rater reliability would require a larger, more diverse expert panel.
• Static analysis only – The similarity metrics focus on code tokens and text; dynamic behavior (e.g., runtime checks) was not evaluated.
• Future directions – Extending the dataset to include non‑Linux platforms, automating the policy‑to‑code translation, and integrating machine‑learning techniques to improve rule similarity detection are suggested next steps.

Authors

• Jukka Ruohonen
• Esmot Ara Tuli
• Hiraku Morita

Paper Information

• arXiv ID: 2603.01520v1
• Categories: cs.SE, cs.CR
• Published: March 2, 2026
• PDF: Download PDF