Reproduce “Towards Socio-Technical Topology-Aware Adaptive Threat Detection in Software Supply Chains” on OpenResearch

About this paper

Thomas Welsh, Kristófer Finnsson, Brynjólfur Stefánsson, Helmut Neukirchen

Researchers from the University of Iceland propose a conceptual framework for adaptive threat detection in software supply chains, integrating socio-technical topology models within a MAPE-K adaptive system. Their analysis of the XZ Utils attack illustrates how monitoring combined social and technical indicators, such as anomalous code changes, increasing developer influence, atypical commit times, and suspicious communication sentiment, can reveal malicious activity.

Key insights

• Integrating social data (e.g., developer sentiment, communication patterns, linguistic style) with technical data (e.g., code churn, commit times, network centrality) is crucial for comprehensive threat detection in SSCs.
• Anomalous changes in combined socio-technical metrics can serve as early warning signs of malicious activity or subversion within an SSC.
• The inherent complexity and dynamics of SSCs can be leveraged as a source of information for adaptive threat detection rather than solely a challenge to be mitigated.

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