Wiz Report Finds SDLC Risk Concentrates in Shared Dependencies, Developer Tools and Automation

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Summary

Wiz’s 2026 SDLC security report says risk increasingly propagates through shared dependencies, developer environments, CI/CD automation and AI-assisted workflows, linking application security with the broader software delivery trust chain.

Key points

  • A small set of widely adopted packages appears across many organizations, allowing insecure patterns in shared dependencies to spread broadly.
  • Developer endpoints have access to code, credentials, version control and deployment pipelines; macOS made up about 86% of observed developer platforms.
  • About 45–50% of organizations use GitHub Actions, and shared workflow components can connect development access to production impact.
  • AI-assisted development may amplify existing weaknesses through faster code generation, reuse and automated changes.
  • Wiz Research reported that roughly one in five organizations using AI-powered development platforms had applications affected by systemic security issues tied to repeatable generation patterns and insecure defaults.
  • The report recommends focusing on how risk propagates across code, tooling, identity systems and automation, rather than treating findings as isolated issues.

Article Details

Publisher
Wiz
Report Period
2026
Scope
Development environments, public repositories, production telemetry, shared dependencies, developer environments, CI/CD systems, and AI-driven workflows.
Key Statistics
  • macOS accounted for roughly 86% of observed developer platforms; the report does not state the observation count.
  • Approximately 45–50% of organizations use GitHub Actions.
  • In September 2025, Wiz Research found that roughly 1 in 5 organizations using AI-powered development platforms had applications affected by systemic security issues linked to repeatable generation patterns and insecure defaults.
Recommendations
  • Assess how risk propagates across code, developer tooling, identity systems, and automation pipelines.
  • Prioritize areas where trust and software reuse are concentrated rather than focusing only on isolated findings.

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