AI Writes Code Fast. Can You Trust What Gets Deployed? | Harness Blog

AI-driven development has accelerated code creation, making the central challenge ensuring that the exact artifacts deployed to production remain trustworthy as threats evolve. Drawing on compromises involving TanStack dependencies, SolarWinds build systems, and LiteLLM pipelines, the discussion argues that attackers increasingly target dependencies, build processes, and deployment artifacts rather than source code alone. It advocates attaching security evidence such as SBOMs, provenance, attestations, vulnerability results, and policy evaluations directly to artifacts, enabling registries to continuously reassess and control their promotion through environments. Effective security requires not only detecting newly disclosed risks but also enforcing responses through quarantine, access controls, deployment gates, and automated remediation. Harness presents AI agents for pipeline management, application security, registry threat monitoring, and artifact lifecycle management as examples of how continuous verification could operate, emphasizing that safe software delivery depends on treating CI/CD pipelines and artifact registries as active security boundaries.

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