Poor Dockerfile practices create measurable DevOps costs — slow builds, bloated images, and cross-environment inconsistencies — long before they become security concerns. Common anti-patterns include unpinned base images, incorrect layer ordering (copying source before installing dependencies), and missing .dockerignore files. A real-world case study from Hypersequent shows CI builds dropping from 12–16 minutes to 3.5–4.5 minutes and image sizes shrinking 60–75% after enforcing multi-stage builds, dependency-before-source ordering, and aligned caching strategies. DockSec, an OWASP Incubator Project, combines Trivy, Hadolint, and Docker Scout with an AI layer to surface Dockerfile anti-patterns in plain language at the pull request stage, making remediation accessible to developers without deep container expertise.
Table of contents
How DockSec Came From a Different Problem EntirelyBuild Consistency as a First-Order DevOps PrincipleWhat Poor Layer Caching Actually CostsThe Standardization Problem in Large Engineering OrganizationsAutomated Quality Gates and the AI LayerWhat Treating Dockerfiles as Production Artifacts Actually RequiresRelatedSort: