03Program
DevSecOps consulting: security controls engineered into the delivery pipeline
Pipeline hardening, policy-as-code, artifact integrity and automated security testing: engineering the delivery platform so the secure path is the fast path.
- Name
- DevSecOps Consulting
- Line
- 03 · Software & Product Development
- Type
- Outcome program, combines several practices
01The problem
Build systems hold production access and are rarely threat-modeled.
CI/CD systems hold production credentials, deploy trusted artifacts and run third-party code, yet are rarely threat-modeled. Meanwhile manual security gates create the friction that pushes teams to bypass controls entirely.
02Scope
What the DevSecOps program covers.
- CI/CD threat modeling and hardening
- Secrets management architecture
- Policy-as-code for infrastructure and deployment
- Automated security testing in pull requests
- SBOM, signing and provenance (SLSA-aligned)
- Developer enablement and champions
03Approach
How a DevSecOps engagement runs.
Works with GitHub, GitLab, Azure DevOps and major CI systems. Controls are delivered as code your team owns. No black boxes.
Threat-model the pipeline
Your build system is production infrastructure with production access. We map its trust boundaries and attack paths first.
Harden the platform
Secrets management, runner isolation, branch protections and artifact signing. The delivery platform itself made defensible.
Shift controls into code
Security checks and infrastructure policy running in pull requests, tuned for signal, enforced as code.
04Outcomes
What the DevSecOps program is built to achieve.
- Build systems hardened: secrets, runners, branch protections, signed artifacts
- Security checks running in pull requests with tuned signal
- Policy-as-code enforcing infrastructure and deployment standards
- Supply chain integrity: SBOMs, provenance and dependency governance
When this work fits
- Engineering teams with working CI/CD and no security checks inside it
- Organizations that found secrets or vulnerable dependencies in a penetration test or audit
- Companies whose enterprise customers ask for evidence of a secure development lifecycle
- Platform teams standardizing pipelines across many repositories and product teams
05Questions
DevSecOps: questions we are asked
The pipeline stays. Security checks are added to it, and the pipeline itself is treated as a production system. That means a threat model of the build process, tighter permissions for runners and service accounts, secrets moved out of repositories and variables, and automated checks placed where developers already work. Most teams keep their existing tools and add only what is missing.
Fast, high-confidence checks run on every pull request: secrets detection, dependency scanning, infrastructure-as-code scanning and incremental static analysis. Slower work runs nightly or before release: full static analysis, container image scanning and dynamic testing against a deployed build. Release gates block only on confirmed, high-severity issues, so the pipeline stays usable.
By tuning before enforcing. Tools first run in report-only mode while rules are adjusted and false positives removed. Findings are de-duplicated across tools, mapped to an owning team and delivered inside the pull request or issue tracker, not in a separate portal. New code is held to the standard first. Existing debt is handled as a planned backlog.
Build systems hold credentials to production, which makes them a target. Controls include isolated or ephemeral runners, short-lived credentials issued through workload identity instead of stored keys, protected branches with required review, pinned dependencies, and signed artifacts with provenance. The SLSA framework gives a useful maturity ladder for this work, and we use it to show progress.
With measures the engineering team already respects: time to fix security defects, the share of releases passing gates without manual exception, secrets found in repositories over time, and the age of vulnerable dependencies. Delivery speed is tracked alongside them, because a secure pipeline that slows releases will be bypassed. An application security program extends this with manual testing.
Often alongside