Security checks built into your CI/CD pipeline, run on every commit

DevSecOps is DevOps with security treated as a shared, automated part of delivery rather than a separate review at the end. DevOps focuses on getting changes to production quickly and reliably. DevSecOps adds the checks that make those changes safe, such as code and dependency scanning, secrets management, infrastructure policy and artefact signing. The pipelines stay the same, with security gates and evidence built into them.

It should add little time to pull requests if the checks are placed well. Fast checks such as secret detection, dependency scanning and focused static analysis run on each pull request in parallel with your tests. Heavier work, such as full repository scans, dynamic testing against staging and base image audits, runs on merge, on a schedule or overnight. We measure pipeline duration before and after each change and adjust if feedback slows down.

We run every new scanner in report-only mode first and enforce only the rules that prove accurate on your code. While it reports, we review results with your developers, disable rules that do not apply to your stack and record confirmed false positives in version-controlled configuration, with a short note explaining each decision. Suppressions are reviewed periodically so they do not hide new problems later. Only agreed high-risk categories block a merge, so a failing security check is worth stopping for.

We place checks at three points so a secret is caught before it reaches a shared branch. A pre-commit hook scans changes on the developer's machine, push protection on GitHub or GitLab rejects pushes containing recognised key formats, and a pipeline scan covers every branch plus the full history once. Anything already exposed is treated as compromised and rotated, because deleting it does not remove cloned copies. Longer term, applications read secrets from a managed store at runtime, leaving less to leak.

Policy as code means writing security and operational rules as versioned, testable code that tools enforce automatically. Examples include rejecting containers that run as root, requiring images from an approved registry, or blocking a Terraform change that removes encryption from a database. Policies run in the pipeline before changes are applied and, for Kubernetes clusters, again at admission time. Because the rules live in a repository, changes are reviewed and exceptions are explicit and time-limited.

A software bill of materials, or SBOM, is a machine-readable list of every component and version inside a build, including transitive dependencies. You need one when customers or regulators ask what your software contains, and it is valuable when a new vulnerability is disclosed, because you can search for the affected package instead of auditing each service by hand. We generate SBOMs in the pipeline and store them with each signed artefact.

We combine automated scanning with disciplined dependency hygiene. Software composition analysis checks each build for known vulnerabilities and licence issues, lock files pin exact versions, and automated pull requests keep packages current in small, testable steps. We also check new dependencies for maintenance activity before adoption, restrict installs to trusted registries and remove unused packages, which reduces what there is to scan and patch in the first place.

Formal training helps, but it is not a prerequisite, because well-designed checks teach as they run. Each finding we surface links to a short explanation and a fix example for your language or framework. During the engagement we run walkthroughs on the most common issues found in your own code, and we can help you appoint a security champion in each team as the first point of contact for questions and rule changes.

We rank vulnerabilities by real risk, not by severity score alone. A critical flaw in a library function your code never calls matters less than a medium one in an internet-facing login service. We weigh exploitability, whether the vulnerable code is reachable, internet exposure, the sensitivity of the data involved and whether a fix exists. Agreed fix windows for each risk level then turn the ranking into a schedule your teams can plan around.

We treat the pipeline as production infrastructure, because it holds the keys to deploy. Cloud access uses short-lived OIDC tokens instead of stored keys, each job gets only the permissions it needs, and production deployments run only from protected branches with required reviews. Third-party actions and plugins are pinned to verified versions, runners are isolated, and changes to pipeline definitions go through the same review as application code.

Baseline controls such as secret scanning, dependency scanning and pipeline credential fixes can often be added within a couple of weeks for a small number of repositories. Tuning, policy as code, image signing and enforcement take longer, depending on how many services you run, how noisy the first results are and how quickly teams can clear existing findings. We phase the work so protection improves from the first sprint.

Cost depends on the number of repositories and services, your cloud and CI platforms, the security tools you already license and how far you want enforcement to go. After a discovery call we run a short review of your repositories and pipelines, then give a fixed quote for the agreed scope. We start with open-source and platform-native scanners where they fit, and only propose paid tools when they clearly add coverage you need.