The DevSecOps process integrates security controls into every phase of software delivery — plan, code, build, test, release, deploy, and operate — so that security becomes a continuous property of the pipeline rather than a gate at the end. Where a traditional model queued a security review right before launch, a DevSecOps process flow distributes many small automated checks across the whole lifecycle, catching problems when they are cheap to fix.
The shift is cultural as much as technical. "Shift left" gets quoted constantly, but the real change is that developers, operations, and security share ownership of risk. Nobody hands a finished build to a security team and waits three weeks. Let's walk the process one stage at a time.
Plan: threat model before you write code
Security starts before the first commit. During planning, teams identify what could go wrong with a feature — what data it touches, what trust boundaries it crosses, what an attacker would target. Lightweight threat modeling (even a whiteboard session answering "what are we building, what can go wrong, what do we do about it") produces security requirements that become acceptance criteria.
This is also where you decide policy: which severity of finding blocks a release, which dependencies are allowed, what compliance obligations apply. Encoding those decisions now means the automation downstream has something concrete to enforce.
Code: guardrails in the editor
The cheapest place to catch a vulnerability is the moment it is typed. In the coding stage, a DevSecOps process leans on:
- IDE plugins and linters that flag insecure patterns as developers write them.
- Pre-commit hooks that block secrets from ever reaching the repository.
- Peer code review with security in scope, not just correctness.
Secret scanning belongs here specifically because a leaked credential in git history is painful to remove and often already compromised by the time you notice. Catching it pre-commit is worth ten post-incident rotations.
Build: lock the supply chain
When code becomes an artifact, the build stage is where dependency and supply-chain risk gets addressed. Modern applications are mostly third-party code, so this stage matters enormously.
# Example CI step: fail the build on high-severity dependency CVEs
- name: Dependency scan
run: |
npm ci
npm audit --audit-level=high
Software composition analysis (SCA) inventories your direct and transitive dependencies and matches them against known CVEs. Generating a software bill of materials (SBOM) here gives you a durable record of what shipped, which becomes invaluable when the next widely-used library turns out to be vulnerable. An SCA tool integrated at build time can fail the pipeline when a dependency crosses your risk threshold — the policy you set back in the planning stage.
Test: automated security testing
The test stage runs the security equivalents of your functional test suite:
- SAST (static application security testing) analyzes source code for injection flaws, insecure deserialization, and similar patterns.
- DAST (dynamic application security testing) exercises the running application the way an attacker would, probing for issues that only appear at runtime.
- IAST instruments the app during functional tests to observe security-relevant behavior.
The key is that these run automatically on every meaningful change, not once a quarter. A finding here is annotated to the exact line or endpoint, so a developer can fix it in the same context they wrote it.
Release and deploy: policy gates and hardened artifacts
By the release stage, most security work is already done; this stage is about enforcement and integrity. A policy gate evaluates the accumulated findings against your rules and decides whether the artifact is allowed to promote. Container images get scanned and signed. Infrastructure-as-code gets checked for misconfigurations — an open security group or a public storage bucket is a vulnerability even though no application code is wrong.
Signing and provenance matter here: you want to be able to prove that the artifact you are deploying is the one your pipeline built, unmodified. This is the integrity half of supply-chain security.
Operate: monitor, detect, respond
Deployment is not the finish line. In the operate stage, runtime protection, logging, and monitoring watch for behavior that static analysis could never predict. New CVEs get published constantly against dependencies you already shipped, so continuous monitoring of your running inventory closes the loop back to the build stage — a newly disclosed vulnerability in a library you use should raise an alert without anyone re-running a scan by hand.
Incident response plans, rehearsed and not just written, belong to this stage too. The feedback from real incidents feeds back into planning, and the cycle repeats.
Making the process stick
A DevSecOps process fails when security becomes a wall of noisy alerts that developers learn to ignore. Three practices keep it healthy:
- Tune for signal. Suppress and triage aggressively so that a blocked build means something real.
- Fix in-context. Findings should land as PR comments or ticket items with remediation guidance, not in a separate portal nobody logs into.
- Measure flow, not just findings. Track mean time to remediate, not the raw count of vulnerabilities, because the count will never be zero.
If you want to go deeper on individual controls, the Safeguard Academy breaks down SAST, DAST, and SCA with hands-on examples.
FAQ
What are the stages of the DevSecOps process?
The common stages are plan, code, build, test, release, deploy, and operate. Each carries specific security activities — threat modeling in plan, secret scanning in code, SCA in build, SAST/DAST in test, policy gates in release/deploy, and runtime monitoring in operate.
How is DevSecOps different from DevOps?
DevOps unifies development and operations for faster, more reliable delivery. DevSecOps extends that by making security a shared, automated responsibility across the same pipeline, rather than a separate review step at the end.
Does a DevSecOps process slow down releases?
Done well, no. The automated checks run in parallel with existing CI stages and catch issues early, when they are fast to fix. Poorly tuned tooling that floods developers with false positives is what actually slows teams down.
Where should I start if we have no security automation today?
Start at the build stage with dependency scanning and secret detection — they deliver the most risk reduction for the least friction. Add SAST and DAST once the team trusts the pipeline, then formalize policy gates.