Building Devsecops Pipeline With Gitlab CiSAFE
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·
Overview
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·
6c59587be632OBSERVED · 2026-10-07What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: building-devsecops-pipeline-with-gitlab-ci
description: Configure a GitLab CI/CD pipeline that embeds SAST (Semgrep, SpotBugs, Gosec, Bandit, NodeJsScan), DAST, container scanning, dependency scanning, and secret detection via GitLab's managed security templates. Use when building a shift-left DevSecOps pipeline in GitLab, adding automated vulnerability scanning stages to .gitlab-ci.yml, or triaging scanner findings with GitLab Duo AI before deployment.
domain: cybersecurity
subdomain: devsecops
tags:
- gitlab-ci
- devsecops
- sast
- dast
- container-scanning
- dependency-scanning
- secret-detection
- cicd-security
version: '1.0'
author: mahipal
license: Apache-2.0
nist_csf:
- PR.PS-01
- GV.SC-07
- ID.IM-04
- PR.PS-04
mitre_attack:
- T1195.001
- T1195.002
- T1552.001
- T1190
- T1610
---
# Building DevSecOps Pipeline with GitLab CI
## Overview
GitLab provides an integrated DevSecOps platform that embeds security testing directly into the CI/CD pipeline. By leveraging GitLab's built-in security scanners---SAST, DAST, container scanning, dependency scanning, secret detection, and license compliance---teams can shift security left, catching vulnerabilities during development rather than post-deployment. GitLab Duo AI assists with false positive detection for SAST vulnerabilities, helping security teams focus on genuine issues.
## When to Use
- When deploying or configuring building devsecops pipeline with gitlab ci capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
## Prerequisites
- GitLab Ultimate license (required for full security scanner suite)
- GitLab Runner configured (shared or self-hosted)
- `.gitlab-ci.yml` pipeline configuration familiarity
- Docker-in-Docker (DinD) or Kaniko for container builds
- Application deployed to a staging environment for DAST scanning
## Core Security Scanning Stages
### Static Application Security Testing (SAST)
SAST analyzes source code for vulnerabilities before compilation. GitLab supports 14+ languages using analyzers such as Semgrep, SpotBugs, Gosec, Bandit, and NodeJsScan. The simplest inclusion uses GitLab's managed templates.
### Dynamic Application Security Testing (DAST)
DAST tests running applications by simulating attack payloads against HTTP endpoints. It detects XSS, SQLi, CSRF, and other runtime vulnerabilities that static analysis cannot find. DAST requires a deployed, accessible target URL.
### Container Scanning
Uses Trivy to scan Docker images for known CVEs in OS packages and application dependencies. Runs after the Docker build stage to gate images before they reach a registry.
### Dependency Scanning
Inspects dependency manifests (package.json, requirements.txt, pom.xml, Gemfile.lock) for known vulnerable versions. Operates at the source code level, complementing container scanning.
### Secret Detection
Scans commits for accidentally committed credentials, API keys, tokens, and private keys using pattern matching and entropy analysis. Runs on every commit to prevent secrets from reaching the repository.
## Implementation
### Complete Pipeline Configuration
```yaml
# .gitlab-ci.yml
stages:
- build
- test
- security
- deploy-staging
- dast
- deploy-production
variables:
DOCKER_IMAGE: $CI_REGISTRY_IMAGE:$CI_COMMIT_SHORT_SHA
SECURE_LOG_LEVEL: "info"
# Include GitLab managed security templates
include:
- template: Security/SAST.gitlab-ci.yml
- template: Security/Secret-Detection.gitlab-ci.yml
- template: Security/Dependency-Scanning.gitlab-ci.yml
- template: Security/Container-Scanning.gitlab-ci.yml
- template: DAST.gitlab-ci.yml
- template: Security/License-Scanning.gitlab-ci.yml
build:
stage: build
image: docker:24.0
services:
- docker:24.0-dind
variables:
DOCKER_TLS_CERTDIR: "/certs"
script:
- docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
- docker build -t $DOCKER_IMAGE .
- docker push $DOCKER_IMAGE
rules:
- if: $CI_COMMIT_BRANCH
unit-tests:
stage: test
image: $DOCKER_IMAGE
script:
- npm ci
- npm run test:coverage
coverage: '/Lines\s*:\s*(\d+\.?\d*)%/'
artifacts:
reports:
junit: junit-report.xml
coverage_report:
coverage_format: cobertura
path: coverage/cobertura-coverage.xml
# Override SAST to run in security stage
sast:
stage: security
variables:
SAST_EXCLUDED_PATHS: "spec,test,tests,tmp,node_modules"
SEARCH_MAX_DEPTH: 10
# Override container scanning
container_scanning:
stage: security
variables:
CS_IMAGE: $DOCKER_IMAGE
CS_SEVERITY_THRESHOLD: "HIGH"
# Override dependency scanning
dependency_scanning:
stage: security
# Override secret detection
secret_detection:
stage: security
# License compliance scanning
license_scanning:
stage: security
deploy-staging:
stage: deploy-staging
image: bitnami/kubectl:latest
script:
- kubectl set image deployment/app app=$DOCKER_IMAGE -n staging
- kubectl rollout status deployment/app -n staging --timeout=300s
environment:
name: staging
url: https://staging.example.com
rules:
- if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH
# DAST runs against deployed staging
dast:
stage: dast
variables:
DAST_WEBSITE: https://staging.example.com
DAST_FULL_SCAN_ENABLED: "true"
DAST_BROWSER_SCAN: "true"
needs:
- deploy-staging
rules:
- if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH
deploy-production:
stage: deploy-production
image: bitnami/kubectl:latest
script:
- kubectl set image deployment/app app=$DOCKER_IMAGE -n production
- kubectl rollout status deployment/app -n production --timeout=300s
environment:
name: production
url: https://app.example.com
when: manual
rules:
- if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH
```
### SecurTrust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- declared (4 observation(s))
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
6c59587be632full audit observations/trust-audit/skill/mukul975__building-devsecops-pipeline-with-gitlab-ci.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-07 | 6c59587be632 | SAFE | B | 89 | first audit |
Questions
What does the Building Devsecops Pipeline With Gitlab Ci skill do?
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·
Is Building Devsecops Pipeline With Gitlab Ci safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Building Devsecops Pipeline With Gitlab Ci access on my machine?
The audit observed that it reaches the network. Each of those is consistent with what it says it does. Secrets in the source: none found.
How current is this page?
The grade is for one exact copy of the source (6c59587be632), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.