building-devsecops-pipeline-with-gitlab-ci

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/building-devsecops-pipeline-with-gitlab-ci
0 commentsdiscussion
summary

Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret detection.

skill.md
name
building-devsecops-pipeline-with-gitlab-ci
description
Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret detection.
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

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

# .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

Security Approval Policies

Configure scan execution policies to enforce mandatory security scans:

  1. Navigate to Security & Compliance > Policies
  2. Create a "Scan Execution Policy" requiring SAST and secret detection on all branches
  3. Create a "Merge Request Approval Policy" requiring security team approval when critical vulnerabilities are detected

Custom SAST Ruleset Configuration

Create .gitlab/sast-ruleset.toml to customize analyzer behavior:

[semgrep]
  [[semgrep.ruleset]]
    dirs = ["src"]

  [[semgrep.passthrough]]
    type = "url"
    target = "/sgrep-rules/custom-rules.yml"
    value = "https://semgrep.dev/p/owasp-top-ten"

  [[semgrep.passthrough]]
    type = "url"
    target = "/sgrep-rules/java-rules.yml"
    value = "https://semgrep.dev/p/java"

Security Dashboard and Vulnerability Management

Vulnerability Report

GitLab consolidates all scanner findings into a single Vulnerability Report accessible at Security & Compliance > Vulnerability Report. Each vulnerability includes:

  • Severity rating (Critical, High, Medium, Low, Info)
  • Scanner source (SAST, DAST, Container, Dependency, Secret)
  • Location in source code or image layer
  • Remediation guidance and suggested fixes
  • Status tracking (Detected, Confirmed, Dismissed, Resolved)

Merge Request Security Widget

Every merge request displays a security scanning widget showing:

  • New vulnerabilities introduced by the MR
  • Fixed vulnerabilities resolved by the MR
  • Comparison against the target branch baseline

Pipeline Optimization

  • Parallel execution: Security scanners run concurrently in the security stage
  • Caching: Use CI cache for dependency downloads to speed up scanning
  • Incremental scanning: SAST can scan only changed files using SAST_INCREMENTAL: "true"
  • Fail conditions: Set allow_failure: false on critical scanners to enforce quality gates

Monitoring and Metrics

MetricDescriptionTarget
Pipeline security coveragePercentage of projects with all scanners enabled> 95%
Critical vulnerability MTTRTime from detection to resolution for critical findings< 48 hours
False positive ratePercentage of dismissed-as-false-positive findings< 15%
Secret detection block ratePercentage of secret commits blocked by push rules> 99%

References

how to use building-devsecops-pipeline-with-gitlab-ci

How to use building-devsecops-pipeline-with-gitlab-ci on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add building-devsecops-pipeline-with-gitlab-ci
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/building-devsecops-pipeline-with-gitlab-ci

The skills CLI fetches building-devsecops-pipeline-with-gitlab-ci from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/building-devsecops-pipeline-with-gitlab-ci

Reload or restart Cursor to activate building-devsecops-pipeline-with-gitlab-ci. Access the skill through slash commands (e.g., /building-devsecops-pipeline-with-gitlab-ci) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.655 reviews
  • Henry Sharma· Dec 28, 2024

    Solid pick for teams standardizing on skills: building-devsecops-pipeline-with-gitlab-ci is focused, and the summary matches what you get after install.

  • Isabella Menon· Dec 16, 2024

    building-devsecops-pipeline-with-gitlab-ci has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Isabella Rao· Dec 16, 2024

    building-devsecops-pipeline-with-gitlab-ci has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Luis Diallo· Nov 19, 2024

    We added building-devsecops-pipeline-with-gitlab-ci from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Anaya Smith· Nov 11, 2024

    Useful defaults in building-devsecops-pipeline-with-gitlab-ci — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Isabella Iyer· Nov 7, 2024

    building-devsecops-pipeline-with-gitlab-ci fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Neel Rahman· Nov 7, 2024

    I recommend building-devsecops-pipeline-with-gitlab-ci for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Isabella Gill· Nov 7, 2024

    building-devsecops-pipeline-with-gitlab-ci fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Jin Brown· Oct 26, 2024

    Useful defaults in building-devsecops-pipeline-with-gitlab-ci — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Liam Jain· Oct 26, 2024

    We added building-devsecops-pipeline-with-gitlab-ci from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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