CI/CD Pipeline Security Workflow | DevSecOps Best Practices

Introduction {#introduction}

Software supply chain attacks have exploded—increasing 742% in 2024 according to Sonatype's latest research. CI/CD pipelines, once viewed as productivity tools, have become prime attack targets. Wiz's 2025 security report reveals that 35% of enterprises use self-hosted runners with weak security controls, creating pathways for credential theft, code injection, and unauthorized production deployments.

The stakes are severe. IBM Security reports the average cost of a supply chain breach at $4.6 million, while attackers increasingly target the softest parts of the development lifecycle: secrets sprawl, vulnerable dependencies, unsigned artifacts, and misconfigured deployment environments.

The CI/CD Security Challenge {#the-cicd-security-challenge}

Modern CI/CD pipelines face four critical threats:

Credential compromise - Hardcoded secrets in repositories, exposed tokens in logs
Vulnerable dependencies - Third-party libraries with exploitable CVEs
Unsigned artifacts - No provenance verification, tampering goes undetected
Weak enforcement - Policy-as-code not implemented, manual approval gates bypassed

The solution isn't a single tool—it's a comprehensive 9-stage security workflow that transforms vulnerable pipelines into hardened supply chains aligned with SLSA (Supply-chain Levels for Software Artifacts) framework best practices.

Why This Workflow Matters {#why-this-workflow-matters}

This guide presents the complete CI/CD pipeline security workflow used by DevOps engineers, platform teams, and security professionals to secure software delivery from commit to production. Unlike basic security checklists, this workflow emphasizes:

Supply chain security - SLSA framework implementation with artifact provenance
Automated testing - SAST, DAST, and SCA integrated into every build
Secrets protection - Centralized management with automatic rotation
Policy enforcement - OPA/Sentinel rules blocking insecure deployments
Continuous monitoring - Real-time threat detection and compliance validation

Whether you're using GitHub Actions, GitLab CI, Jenkins, or Azure DevOps, this workflow provides the roadmap to production-grade pipeline security. Let's begin with assessment.

Stage 1: Pipeline Security Assessment (15-30 minutes) {#stage-1-pipeline-security-assessment-15-30-minutes}

Before implementing security controls, you must understand your current attack surface. This assessment reveals credential exposure, access control gaps, and compliance violations.

Step 1.1: Infrastructure Inventory {#step-11-infrastructure-inventory}

Why: Different CI/CD platforms have different attack vectors. Self-hosted Jenkins instances face different risks than GitHub-hosted runners. Understanding your architecture drives security priorities.

Document Your Pipeline Architecture:

Build servers (Jenkins, GitLab CI, GitHub Actions, CircleCI, Azure DevOps)
Runner type (self-hosted vs cloud-hosted)
Container registries (Docker Hub, ECR, GCR, ACR, Harbor)
Artifact repositories (Artifactory, Nexus, S3, GitHub Packages)
Secret stores (HashiCorp Vault, AWS Secrets Manager, Azure Key Vault)
Deployment targets (Kubernetes, ECS, Lambda, VMs)

Key Questions:

Who can trigger builds? Modify pipeline configurations?
Where are production credentials stored?
What security scans run automatically?
Are artifacts signed before deployment?

Step 1.2: Access Control Audit {#step-12-access-control-audit}

Why: Overly permissive access is the #1 cause of pipeline compromise. Attackers with developer access can inject malicious code, steal credentials, or deploy backdoors.

Review RBAC Policies:

Who can trigger production deployments?
Who can modify pipeline configurations?
Who can access production secrets?
Is MFA enforced for privileged operations?
Are service accounts following least privilege?

Use Diff Checker to compare current RBAC policies against baseline configurations:

Export current permission settings
Compare against security baseline
Identify permission drift and overly permissive roles
Flag unauthorized access grants

Step 1.3: Secrets Sprawl Discovery {#step-13-secrets-sprawl-discovery}

Why: Hardcoded secrets are the fastest path to breach. A single exposed API key can compromise entire production environments.

Audit Common Secret Locations:

Version control repositories (.env files, configuration files)
CI/CD pipeline YAML configurations
Container images (embedded credentials)
Build logs (accidentally printed secrets)
Infrastructure-as-Code templates

Scan with Secret Detection Tools:

# TruffleHog - scan git history
trufflehog git file://. --since-commit HEAD~100 --json

# GitGuardian - comprehensive secret scanning
ggshield secret scan repo .

# git-leaks - lightweight scanner
gitleaks detect --source . --verbose

Use Hash Generator to create baseline checksums of configuration files for integrity monitoring and drift detection.

Key Deliverable: Security assessment report, access control audit, secrets inventory, compliance gap analysis.

Stage 2: Secrets Management Implementation (30-60 minutes) {#stage-2-secrets-management-implementation-30-60-minutes}

Centralized secrets management eliminates hardcoded credentials and enables automatic rotation, audit logging, and just-in-time access.

Step 2.1: Select Secret Management Platform {#step-21-select-secret-management-platform}

Why: Different platforms excel in different environments. Choose based on your infrastructure and compliance requirements.

Top Options:

HashiCorp Vault - Multi-cloud, dynamic secrets, fine-grained policies, comprehensive audit logging
AWS Secrets Manager - Native AWS integration, automatic RDS rotation, IAM-based access
Azure Key Vault - Azure-native, HSM backing, managed identity integration
Google Cloud Secret Manager - GCP-native, versioning, automatic replication

Step 2.2: Integrate with CI/CD {#step-22-integrate-with-cicd}

GitHub Actions with HashiCorp Vault:

- name: Import Secrets
  uses: hashicorp/vault-action@v2
  with:
    url: https://vault.example.com
    method: jwt
    role: ci-pipeline
    secrets: |
      secret/data/db password | DB_PASSWORD
      secret/data/api key | API_KEY

GitLab CI with AWS Secrets Manager:

variables:
  DB_PASSWORD:
    vault: production/db/password
    file: false

Jenkins with Azure Key Vault:

azureKeyVault(
  credentialID: 'azure-sp',
  keyVaultURL: 'https://vault.azure.net',
  secrets: [
    [secretType: 'Secret', name: 'db-password', envVariable: 'DB_PASSWORD']
  ]
)

Step 2.3: Implement Secret Rotation {#step-23-implement-secret-rotation}

Why: Automatic rotation limits the window of opportunity if credentials are compromised.

Rotation Schedules:

Daily: CI/CD service account credentials
Weekly: Database passwords (staging/dev)
Monthly: Production database passwords, API keys
Quarterly: TLS/SSL certificates, SSH keys

Generate strong SSH keys for your CI/CD pipelines with our free SSH Key Generator tool (supports RSA, Ed25519, and ECDSA algorithms).

Use JWT Decoder to validate service tokens, verify expiration claims, and detect weak signing algorithms.

Step 2.4: Enable Audit Logging {#step-24-enable-audit-logging}

Why: Detecting credential theft requires comprehensive visibility into secret access patterns.

Monitor for Anomalies:

Access from unexpected IP ranges
High-volume secret retrieval
Failed authentication attempts (>5 in 1 hour)
Access to deprecated secrets

Use Unix Timestamp Converter to analyze vault audit logs, create security event timelines, and identify suspicious access patterns.

Key Deliverable: Centralized secret management, automated rotation, audit logging, migration runbook.

Stage 3: Static Application Security Testing (SAST) (20-40 minutes) {#stage-3-static-application-security-testing-sast-20-40-minutes}

SAST tools analyze source code for security vulnerabilities before runtime, catching issues like SQL injection, XSS, and hardcoded secrets during development.

Step 3.1: Select and Configure SAST Tool {#step-31-select-and-configure-sast-tool}

Top SAST Options:

SonarQube - 29+ languages, quality gates, technical debt measurement
Semgrep - Fast scanning, YAML-based custom rules, CI/CD optimized
CodeQL - Deep dataflow analysis, GitHub native, precise detection
Snyk Code - Real-time IDE scanning, AI-powered fix suggestions

Step 3.2: Integrate into Pipeline {#step-32-integrate-into-pipeline}

GitHub Actions with Semgrep:

- name: Run Semgrep
  uses: semgrep/semgrep-action@v1
  with:
    config: p/security-audit
    severity: ERROR

GitLab CI with SonarQube:

sonarqube-check:
  image: sonarsource/sonar-scanner-cli:latest
  script:
    - sonar-scanner
      -Dsonar.projectKey=$CI_PROJECT_NAME
      -Dsonar.qualitygate.wait=true
  only:
    - merge_requests
    - main

Step 3.3: Configure Security Rules {#step-33-configure-security-rules}

Why: Generic rulesets generate false positives. Tune detection for your tech stack and risk tolerance.

Enable OWASP Top 10 Detection:

SQL Injection, Cross-Site Scripting (XSS)
Broken Authentication, Sensitive Data Exposure
XML External Entities (XXE), Broken Access Control
Security Misconfiguration, Insecure Deserialization
Using Components with Known Vulnerabilities
Insufficient Logging & Monitoring

Language-Specific Rules:

JavaScript/TypeScript: Prototype pollution, ReDoS
Python: Pickle deserialization, command injection
Java: Deserialization, JNDI injection
Go: SQL injection, path traversal

Set Build-Blocking Thresholds: Block builds on HIGH/CRITICAL severity findings.

Use Diff Checker to compare baseline scans vs current scans, identify new vulnerabilities, and track remediation progress.

Key Deliverable: SAST integrated in CI/CD, security rules configured, false positive management process.

Stage 4: Dynamic Application Security Testing (DAST) (30-50 minutes) {#stage-4-dynamic-application-security-testing-dast-30-50-minutes}

DAST tools test running applications for runtime vulnerabilities that SAST can't detect—authentication bypasses, session management flaws, and configuration issues.

Step 4.1: Select DAST Tool {#step-41-select-dast-tool}

Top DAST Options:

OWASP ZAP - Open-source, proxy-based, API scanning support
Burp Suite Enterprise - Advanced crawling, low false positives, CI/CD native
Nuclei - Template-based, fast, YAML templates, active community

Step 4.2: Integrate DAST into Pipeline {#step-42-integrate-dast-into-pipeline}

GitHub Actions with OWASP ZAP:

- name: ZAP Scan
  uses: zaproxy/[email protected]
  with:
    target: 'https://staging.example.com'
    rules_file_name: '.zap/rules.tsv'
    cmd_options: '-a -j'

GitLab CI with OWASP ZAP:

zap_scan:
  image: owasp/zap2docker-stable
  script:
    - zap-baseline.py -t https://staging.example.com -r zap-report.html
  artifacts:
    paths:
      - zap-report.html
    when: always

Step 4.3: API Security Testing {#step-43-api-security-testing}

Why: APIs have unique attack surfaces—broken authentication, mass assignment, excessive data exposure.

Test API-Specific Vulnerabilities:

Broken authentication (token validation, session management)
Broken authorization (IDOR, privilege escalation)
Mass assignment (parameter pollution)
Injection (SQL, NoSQL, Command, LDAP)
Rate limiting (brute force protection)

Use JSON Formatter to analyze API responses for sensitive data exposure, validate response structure, and identify missing security headers.

Step 4.4: Schedule Continuous Scanning {#step-44-schedule-continuous-scanning}

Scanning Cadence:

Daily: Critical production endpoints
Weekly: Full staging environment scan
Monthly: Comprehensive production scan

Key Deliverable: DAST tool integrated, API security testing configured, continuous monitoring schedule.

Stage 5: Dependency Scanning & SCA (25-45 minutes) {#stage-5-dependency-scanning-sca-25-45-minutes}

Software Composition Analysis (SCA) identifies vulnerabilities in third-party dependencies—the most common source of production breaches.

Step 5.1: Select SCA Tool {#step-51-select-sca-tool}

Top SCA Options:

Snyk - Extensive vulnerability database, auto-fix PRs, license compliance
Dependabot - GitHub native, automatic PR creation, free
OWASP Dependency-Check - Open-source, NVD integration, multi-ecosystem

Step 5.2: Integrate Dependency Scanning {#step-52-integrate-dependency-scanning}

GitHub Actions with Snyk:

- name: Run Snyk to check for vulnerabilities
  uses: snyk/actions/node@master
  env:
    SNYK_TOKEN: ${{ secrets.SNYK_TOKEN }}
  with:
    args: --severity-threshold=high

npm/yarn Audit:

# Audit npm dependencies
npm audit --audit-level=high

# Automated fix
npm audit fix

Step 5.3: Generate Software Bill of Materials (SBOM) {#step-53-generate-software-bill-of-materials-sbom}

Why: SBOMs provide transparency for vulnerability tracking, license compliance, and supply chain attack detection.

SBOM Tools:

Syft: Container image SBOM generation
CycloneDX: Standard SBOM format
SPDX: Linux Foundation standard

Use JSON Formatter to parse SBOM files, extract dependency information, and identify transitive dependencies.

Step 5.4: Prioritize Vulnerabilities {#step-54-prioritize-vulnerabilities}

Why: Not all CVEs are equal. Prioritize based on exploitability and exposure.

Prioritization Criteria:

CVSS Score: Critical (9.0-10.0) → High (7.0-8.9) → Medium (4.0-6.9)
Exploitability: Known exploits in the wild (CISA KEV catalog)
Reachability: Is vulnerable code path actually used?
Exposure: Internet-facing vs internal services

Use CVE Lookup Tool to research vulnerability details, analyze CVSS scores, and review vendor advisories.

Remediation SLAs:

Critical: 7 days
High: 30 days
Medium: 90 days
Low: Next major release

Key Deliverable: SCA tool integrated, SBOM generation automated, vulnerability prioritization framework.

Stage 6: Container Scanning & Artifact Signing (30-50 minutes) {#stage-6-container-scanning-artifact-signing-30-50-minutes}

Container images and build artifacts must be scanned for vulnerabilities and cryptographically signed to prevent tampering and establish provenance.

Step 6.1: Container Image Scanning {#step-61-container-image-scanning}

Top Container Scanners:

Trivy - OS and application vulnerabilities, misconfigurations, secrets detection
Grype - Fast and accurate, multiple data sources, CI/CD optimized
AWS ECR Scanning - Native AWS integration, Clair + Snyk

GitHub Actions with Trivy:

- name: Build Docker image
  run: docker build -t myapp:${{ github.sha }} .

- name: Run Trivy vulnerability scanner
  uses: aquasecurity/trivy-action@master
  with:
    image-ref: myapp:${{ github.sha }}
    format: 'sarif'
    severity: 'CRITICAL,HIGH'
    output: 'trivy-results.sarif'

Step 6.2: Dockerfile Security Best Practices {#step-62-dockerfile-security-best-practices}

Use Minimal Base Images:

Distroless: No shell, minimal attack surface
Alpine: Lightweight (5MB base)
Scratch: Ultimate minimal (static binaries only)

Run as Non-Root:

RUN adduser -D -u 1000 appuser
USER appuser

Multi-Stage Builds:

FROM node:18 AS builder
WORKDIR /app
COPY . .
RUN npm ci && npm run build

FROM node:18-alpine
WORKDIR /app
COPY --from=builder /app/dist ./dist
CMD ["node", "dist/server.js"]

Step 6.3: Artifact Signing with Cosign {#step-63-artifact-signing-with-cosign}

Why: Signing prevents tampering, verifies authenticity, and enables policy enforcement (only run signed images).

GitHub Actions with Cosign:

- name: Install Cosign
  uses: sigstore/cosign-installer@v3

- name: Sign container image
  run: |
    cosign sign --yes \
      -a "repo=${{ github.repository }}" \
      -a "workflow=${{ github.workflow }}" \
      ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}
  env:
    COSIGN_EXPERIMENTAL: 1  # Enable keyless signing

Verify Signed Image:

cosign verify \
  --certificate-identity-regexp="https://github.com/myorg/*" \
  --certificate-oidc-issuer=https://token.actions.githubusercontent.com \
  myregistry.io/myimage:tag

Step 6.4: SLSA Framework Implementation {#step-64-slsa-framework-implementation}

Why: SLSA provides a framework for supply chain security maturity.

SLSA Levels:

Level 1: Build provenance (who, what, when, how)
Level 2: Signed provenance (cryptographically signed)
Level 3: Hardened build platform (hermetic builds, prevent credential forgery)

Generate SLSA Provenance:

- name: Generate SLSA provenance
  uses: slsa-framework/slsa-github-generator/.github/workflows/[email protected]

Use Hash Generator to verify artifact integrity by comparing SHA-256 hashes before/after transfer.

Key Deliverable: Container scanning integrated, Dockerfile hardening, artifact signing with Cosign, SLSA provenance.

Stage 7: Policy Enforcement & Deployment Validation (20-40 minutes) {#stage-7-policy-enforcement-deployment-validation-20-40-minutes}

Policy-as-code ensures only secure, compliant artifacts reach production—blocking unsigned images, missing security contexts, and misconfigured deployments.

Step 7.1: Implement Policy-as-Code with OPA {#step-71-implement-policy-as-code-with-opa}

Why: Automated policy enforcement removes human error and prevents security regressions.

OPA Policies for Kubernetes:

Block unsigned container images
Require security contexts (non-root)
Enforce resource limits
Mandate network policies

Example OPA Policy (Rego):

package kubernetes.admission

deny[msg] {
  input.request.kind.kind == "Pod"
  image := input.request.object.spec.containers[_].image
  not image_is_signed(image)
  msg := sprintf("Container image %v is not signed", [image])
}

deny[msg] {
  input.request.kind.kind == "Pod"
  container := input.request.object.spec.containers[_]
  container.securityContext.runAsNonRoot != true
  msg := sprintf("Container %v must run as non-root", [container.name])
}

Step 7.2: Pre-Deployment Validation Checklist {#step-72-pre-deployment-validation-checklist}

Why: Automated gates prevent insecure deployments from reaching production.

Validation Checks:

✓ Container image scanned (no HIGH/CRITICAL vulnerabilities)
✓ Image signature verified
✓ SBOM generated and stored
✓ Deployment manifest passes OPA policies
✓ Secrets fetched from vault (not hardcoded)
✓ Resource limits defined
✓ Network policies applied

Step 7.3: Deployment Rollback Strategy {#step-73-deployment-rollback-strategy}

Canary Deployments:

Deploy to 5% of traffic
Monitor error rates and latency
Gradually increase to 100%
Automatic rollback on anomalies

Blue-Green Deployments:

Deploy to "green" environment
Run smoke tests
Switch traffic to green
Keep blue as rollback target

Use Diff Checker to compare deployment manifests, highlight configuration changes, and identify risky modifications.

Use Unix Timestamp Converter to track deployment timelines, measure deployment duration, and analyze rollback response times.

Key Deliverable: OPA/Sentinel policies enforced, pre-deployment validation checklist, rollback strategy.

Stage 8: Audit Logging & Continuous Monitoring (Ongoing) {#stage-8-audit-logging-continuous-monitoring-ongoing}

Comprehensive logging and monitoring detect threats in real-time, enable incident response, and provide compliance evidence.

Step 8.1: Comprehensive Audit Logging {#step-81-comprehensive-audit-logging}

Log All Security-Relevant Events:

Authentication events (login attempts, MFA challenges, token generation)
Authorization events (permission changes, role assignments)
Code commits (who, what, when)
Build events (triggers, parameters, outcomes)
Deployment events (who deployed what to where)
Secret access (which secrets accessed by which pipelines)
Policy violations (OPA/Sentinel blocks)
Security scan results (SAST/DAST/SCA findings)

Centralize in SIEM:

Splunk Enterprise Security
Datadog Security Monitoring
ELK Stack with security plugins
AWS Security Hub + EventBridge

Step 8.2: Security Event Monitoring {#step-82-security-event-monitoring}

Alert on Anomalies:

Builds triggered at unusual hours (2-6 AM)
Production deployments from personal accounts
Pipeline configuration changes without approval
Disabled security scans
High-volume secret retrieval
Failed authentication attempts (>5 in 1 hour)
New CRITICAL vulnerabilities in dependencies
Unsigned artifacts pushed to production registry

Use JSON Formatter to parse security event logs, extract event details, and analyze patterns.

Step 8.3: Track Security Metrics {#step-83-track-security-metrics}

Key Performance Indicators:

Vulnerability Management: Mean Time to Remediate (MTTR), vulnerability backlog trend
Pipeline Security: % of builds with security scans, secret rotation compliance
Incident Response: Time to detect, time to respond, incidents per quarter

Use Unix Timestamp Converter to compute MTTR from vulnerability detection to fix deployment and measure SLA compliance.

Key Deliverable: Centralized audit logging, security event monitoring, compliance reporting.

Stage 9: Continuous Improvement & Security Culture (Ongoing) {#stage-9-continuous-improvement-security-culture-ongoing}

Security is not a destination—it's a continuous journey requiring cultural change, ongoing training, and proactive threat modeling.

Step 9.1: Security Champions Program {#step-91-security-champions-program}

Why: Embedding security expertise within development teams accelerates secure development.

Security Champion Responsibilities:

Bridge between security and development teams
Advocate for security best practices
Conduct peer security reviews
Stay current on threats and mitigations

Recognition: Quarterly meetings, career paths, public acknowledgment.

Step 9.2: Developer Security Training {#step-92-developer-security-training}

Training Programs:

Onboarding: Secure coding basics, pipeline security overview
Quarterly Workshops: OWASP Top 10, new threat landscape
Hands-On Labs: Exploiting and fixing vulnerabilities
Lunch-and-Learns: Recent incidents, lessons learned

Use Diff Checker for training exercises comparing vulnerable vs secure code samples.

Step 9.3: Threat Modeling for CI/CD {#step-93-threat-modeling-for-cicd}

Identify Pipeline Threat Vectors:

Supply chain attacks (compromised dependencies, malicious packages)
Insider threats (malicious developers, compromised accounts)
Infrastructure attacks (compromised build servers, runner hijacking)
Secret theft (exposed credentials in logs, version control)

STRIDE Threat Modeling:

Spoofing: Impersonation of CI/CD service accounts
Tampering: Unauthorized code/config modifications
Repudiation: Lack of audit trail for actions
Information disclosure: Secret exposure, log leaks
Denial of service: Pipeline disruption, resource exhaustion
Elevation of privilege: Privilege escalation in build environments

Step 9.4: Red Team Exercises {#step-94-red-team-exercises}

Why: Validating defenses requires adversarial testing.

Simulate Pipeline Attacks:

Inject malicious code via compromised dependency
Extract secrets from build logs
Test lateral movement from CI/CD to production
Evaluate detection and response times

Quarterly Red Team vs Blue Team Exercises: Document findings and improve defenses.

Key Deliverable: Security champions program, training curriculum, threat model, red team findings.

Conclusion {#conclusion}

Securing your CI/CD pipeline is no longer optional—it's a business imperative. This 9-stage workflow provides comprehensive defense-in-depth, from secrets management and automated security testing to artifact signing, policy enforcement, and continuous monitoring.

Key Achievements {#key-achievements}

Eliminated hardcoded secrets with centralized management and automatic rotation
Integrated SAST, DAST, and SCA into every build for comprehensive vulnerability detection
Implemented artifact signing and SLSA provenance tracking for supply chain security
Enforced policy-as-code for deployments, preventing insecure configurations
Established continuous monitoring and compliance validation

Best Practices Summary {#best-practices-summary}

Shift security left - Catch issues early in development
Automate everything - Consistency and scale through automation
Enforce policy-as-code - No manual gates, automated enforcement
Sign and verify all artifacts - Supply chain security and provenance
Monitor continuously - Detect and respond to threats in real-time
Foster security culture - Everyone is responsible for security

ROI Metrics {#roi-metrics}

According to industry research, organizations implementing comprehensive CI/CD security workflows achieve:

70% reduction in vulnerabilities reaching production
80% faster vulnerability remediation with automated updates
95% reduction in secret exposure incidents
60% faster compliance audits with automated evidence collection

Advanced Topics {#advanced-topics}

Ready to take your pipeline security to the next level? Explore:

AI/ML for anomaly detection in pipelines
Zero-trust architecture for CI/CD
Post-quantum cryptography for artifact signing
Chaos engineering for pipeline resilience
GitOps security best practices

This workflow integrates 11 free security tools from InventiveHQ:

Diff Checker - Compare RBAC policies, deployment configs, scan results
Hash Generator - Create artifact checksums, verify integrity
JWT Decoder - Decode service tokens, verify claims
Unix Timestamp Converter - Analyze audit logs, calculate MTTR
JSON Formatter - Parse SBOMs, analyze security event logs
CVE Lookup Tool - Research vulnerabilities, analyze CVSS scores
Base64 Encoder/Decoder - Decode secrets from logs/configs
X.509 Certificate Decoder - Validate SSL/TLS certificates
Security Headers Analyzer - Test deployed application headers
YAML to JSON Converter - Convert pipeline configurations
Data Format Converter - Normalize configuration formats

Frequently Asked Questions {#faqs}

What is the SLSA framework and why does it matter? {#what-is-the-slsa-framework}

SLSA (Supply-chain Levels for Software Artifacts) is a security framework developed by Google to prevent supply chain attacks. It defines four maturity levels for build integrity, from basic provenance (Level 1) to hardened build platforms (Level 4). SLSA matters because it provides standardized guidelines for securing the software supply chain, preventing tampering, and establishing artifact provenance.

How often should I rotate CI/CD secrets? {#how-often-should-i-rotate-secrets}

Rotation frequency depends on risk level: Daily for CI/CD service account credentials, Weekly for dev/staging database passwords, Monthly for production credentials and API keys, Quarterly for TLS certificates and SSH keys. Use dynamic secrets from HashiCorp Vault where possible for automatic rotation.

Should I use SAST, DAST, or both? {#should-i-use-sast-dast-or-both}

Both. SAST analyzes source code for vulnerabilities (SQL injection, XSS, hardcoded secrets) before runtime, while DAST tests running applications for runtime issues (authentication bypasses, configuration errors). They complement each other—SAST catches issues early, DAST validates deployed applications. Best practice: SAST on every commit, DAST on staging deployments.

How do I prioritize vulnerability remediation? {#how-do-i-prioritize-vulnerability-remediation}

Prioritize based on four factors: CVSS score (Critical 9.0-10.0 first), Exploitability (known exploits in CISA KEV catalog), Reachability (is vulnerable code path actually used?), and Exposure (internet-facing vs internal). Critical internet-facing vulnerabilities with known exploits require immediate remediation (7-day SLA), while low-risk internal vulnerabilities can wait for next release.

What's the difference between container scanning and dependency scanning? {#whats-the-difference-between-container-scanning-and-dependency-scanning}

Container scanning analyzes Docker/OCI images for OS vulnerabilities, misconfigurations, and embedded secrets. Dependency scanning (SCA) analyzes application dependencies (npm, pip, Maven) for vulnerable libraries. Container scanning covers the full image stack (base OS + application), while SCA focuses specifically on third-party libraries. Best practice: Use both—Trivy for containers, Snyk for dependencies.

How do I implement policy-as-code without blocking developers? {#how-do-i-implement-policy-as-code-without-blocking-developers}

Start with audit mode (log violations without blocking) to establish baselines and tune policies. Engage developers early to explain rationale and provide remediation guidance. Implement policies gradually: start with critical security rules (unsigned images, root containers), then expand to best practices. Provide fast feedback loops with pre-commit hooks and IDE plugins so developers catch issues before CI/CD.

Service Integration {#service-integration}

InventiveHQ's Cybersecurity Services help organizations implement comprehensive CI/CD pipeline security:

Security Assessment & Gap Analysis - Identify pipeline vulnerabilities and compliance gaps
DevSecOps Implementation - Integrate SAST, DAST, SCA, and policy enforcement
Secret Management Architecture - Design and deploy centralized secrets management
Container Security - Implement image scanning, signing, and runtime protection
Compliance Validation - SOC 2, PCI-DSS, HIPAA CI/CD security controls

Cloud Solutions - Secure cloud-native CI/CD pipelines
IT Security Consulting - DevSecOps strategy and roadmap
Managed IT Services - 24/7 pipeline security monitoring

Call to Action {#call-to-action}

Ready to secure your CI/CD pipeline and protect your software supply chain? Contact InventiveHQ today for a free security assessment and discover how our DevSecOps experts can help you implement comprehensive pipeline security.

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Document Version: 1.0 Last Updated: December 8, 2025 Word Count: ~5,800 words