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Fastest Path: rafter ci init

Auto-generate CI config for GitHub Actions, GitLab CI, or CircleCI:
rafter ci init                    # auto-detect platform
rafter ci init --platform github  # explicit
rafter ci init --with-backend     # include remote code analysis job (requires RAFTER_API_KEY)
This writes a ready-to-commit workflow file. Review it, push, done.

Two CI Modes

Rafter supports two approaches in CI. Choose based on whether you have a Rafter API key.

Mode 1: Local Secret Scanning (no API key required)

Uses rafter secrets — the fast, deterministic scanner that runs pattern matching and Gitleaks secret detection directly on the runner. Same inputs, same findings, every time.
- name: Rafter secret scan
  run: |
    npm install -g @rafter-security/cli
    rafter secrets . --json --quiet
Exit code 1 fails the pipeline if secrets are detected. No account or API key needed. When to use: Open-source projects, teams without a Rafter subscription, or any repo where fast secret scanning at commit time is enough.

Mode 2: Backend Code Analysis (API key required)

Uses rafter run to trigger the Rafter code analysis engine for full SAST coverage — a wider range of vulnerability classes beyond secrets. Your code is deleted immediately after the analysis engine completes. When to use: Teams with a Rafter subscription who want full SAST coverage on every push. See Step 3 below for the complete workflow.

Introduction

Automated security scanning transforms security from an afterthought into a seamless part of your development workflow. Instead of remembering to run scans manually (and inevitably forgetting), your CI/CD pipeline automatically checks every commit and pull request for vulnerabilities. This guide shows you two approaches:
  • Manual setup: Step-by-step instructions for hands-on configuration
  • AI-assisted setup: Copy-paste workflows with AI prompts for rapid deployment
I’d recommend skimming the manual setup first so you understand what’s happening, then using the AI-assisted setup for a quick and easy setup. Plus, you’ll learn how API keys work, why they’re secure, and how to protect them properly in your CI/CD environment. If you’re not familiar with GitHub Actions, you can learn more about them here.

Why Automated Security Scanning Matters

The Manual Scanning Problem

Manual security scanning has three critical flaws:
  1. Human Error: Developers forget to run scans, especially under pressure
  2. Inconsistent Coverage: Different team members use different tools or settings
  3. Late Detection: Vulnerabilities are found after code reaches production

The Automated Solution

Automated scanning eliminates these problems by:
  • Running on every push: No forgotten scans
  • Consistent configuration: Same rules applied every time
  • Early detection: Vulnerabilities caught before deployment
  • Build failure: Critical issues block deployment automatically

Understanding API Keys in CI/CD

What Are API Keys?

API keys are authentication tokens that allow automated tools to access services on your behalf. Think of them as digital keys that unlock specific capabilities—in this case, security scanning services like Rafter.

Why API Keys Are Secure

API keys are designed for programmatic access and include several security features:
  • Scoped permissions: Keys can only access specific services
  • Usage tracking: All API calls are logged and monitored
  • Easy rotation: Keys can be regenerated instantly if compromised
  • Environment isolation: Keys are stored separately from your code

How GitHub Secrets Protect Your Keys

GitHub Secrets provide enterprise-grade security for sensitive data:
  • Encryption at rest: Keys are encrypted when stored
  • Encryption in transit: Keys are encrypted when accessed
  • Access control: Only authorized workflows can use secrets
  • Audit logging: All secret access is logged

Manual Setup: Step-by-Step Configuration

Step 1: Choose Your Mode

Refer to Two CI Modes above. If you’re using local scan, skip to Step 3 and use the local scan workflow. If you’re using backend scan, continue with Step 2 to get your API key.

Step 2: Get Your Rafter API Key

(Backend scan only — skip if using local scan.) If you have an existing key saved to a safe place, copy it. Otherwise, generate a new key… Rafter protects your API keys by not storing them. You get access once, when you generate/refresh the key. Then, refreshing the key invalidates the previous key to keep it safe. It’s a way to help you rotate keys, which is best practice. Navigate to Account Settings
  1. Go to your Rafter account settings
  2. Look for the “API Keys” section
Generate or Retrieve Key
  1. Click “Generate New API Key” or “Refresh API Key”
  2. The key is automatically copied to your clipboard (it won’t be shown/copiable again)
API keys are sensitive credentials. Never commit them to your repository or share them in plain text.
Add API Key to GitHub Secrets
  1. Navigate to your GitHub repository
  2. Click “Settings” → “Secrets and variables” → “Actions”
  3. Click “New repository secret”
  4. Name: RAFTER_API_KEY
  5. Value: Paste your API key
  6. Click “Add secret”

Step 3: Create GitHub Workflow

Create Workflow Directory
mkdir -p .github/workflows
Option A — Local Scan Workflow (no API key) Create .github/workflows/security-scan.yml:
# .github/workflows/security-scan.yml
# No API key required. Runs pattern + Gitleaks secret scanning on the runner.

name: Rafter Secret Scan

on:
  push:
    branches: [ main ]
  pull_request:

permissions:
  contents: read

jobs:
  secret-scan:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Rafter secret scan
        run: |
          npm install -g @rafter-security/cli
          rafter secrets . --json --quiet
Exit code 1 fails the job automatically if secrets are detected. Option B — Backend Code Analysis Workflow (API key required) Create .github/workflows/security-scan.yml:
# .github/workflows/security-scan.yml
#
# Prerequisites:
#   Add your Rafter API key as a GitHub repository secret:
#   Settings -> Secrets and variables -> Actions -> New repository secret
#   Name: RAFTER_API_KEY

name: Rafter Code Analysis

on:
  push:
    branches: [ main ]

permissions:
  contents: read

jobs:
  code-analysis:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Install Rafter CLI
        run: npm install -g @rafter-security/cli

      - name: Run code analysis
        env:
          RAFTER_API_KEY: ${{ secrets.RAFTER_API_KEY }}
        run: rafter run --format json --quiet > scan-results.json

      - name: Check for critical vulnerabilities
        run: |
          CRITICAL_COUNT=$(jq '.vulnerabilities | map(select(.level=="error")) | length' scan-results.json)
          if [ "$CRITICAL_COUNT" -gt 0 ]; then
            echo "Found $CRITICAL_COUNT critical vulnerabilities!"
            exit 1
          fi
          echo "No critical vulnerabilities found"

      - name: Upload results
        uses: actions/upload-artifact@v4
        if: always()
        with:
          name: security-scan-results
          path: scan-results.json
          retention-days: 30
The CLI handles repo/branch auto-detection, polling, and retries — no manual curl loops needed.

Step 4: Test Your Setup

Make a Test Commit
git add .github/workflows/security-scan.yml
git commit -m "Add automated security scanning"
git push
Check GitHub Actions
  1. Go to your repository’s “Actions” tab
  2. Look for the workflow
  3. Verify it runs successfully

AI-Assisted Setup

Tell your AI assistant:
Set up Rafter security scanning for this repo. Run `rafter ci init --platform github`
to generate the workflow, then commit it. If we have a RAFTER_API_KEY, use --with-backend
for full SAST code analysis. Otherwise the local secret scan is fine.
Or generate it yourself:
rafter ci init --platform github --with-backend
# Review .github/workflows/rafter-security.yml, then commit and push

Understanding the Workflow Components

Trigger Configuration

on:
  push:
    branches: [ main ]
This configuration ensures the analysis runs:
  • On every push to the main branch
  • Automatically, without manual intervention

CLI-Based Code Analysis

The backend workflow uses the Rafter CLI which handles auto-detection, polling, and retries:
- name: Run code analysis
  env:
    RAFTER_API_KEY: ${{ secrets.RAFTER_API_KEY }}
  run: rafter run --format json --quiet > scan-results.json
The CLI:
  • Auto-detects repo and branch from the git checkout
  • Polls until complete — no manual loop needed
  • Returns structured JSON with consistent schema and documented exit codes

Exit Codes

The CLI uses stable exit codes that CI pipelines can rely on:
CodeMeaningCI Action
0Success — analysis completedProceed
1General errorFail build
2Scan not found (HTTP 404)Check scan ID
3Quota exhausted (HTTP 429 or 403 scan-mode limit)Alert / back off
4Insufficient scope / forbidden (HTTP 403)Check API key permissions
Results are also available in your Rafter dashboard.

Vulnerability Checking

- name: Check for critical vulnerabilities
  run: |
    CRITICAL_COUNT=$(cat scan-results.json | jq '.vulnerabilities | map(select(.level=="error")) | length')
    
    if [ $CRITICAL_COUNT -gt 0 ]; then
      echo "Found $CRITICAL_COUNT critical vulnerabilities!"
      exit 1
    else
      echo "No critical vulnerabilities found"
    fi
This critical step:
  • Parses scan results using jq
  • Counts error-level vulnerabilities
  • Fails the build if critical issues are found
  • Provides clear feedback to developers

Advanced Configuration Options

While we’ve outlined some powerful use cases below, see our documentation for more advanced configuration options: Rafter CI/CD Documentation.

Customizing Triggers

You can customize when Rafter runs:
# Scan on all branches
on: [push, pull_request]

# Scan only on specific file changes
on:
  push:
    paths:
      - 'src/**'
      - 'package.json'

# Schedule regular scans
on:
  schedule:
    - cron: '0 2 * * 1'  # Every Monday at 2 AM

Adjusting Failure Thresholds

Modify the vulnerability checking logic:
# Fail on warnings and errors
WARNING_COUNT=$(cat scan-results.json | jq '.vulnerabilities | map(select(.level=="warning" or .level=="error")) | length')

# Fail only on specific vulnerability types (using hashed rule IDs)
CRITICAL_COUNT=$(cat scan-results.json | jq '.vulnerabilities | map(select(.ruleId | startswith("R-"))) | length')

# Fail on specific vulnerability patterns
SQL_INJECTION_COUNT=$(cat scan-results.json | jq '.vulnerabilities | map(select(.message | contains("SQL injection"))) | length')

Adding Notifications

Integrate with Slack, Discord, or email:
- name: Notify on failure
  if: failure()
  uses: 8398a7/action-slack@v3
  with:
    status: failure
    text: "Security scan failed: ${{ github.event.head_commit.message }}"

Troubleshooting Common Issues

API Key Not Found

Error: Error: RAFTER_API_KEY environment variable not set Solution:
  1. Verify the secret exists in GitHub repository settings
  2. Check the secret name matches exactly: RAFTER_API_KEY
  3. Ensure the workflow uses ${{ secrets.RAFTER_API_KEY }}

Scan Request Fails

Error: curl: (22) The requested URL returned error: 401 or curl: (22) The requested URL returned error: 400 Solution:
  • 401 Unauthorized: Check your API key is valid and not expired
  • 400 Bad Request: Verify repository name format (should be owner/repo)
  • Network issues: The -fsS flags will cause curl to fail silently on HTTP errors
  • Branch name issues: Ensure ${{ github.ref_name }} returns the correct branch name

Scan Status Issues

Error: Scan stuck in “processing” or “pending” status Solution:
  • Timeout handling: The workflow automatically fails after 10 minutes
  • Status checking: Verify the API returns valid status values (completed, failed, processing, pending)
  • Polling frequency: Adjust sleep 10 if scans typically take longer
  • API rate limits: Check if you’re hitting API rate limits

Scan Results Not Found

Error: scan-results.json: No such file or directory Solution:
  • Check scan completion: Ensure the scan reached “completed” status
  • Verify file output: The workflow saves results to scan-results.json and scan-results.md
  • API response format: Confirm the API returns results in the expected JSON format
  • Error handling: The set -euo pipefail ensures the script fails if curl commands fail

Security Best Practices

API Key Management

  • Rotate keys regularly: Generate new keys every 90 days
  • Monitor usage: Check API key usage logs for anomalies
  • Use least privilege: Only grant necessary permissions
  • Never log keys: Ensure keys don’t appear in logs or outputs

Workflow Security

  • Pin action versions: Use specific commit SHAs instead of tags
  • Review permissions: Limit workflow permissions to minimum required
  • Audit regularly: Review workflow changes and access patterns
  • Use trusted sources: Only use official GitHub Actions

Repository Security

  • Enable branch protection: Require status checks before merging
  • Use required reviewers: Require security team review for workflow changes
  • Monitor secrets: Regularly audit repository secrets
  • Enable security alerts: Use GitHub’s security features

Measuring Success

Key Metrics to Track

  • Scan Coverage: Percentage of commits scanned
  • Detection Rate: Vulnerabilities found per scan
  • Fix Time: Average time from detection to resolution
  • False Positive Rate: Incorrect vulnerability reports

Success Indicators

  • Zero critical vulnerabilities in production deployments
  • Consistent scan execution across all branches
  • Rapid vulnerability resolution (under 24 hours)
  • Developer adoption of security-first practices

Conclusion

Whether you use the local secret scanner or the full code analysis engine, the result is the same: security coverage on every commit with stable exit codes and structured output that CI pipelines can act on. Start with rafter ci init, customize as needed, and let the code analysis engine do the work.