How to Integrate DAST Into Your CI/CD Pipeline
Written by the Rafter Team
DAST in CI/CD automates runtime vulnerability detection by scanning your deployed application on every build. Unlike static analysis, DAST tests your running application — hitting real endpoints, submitting real payloads, and finding misconfigurations that only exist at runtime. Integrating automated DAST scanning into your pipeline catches authentication flaws, injection vulnerabilities, and missing security headers before they reach production.
The challenge is that DAST scans are slow and require a running target. A naive integration blocks your pipeline for 45 minutes and floods developers with false positives. The fix: fast baseline scans on every PR, full scans on a schedule, and clear rules for what blocks a merge.
DAST without a staging environment scans production. If your pipeline deploys directly to production and then runs DAST, attack payloads from the scanner hit your production database. Always scan a staging or ephemeral environment that mirrors production but is isolated from real user data.
Try Rafter free — add SAST scanning to your pipeline and catch source-level vulnerabilities alongside your DAST coverage.
Set Up a Staging Environment for DAST
Your DAST scanner needs a running target as close to production as possible — same dependencies, same configurations, same authentication flows — but fully isolated.
Ephemeral environments work best for PR-level scanning. Spin up a preview deployment for each pull request, run DAST against it, and tear it down when the PR closes.
Shared staging works for scheduled full scans. Dedicate a staging instance that stays current with your main branch and reset its database before each scan for consistent results.
Seed either environment with realistic test data. DAST scanners can only test what they can discover — an empty application produces an empty scan.
Configure Authenticated Scans
Most DAST scanners only test unauthenticated surfaces by default. That leaves your authenticated routes — admin panels, user dashboards, API endpoints behind tokens — completely untested.
Configure your scanner with valid credentials or session tokens to test the full application surface. Most tools accept authentication through recorded login sequences, API tokens injected via headers, or pre-authenticated browser sessions.
Store credentials in your CI/CD secrets manager, not in configuration files. Use a dedicated test account with realistic permissions — scanning as an admin misses authorization bypass vulnerabilities that a regular user would expose.
Set Failure Thresholds
Not every DAST finding should block a merge. Define severity-based thresholds that match your risk tolerance.
A practical starting point: block merges on high and critical findings. Warn on medium findings. Ignore informational ones entirely. Fix the critical injection vulnerability before merging, but the missing X-Content-Type-Options header can wait for a follow-up.
Tune thresholds over time. If your scanner produces consistent false positives for a specific rule, suppress that rule rather than raising the threshold.
Manage Scan Duration
Full DAST scans can take 30 minutes to several hours depending on application size. Running a full scan on every PR is impractical.
Split scans into two tiers. Run a fast baseline scan (5-10 minutes) on every pull request targeting the highest-risk vulnerability classes — SQL injection, XSS, authentication bypass — without crawling the entire application. Schedule full scans nightly or weekly against your staging environment.
Limit crawl depth and scope for PR scans. If a PR only modifies the billing module, configure the scanner to focus on billing endpoints. Most DAST tools support URL inclusion and exclusion lists for targeting specific areas.
Interpret Results in Pull Requests
Surface DAST results directly in pull requests as comments or status checks so developers see findings without switching tools.
Group findings by severity and endpoint. A single SQL injection finding on /api/users is more actionable than a list of 47 findings sorted alphabetically. Include the request that triggered the finding and a remediation suggestion.
Mark verified false positives and suppress them so they don't reappear. Every unsuppressed false positive erodes trust in the scanner and makes developers less likely to investigate real findings.
Start scanning your code with Rafter — combine SAST and dependency scanning with your DAST pipeline for full-stack vulnerability coverage.