How to Efficiently Implement DAST in CI/CD (2025 Guide)

Antoine Carossio -

Working with multiple customers implementing DAST in CI/CD has allowed us to learn a lot about what works, what doesn’t, and most importantly how to do it efficiently.

The truth is, it’s not about adopting just any tool. It's about making testing for runtime vulnerabilities fit seamlessly into your existing workflow, without slowing things down or creating bottlenecks.

The teams that succeed don’t just “plug in” a scanner, hope it works and just checks their box. They adapt their workflows, choose the right test data at the right time, and most importantly prioritize high-value security signals over noise. If DAST creates delays, flags minor issues, or slows down merges, it gets ignored.

In this article, we’ll share what we’ve learned working with AppSec & DevSecOps teams who’ve made DAST a natural part of their CI/CD loop, without disrupting their development velocity.

    What Is DAST ?

    Dynamic Application Security Testing (DAST) is a black-box testing approach that analyzes your application from the outside, just like an attacker would. It doesn’t need access to your codebase. Instead, it interacts with your app in its running state to find real vulnerabilities, things like broken authentication, missing access controls, or business logic flaws that only show up when the app is live.

    DAST serves as a critical complement to SAST. While developers appreciate SAST for its fast, in-IDE feedback early in the SDLC, it has a major limitation: it only scans source code, leaving a significant "context gap." This gap results in noisy false positives and, more concerning, the inability to catch critical runtime vulnerabilities.

    DAST is designed to fill this gap by testing what the app actually does in its running state. It identifies exploitable flaws that SAST can’t see, offering real-time insights into vulnerabilities that only appear when the app is live.

    In today’s modern stacks, where:

    • Web apps have transitioned to single-page applications (SPAs),
    • The number of APIs scales weekly,
    • And AI tools are generating code faster than security teams can review it,

    DAST has become more relevant than ever. It allows teams to find vulnerabilities that traditional static analysis tools miss, providing real-time insights into how the application behaves in production-like environments.

    Why DAST is More Critical Than Ever in 2025

    Not every vulnerability can be predicted in threat modeling or caught during code reviews. This is where DAST becomes essential. With a proper DAST tool in place, you can:

    • Identify critical, exploitable vulnerabilities that only surface when your services are running together in a live environment.
    • Spot authorization flaws (like IDORs) that often go unnoticed by static tools.
    • Uncover flaws in business logic that aren't documented and may not be evident until your app is live.

    DAST isn’t just about scanning after a release. It’s about integrating feedback about runtime vulnerabilities directly into your CI/CD pipeline and catching vulnerabilities before they hit production. Done right, it ensures that security issues are detected early, without putting a halt to your development pace. This article will dive deeper into how teams can implement DAST effectively within their CI/CD pipeline.

    Why Traditional DAST Fails in CI/CD

    Trying to add DAST to CI/CD usually hits the same wall. Not because DAST is a bad idea, but because the tools just don’t fit how engineering teams work today.

    Most legacy DAST tools assume you have a long-lived staging environment, time to configure everything manually, and hours to wait for a scan to finish. That’s not how modern pipelines run.

    Here’s where they break down in real CI/CD setups:

    The High Cost of Manual Configuration

    The single biggest point of friction with legacy DAST tools is the sheer amount of manual configuration required to get any value. This "tuning tax" is often a significant, hidden cost and includes:

    • Scripting Complex Authentication: Manually creating and maintaining brittle login scripts to allow the scanner to test authenticated endpoints.
    • Defining Scan Policies: Sifting through hundreds of vulnerability categories to disable tests that are irrelevant to the application’s tech stack.
    • Creating Suppression Rules: Running initial scans, being flooded with false positives, and then painstakingly creating rules to ignore all the noise.

    This work isn’t a one-time setup; it’s a continuous maintenance burden. Every time the application changes, the configuration risks breaking, making the tool a high-cost asset that fails to scale with the engineering team.

    A False Choice: Too Slow vs. Too Shallow

    Rather than offering an automatic "full coverage" scan, most legacy DAST tools require teams to select from predefined "scan profiles." In a CI/CD context, this presents a false choice:

    • The "Full Scan" Profile: This attempts a comprehensive crawl of every route, often taking hours to complete. It's built for post-deployment analysis and isn’t suitable for CI/CD environments, where rapid feedback loops are essential.
    • The "Quick Scan" Profile: This profile is faster but often too superficial. It typically checks for a limited set of common vulnerabilities and often misses more complex, context-dependent flaws like authorization issues, which can be the most critical.

    In fast-moving development cycles, where pipelines are expected to complete in minutes, neither option is practical. Scans that are either too slow or too shallow introduce friction, undermining the release process. As a result, teams may bypass these scans entirely or run them asynchronously, reducing their effectiveness and visibility.

    Too Many False Positives

    Traditional DAST tools often overwhelm teams with irrelevant findings.

    They flag “sensitive data exposure” on login forms, even when the fields are expected and intentionally visible. They raise alerts on 302 redirects, standard 404 pages, or flows that aren’t even accessible during testing.

    Common issues include:

    • Vulnerabilities unrelated to the application’s tech stack
    • Alerts triggered on expected behavior like redirects or session cookies
    • Warnings about pages (e.g. password reset) that were intentionally excluded from the test scope

    Without proper context, these results erode trust. Developers stop paying attention, and the tool is eventually sidelined.

    Incompatible with Ephemeral Environments

    In many modern CI pipelines, applications are deployed to temporary containers or preview environments that exist only for the duration of the test run often less than 10 minutes. These environments are dynamically generated, have unpredictable URLs, and are torn down immediately after use.

    Traditional DAST tools typically expect a fixed staging URL, a stable IP address, and a persistent environment where manual authentication or scanner setup can be reused. In a short-lived, isolated test environment, these assumptions don’t hold.

    If a scanner can’t handle dynamic deployment targets or operate without manual configuration, it introduces failure points. Authentication frequently breaks, target discovery fails, and the scan either doesn’t run or returns incomplete results.

    Legacy DAST tools don’t understand modern APIs

    Most traditional DAST tools were built around monolithic web applications with HTML interfaces and crawlable links. But modern applications expose attack surfaces through GraphQL, OpenAPI-based REST endpoints, and distributed microservices often with distinct authentication mechanisms per service.

    These tools often fail to keep up with current architectures. Common issues include:

    • Inability to detect non-UI-based routes exposed through APIs
    • Broken authentication on multi-step or token-based login flows
    • No understanding of stateful logic or request chaining required to reach real attack surfaces

    Without full context of how the application behaves in production, scanners either miss critical functionality or over-scan irrelevant paths, resulting in false negatives or noisy reports.

    How to Actually Make DAST Work in CI/CD

    Adding dynamic security testing to a CI/CD pipeline sounds straightforward in theory: run a scan with each commit and surface issues early. In practice, the execution is rarely that simple.

    Pipeline timing constraints, authentication failures, and poor test coverage are all common failure points. If the scanner slows down deploys or produces unactionable results, it won’t be adopted.

    Through direct work with engineering teams including fintech companies facing compliance audits and SaaS teams deploying multiple times per day, we’ve seen what makes the difference.

    What follows is a practical approach to integrating DAST in CI/CD pipelines in a way that supports engineering velocity while improving security coverage.

    Dast implementation checklist

    Step 1: Start with Feedback, Evolve to a Security Gate

    One of the fastest ways to erode trust in DAST is to make it a hard blocker on every pull request from day one. To avoid this, successful teams adopt a phased approach:

    Phase 1: Run in Non-Blocking "Audit Mode"

    Initially, DAST should not be a gating condition. The goal is to provide visibility without interrupting the development workflow. Common patterns include:

    • Running scans on merge to a staging environment.
    • Setting up nightly or scheduled scans on the main branch.
    • Piping all findings to developer-visible channels like PR comments, Slack alerts, or Jira tickets.

    At this stage, you are building trust and tuning the scanner. Developers shouldn’t be punished for pre-existing issues or the initial noise of a new tool.

    Phase 2: Evolve to a Smart, Blocking Gate

    Once the integration is stable and producing consistent, actionable results, you can gradually introduce fail conditions. A mature and effective policy is to block merges only when a new critical and exploitable vulnerability is found in user-facing code.

    This approach ensures teams adopt DAST without slowing down delivery, while still getting early feedback on regressions and potential risks.

    Step 2: Scope Smartly: From Manual Targeting to Automated Discovery

    In CI/CD environments, scanning the entire application on every run is rarely practical especially when dealing with microservices, ephemeral test environments, or large surface areas.

    The goal isn’t brute-force coverage on every commit. Instead, it’s about applying intelligent coverage: focusing your most intensive testing on the routes that pose the highest risk and are most relevant to the changes being made.

    How teams scope effectively:

    • Targeted Scans with HAR Files: A highly effective technique is defining scan targets using HAR (HTTP Archive) files generated from existing test automation (e.g., Cypress or Playwright). These files record real user flows, ensuring the scanner focuses on reachable, meaningful routes and ignores irrelevant noise. This transforms what could be an hour-long scan into a fast, focused check that takes just minutes.
    • Automated Discovery from Your Sources of Truth: A more mature approach involves automating the discovery of your application's entire attack surface. Modern DAST platforms, like Escape, integrate seamlessly with your ecosystem to build a comprehensive inventory from your sources of truth, including:
      • Cloud provider inventories (e.g., AWS)
      • API gateways (e.g., Cloudflare)
      • Developer tools (e.g., Postman Collections)

    This automated discovery ensures you always have a complete, up-to-date map of your applications, enabling you to run targeted scans on high-impact services (such as those tagged as "external-facing" or containing sensitive data) without requiring manual effort.

    By combining automated discovery with targeted HAR-based scanning in the pipeline, DAST becomes faster, more stable, and much easier for teams to trust.

    Step 3: Focus on Criticality and Exploitability

    Rather than testing for every vulnerability category from the start, successful teams improve their signal-to-noise ratio by prioritizing vulnerabilities that are both high-criticality and likely to be exploited. This risk-based approach ensures that developer attention is focused on the vulnerabilities that pose the greatest, most immediate threat to the business.

    What to prioritize first:

    • High-Impact Injection Flaws: Focus on critical issues like SQL injection, NoSQL injection, and command injection, which are easily exploitable and have a direct, severe impact on your application’s security.
    • Authentication and Authorization Bypasses: Prioritize flaws that could allow an attacker to impersonate users or escalate privileges, such as broken authentication or Insecure Direct Object References (IDORs).
    • Misconfigurations in Critical Flows: Address issues in high-risk workflows like user registration, password resets, and payment processing, where flaws can have immediate and severe business consequences.

    Once your initial testing workflow is stable and developer engagement is consistent, you can start addressing more complex, context-dependent vulnerabilities or lower-impact issues.

    Key takeaway: It’s far more effective to fix one critical, exploitable vulnerability than to report ten low-risk issues that won’t be addressed.

    Step 4: Use Schemas as Your Map, and HAR Files as Your Guide

    A common challenge for DAST tools is their reliance on API schemas, such as OpenAPI or GraphQL introspection. In fast-moving engineering teams, these specs can quickly fall out of sync with what's actually deployed.

    However, abandoning schemas entirely isn't the solution. The key is to treat schemas as the foundational map of your application’s surface area, and then enrich that map with real-world context.

    What teams do in practice:

    • Validate the Map: Start by ensuring your schema is as accurate as possible. Integrating a schema linter (e.g., Spectral) into your CI pipeline can run basic validation. This is a non-blocking step that catches issues like missing security definitions or undocumented routes, creating a cleaner foundation for your DAST tool.
    • Provide the Guide: Then, enhance the schema with real-time context using a HAR file from your E2E tests. A HAR file doesn’t replace the schema, but enriches it by providing the actual user journey, including valid authentication tokens, session cookies, and realistic data formats. This context gives the scanner critical information that a schema alone cannot provide.

    Dynamic testing should never break because a spec is incomplete. Escape is designed to use the best of both worlds: leveraging the schema for an architectural overview, and utilizing HAR files to execute fast, targeted, and highly realistic scans on the most relevant user flows.

    Key Takeaway: A clean schema tells your scanner what to test; a HAR file tells it how to test and where to focus in the pipeline. Combining both ensures fast, accurate, and low-noise DAST.

    Step 5: Schedule Deep Scans According to Your Risk Profile

    While fast, scoped scans are crucial for the PR pipeline, deeper, more comprehensive testing is essential for broader security coverage. The key is to schedule these scans based on your team’s velocity and risk appetite avoiding unnecessary scans on every commit while still ensuring comprehensive security validation.

    What this looks like in practice:

    • The Standard Approach (Nightly Scans): Many teams find the best balance by running extended DAST scans on a scheduled job (e.g., nightly or weekly) against a stable staging environment. This provides a regular, deep security baseline without blocking daily deployments or slowing down development.
    • The Advanced Approach (Pre-Deployment Gates): For teams with higher security requirements, you may prefer running a comprehensive scan before every deployment to production. To avoid bottlenecks, parallelize the workload. Instead of one large, monolithic scan, split testing tasks across logical boundaries, such as:Running these jobs in parallel via CI/CD matrix jobs improves speed and makes failures easier to isolate.
      • Individual services (/auth, /admin, etc.)
      • Specific test environments or feature flags
      • Distinct API groups (e.g., GraphQL queries vs. mutations)

    Tools for the Job: A flexible CLI, like the one provided by Escape, is essential for this approach. It enables isolated, headless scan jobs for different parts of your application, with results collected in a centralized dashboard without requiring constant manual setup.

    Step 6: Integrate Security into Developer Workflows with Automated Triage

    Even the best DAST configuration won’t help if the results don’t reach the right people or can’t be acted on quickly. The goal isn’t just to scan for issues, but to surface them where teams already track work, with enough context to support triage and remediation.

    Modern AppSec teams achieve this by building automated triage workflows.

    How teams build effective workflows:

    • Automate Ticket Creation with Conditional Logic: Instead of manually creating tickets, set up automated rules. A modern security platform like Escape allows you to build workflows based on a WHEN... IF... THEN... model. For example:
      • WHEN a New Issue is found,
      • IF the Severity is CRITICAL,
      • THEN automatically create a Jira Ticket and assign it to the correct project.
    • Route Findings to the Right Team, Automatically: Clearly assign ownership from the start. A powerful workflow can use metadata to route findings to the right team automatically. For example, if an issue is found in a service owned by the auth team, the workflow can use code ownership information or tags to assign the Jira ticket and send a Slack alert directly to the #auth-team channel.
    • Ensure Every Alert Includes Full Context: Every automated ticket or alert must be immediately actionable. Ensure your tool provides full context in each report, including the affected endpoint, the request/response payload to reproduce the issue, a clear severity rating, and a link to remediation documentation.

    By automating the triage process, you eliminate the manual busywork of creating and assigning tickets. This frees up the security team to focus on higher-level tasks and ensures that developers get the right information, in the right place, at the right time.

    Tip: Add a “DAST Triage” item to recurring team rituals like sprint planning or bug review. It keeps security visible and makes the feedback loop a natural part of the development process.
    💡
    See how to build a fully automated DAST workflow, from CI scan to developer-ready Jira ticket, in a personalized demo here

    What to Look For in CI/CD-Compatible DAST Tools

    Dynamic testing in CI/CD requires tools that seamlessly integrate into your existing pipeline, minimizing overhead and avoiding deployment blockers. When evaluating options, prioritize tools that support scoped, repeatable, and highly automated workflows.

    Key Capabilities to Prioritize:

    • Automated Discovery and Inventory: Modern DAST tools should automatically discover your application's full attack surface. Look for tools that can build a comprehensive inventory by integrating with your sources of truth, including cloud providers (AWS, GCP), API gateways (Cloudflare), and developer tools (Postman). This eliminates the need for manual updates and ensures your scans are always up-to-date.
    • Context-Aware Scoping: To maintain speed without compromising coverage, your DAST tool should support fast, targeted scans. It should accept test artifacts like HAR files from E2E suites, ensuring you focus on real user flows. Additionally, leveraging API schemas (OpenAPI, GraphQL SDL) can enhance scan precision, providing a more contextual understanding of your application’s attack surface.
    • Flexible Pipeline Integration: A good DAST tool should be flexible in how it integrates into your pipeline. Start with a non-blocking "audit mode" where results are posted to developer-visible channels like Jira or GitHub PR comments. As your program matures, you should be able to configure it to act as a blocking gate for critical vulnerabilities or regressions.
    • First-Class CLI and CI Integrations: The tool must be fully automatable, with a robust CLI that works seamlessly in containerized environments and integrates with CI/CD platforms like GitHub Actions.
    • Actionable, Developer-First Findings: This ensures security is managed as code, just like any other test stage, enabling automation at scale.
      • Full Context for Triage: Include the complete request/response payload, the affected endpoint, and a clear severity rating to make triage simple.
      • One-Click Reproducibility: Provide a cURL command so developers can instantly reproduce the vulnerability and verify the issue.
      • Clear Remediation Guidance: Offer concise, actionable advice on how to fix each specific vulnerability, helping developers resolve issues quickly without confusion.

    Where Escape Fits In

    Traditional DAST tools weren’t built for today’s fast-paced CI/CD pipelines. Escape was.

    Designed with modern development workflows in mind, Escape works seamlessly in environments with Single Page Applications (SPAs), GraphQL, OpenAPI, and microservices. While other tools tend to slow things down, Escape integrates smoothly into your existing processes without complicated setups.

    Here’s how Escape makes security testing work better:

    Context-Aware Testing with OpenAPI, HAR, and cURL

    → Escape lets you scope tests using OpenAPI schemas, HAR recordings, and cURL requests, offering flexibility for everything from bug bounty findings to custom security rules. These tests run continuously in your pipeline, making security a natural part of the development cycle.

    Fast and Parallel Scans

    → Teams often configure Escape to run quick, targeted scans for each microservice or on each pull request. This keeps your pipelines fast by ensuring tests only focus on the changes that matter, rather than scanning everything every time.

    Simple CI/CD Integration

    → Whether you use GitHub Actions, GitLab, or CircleCI, Escape drops right into your pipeline with just a few lines of code. No wrappers, no custom runners just clean, simple integration.

    Automated Triage with Actionable Workflows

    → Escape's powerful workflow engine automates the triage and routing of findings based on severity and relevance. For example, you can automatically create a Jira ticket for critical vulnerabilities and send notifications to specific Slack channels, ensuring the right team addresses the issue promptly.

    Built for Runtime API and Business Logic Security

    → Escape is built to keep up with modern apps. It catches complex business logic flaws and API-level vulnerabilities that other tools miss, giving you real, actionable security insights that matter.

    Escape isn’t just compatible with CI/CD. It’s built to fit the way your team works: fast, collaborative, and API-first.

    Building Your DAST Workflow Toolchain with Open Source

    A solid application security pipeline isn’t about a single tool; it’s about layering the right tools for the right jobs. Building an effective DAST workflow often involves combining several powerful open-source projects to cover your bases from ensuring data quality to running foundational scans. Here’s a look at the essential components modern security teams use to create a fast, accurate, and developer-friendly process.

    1. Prepare Your Inputs - Schema & Context

    Spectral

    Use Spectral in your CI pipeline to validate and enforce the quality of your OpenAPI or GraphQL schemas. A clean and accurate schema is the foundation for any reliable DAST scan, ensuring that your tool knows what to test and reducing false positives.

    Playwright & Cypress

    Configure your E2E (End-to-End) testing suites, such as Playwright or Cypress, to generate HAR files. These files capture the crucial runtime context, including user flows and authentication tokens. HAR files guide your DAST tool to focus on what truly matters, drastically improving the accuracy and speed of your scans.

    2. The Engine - Foundational DAST Scanners

    ZAP is one of the most widely used open-source DAST scanners. It’s a great starting point for basic web security testing. However, our comprehensive DAST benchmark shows that ZAP struggles with modern API coverage and complex business logic flaws, which are crucial for modern apps.

    A modular DAST framework in Ruby that provides a REST API to trigger scans remotely from CI/CD jobs, making it ideal for complex environments.

    3. Manage the Outputs - Triage & Aggregation

    • DefectDojo: Open-source vulnerability management platform that centralizes findings from SAST, DAST, and other tools. It helps track vulnerabilities, manage SLAs, and prioritize remediation for faster resolution.

    Conclusion: DAST That Works in CI/CD Isn’t a Myth - It’s a Mindset Shift

    DAST isn’t the problem how it’s been implemented is. From working with various AppSec teams, we’ve found that the key to successful DAST in CI/CD isn’t about running more scans or finding more issues. It’s about integrating it the right way:

    • As a non-blocking layer that supports development velocity.
    • By testing the business logic that is most relevant and high-risk.
    • Using trusted inputs like schemas, HAR files, and custom rules.
    • Ensuring workflows that developers can engage with, not ignore.

    When DAST is aligned with modern development practices fast-moving codebases, evolving APIs, and dynamic environments it becomes an essential tool that adds real value.

    When you focus on real-world behaviors, DAST transforms into a powerful runtime safety net that helps protect your applications without slowing you down.

    Ready to see what a CI/CD-compatible DAST tool looks like? Explore Escape to learn more.

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