StackHawk logo featuring a stylized hawk icon on the left and STACKHAWK in bold, uppercase letters to the right. The white text and icon on a light gray background reflect its focus on Shift-Left Security in CI/CD.
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Shift-Left DAST for the AI-DLC

Runtime security testing built for modern apps, APIs, and AI components, embedded throughout your development lifecycle.

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Why Runtime Testing

AI Changed The Math On AppSec. Runtime Testing Is How You Keep Up.

AI is shipping code faster than humans can review it, into architectures that static analysis was never built to see. Runtime testing catches what everything else misses.

A flow diagram with two labeled boxes connected by a line: “SQL Injection” on the left in a dark box and “Remediation” on the right in a teal box, highlighting Shift-Left Security in CI/CD. A faint bird and hexagon are in the background.

Code Volume Is Up. So Are Alerts.

SAST flags patterns without exploitability context, distracting teams from the risks that actually need fixing.

A dashboard displays scan results for GraphQL & gRPC API Security: 16 apps with 0 failed scans, scan frequency colored bars, 71 findings (0 high, 24 medium, 47 low), and a donut chart showing 76% attack surface coverage.

Static Analysis Alone Leaves Gaps

Critical risks like auth bypasses, business logic flaws, and broken assumptions only surface when apps are running.
A dashboard with three panels shows code analytics: 31% of repositories contain applications or APIs, 76% of the API attack surface is mapped, and a summary displays 26 repositories, 8 mapped surfaces, and 208 commits in 30 days.

New Attack Surfaces Are Major Blind Spots.

LLM integrations, MCP servers, and agent-driven APIs bring new risk and attack vectors that existing tools aren’t built for. StackHawk tests them like an attacker would.

How It’s Built

It’s DAST, But Different

Three things make StackHawk different: where it runs, what it’s built for, and how developers actually use it.

Runs where your code runs

Ephemeral scans that fit into any pipeline, any environment. No vendor cloud, no traffic traversing the internet to reach your apps.

  • CLI or Docker container; spins up and shuts down per scan
  • YAML config-as-code, versioned alongside your app
  • Executes directly in GitHub Actions, GitLab, Jenkins, CircleCI
A grid of dark squares displays logos for GitHub, Azure, CircleCI, AWS, Jenkins, and GitLab—highlighting Shift-Left Security in CI/CD; some squares have a checkmark. The right side softly fades into white.
A dashboard displaying gRPC-Beak-Performance scan results: 11 high, 32 medium, and 43 low issues. Findings include SQL Injection and Path Traversal, with AppSec Risk Prioritization applied to highlight high-criticality risks.

Built For Microservice Architectures

Small, fast services tested in minutes, not hours. Coverage scales as your app surface grows.

  • Microservice-first architecture with full API testing support
  • Parallel execution alongside existing CI/CD tests
  • Incremental testing on code changes, not full-app rescans

Developer-Native Workflow

Findings land where developers already work, with the context to act on them immediately.

  • Results in PR comments, Slack, Jira, and Datadog
  • Re-run only failed tests to validate fixes before merge
  • Fix guidance developers can act on without security handoffs
A web interface displays a warning about SQL Injection (high severity, CWE-89). The Remediation section highlights API Attack Surface Discovery and suggests using Object Data Models (ODMs) with a Node.js Mongoose snippet for MongoDB.

Loved by Devs.
Trusted by AppSec.
Backed by Badges.

Our G2 badges aren’t just for show—they reflect real-world impact and the confidence developers and security teams have in StackHawk.
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What We Test

DAST Is What We Do, But This Is What We Test

StackHawk automatically uncovers all the LLM risks that are relevant to application development using specialized attack patterns during runtime testing. No configuration required—if your application has LLM integrations, we automatically test for relevant vulnerabilities.
A minimalist teal line drawing of a computer monitor displays "API" on its screen, symbolizing GraphQL & gRPC API Security, set against a light blue background.

API Security Testing

REST, GraphQL, SOAP, and gRPC tested the way they actually run, with real requests, auth flows, and attack scenarios across your full API surface. We auto-generate specs to scale coverage as your API footprint grows.

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A simple blue line drawing of four pillows of various sizes on a light blue background, symbolizing the layered approach of Shift-Left Security in CI/CD processes.

LLM Security Testing

AI features introduce risks that static tools can’t see. StackHawk tests LLM interfaces for risks like prompt injection, data leakage, and unvalidated model outputs at runtime, where these vulnerabilities actually surface.

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A simple blue line drawing shows a rectangle at the top connected by lines to two cubes below, resembling a hierarchical or network structure—ideal for illustrating Shift-Left Security in CI/CD on a light blue background.

Remote MCP Server Security Testing

As agents connect to external tools and data through MCP, those interfaces need to be tested for injection, unauthorized access, and data exposure before they reach production — and that’s what StackHawk does.

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More Than Testing

Extended by our AppSec Intelligence Platform

StackHawk’s DAST is the testing engine. The StackHawk platform extends it with visibility from code and oversight across your AppSec program:
  • Attack surface discovery from source code: Integrate your SCM and StackHawk maps every API and app component from the code itself — including shadow APIs and AI/LLM interfaces
  • Risk-based prioritization: Risk insights from code focus testing on the repositories and applications that carry the most exposure
  • Deep integrations: Native connections to GitHub, GitLab, Jira, Slack, Datadog, and the SIEM and ticketing tools your teams already run
  • Program-level intelligence: Tracks coverage, vulnerability trends, so AppSec leaders can prove program value
StackHawk's Platform including API Discovery, HawkScan, and Integrations.

How It Compares

Dynamic Testing for the AI Era

A light blue outline of a triangular warning sign with an exclamation mark in the center, highlighting API Attack Surface Discovery, set against a pale blue background.

Legacy DAST Problems:

  • Tests production, where fixes mean rollbacks and firefighting
  • Brittle config that breaks and needs rebuilding
  • Too slow to run on every build
  • Misses authorization and business logic flaws that cause breaches
  • Built for monoliths and known endpoints
A stylized turquoise eagle with outstretched wings is centered in front of geometric hexagonal shapes on a light blue background, symbolizing the strength of Dynamic Application Security Testing (DAST).

StackHawk’s Modern Approach:

  • Can test pre-production, where fixes are 50% cheaper
  • YAML config-as-code, versioned with your app
  • Scans in minutes, run locally or in CI/CD
  • Catches the runtime vulnerabilities that cause breaches
  • Built for APIs, microservices, and AI interfaces

StackHawk DAST FAQs

How is StackHawk different from static analysis tools?

Static analysis examines code patterns but can’t detect runtime vulnerabilities like authorization bypasses or business logic flaws. StackHawk tests APIs as they actually operate, finding the critical security issues that only emerge when applications are running.

What makes StackHawk different from legacy DAST tools?
Legacy DAST tools test production or staging environments after development is complete, making fixes expensive and disruptive. StackHawk runs within your CI/CD infrastructure on incremental code changes, finding vulnerabilities when developers can fix them immediately as part of their normal workflow.
Won't running security tests in CI/CD slow down our builds?
StackHawk tests only the code being changed in each build, not entire applications. This incremental approach delivers security feedback in minutes without impacting development velocity. Many teams find builds actually get faster because they catch issues early instead of dealing with emergency fixes later.
How does StackHawk handle modern authentication and API complexity?
StackHawk is built specifically for today’s API-driven applications, with native support for REST, GraphQL, SOAP, and gRPC endpoints. We understand modern authentication patterns, JWT tokens, OAuth flows, and the complex authorization logic in microservices architectures.
What about false positives? Will this create noise for our developers?
Runtime testing dramatically reduces false positives because we test against actual running applications, not code patterns. StackHawk focuses on genuinely exploitable vulnerabilities with clear remediation guidance, so developers get actionable findings they can fix immediately.
Can StackHawk scale with our development team growth?
Yes. Because StackHawk runs automated tests within your existing CI/CD infrastructure, security testing scales automatically as you add developers and applications. There’s no need to hire additional security staff or coordinate manual testing processes.
Can you write custom scripts?

Yes, with StackHawk you can create custom test scripts to cover specific scenarios for your application.

Does StackHawk only scan APIs?

We focus on APIs because they are the biggest, fastest-growing attack surface for modern apps, and that is where we provide the best value, but you can scan SPAs and classic web apps with StackHawk as well.

Can you schedule scans?

You can schedule tests with StackHawk using any scheduling tool your team already uses, such as cron jobs, CI/CD pipeline schedules, or enterprise schedulers.

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See how StackHawk enables security at the pace of AI development.

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