Now scanning 12,000+ endpoints

You shipped it fast.
Now make sure it's safe.

AI-driven penetration testing for startups, indie hackers, and teams that move faster than their security budget. Get a full vulnerability report in minutes - not weeks.

~20 minaverage scan timeOWASPTop 10 coverage0setup needed
penetrify scan - myapp.vercel.app
$ penetrify scan https://myapp.vercel.app
// Initializing AI-driven reconnaissance...
◉ Mapping attack surface... 47 endpoints found
◉ Testing authentication flows...
◉ Checking API security, headers, configs...
 
▸ CRITICAL Broken auth - email verification bypass via direct API call
▸ CRITICAL IDOR on /api/users/:id - any authenticated user can read others
▸ MEDIUM Missing rate limiting on /api/login (brute-force possible)
▸ LOW Security headers missing: X-Frame-Options, CSP
 
✓ Scan complete. 4 findings. Full report → app.penetrify.cloud/reports/a3f8c

Why builders need this

Shipping fast is great.
Shipping insecure isn't.

Most security tools are built for enterprises with 6-figure budgets. Penetrify is built for everyone else.

🔓

Broken auth flows

Vibe-coded apps ship fast - and often skip email verification, session management, or password reset flows. We catch what your framework didn't scaffold.

🪪

Exposed user data

IDOR vulnerabilities, leaky APIs, misconfigured database rules. One wrong permission and your users' data is anyone's to read. We find these before someone else does.

No-code blind spots

Bubble, Supabase, Firebase - great tools, but their defaults aren't always secure. Penetrify checks the actual attack surface, not just the config panel.

How it works

Three steps. Ten minutes.
No security team required.

01

Enter your URL

Paste your app's URL into Penetrify. No agents to install, no code to add, no infrastructure changes. Works with any stack - React, Next.js, Django, Rails, no-code, anything public.

https://yourapp.com
02

AI scans everything

Our engine maps your attack surface autonomously - endpoints, auth flows, APIs, headers, configs. It thinks like a pentester: chaining findings, testing logic flaws, not just running CVE lists.

~47 checks per endpoint
03

Get actionable results

A clear report with severity ratings, reproduction steps, and fix guidance you can actually follow. No 200-page PDFs full of false positives. Just what matters and how to fix it.

CRITICAL → MEDIUM → LOW

The Case for AI

Why Development Teams Are Switching to Continuous AI Penetration Testing

The Annual Pen Test Is No Longer Enough

Modern software teams ship code weekly or daily. A single annual security assessment leaves up to 364 days of unscanned exposure between reviews. Every sprint introduces new API endpoints, new authentication flows, new dependencies. By the time a manual tester examines your application, the code they're testing may look nothing like what's running in production.

Every code push is a potential introduction of new vulnerabilities. The traditional model — test once, then wait — was designed for software that shipped quarterly. It is ill-suited to products that deploy dozens of times a week.

The cost of point-in-time testing:

  • New features deployed after the assessment remain unscanned until the next engagement
  • Regression vulnerabilities reintroduced by code changes go undetected for months
  • A single manual engagement costs $10,000–$50,000 and covers one point in time
  • Procurement, scoping, and scheduling add weeks before testing even begins

What Changes When Security Tests Run on Every Deploy

When security tests run on every CI/CD build, the security posture in your dashboard reflects the code running today — not the code from last quarter. Vulnerabilities are caught when they're cheapest to fix: in a pull request, before the feature ever reaches production.

Finding a vulnerability in a pull request takes an hour to fix. Finding the same vulnerability three months after deployment — after it's been in production, after customers have interacted with it — takes days and creates compliance exposure. The economics are not comparable.

What continuous testing delivers:

  • Security vulnerabilities caught in the same sprint they're introduced
  • A clear, auditable record of security posture at every deployment
  • CI/CD gates that block deployments containing critical or high-severity findings
  • Security teams freed from manual triage to focus on architecture and threat modeling

Breadth No Human Team Can Match

A human penetration tester works within a time box. Given five days to assess a 200-endpoint API, they make judgment calls about where to invest effort — and some endpoints get skipped. Penetrify tests every discovered endpoint, every parameter, and every authentication flow against the full catalog of known vulnerability classes, every time. No endpoint is de-prioritized because time ran short.

Every scan covers:

  • All OWASP Top 10 vulnerability categories — every endpoint, every time
  • Authentication, session management, and privilege escalation testing
  • IDOR and broken access control across all user roles and data objects
  • REST API and GraphQL-specific vulnerabilities including mass assignment and introspection abuse
  • SQL injection, XSS, CSRF, XXE, and injection variants across all input surfaces
  • Secret and API key exposure in responses, headers, and error messages

Under the hood

Not a toy scanner.
Real pentesting methodology.

Penetrify runs the same checks a senior security engineer would - automated, repeatable, and without the $20K invoice.

🔍What we test

Our engine doesn't just run a CVE scanner. It performs active reconnaissance, maps your full attack surface, and tests application-layer logic - authentication flows, authorization boundaries, API access controls, and business logic flaws.

OWASP Top 10Auth & session mgmtIDOR detectionAPI fuzzingHeader analysisSecret exposureInjection testingCORS & CSP

🧠How we test

The AI engine chains findings together - just like a real attacker would. A leaked endpoint becomes a reconnaissance target. An unauthenticated route becomes an IDOR test. Context-aware scanning means fewer false positives and more findings that actually matter.

Autonomous reconChained exploitationContext-aware AILow false-positive rateSeverity scoring

📋What you get

Not a 200-page PDF full of noise. Every finding includes severity, reproduction steps, and concrete fix guidance written for developers - not compliance officers.

CRITBroken auth - email verification bypassFix guide →
MEDNo rate limiting on /api/loginFix guide →
LOWMissing CSP and X-Frame-OptionsFix guide →

🛡️Safe by design

Penetrify never modifies your data, never writes to your database, and never performs destructive actions. All testing is read-only and non-invasive. Your users won't notice a thing. Your app stays up.

Read-only scanningNo data modificationNon-invasiveZero downtime impactYour data stays yours
47+Checks per endpoint
OWASPTop 10 full coverage
<5%False positive rate
0Destructive actions

Coverage

What Penetrify tests

Penetrify runs the same checks a senior security engineer would — not just CVE lists, but active reconnaissance and chained attack logic across every layer of your application. Here is what the AI agent covers on every scan.

🔐

Authentication & Session Management

The agent tests all critical authentication flows — not just whether a login form exists, but whether it can be bypassed. It attempts email verification bypasses, token replay attacks, broken password reset flows, session fixation, and missing rate limiting on credential endpoints.

Common findings

  • Email verification not enforced on protected endpoints
  • Session tokens not rotated on privilege escalation
  • No account lockout after repeated failed logins — brute-force possible
  • JWT algorithm confusion attacks (RS256 → HS256 downgrade)
  • Password reset tokens without expiry or single-use enforcement
🔑

Authorization & Access Control (IDOR)

Insecure Direct Object References (IDOR) are the most frequently exploited vulnerability class in modern web applications. Penetrify systematically replaces user-controlled identifiers across all endpoints and checks whether ownership is enforced consistently on every route.

Common findings

  • /api/users/:id accessible by any authenticated user, not just the record owner
  • Export or download endpoints accepting user IDs without ownership checks
  • Admin-only routes reachable by regular user accounts
  • Horizontal privilege escalation through guessable or sequential resource IDs
  • Database row-level security (RLS) policies missing or misconfigured
💉

Injection & Input Validation

The engine tests for SQL injection, NoSQL injection, command injection, XPath injection, and server-side template injection across all input vectors — form fields, query parameters, HTTP headers, JSON bodies, and file uploads.

Common findings

  • SQL injection in search, filter, and pagination parameters
  • Reflected XSS through user input rendered without HTML encoding
  • Stored XSS in user-supplied content fields (names, bios, comments)
  • Server-Side Template Injection (SSTI) in templating engines (Jinja2, Twig, Handlebars)
  • XML External Entity (XXE) injection via file upload or XML API endpoints
🔌

API Security

Modern applications are API-first. Penetrify automatically maps REST and GraphQL APIs, testing for broken object-level authorization, missing authentication on internal routes, verbose error disclosure, unsafe CORS policies, and GraphQL introspection left open in production.

Common findings

  • Unauthenticated API routes returning sensitive user data
  • Wildcard CORS (Access-Control-Allow-Origin: *) enabling cross-origin authenticated reads
  • API responses including hidden or shadow fields not shown in the UI
  • GraphQL introspection enabled in production, exposing the full schema to anonymous requests
  • Mass assignment vulnerabilities accepting undocumented fields in API request bodies
⚙️

Configuration & Secret Exposure

Beyond application logic, Penetrify checks HTTP security headers, debug mode, dependency version disclosure, and whether API keys or credentials are exposed in JavaScript bundles, environment variables, or API error responses.

Common findings

  • Missing security headers: Content-Security-Policy, X-Frame-Options, HSTS, Referrer-Policy
  • Debug endpoints or verbose stack traces exposing internal file paths and framework versions
  • API keys and secrets embedded in client-side JavaScript bundles served to the browser
  • Sensitive data returned in API error responses (stack traces, DB connection strings)
  • Open redirect vulnerabilities on login or callback endpoints usable for phishing

How the AI engine approaches each scan

Unlike traditional scanners that fire fixed payloads at every field, Penetrify's AI agent first maps the full attack surface — discovering endpoints, understanding data flows, and identifying authentication boundaries. It then chains findings together: a leaked endpoint becomes a reconnaissance target, an unauthenticated route becomes an authorization test, a verbose error reveals an injection surface. This context-aware approach is why Penetrify maintains a false positive rate below 5%, while catching vulnerability chains that single-check scanners miss entirely.

Real scans, real findings

What Penetrify catches
in the wild

These are representative findings from scans on early-stage SaaS products - the exact kind of vulnerabilities that get exploited before you even know they exist.

Case Study #1

The Weekend MVP That Leaked Every User's Data

SaaS Productivity Tool - Next.js + Supabase · Shipped in 48 hours
2Critical
3Medium
8 minScan time

The situation

A solo founder built a task management SaaS during a weekend hackathon and launched on Product Hunt within days. The app used Next.js with Supabase for auth and database. Everything looked polished - clean UI, working login, Stripe integration. Within the first week, 200+ users signed up.

What Penetrify found

  • CRITICALSupabase Row Level Security (RLS) policies not enabled on the profiles table - any authenticated user could query all user records via the REST API
  • CRITICALEmail verification not enforced - accounts could be created with arbitrary emails and immediately access protected endpoints
  • MEDIUMAPI route /api/export accepted user ID as query parameter with no ownership check (IDOR)
  • MEDIUMNo rate limiting on login endpoint - brute-force attacks possible at ~500 req/s
  • MEDIUMJWT tokens stored in localStorage with no expiry rotation

The outcome

The founder fixed the RLS policies and email verification within 2 hours using Supabase's dashboard - no code rewrite needed. The IDOR was a one-line middleware fix. Total remediation time: half a day. Without the scan, these issues could have sat exposed for months. The Supabase RLS gap alone would have been a reportable data breach under GDPR.
Case Study #2

The No-Code Marketplace With Admin-Level API Keys in the Frontend

Two-sided Marketplace - Bubble.io + Stripe Connect · 1,500 users
1Critical
4Medium
12 minScan time

The situation

A two-person team built a freelance marketplace using Bubble.io, handling payments through Stripe Connect. The platform had processed $40K+ in transactions and was growing through word of mouth. Neither founder had a security background - they assumed Bubble's platform handled security for them.

What Penetrify found

  • CRITICALStripe Secret API key exposed in client-side JavaScript bundle - full read/write access to payment data, refunds, and customer records
  • MEDIUMBubble privacy rules misconfigured - seller bank account details visible to any logged-in user via API calls
  • MEDIUMPassword reset flow accepted any email without verification, enabling account enumeration
  • MEDIUMNo Content Security Policy - reflected XSS possible through search parameter injection
  • LOWCORS policy set to wildcard (*) allowing any origin to make authenticated requests

The outcome

The exposed Stripe key was the most urgent issue - with it, an attacker could have issued refunds, accessed PII, or redirected payouts. The founders rotated the key immediately. The Stripe key had been exposed for 4 months without anyone noticing. Total cost of not finding this: potentially the entire business.
Case Study #3

The AI Wrapper Startup That Forgot About Its Own API

AI Writing Tool - Python/FastAPI + React · YC Application Stage
1Critical
2Medium
7 minScan time

The situation

A technical founder built an AI writing assistant using FastAPI on the backend and React on the frontend. The product proxied calls to OpenAI's API, adding custom prompts and user history. The app was gaining traction on Twitter/X and the founder was preparing a YC application. Roughly 800 users on a freemium model.

What Penetrify found

  • CRITICALOpenAI API key passed to frontend in response headers - any user could extract it and use the founder's API credits directly (est. $2K+/month burn)
  • MEDIUMUser prompt history endpoint /api/history/:userId had no auth middleware - all users' conversation logs accessible by changing the ID
  • MEDIUMDebug mode still enabled in production (FastAPI(debug=True)) - full stack traces with internal paths and dependency versions exposed on errors
  • LOWNo HTTPS redirect - HTTP version of the app served without redirect, allowing session hijacking on public networks

The outcome

The founder was unknowingly burning money from API key abuse - unexplained spikes in OpenAI billing turned out to be external usage via the leaked key. The prompt history IDOR was especially sensitive. All fixes were deployed within 3 hours - most were single-line changes. The founder now runs a Penetrify scan before every major release.

What users say

Trusted by founders, CTOs, and security teams

Caught a Supabase RLS misconfiguration in 9 minutes. Without this scan, every user's profile was readable by any authenticated user. Would have been a GDPR breach.
A
Alex M. · Solo Founder
Productivity SaaS · 300 users
Found our Stripe secret key exposed in the frontend JavaScript bundle. It had been there for 4 months. Key rotated within the hour. Without Penetrify, that's the entire business gone.
S
Sarah K. · Co-founder
Freelance Marketplace · 1,200 users
We run it before every deploy. In 2 months it caught 3 regressions in our auth flow before they shipped. At $600/month it's the cheapest engineer on the team.
D
David R. · CTO
AI writing tool · YC W26

Who's behind this

Built by a CTO,
not a marketing team.

Viktor Bulanek

Viktor Bulanek

Founder & CTO

20+ years building and securing production systems at scale - from fintech platforms processing millions in transactions to IoT infrastructure managing real-time energy grids. I built Penetrify because startups deserve the same security testing that enterprises pay $50k+ for.

MSc IT Security - Masaryk University4x Ex-CTOFintech · IoT · SaaS

Pricing

Simple, transparent pricing.

No hidden fees. No sales calls. Pick the plan that fits your security needs.

Starter
$50 / month

Perfect for side projects and early MVPs.

  • 1 penetration test per month
  • Automatic and semi-automatic modes
  • Standard vulnerability scanning
  • PDF reports
  • Email support
  • 30-day result history
Get started
Professional
$600 / month

For growing products with real users.

  • 20 penetration tests per month
  • All Starter features
  • Advanced vulnerability detection
  • Custom report branding
  • API access
  • Priority support (24h response)
  • 90-day result history
  • Team collaboration (up to 5 users)
Start Pro trial →
Enterprise
$2,500 / month

For startups approaching compliance.

  • 100 penetration tests per month
  • All Professional features
  • Dedicated security consultant
  • Custom integrations
  • SLA guarantee (99.9% uptime)
  • Phone support
  • Unlimited result history
  • Unlimited team members
  • White-label reports
  • Compliance reporting (SOC 2, ISO 27001)
Contact us →

Quick Answers

Everything you need to know

How much does AI penetration testing cost?

Penetrify starts at $50/month for the Starter plan (1 scan/month), $600/month for Professional (20 scans/month), and $2,500/month for Enterprise (100 scans/month). That is 95–99% cheaper than traditional manual penetration tests, which typically cost $15,000–$50,000 per engagement.

How long does a penetration test take?

Penetrify completes a quick scan in 15–30 minutes, a standard scan in 1–2 hours, and a deep scan in several hours for complex applications. Traditional penetration tests take 1–4 weeks to schedule, execute, and receive results.

What vulnerabilities does Penetrify detect?

Penetrify detects all OWASP Top 10 vulnerability categories: SQL injection, Cross-Site Scripting (XSS), CSRF, Insecure Direct Object References (IDOR), broken authentication, security misconfigurations, sensitive data exposure, and more. It also tests API security, session management, business logic flaws, and common misconfigurations in Supabase, Firebase, and Bubble.

Is Penetrify safe to run on a live production application?

Yes. Penetrify is non-destructive by design: it never modifies data, never writes to your database, and performs zero destructive actions. All testing is read-only and non-invasive. Your users will not notice anything — no downtime, no data changes, no side effects.

What is Penetrify's false positive rate?

Penetrify maintains a false positive rate below 5%. The AI engine validates each finding contextually before reporting it, so developers see only real, exploitable issues — not scanner noise. Traditional automated scanners typically report 40–60% false positives.

Does Penetrify require installation or code changes?

No installation is required. Penetrify is 100% cloud-based and agent-free. You provide your application's URL and the AI handles everything else. No code changes, no plugins, no agents to deploy — it works with any web stack including React, Next.js, Django, Rails, and no-code platforms like Bubble, Webflow, and Supabase.

FAQ

Got questions?

Quick answers to the most common questions about Penetrify.

Technical Details

Product FAQ: How Penetrify Works

What types of applications and APIs does Penetrify test?

Penetrify tests web applications, REST APIs, and GraphQL APIs. It supports both unauthenticated (black-box) and authenticated (grey-box) testing. You can target any publicly accessible or VPN-reachable URL — no SDK, agent, or code change required. The AI agent discovers endpoints automatically through crawling and API schema analysis.

How does Penetrify handle authenticated testing?

Penetrify accepts credentials, session tokens, or API keys before a scan begins. The AI agent logs in, maintains session state across the entire test, and verifies access controls across multiple user roles. Authenticated testing is essential for finding IDOR, broken access control, and privilege escalation vulnerabilities that only appear when logged in.

How long does a Penetrify scan take?

Most scans complete in under 30 minutes. A quick scan on a small API returns initial findings in minutes; a comprehensive scan of a complex web application with hundreds of endpoints typically completes within 2–3 hours. Findings are delivered progressively as the AI agent discovers them — you do not wait for the full scan to see results.

Can I run Penetrify against a staging environment before production?

Yes — and this is the recommended workflow. Point Penetrify at your staging environment as part of your CI/CD pipeline, and promote to production only after the scan returns no critical or high findings. Penetrify also supports production scanning with non-destructive, read-only operations that leave no lasting changes in your system.

What does a Penetrify vulnerability report include?

Each report includes a severity-ranked list of all findings (CVSS score, OWASP category, affected endpoint), full reproduction steps with proof-of-concept evidence, and developer-focused remediation guidance. Reports export as PDF or structured JSON and are suitable for sharing with security auditors, compliance teams, and engineering leads.

Does Penetrify integrate with CI/CD pipelines?

Yes. Penetrify provides a REST API and pre-built integrations for GitHub Actions, GitLab CI, and similar pipelines. You can configure pass/fail thresholds — for example, fail the pipeline on any critical finding — and automate scans to trigger on every pull request, deployment, or nightly schedule.

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Make sure you deserve it.

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