Automated pentesting SaaS
Pentesting on autopilot, plus a real engagement when it matters.
Two products in one platform: continuous, production-safe scans for daily coverage, and on-demand AI pentesting for proof-of-exploit findings.
What's in the box
From continuous coverage to aggressive AI pentests.
Continuous
Always-on production-safe scans
Daily or weekly cadence across TLS, headers, CORS, cookies, DNS, email auth, network exposure. No payloads, no surprises, safe to run in prod.
AI pentesting
Deeper testing on demand
When you need it, our AI actively attacks your app, chains requests, and confirms genuinely exploitable vulnerabilities with reproducible proof-of-exploit.
API-aware
Coverage for APIs too
Not just the front-end. AI pentesting probes API surfaces for broken access control, IDOR, SSRF, and business-logic abuse.
Triage
Severity-prioritized findings
Critical and high at the top, score-impact-weighted. Auditor-ready PDFs and CSV exports out of the box.
Stack-aware
Framework-specific remediation
Remediation written for Next.js, Django, Laravel, Express, Rails. Copy-paste-ready, not OWASP boilerplate.
Safe by design
Rate-limited and non-destructive
Both continuous and AI pentesting are designed to confirm exploitability without altering data or affecting availability.
When to use each
Pair the two for full coverage.
- ✓Continuous monitoring catches misconfiguration drift between releases
- ✓AI pentesting validates exploitability before audits, launches, or board reviews
- ✓Together they replace the gap between an annual pentest and a real security team
- ✓Reports from both feed the same audit-ready evidence pack
- ✓Findings flow into GitHub PRs for the engineering team to triage
FAQ
Automated pentesting, answered.
What's the difference between continuous monitoring and AI pentesting?
Continuous monitoring is production-safe and passive, it observes what your live app exposes (TLS, headers, DNS, network surface) and flags misconfiguration drift in real time. AI pentesting is active testing: the AI sends crafted requests, chains them, and confirms exploitable vulnerabilities like SQL injection, XSS, broken access control, and IDOR with reproducible proof. Most teams pair the two: monitoring for ongoing hygiene, pentesting before audits and launches.
Is automated pentesting accurate enough to replace human pentesters?
For the large majority of web app and API testing, yes. Barrion's AI pentesting goes beyond pattern-based scanning: it chains multi-step attacks, probes business-logic abuse, and confirms exploitability with reproducible proof, with results reviewed by our security team. Where a human still adds value is deep, domain-specific logic and creative one-off targets, and the report doubles as a head start for any human engagement you commission.
How does AI pentesting confirm exploitability without breaking my app?
AI pentests are rate-limited and non-destructive. They confirm exploitability by observing the response signature (e.g. a successful blind SQLi returns observable timing differences; broken access control returns a 200 where it should return 403) rather than by writing data or destroying state. Every confirmed finding includes the exact request, response, and exploit chain for verification.
Can I run continuous pentesting against staging instead of production?
Yes, and many teams do. Continuous monitoring on Essential or Business supports any domain you control, staging, preview environments, or pre-launch surfaces all work. AI pentesting can also target staging, which is often the safer choice for a first deeper run.
Will automated pentesting findings be accepted as compliance evidence?
For SOC 2, ISO 27001, and PCI DSS, automated scanning with documented cadence is widely accepted as ongoing-monitoring evidence (control families like SOC 2 CC7 and PCI DSS Requirement 11). For pentest-specific requirements like PCI DSS Requirement 11.3 (penetration testing), Barrion's AI pentest delivers an audit-ready report with documented scope, methodology, and proof-of-exploit, reviewed by our security team before release. Auditors decide acceptance, and the report gives them what they need to make that call.
See it run against your app.
60 seconds to your first report. Sign up to set up continuous monitoring, or run an AI pentest, free to start.