We deliver the only proof-based application security platform that finds, validates, and prioritizes real vulnerabilities before attackers can exploit them.
Austin, TX
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Financial apps are built around context: identity, permissions, APIs, transactions + business logic.
Agentic pentesting can reason across those workflows, adapt its testing, pursue deeper attack paths + validate the results at runtime.
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Healthcare apps combine sensitive data, complex authorization + constantly changing APIs.
Agentic pentesting can explore those workflows adaptively, pursue deeper attack paths and validate exploitable findings with runtime evidence.
Our latest guide: okt.to/VyINWS
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More apps. More APIs. Faster releases.
All supported by the same lean security team.
Our new white paper examines the economics of AppSec tool sprawl – and how consolidation and runtime validation help teams focus resources on real risk.
Download: okt.to/5Z3fLF
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Agentic pentesting can run in production, but autonomy requires boundaries.
Enforce scope. Limit privileges + traffic. Use minimum-impact proof. Define stop conditions.
A practical guide to bounded autonomy: okt.to/xdXs0q
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How much pentesting work still requires a human?
Automate repeatable + verifiable work.
Use agents for adaptive investigation.
Keep humans where context + judgment change the answer.
A practical CISO framework for AI pentesting: okt.to/13jvEn
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Your attack surface changes continuously. Your view of risk should too.
Periodic scans create snapshots that start aging immediately.
Invicti CISO Matthew Sciberras on closing the exposure gap with continuous visibility, validation + verified remediation: okt.to/HP40xT
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The CISO question for agentic pentesting: how much more of the application portfolio can you test deeply, frequently and credibly?
Think coverage. Runtime validation. Clear controls. Fast retesting. Human judgment where it matters most.
Our expert guide: okt.to/79mq8g
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You can verify identity, device posture + network policy, and still serve a user a vulnerable application.
The DoW Zero Trust model gives Applications & Workloads its own pillar for good reason. Where AppSec provides the evidence:
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Severity is only one signal.
Reachability. Exploitability. KEV + EPSS. Business criticality. Ownership. Retest status.
Vulnerability enrichment turns raw findings into prioritized, actionable risk. Here's what to look for: okt.to/i76VY0
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API vulnerabilities often live between requests.
Identity → object access → state change → another endpoint.
Agentic pentesting can preserve that context and pursue attack paths that fixed test sequences may miss, then validate the result in runtime: okt.to/bQcNvG
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AI can make DAST smarter where teams feel the most friction.
Prioritize risk. Navigate complex apps. Find shadow APIs. Correlate findings.
All the while keeping vulnerability testing grounded in runtime evidence.
A practical look at AI-powered DAST: okt.to/W0YDCS
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CSP. HSTS. Permissions-Policy. COOP. COEP.
Which HTTP security headers still matter? Which should you retire?
Our updated reference guide: okt.to/o90x3E
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An application inventory is only useful if it drives action.
Discover → add context → test → prioritize → remediate → measure.
That continuous loop turns attack surface visibility into actual risk reduction – and greater confidence for your board.
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AI agent estates are growing faster than security coverage. That makes stale evidence a governance risk.
Inventory agents. Bound autonomy. Secure identities + dependencies. Test the apps and APIs they can reach. Revalidate when anything material changes.
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Pentesting ROI comes down to one question: How much of your application portfolio can you keep deeply tested?
Agentic pentesting adds adaptive depth between continuous DAST and human testing, without scaling expert effort and costs at the same rate: okt.to/ozGIy1
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AI agents shouldn’t be granted permanent trust at login.
Verify identity. Constrain permissions. Observe behavior. Limit data access.
Prepare for containment. Increase autonomy only when the evidence supports it.
Zero Trust for the agentic era: okt.to/KTx1ed
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Agentic AI can automate more of the AppSec loop:
Test → investigate → prioritize → act → verify → adapt
The opportunity is a security program that responds continuously as applications change, with decisions grounded in validated evidence: okt.to/86vZdi
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Agentic automation gives security testing the ability to adapt.
Reason about the app. Form hypotheses. Change tactics. Pursue attack paths. Validate findings with evidence.
That’s a giant leap beyond fixed, predefined testing workflows. Read more: okt.to/SxGqHB
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Offensive security is moving into CI/CD. Agentic workflows can decide what to test, where to focus, and what deserves action.
But the more autonomy you add, the more trustworthy the underlying evidence has to be.
A practical guide to agentic DevSecOps: okt.to/2UFV19
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Sunday reading for security leaders:
🌙 CISO’s Corner → what’s changing the risk calculus in 2026: okt.to/GAF0fY
🤖 NIST AI RMF → turning governance into evidence: okt.to/8PSB5p
📈 AppSec → becoming a business and buying issue: okt.to/xFsgr7
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