Platform
Continuous, autonomous penetration testing that matches human creativity at machine speed — mapping your attack surface, exploiting real attack paths, and validating every finding. Audit-ready, all year round.
Definition
Attack Insights deploys intelligent agents that first map what can be attacked — in white-, grey- or black-box mode — then run targeted attacks across your applications and APIs the way a red team would, not a checklist scanner. Each potential issue is actively exploited and confirmed before it is reported, so you get a continuously current view of real, demonstrated risk instead of a once-a-year snapshot that ages the day it lands.
Why it matters
Your environment changes weekly, but traditional pen tests happen once or twice a year and take weeks to schedule and deliver. Continuous, AI-driven testing dramatically widens coverage between manual engagements. And it stays safe by default — when a finding could be escalated, it pauses for human review rather than chaining exploits on its own.
Coverage
Exploitable flaws across your public and internal web apps.
REST, GraphQL, gRPC and SOAP — authentication, authorisation and data exposure.
Broken access control and cross-user or cross-tenant data leakage.
Abuse of intended behaviour that scanners simply cannot reason about.
Injection, misconfiguration and the rest of the classic high-impact flaws.
Combinations of issues that lead to real, demonstrated impact.
Prompt injection and the OWASP Top 10 for LLMs — see AI Security.
Whether disclosed vulnerabilities are genuinely exploitable in your context.
How it works
Agents map your features, endpoints, APIs and attack surface in scope.
Parallel agents focus on specific attack vectors and try to break expected behaviour.
Each finding is confirmed against the live target; false positives are dropped.
Get audit-ready evidence and guidance, fix, then retest instantly.
Related
FAQ
It uses autonomous agents to simulate real attacks on your applications and APIs at machine speed — discovering, exploiting and validating vulnerabilities continuously, rather than waiting weeks for a manual engagement.
It complements it. Continuous AI testing provides year-round validation between engagements, while human testers remain valuable for highly contextual edge cases and non-web targets.
Yes. Scope and guardrails are enforced, and critical findings pause for human review rather than auto-escalating.
Findings appear as agents work, with audit-ready reports available in hours rather than weeks.
Yes — including prompt injection and the OWASP Top 10 for LLMs. See our dedicated AI Security page.
Every finding is confirmed by exploiting it against the live target; anything that cannot be validated is discarded and never reported.
Move from a once-a-year snapshot to continuous, validated proof of what’s exploitable — book a demo.
