Pentest Reports Developers Can Act On

Spend less time translating a finding into a fix

A severity label alone does not tell a developer where to start. When the affected flow, preconditions, and supporting evidence are missing, remediation turns into a chain of follow-up questions.

The PentestAI reporting approach keeps the observation, impact, and remediation context together, giving security and engineering a shared basis for deciding what to do next.

Make AI findings easier to challenge and review

Put request and response evidence close to the claim it supports. Explain what was observed, what is inferred, and which conditions affect the result. A reviewer should be able to follow the reasoning behind a finding.

Severity depends on exposure, prerequisites, and business impact. Your team retains the professional judgment needed to decide what matters most.

See the evidence before choosing a paid plan

The early access first-scan offer includes one complete high-severity finding for free, if the scan identifies one. The aim is to let you evaluate the observation, evidence, impact, and remediation guidance before committing to further paid testing.

Keep the fix connected to the original issue

A remediation review should link back to the original finding and show the evidence behind the new conclusion. Keeping both records together makes it easier to understand why an issue was closed or returned for investigation.

Explore the report before you commit

Open the interactive Overview, Evidence, and Retest tabs to review an original PentestAI example with fictional data. The sample lets you assess the evidence structure without providing target access.

The public report sample uses fictional evidence. Your company workspace shows findings from its own assessments according to your role. The free-scan offer is planned and not open yet.