A CVSS-weighted risk score
The overall risk gauge is computed across every validated finding, not asserted, with the two criticals and three highs that produced it visible on the same screen.
A scanner tells you a port is openThis shows you the data it pulled through it
An autonomous offensive engine that coordinates parallel attack agents across eleven categories, validates every finding independently before reporting it, and hands you a reproducible proof of concept for each one.
Try it
Interactive demo with a completed engagement, no signup, no cloud account
How It Works
Recon, attack, validate, prove.
01
Recon
A coordinator enumerates the target and fingerprints the stack, then plans attack coverage across the eleven categories rather than firing a fixed template.
02
Attack
Executors are spawned in bounded batches, injection, client-side, server-side, authentication, API, app logic, infrastructure, cloud and AI threat testing, with the coordinator reasoning between them.
03
Validate
Adversarial skeptics run at fixed checkpoints, and a blind validator independently confirms every finding through a five-check process before it reaches the report.
04
Prove
Each finding ships with the payload, a one-line curl, the full HTTP request and response, and numbered reproduction steps, so it can be verified, not just believed.
What You Can Do
Everything the engine does.
Validated, not merely detected
Every finding survives a blind five-check validation before it is counted, and the false-positive number is shown, because a report that inflates its findings is the one that wastes the client's week.
The kill chain, stage by stage
Thirteen pipeline stages from reconnaissance through cloud metadata to the validator, each annotated with what it found, so coverage is a narrative rather than a number.
Every finding standards-mapped
CVSS, CWE, OWASP Top 10 and a MITRE ATT&CK technique on each finding, filterable by severity and by fix priority, expanding to impact and remediation.
Reproducible proof, per finding
The exact payload, a curl to reproduce it, the full HTTP exchange and numbered steps, each copyable. The SQL injection is confirmed because the response returned the database version, not because a banner matched.
Fifty-plus attack types, eleven categories
Injection, client-side, server-side, authentication, API, application logic, cloud and containers, infrastructure, system, social engineering and AI threat testing, including OWASP LLM Top 10 coverage.
AI threat testing built in
Prompt injection and jailbreak attempts against your own AI features are part of the standard engagement, reported alongside the traditional web and cloud findings.
A remediation roadmap, prioritised
Findings grouped Immediate, Short-term and Medium-term by how exploitable they are today, each with its specific fix, so the first thing touched removes the most risk.
What was tested, not just what was found
A coverage matrix shows tests-run, findings and hit rate per category, so a clean category reads as tested-and-clear rather than as a gap in the engagement.
Business Outcomes
What it changes.
Proven
Every finding arrives with a working proof of concept, so the argument is not whether it is real but how fast it is fixed.
Trusted
Independent validation and a visible false-positive count mean the report can be acted on without a second team re-testing it first.
Continuous
An engagement is a run, not a quarter-long project, so the storefront can be tested after every significant change rather than once a year.
See what an attacker would actually reach.
Authorise a target and the first engagement returns validated, reproducible findings.