Argus Pentest logs in first. A scripted sign-in through the same credential store the QA engine uses hands the scanner real session cookies and a bearer token, and the endpoints discovered on the way seed its API spec — so the scan runs across the authenticated surface, where the findings that matter actually are.
An unauthenticated scan sees the marketing shell and the sign-in form. The business logic, the roles and the interesting data all sit behind that form.
A manual penetration test happens on an annual cycle while the application ships every sprint, so most releases go out with no security check at all.
Raw scanner output arrives as a long list of maybes, and the work of separating the real from the theoretical falls on a team that does not have the hours.
Authenticated scanning means handing a third party working logins to an internal system — which a regulated organisation cannot do.
A scripted login yields session cookies and a bearer token from the encrypted credential store, so the scanner works the application as a real signed-in user.
Endpoints discovered during login and crawling are assembled into a synthesized API spec, so the scan reaches routes no unauthenticated crawl would ever see.
Scans run against an explicit allow-list. A target has to be added deliberately before anything can be pointed at it.
The engine underneath is Deep Eye, driven only through its CLI contract — so it can be upgraded or swapped without touching the platform around it.
The model generates payloads and triages findings — text in, text out, never vision — and results arrive by severity with HTML and JSON reports.
Self-hosted alongside the other two engines: the credentials, the scan traffic and the reports all stay on your own infrastructure.
Reach the authenticated surface on every release instead of once a year, and spend the time on real findings rather than on getting a scanner logged in.
Evidence that the application was security-tested before it shipped, produced without sending credentials to a third party.
Reuse the credentials and target configuration already set up for regression testing — one platform, one credential store.
Run it inside your own perimeter, with the scanner engine treated as a replaceable dependency.
Authenticated scanning is the differentiator. Anyone can scan a public page; reaching the roles, forms and APIs behind a sign-in is where the findings live.
The credential store, model router and cost ledger are the same ones the regression engine uses — set up once, used by all three engines.
Working logins to an internal system never leave your infrastructure, which is the only way authenticated scanning is possible in a regulated industry.
It is shipped and running, but it has not yet been measured against unauthenticated scanning on the same targets, and per-scan cost accounting is still missing. We would rather say so than imply a number we have not taken.
In Greek myth, Argus Panoptes was the giant with a hundred eyes who never slept — the all-seeing watchman. The pentest engine is the half of that watch that looks for the way in: not whether the application works, but whether someone who should not be inside can get there.
Argus Pentest only scans what you have explicitly approved: a target must be added to an allow-list before it can be pointed at, and the credentials it authenticates with are yours, held in your own encrypted store. A scanner that cannot log in reports an environment failure rather than a security finding — the same honest-failure rule the QA engine applies, because a false alarm costs a security team more than a missed scan.
The QA, AI and pentest engines run on the same runtime and share a browser layer, a model router, an encrypted credential store and a single cost ledger — so models, credentials and deployment are configured once for all three, and whatever any of them finds lands in the same evidence trail.
Drives your business workflows through the real interface and reports what broke, with a screenshot and a stated reason behind every step.
Runs thousands of synthetic users against your assistant and scores every conversation with an Azerbaijani-native judge.
Scans your approved targets as a logged-in user, so the check reaches past the login wall, and reports findings by severity.
Allmaz is the AI product studio of Smart Solutions, which built and operates Azerbaijan's unified public procurement portal — established by presidential decree and delivered as one of the country's first public-private partnerships in digital government.
Request a demo to see an authenticated scan reach the surface behind your own login.