Let real sign-ins through. Stop the replayed ones.
Every large password breach becomes a script somewhere else, usernames and passwords replayed against thousands of other logins, betting on reuse. MTCaptcha reads the pattern of the attempt, not just the credentials, so a real sign-in and a password manager pass invisibly while a scripted one gets stopped.
This is the real widget, live, not an illustration. Try it above the way a visitor to app.yoursite.com would.
What credential stuffing actually looks like from the login form
Credential stuffing isn't guessing, it's replay. An attacker takes a list of real username/password pairs leaked in an unrelated breach and fires them, automated, at a login form that has nothing to do with the original breach, betting that some fraction of users reused the same password. At scale, even a 0.1% success rate against a million-row breach list is a real number of compromised accounts.
It looks like ordinary login traffic on any single request, a username, a password, a submit. What gives it away is pattern: volume from a narrow set of networks, submissions faster than a person types, and a success rate on stolen pairs that doesn't match how real users behave. That pattern is exactly what a static CAPTCHA, checked once at page load, cannot see.
Why a successful takeover is worse than it looks
Fraud happens inside a trusted session
Once in, an attacker isn't breaking anything, they're acting as the account owner, which is exactly what makes the resulting fraud, data access, or purchases hard to unwind after the fact.
Support absorbs the cleanup cost
Every takeover becomes a support ticket, a password reset, and often a trust-and-safety review, cost that scales with attack volume, not with how many actually succeed.
It is rarely a single account
A credential-stuffing run tests thousands of pairs in one campaign; a login form that stops none of it is exposed to all of it, not to an isolated incident.
Reused sessions look identical to the real thing
Once a session token is issued, downstream systems have no way to know the session started with a stolen password rather than a real one, the login form is the only place this is stoppable.
How MTCaptcha defends the login form
The goal is to never slow down the person the password actually belongs to.
Adaptive risk engine
Reads submission velocity, network reputation, and behavioral signals in real time, and raises verification difficulty specifically where a credential-stuffing pattern is forming.
Invisible NoCAPTCHA by default
A real sign-in, including one completed through a password manager's autofill, passes without a visible challenge, friction is reserved for traffic the risk engine actually flags.
Enterprise dashboards
Gives a security team visibility into attempted-vs-blocked volume on the login endpoint specifically, rather than inferring it from downstream fraud reports.
GDPR-compliant, no invasive tracking
Distinguishes attack patterns from real traffic without fingerprinting or tracking the people signing in legitimately.
Deployed in the wild
State government (public benefits)
On: Citizen login for a benefits-enrollment portal
Protects: Sign-in from credential-replay attempts against citizen accounts
Fintech (fleet & toll payments, Brazil)
On: Business account login
Protects: Account access for automatic toll, fuel-card and freight payment
Real deployments, industry and mechanism only, no company names, by design.
Show us your login flow
Tell us what you're seeing at the login form, we'll show you what the risk engine would have caught.
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