ScenarioB2B SaaS

Stopping automated account takeovers at the network edge

A multi-tenant SaaS platform layered IP intelligence into login flows to detect bots, credential stuffing, and risky networks.

Audience

Multi-tenant SaaS

B2B SaaS

Reference stack

Node.js • Next.js • PostgreSQL • Redis

Anonymized scenario. Composite write-up drawn from real production deployments. Customer name withheld and metrics described qualitatively \u2014 outcomes vary with traffic mix and rules. Ask for a tailored walkthrough.

Most credential-stuffing traffic challenged or blocked before password verification

Faster incident response with IP, ASN, and reputation context in the analyst dashboard

Rolled out per-tenant with no customer-visible downtime

A multi-tenant SaaS serving thousands of mid-market customers saw a wave of credential-stuffing attacks targeting shared admin accounts and weak passwords.

The security team wanted to stop automated traffic without degrading the experience for legitimate admins logging in from hotels, VPNs, or mobile networks.

They integrated Predax into the login pipeline as a pre-auth check. For each attempt, they evaluated the IP's risk score, proxy/VPN status, and ASN reputation. High-risk attempts were routed through additional verification steps, while known-good networks sailed through.

Because Predax exposes a simple HTTP API, the team implemented the integration in a few days and rolled it out gradually by tenant and region. Security operations gained a new set of signals in their SIEM, making it easier to investigate suspicious sessions and tune controls over time.

Results with Predax

  • Most credential-stuffing traffic was blocked or challenged before password verification, significantly reducing load on downstream systems.
  • Incident response sped up materially, as analysts could pivot on IP reputation, ASN, and historical behavior directly from their dashboards.
  • The rollout completed with no customer-visible downtime and no measurable increase in support tickets related to login friction.