Stop Fraud Way Before It Starts

Standard fraud signals (device fingerprint, behavioral velocity, IP reputation) generate high false positive rates because they flag anomalous behavior regardless of whether the user’s identity is actually compromised. SpyCloud adds a confirmed exposure layer: when SpyCloud’s recaptured data shows that a specific user’s credentials or session cookies are circulating in criminal markets, that is a confirmed risk signal, not a behavioral anomaly that might have a legitimate explanation. Fraud teams using SpyCloud report that confirmed exposure signals dramatically reduce false positives because the challenge or block is applied only to users with known compromise evidence, not to anyone exhibiting unusual behavior.

SpyCloud provides meaningful signals at three touchpoints. At account creation, the Consumer IDLink API detects synthetic identity patterns by correlating multiple submitted identity artifacts against SpyCloud’s recaptured dataset simultaneously. At login, the User Exposure API checks whether the authenticating user has a confirmed credential or session exposure, triggering step-up authentication for high-risk users only. At transaction review, IDLink correlation can escalate risk scoring for accounts whose identity profile shows broader criminal exposure patterns. Most production fraud deployments run the User Exposure API inline at login as the primary signal and use IDLink escalation for high-value transactions.

MFA verifies identity at login but generates a session cookie after authentication succeeds. Infostealer malware and AitM phishing both capture these post-authentication session cookies, giving attackers a valid authenticated session that bypasses all login-time fraud controls. SpyCloud’s Session Identity Protection API provides a continuously updated feed of compromised session cookies tied to application domains. When a session cookie matches a known-compromised artifact, the system terminates the session without impacting legitimate users. A global financial services company used this capability to respond quickly, invalidate cookies, and protect millions of customer dollars.

SpyCloud is an enrichment signal, not a fraud decisioning platform. It does not replace existing fraud engines. The standard integration pattern is adding SpyCloud’s exposure signals as an additional risk feature in the fraud decisioning engine: a user with a confirmed credential exposure receives an elevated risk score that can trigger step-up authentication, additional friction, manual review, or transaction block based on the organization’s risk policy. SpyCloud’s REST API with JSON output integrates into any decisioning platform as a feature input. For fraud teams at organizations running Sift, Sardine, or custom ML models, SpyCloud API output is consumed as a feature alongside behavioral, device, and network signals.

A global airline achieved a 90% reduction in account takeover after deploying SpyCloud Consumer Threat Protection. A global hotel search site identified 6,000 infected customers whose credentials and session cookies had been exfiltrated. A Fortune 100 technology company achieved a 20% performance improvement in their fraud detection pipeline after adding SpyCloud’s exposure signals. A global financial services company reported protecting millions of customer dollars from a single session hijacking campaign by using SpyCloud to invalidate compromised cookies in near-real time.