intliq.ai monitors the dark web specifically for infostealer malware logs — a category of threat data that broad breach notification services routinely overlook. Where generic monitors flag email/password pairs from old data dumps, intliq.ai surfaces active session cookies, device fingerprints, and credential sets extracted by malware like RedLine, Raccoon, and Lumma. A stolen session cookie can bypass MFA and hand an attacker live account access, so detecting it early is the difference between containment and a full compromise. The platform is built for security teams, IT admins, and organizations that need to know when employee or customer credentials appear in fresh infostealer logs — not weeks later in a public breach database. The narrow focus on infostealer-specific data means less noise and more context than you get from general dark web monitoring tools.