Red Sift
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With Red Sift OnDMARC, you can stop exact domain impersonation in the inbox by getting to DMARC enforcement (p=reject) quickly and effectively. You will also boost deliverability and be eligible for Brand Indicators for Message Identification (BIMI).
With Red Sift Brand Trust, you can discover and monitor fraudulent domains that are imitating your legitimate brand. Our AI-driven brand impersonation technology helps to protect your reputation by always staying a step ahead of the attackers.
With Red Sift ASM (Attack Surface Management), you can continuously discover, inventory and manage your business’s critical external-facing and cloud assets.
Red Sift Certificates is an automated certificate discovery and monitoring application. It focuses on providing immediate and continuous visibility of an organization's certificate estate, expired certificates, upcoming expirations, misconfigurations and misissuances to avoid PKI-related downtime and risk.
Red Sift Reviews
Robert T.
Enterprise (> 1000 emp.)Easy-to-Navigate Portal with Helpful OnDMARC Engineer Support
Emeric K.
Cybersecurity engineerMid-Market (51-1000 emp.)Red Sift OnDMARC: A Must-Have Solution for Email Domain Security
J Y.
ITMid-Market (51-1000 emp.)Streamlined Email Security with Top-Notch Updates
About
What is Red Sift?
Red Sift enables organizations to anticipate, respond to, and recover from cyber attacks while continuing to operate effectively. The award-winning Red Sift application suite is the only integrated solution that combines four interoperable applications, internet-scale cybersecurity intelligence, and innovative generative AI that puts organizations on a robust path to cyber resilience. Red Sift is a global organization with offices in North America, Australia, Spain, and the UK. It boasts a global client base across all industries, including Domino’s, ZoomInfo, Athletic Greens, Pipedrive, and top global law firms. Red Sift is also a trusted partner of Entrust, Microsoft, Cisco and Validity, among others. Learn more at redsift.com.