fidelityworkplacebw[.]shop
“Log In to Fidelity NetBenefits”
fidelityworkplacebw.shop — Conteúdo indisponível. Tipo de golpe: Banking Phishing. Resumo das evidências: VirusTotal 16/93 (ADMINUSLabs, alphaMountain.ai, BitDefender, CRDF, CyRadar); PhishDestroy score 95/100.
A análise detalhada do PhishDestroy AI permanece em inglês para preservar o registro forense original.
This domain, fidelityworkplacebw.shop, is identified as a credential harvesting portal specifically designed to impersonate the legitimate Fidelity NetBenefits login interface. The threat type is classified as a fake login page targeting users of financial and retirement benefit services. As of the latest verification, the domain has been taken offline, though prior activity remains a concern for retrospective analysis and potential re-emergence. Analysis indicates the domain was flagged by 16 of 95 security vendors on VirusTotal, reflecting a moderate-to-high detection rate. Infrastructure analysis reveals the domain was registered on February 21, 2026, an anomalous future date suggesting potential manipulation or misconfiguration. It resolved to the IP address 43.162.112.41, hosted under AS132203 in a data center located in the US, despite the autonomous system being associated with an overseas provider. The SSL certificate was graded E8, indicating poor cryptographic practices or potential misuse. The domain appears on two security blocklists and is explicitly blocked by at least two threat intelligence feeds. Current status confirms the domain is offline, reducing immediate exposure risk. However, the infrastructure and registration anomalies warrant continued monitoring. Organizations and individuals are advised to review logs for connections to 43.162.112.41 or fidelityworkplacebw.shop, particularly from February 2024 onward. End users should be alerted to verify domain authenticity before entering credentials, especially for financial or benefits-related platforms. Security teams are recommended to update blocklists with the domain and IP, and to implement domain generation algorithm (DGA) detection rules to identify similar impersonation attempts.
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