[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fX7S9yjBSQOeQm2P8qUsDZBY6sDDvhx3OB3eVCrLZ2Yc":3},{"lesson":4},{"id":5,"slug":6,"article_id":7,"title":8,"body":9,"prevention":10,"framework_refs":11,"status":25,"created_at":26,"published_at":27,"article":28,"tags":32,"podcasts":51},"0862785f-a60b-47b8-8409-41eb6c585d74","social-engineering-attack-on-revolut-leads-to-147gb-data-breach-and-3m-ransom-demand","23d888a6-a520-4a70-8f89-aacb77aec9a9","Social Engineering Attack on Revolut Leads to 147GB Data Breach and $3M Ransom Demand","Hackers successfully impersonated an Italian government agency to socially engineer Revolut employees into disclosing sensitive customer data — including passports and financial records — over a five-month period. The root failure was the absence of robust identity verification protocols for external data requests, allowing a threat actor to exploit procedural trust rather than technical vulnerabilities. This breach demonstrates that even sophisticated fintech companies remain vulnerable to human-layer attacks when staff lack adequate verification procedures. The extended five-month window also points to serious gaps in anomaly detection and data access monitoring that should have flagged unusual or high-volume data sharing activity far earlier.","**Immediate actions:**\n- Implement a strict, multi-step verification process for all external data requests, requiring out-of-band confirmation directly with the requesting agency via official contact details.\n- Audit all data-sharing activities from the past 12 months to identify any other potentially unauthorized disclosures.\n- Alert and notify affected customers as required under applicable data protection regulations (e.g., GDPR Article 33\u002F34).\n\n**Long-term improvements:**\n- Establish a formal, documented procedure for handling government and law enforcement data requests, including legal review before any data is released.\n- Apply the principle of least privilege so that only authorized personnel with a clear business need can access and export sensitive customer data.\n- Conduct regular social engineering awareness training and simulated impersonation drills for all customer-facing and data-handling staff.\n\n**Detection measures:**\n- Deploy data loss prevention (DLP) controls to automatically flag and block bulk exports of personally identifiable information (PII) or financial data.\n- Set up real-time alerting for anomalous data access patterns, such as unusually large or repeated data pulls by a single user or team.\n- Integrate SIEM rules to correlate external data request volumes against historical baselines and trigger reviews for outliers.",[12,13,14,15,16,17,18,19,20,21,22,23,24],"CIS Control 3: Data Protection","CIS Control 14: Security Awareness and Skills Training","CIS Control 13: Network Monitoring and Defense","NIST SP 800-53 AC-2: Account Management","NIST SP 800-53 AT-2: Literacy Training and Awareness","NIST SP 800-53 SI-4: System Monitoring","NIST SP 800-53 MP-6: Media Sanitization","GDPR Article 5: Principles Relating to Processing of Personal Data","GDPR Article 25: Data Protection by Design and by Default","GDPR Article 33: Notification of a Personal Data Breach to the Supervisory Authority","GDPR Article 34: Communication of a Personal Data Breach to the Data Subject","NIST CSF PR.AT-1: Awareness and Training","ISO\u002FIEC 27001 A.7.2.2: Information Security Awareness, Education and Training","published","2026-09-17T14:20:23.423253+00:00","2026-09-17T14:20:22.635+00:00",{"id":7,"url":29,"slug":30,"title":31},"https:\u002F\u002Fwww.securityweek.com\u002Frevolut-data-breach-5-months-680-high-profile-accounts-3m-ransom\u002F","revolut-data-breach-5-months-680-high-profile-accounts-3m-ransom-23e014","Revolut Data Breach: 5 Months, 680 High-Profile Accounts, $3M Ransom",[33,39,45],{"id":34,"name":35,"slug":36,"description":37,"color":38},"1ec88fde-2d0f-4ed8-932a-33f5ccc0fdc7","Access Control","access-control","Excessive privileges, missing MFA, weak auth","#f97316",{"id":40,"name":41,"slug":42,"description":43,"color":44},"7261eb8f-acd4-4d93-a489-7fdd652ec0ea","Security Awareness","security-awareness","Phishing, social engineering, human error","#22c55e",{"id":46,"name":47,"slug":48,"description":49,"color":50},"c8b843a5-d5a7-41d1-8d3b-cabded09d2ef","Data Protection","data-protection","Unencrypted data, missing DLP, poor classification","#3b82f6",[]]