[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fLTFZttEKZ8W3hgcJIOtP5YYLLYkNHrIfMLBL4jfs0wo":3},{"lesson":4},{"id":5,"slug":6,"article_id":7,"title":8,"body":9,"prevention":10,"framework_refs":11,"status":20,"created_at":21,"published_at":22,"article":23,"tags":27,"podcasts":40},"d8ecf286-50f3-4b88-a74d-5a519a4b17d6","ifood-data-breach-exposes-12m-users-due-to-inadequate-data-protection","7e44f579-d26d-4933-8f93-91e5f1b6e568","iFood Data Breach Exposes 1.2M Users Due to Inadequate Data Protection","iFood suffered a significant data breach affecting 1.2 million Brazilian users, exposing sensitive personal information including names, addresses, phone numbers, and CPF numbers (Brazilian tax IDs). The incident highlights critical failures in data protection controls and incident response, as hackers claimed much larger datasets were compromised and made ransom demands on dark web forums. The discrepancy between iFood's confirmed breach size and hackers' claims suggests potential ongoing security gaps or incomplete breach assessment, putting additional customer data at risk.","**Immediate actions:**\n- Implement end-to-end encryption for all customer personal data at rest and in transit\n- Deploy data loss prevention (DLP) tools to monitor and block unauthorized data exfiltration\n- Establish real-time security monitoring with automated breach detection capabilities\n\n**Long-term improvements:**\n- Adopt data minimization practices to collect and store only essential customer information\n- Implement zero-trust architecture with strict access controls for sensitive customer databases\n- Develop comprehensive incident response procedures including breach size verification and threat actor communication protocols\n\n**Detection measures:**\n- Deploy database activity monitoring to detect unusual data access patterns\n- Implement threat intelligence feeds to monitor dark web forums for company data exposure\n- Establish regular security audits and penetration testing focused on customer data protection",[12,13,14,15,16,17,18,19],"CIS Control 3","CIS Control 13","NIST PR.DS-1","NIST PR.DS-5","NIST DE.CM-1","NIST RS.CO-2","GDPR Article 32","GDPR Article 33","published","2026-06-04T18:06:48.364149+00:00","2026-06-04T18:06:48.279+00:00",{"id":7,"url":24,"slug":25,"title":26},"https:\u002F\u002Fhackread.com\u002Fifood-confirms-data-breach-brazil-users\u002F","ifood-confirms-data-breach-affecting-1-2-million-users-in-brazil-fc89ef","iFood Confirms Data Breach Affecting 1.2 Million Users in Brazil",[28,34],{"id":29,"name":30,"slug":31,"description":32,"color":33},"182e11d5-57c4-444e-8ec8-4682ad60261b","Incident Response","incident-response","Slow detection, poor containment, missing playbooks","#14b8a6",{"id":35,"name":36,"slug":37,"description":38,"color":39},"c8b843a5-d5a7-41d1-8d3b-cabded09d2ef","Data Protection","data-protection","Unencrypted data, missing DLP, poor classification","#3b82f6",[]]