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@LOBO_X93
PERRO PASTOR / LOBO SOLITARIO -ESTO ES UNA GUERRA ENTRE EL BIEN Y EL MAL-

🔴🔴 Detienen a 11 personas por un fraude millonario en el Servicio Murciano de Salud. La Policía Nacional cifra los sobrecostes en un 1.287% . Aseguran, además, que se utilizaron productos sanitarios caducados en operaciones médicas. 🔊@policia

Creen que el contenido generado con IA debería obligatoriamente tener una "marca" que lo diferencie del contenido generado por humanos?


On Friday the 15th of May, we became aware of a fingerprinting issue affecting Mullvad users. We have a method which changes this behaviour currently being tested, with plans to begin rolling it out to our VPN servers in the coming weeks. Read more here: mullvad.net/blog/exit-ip-f…





🇪🇸 A threat actor is advertising an alleged dataset tied to Spain’s Agencia Tributaria electronic platform — the country’s official tax administration portal. According to the listing, the exposed records allegedly include: • full names • DNI/NIE/CIF national identity identifiers • birth dates • residential information • multiple phone numbers • country/province data • taxpayer-related metadata • technical indicators/flags And if authentic, this is exactly the kind of dataset cybercriminals love most: high-confidence identity infrastructure. Why? Because government-linked identity datasets dramatically increase the effectiveness of: • financial fraud • tax scams • identity theft • synthetic identity creation • banking impersonation • social engineering • telecom fraud • SIM swapping • account recovery abuse One especially important point: DNI/NIE identifiers are foundational identity attributes in Spain. When attackers combine: • national IDs • phone numbers • birth dates • residence information they can often build highly convincing fraud profiles. And modern cybercrime is increasingly about: identity correlation. Not just “stealing passwords.” Another major concern: tax-related data carries unusually high trust value. People panic when they receive: • tax notices • audit warnings • refund alerts • “missing payment” messages Attackers know this extremely well. So datasets like these can become fuel for: • phishing campaigns impersonating tax authorities • fake refund operations • identity verification fraud • malicious e-signature requests • banking takeover attempts tied to tax filings And yes… some phishing emails now have better branding consistency than government portals themselves. The listing also references: • electronic certificates • digital signatures • taxpayer verification systems which is particularly notable because trust ecosystems around digital identity infrastructure are now prime targets globally. Governments increasingly rely on: • centralized citizen identity systems • e-government platforms • electronic signatures • digital tax workflows which means compromise impact scales rapidly. Another trend worth watching: large citizen identity datasets are becoming strategic underground assets. They are reused repeatedly across: • fraud marketplaces • credential stuffing ecosystems • KYC bypass operations • crypto onboarding fraud • mule recruitment • financial identity laundering because verified identity data is now effectively a commodity. At this stage, the authenticity and scope remain unverified. However, organizations operating national-scale digital identity infrastructure should continuously monitor for: • credential exposure • unauthorized API access • abnormal taxpayer queries • identity enumeration activity • phishing campaigns abusing government branding • suspicious document verification requests • e-signature abuse attempts • underground marketplace activity targeting citizen records Because once identity infrastructure data enters criminal ecosystems, the downstream effects can persist for years. 🇪🇸 #DDW #Intelligence #CyberSecurity #DarkWeb #Spain #DataLeak #ThreatIntelligence #IdentityTheft #Infosec #Fraud


Una chica denuncia el intento de violación y la brutal paliza de un africano y recrimina que el alcalde socialista de Mérida no le haya llamado: "Estos negros que vienen de Nigeria no tienen que venir".

















