DBHunter
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Hello DNA community,
I managed to extract the data from the subsidy system of SEDEM (Servicio de Desarrollo de las Empresas Públicas Productivas de Bolivia), obtaining a full and detailed extraction of their database.
Download link:
I managed to extract the data from the subsidy system of SEDEM (Servicio de Desarrollo de las Empresas Públicas Productivas de Bolivia), obtaining a full and detailed extraction of their database.
This leak directly exposes the complete registry of beneficiaries, biometric control data, validity periods, assigned amounts, and critically, extracted personal data including residential physical addresses and emails.
The data is packaged in a single compressed file named SedemBoliviaSubsidyData.rar containing a total of 526,048 JSON files meticulously organized.
RAR File Structure
Upon extracting the file, you will find the information structured into two main folders:
1. BeneficiarySubsidyBalanceData
Total records: 205,207 JSON files.
Content: Exposes personal data (ID card number, full name, exact address, emails), enrollment status, and the list with the breakdown of balances assigned and consumed per food group (Fruits, meats, vegetables, dairy, etc.).
2. SubsidyBeneficiariesData
Total records: 320,841 JSON files.
Content: Exposes the status of the enrollment process, full names, ID card number (CI), exact validity periods of the benefit, and the fingerprint registration mapping from the biometric system.
Complete Data Structure (Real Examples)
1. BeneficiarySubsidyBalanceData (JSON Structure)
Each file is named after the ID card number or the registry identifier. Here is the exact field schema:
{
"persona": {
"cedula": 5150983,
"nombre": "AJATA TOPOCO LIDIA EMMA",
"direccion": "AV. PANDO Y 2DA CIRCUNVALACION S/N - Z QUERU. CBBA",
"zona": null,
"email": null
},
"sistema_enrolamiento": {
"id_administrativo_persona": 1820,
"id_biometrico_enrolado": 192005,
"id_estado_enrolado": 18,
"id_tipo_enrolado": 1,
"id_fact_persona": 0,
"tipo_biometrico_persona": 1,
"tipo_enrolado": "DIRECTO",
"fotografia": null
},
"datos_referenciales_beneficiario": {
"benef_cedula": null,
"benef_nombre": null,
"benef_idbio_enrolado": 0,
"benef_idc_estadoenrolado": 0,
"benef_idc_tipoenrolado": 0,
"benef_idfact_persona": 0,
"benef_tipoenrolado": null
},
"datos_referenciales_dependiente": {
"depen_cedula": null,
"depen_nombre": null,
"depen_idbio_enrolado": 0,
"depen_idc_estadoenrolado": 0,
"depen_idc_tipoenrolado": 0,
"depen_idfact_persona": 0,
"depen_tipoenrolado": null
},
"lista_saldos": [
{
"cedula_asociada": 5150983,
"grupo_alimenticio": "FRUTAS",
"tipo_subsidio": "PRENATAL/LACTANCIA",
"monto_asignado": 545.16,
"monto_consumido": 0,
"saldo_disponible": 0,
"id_grupo_alimenticio": 701,
"id_monto_consumo": 536965,
"id_monto_grupo_alimenticio": 1015526,
"id_subsidio_beneficio": 1,
"id_tipo_grupo": 0,
"id_tipo_subsidio": 0,
"id_administrativo_persona_saldo": 1594752,
"id_generacional_beneficiario": 0,
"id_sub_titular_beneficiaria": 0,
"tipo_grupo": null,
"fecha_creacion": "2025-04-28T17:37:11.337626",
"fecha_modificacion": "2025-07-25T16:50:49.285187"
}
// ... ETC (The balance list continues for other food groups like meats, vegetables, tubers, etc.)
]
}
2. SubsidyBeneficiariesData (Full JSON)
Schema focused on the validity of the benefit and the biometric authentication mapping:
{
"proceso_enrolado": "ENROLADO",
"persona": {
"cedula": 10000014,
"nombre": "MAMANI MAMANI CRISTINA",
"tipo_persona": "BENEFICIARIO"
},
"titular": {
"ci_titular": null,
"nombre_titular": null
},
"sistema": {
"id_administrativo_persona": 1430718,
"id_beneficiaria": 0,
"id_biometrico_enrolado": 7640,
"id_sub_titular": 0,
"id_estado": 0,
"id_tipo_persona": 44,
"cuenta_con_huellas": 1
},
"vigencia": {
"periodo_inicial": "25/01/2024",
"periodo_final": "31/12/2025"
},
"biometria": {
"fotografia": null,
"tiene_fotografia": 0,
"registro_huellas": {
"huella_0": 0,
"huella_1": 0,
"huella_2": 0,
"huella_3": 1,
"huella_4": 0,
"huella_5": 0,
"huella_6": 1,
"huella_7": 0,
"huella_8": 0,
"huella_9": 0
}
}
}
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