{"id":2707,"date":"2017-06-01T10:48:53","date_gmt":"2017-06-01T17:48:53","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=2707"},"modified":"2025-06-13T23:43:24","modified_gmt":"2025-06-14T06:43:24","slug":"find-pii-in-your-database","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/es\/find-pii-in-your-database\/","title":{"rendered":"La forma m\u00e1s r\u00e1pida de identificar PII almacenados en su base de datos: Un ejemplo sencillo usando N1QL, Nodejs y Docker"},"content":{"rendered":"

Una petici\u00f3n frecuente de los clientes es una manera de identificar PII dentro de sus bases de datos. He pensado en mostrar un breve ejemplo de c\u00f3mo hacerlo.<\/p>\n

Historia de usuario<\/b>: \"Quiero identificar n\u00fameros de tarjetas de cr\u00e9dito y de la seguridad social sin cifrar dentro de los documentos para asegurarme de que los desarrolladores no est\u00e1n almacenando cosas que no deber\u00edan en la base de datos\".<\/p>\n

Antecedentes:\u00a0\u00a0<\/b>N1QL tiene un \"tokenizador<\/a>\"a partir de la versi\u00f3n 4.6. Combine esto con\u00a0funciones regex<\/a>\u00a0en N1QL, \u00edndices secundarios espec\u00edficos y disponemos de un potente conjunto de herramientas para identificar patrones dentro de la base de datos.<\/p>\n

Ejemplo de soluci\u00f3n: \u00a0<\/b>He creado una consulta para identificar n\u00fameros de la seguridad social sin cifrar almacenados en un bucket (el bucket \"por defecto\" en este caso). Busco cualquier patr\u00f3n de d\u00edgitos que coincida con xxx-xx-xxxx o xxxxxxxxx. La funci\u00f3n TOKENS me permite tratar un documento como una matriz de cadenas. Us\u00e9 la bandera \"specials\" para decirle a N1QL que mantenga estas cadenas intactas. Si no utilizo esta opci\u00f3n, se eliminar\u00e1n los espacios y los guiones y se ignorar\u00e1n los elementos que sigan a estos caracteres. Luego busco cualquier expresi\u00f3n regular que coincida con un elemento dentro de la matriz de tokens.<\/p>\n

SELECT * FROM default\r\n WHERE ANY v IN\r\n TOKENS(default, {\"specials\":true}) SATISFIES\r\n REGEXP_LIKE(TOSTRING(v),'(\\\\d{3}-\\\\d{2}-\\\\d{4})|(\\\\b\\\\d{9}\\\\b)')\r\nEND<\/pre>\n
La identificaci\u00f3n de n\u00fameros de tarjetas de cr\u00e9dito sin cifrar almacenados en un cubo utiliza el mismo enfoque:<\/p>\n
SELECT * FROM default\r\n WHERE ANY v IN\r\n TOKENS(default, {\"specials\":true}) SATISFIES\r\n REGEXP_LIKE(TOSTRING(v),'(\\\\d{4}-\\\\d{4}-\\\\d{4}-\\\\d{4}))|(\\\\b\\\\d{16}\\\\b)')\r\nEND<\/pre>\n
Para acelerar el tiempo de procesamiento, utilizo \u00edndices secundarios optimizados en memoria (MOI) para las consultas anteriores.  Cada mutaci\u00f3n en Couchbase se env\u00eda as\u00edncronamente al proyector del \u00edndice.   Los MOI tienen la ventaja a\u00f1adida de actualizar la informaci\u00f3n contenida en el \u00edndice cada 20 ms. Los \u00edndices tambi\u00e9n hacen uso de la tokenizaci\u00f3n.<\/p>\n
CREATE INDEX `find_pii_ssn` ON `default`(\r\n (DISTINCT (ARRAY `v` FOR `v` IN\r\n TOKENS(self, {\"specials\": true}) END)))\r\n WHERE ANY `v` IN\r\n TOKENS(self, {\"specials\": true}) SATISFIES REGEXP_LIKE(TO_STRING(`v`), \"(\\\\d{3}-\\\\d{2}-\\\\d{4})|(\\\\b\\\\d{9}\\\\b)\")\r\n END<\/pre>\n
...y para tarjetas de cr\u00e9dito no encriptadas<\/p>\n
CREATE INDEX `find_pii_ccn` ON `default`(\r\n (DISTINCT (ARRAY `v` FOR `v` IN\r\n TOKENS(self, {\"specials\": true}) END)))\r\n WHERE any `v` IN\r\n TOKENS(self, {\"specials\": true}) SATISFIES REGEXP_LIKE(TO_STRING(`v`), \"(\\\\d{4}-\\\\d{4}-\\\\d{4}-\\\\d{4}))|(\\\\b\\\\d{16}\\\\b)\")\r\n END\r\n<\/pre>\n
Pru\u00e9balo:<\/strong>\u00a0Docker es mi forma favorita de crear un entorno de desarrollo.   Un repositorio f\u00e1cil de usar para los ejemplos anteriores est\u00e1 en github: n1ql-query-nodejs <\/a>.  Utiliza docker-compose para construir dos servicios:<\/p>\n
    \n
  1. Un servicio de cl\u00faster Couchbase de nodo \u00fanico.<\/li>\n
  2. Un servicio nodejs para aprovisionar el cl\u00faster Couchbase con 250.000 perfiles de usuario e \u00edndices para varios ejemplos, incluida la b\u00fasqueda de PII sin cifrar.<\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"
    A frequent request from customers is a way to identify PII within their databases.\u00a0\u00a0 I thought I\u2019d show a brief example how this can be done. User Story: “I want to identify unencrypted credit card numbers and social security numbers […]<\/p>","protected":false},"author":20,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1822,1812],"tags":[1519,1896],"ppma_author":[9019],"class_list":["post-2707","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-node-js","category-n1ql-query","tag-docker","tag-docker-compose"],"acf":[],"yoast_head":"\nThe Fastest Way to Identify PII Stored in your Database: A Simple Example Using N1QL, Nodejs and Docker - The Couchbase Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/es\/find-pii-in-your-database\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Fastest Way to Identify PII Stored in your Database: A Simple Example Using N1QL, Nodejs and Docker\" \/>\n<meta property=\"og:description\" content=\"A frequent request from customers is a way to identify PII within their databases.\u00a0\u00a0 I thought I\u2019d show a brief example how this can be done. 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