GitHub ha anunciado la incorporaci\u00f3n de un sistema experimental de aprendizaje autom\u00e1tico al servicio de Code scanning para detectar tipos comunes de vulnerabilidades en el c\u00f3digo. En la etapa de prueba, esta nueva funcionalidad est\u00e1 disponible solo para repositorios con c\u00f3digo en JavaScript y TypeScript. Se destaca que el uso del sistema de aprendizaje autom\u00e1tico ha permitido ampliar significativamente el espectro de problemas detectables, ya que ahora no se limita a verificar patrones predefinidos ni se asocia a marcos de trabajo conocidos. Entre los problemas detectados por el nuevo sistema se mencionan errores que provocan scripting entre sitios (XSS) y la distorsi\u00f3n de rutas de archivo (por ejemplo, mediante la especificaci\u00f3n \u00ab\/..\u00bb). <\/p>\n
El servicio de Code scanning permite identificar vulnerabilidades en las primeras etapas del desarrollo mediante el escaneo de cada operaci\u00f3n de \u00abgit push\u00bb en busca de problemas potenciales. El resultado se adjunta directamente a la solicitud de extracci\u00f3n. Anteriormente, la verificaci\u00f3n se realizaba utilizando el motor CodeQL, que analiza patrones con ejemplos t\u00edpicos de c\u00f3digo vulnerable (CodeQL permite crear un patr\u00f3n de c\u00f3digo vulnerable para detectar la presencia de vulnerabilidades similares en el c\u00f3digo de otros proyectos). El nuevo motor, que utiliza aprendizaje autom\u00e1tico, puede identificar vulnerabilidades previamente desconocidas, ya que no est\u00e1 limitado a la b\u00fasqueda de patrones de c\u00f3digo que describan vulnerabilidades espec\u00edficas. El costo de esta capacidad es un aumento en la cantidad de falsos positivos en comparaci\u00f3n con las verificaciones basadas en CodeQL. 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Fuente: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"