MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_NextPart_01D75EAD.3B5C3210" Este documento es una página web de un solo archivo, también conocido como "archivo de almacenamiento web". Si está viendo este mensaje, su explorador o editor no admite archivos de almacenamiento web. Descargue un explorador que admita este tipo de archivos. ------=_NextPart_01D75EAD.3B5C3210 Content-Location: file:///C:/CF1A1564/05_RIESGOSDESEGURIDADINFORMATICAENSERVICIOSWEBORCID.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" Densidad de Líquidos Iónicos usando Contribució= ;n de Grupos y Redes Artificiales Neuronales

Recibido: 06-= 04-2021 / Revisado: 14-04-2021 / Aceptado: 09-05-2021 / Publicado: 04-06-2021<= /o:p>

 

 =

Aplicación de MAGERIT pa= ra reducir riesgos en servicios Web en un contexto académico en Ecuador= .

DOI:  https://doi.org/10.33262/ap.v3i2.2.60  <= o:p>

 

 

Applicatio= n of MAGERIT to reduce risks in Web services in an academic context in Ecuador.<= /span>

 

 

Diego Jácome Segovia. [1], Jessica Castillo Fiallos. [2], Carmita  Mantilla Cabrera. [3] & Byron Ernesto Vaca Barahona. [4]<= /span>

 

 =

&n= bsp;

Abstract

This study prese= nts an adaptation of the MAGERIT methodology that allows us to manage the IT secur= ity risks of a company's web services. For this purpose, the first step was to determine the company’s information assets along with possible threat= s, and in the event of materialization the impact of these threats was then measured to identify the safeguards of these assets. After this, a web serv= ices vulnerability detection test was performed using a free software tool called VEGA. Finally, the level of risk was determined so that IT staff will be be= tter able to make future decisions. In the analysis of the vulnerability of web services, the most common vulnerabilities found were: SQL Injection, PHP Er= ror Detected and Directory Listing Detected, among others. With the implementat= ion of this model, high risk vulnerabilities were reduced to 87.87% and 12.13% = of all vulnerabilities were eliminated. 

Keywords: Vulnerability, Risk, Web Services, Security, MAGERIT, VEGA<= o:p>

Resumen

 

Se presenta un modelo basado en la metodología MAGERIT que permite gestionar los riesgos de seguridad informática de los servicios web de una empresa. Para este propósito se determinaron los activos de información con sus posibles amenazas y el impacto que estas tendrían si se materializaran, luego se identificó las salvaguardas de los activos y se realizó la detección de vulnerabilidades en los servicios web mediante el uso de la herramienta gratuita VEGA. Finalmente, se determinó el nivel del riesgo que a fu= turo permitirá al personal de tecnologías tomar mejores decisiones= . En el resultado del análisis de vulnerabilidades de los servicios web se identificaron como más frecuentes: SQL Injectio= n, PHP Error Detected y Direc= tory Listing Detected, e= ntre otras, con lo que al aplicar el modelo propuesto se redujo un 87.87% las vulnerabilidades altas encontradas  y se eliminaron el 12.13% d= e las mismas.

 =

Palabras clave: Inseguridad, Amenazas, URLs, Seguridad,  MAGERIT, VEGA

 

Introducción.

Con la gran cantidad de vulnerabilidades informáticas conocidas y amenazas, los activos informáticos están más expuestos que nunca a riesgos de índole como= : el robo de información, perdida de dinero y clientes, falta de disponib= ilidad del servicio, y sobre todo la credibilidad de la empresa hacia el mundo exterior, por esto es necesario que las empresas u organizaciones cuenten c= on un modelo de gestión de riesgos que ayude a reducir el impacto que ocasionaría que una de las vulnerabilidades si llegase a ser materia= lizada.  La gestión de riesgos es un enfoque que nos permite manejar la probabilidad de que una o varias amenazas tomen ventaja de una vulnerabilidad y el impacto asociado que estas causarían en el evento de que sucedan. Por lo que se utilizan difere= ntes controles, políticas, normas, estrategias para poder manejarlo y mitigarlo utilizando los recursos disponibles (Freitas, 2009).

La gestión de riesgos en los sistema= s web puede ser compleja debido al desconocimiento con respecto a este tema. Por = lo que el principal problema en Ecuador es la falta de un estándar específico para la gestión de este tipo de riesgos por lo que= es necesario un modelo o metodología que establezca reglas, normas, controles, políticas y procedimientos para los mismos, con el objeti= vo de analizar, prevenir, proteger o mitigar las posibles vulnerabilidades que= son condiciones que cuando son explotadas por personas malintencionadas pueden = dar lugar a fallas de seguridad, lo que representa una debilidad latente en la seguridad, integridad, disponibilidad de la información sensible que estos sistemas manejan, la cual podría ser utilizada por terceras pe= rsonas sin la autorización de la institución  (Shirey, 2000).

El siguiente trabajo propone un modelo para= la gestión de riesgos para servicios web basado en la metodología MAGERIT, el cual consta de seis etapas: identificación de activos según su importancia en la organización, determinación= de amenazas que existen en el entorno, las salvaguardas que existen al momento= de realizar la primera evaluación de riesgos, el impacto asociado al riesgo, análisis de las posibles y conocidas vulnerabilidades y finalmente el riesgo actual de la organización. Este modelo est&aacu= te; enfocado para ser implementado en Instituciones educativas ya que son un potencial objetivo para cometer delitos informáticos  (Desogles, 2005).

Trabajos relacionados

Para el estudio se consideraron= de mayor relevancia los resultados de las investigaciones que se listan a continuación:

En la publicación efectu= ada en octubre del 2018, titulada Modelo para la reducción de riesgos de seguridad informática en servicios web (Castillo, Cisner= os, Mendez, & Jácome, 2018), manifiesta qu= e se ha considerado la problemática y falencias internas que generan los tip= os de vulnerabilidades a los que son sujetos los servicios web que brinda la ESPOCH. Debido a la utilización de software no certificado y a la es= casa capacitación de recurso humano en el manejo de etapas crítica= s al momento de administrar y modificar los servicios web.

En un trabajo previo de (Montev= erde y Campiolo, 2014), menciona que la seguridad web es importante para proporcionar protección a los clientes y a los servi= cios web. Múltiples vulnerabilidades web son explotadas todos los d&iacut= e;as y los ataques tienen aumentado debido a las nuevas herramientas y aplicacio= nes web, se lleva a cabo un análisis de vulnerabilidades web en diferent= es tipos de aplicaciones con la herramienta de escáner VEGA. Un conjunt= o de Sitios Web heterogéneos y brasileños fueron seleccionados y analizados, en consecuencia, las principales formas de ataques utilizados en aplicaciones web se han investigado, los resultados muestran cómo las vulnerabilidades web pueden ser explotadas fácilmente, por lo que se= verifica que los sitios web deben mejorar su seguridad con urgencia.

(Khari y Singh, 2014), en su investigación, indica que las aplicaciones resul= tan ser herramientas de uso cotidiano por muchos usuarios con la creciente popularidad de la web, con lo que los usuarios son más propensos a l= os ataques maliciosos en consecuencia la necesidad de pruebas de seguridad sur= ge también para ayudar a mitigar las vulnerabilidades en la web. Lo que ocurre frecuentemente en aplicaciones web son el resultado de problemas de validación de entrada de genéricos como: Inyección SQL= y Cross-Site Scripting (XSS), etc, estas vulnerabilidades son más a menudo explotados por atacantes que= tengan acceso a información sensible. VEGA y ZAP son escáneres de código abierto que ofrecen una buena opción para probar vulnerabilidades potenciales en forma automatizada, como resultado de esto = muchos sitios web en Internet que son vulnerables.

El estudio de  (Vicente y Ji= menez, 2014), indica que se han desarrollado varios métodos basados en la n= orma ISO 27000 norma internacional / IEC para lidiar con el análisis de riesgos en los sistemas de información (SI) y proponen una extensión de la metodología MAGERIT basado en modelos computa= cionales difusos clásico, usa una escala lingüística térmi= no para representar los valores de activos, sus dependencias, frecuencia y la degradación de los activos asociados a las amenazas y respecto a la selección de las salvaguardias preventivas para reducir los riesgos = en IS, propone un método basado en programación dinámica = que incorpora recocido simulado para hacer frente a los problemas optimizaciones con el objetivo de minimizar los costos mientras se mantiene el riesgo a niveles aceptables.

La investigación científica propuesta por (Kyushu, Hori y Sakurai, 2009), co= mpara cuatro métodos de análisis de riesgos: Mehari, Magerit, NIST800-30 y la Guía de Gestió= n de Seguridad de Microsoft. Mehari es un método para el análisis y gestión de riesgos, Magerit es un análisis de riesgos y metodología de gestión de sistem= as de información, NIST 800-30 es una guía d= e  riesgos para los sistemas de tecnología de la información y la seguridad es una guí= a de gestión de riesgos de seguridad desarrollado por Microsoft. Compara = los métodos basados en dos criterios principales: los pasos que utilizan= los métodos para llevar a cabo la evaluación del riesgo y el contenido de los métodos y documentos complementarios previstos con ellos. Se encontró que todos los métodos siguen los tres prim= eros pasos generales del análisis de riesgos. Sin embargo, el méto= do Mehari, el método Magerit y la Guí= ;a de administración de seguridad de Microsoft no incluyen recomendaciones para el control.

La investigación plantea= da por (Kwan & Leung, 2010) indica que los riesgos= no siempre son independientes ya que no existe una administración clara entre ellos. Las dependencias pueden ser identificadas de forma explícita y analizadas, los administradores del proyecto deben ser capaces de planificar estrategias efectivas contra los riesgos con la final= idad de tomar decisiones, sin embargo, la investigación fue solamente teórica y no fue implementada para verificar la reducción de riesgos que pruebe la propuesta.

Las Instituciones educativas no= cuentan con estándares para garantizar la integridad de su informació= n, ya que existe una variedad de vulnerabilidades las cuales pueden aprovechar las amenazas y convertirse en riesgos que perjudican y ocasionan pérdidas económicas en las mismas, La investigación se realizó = en el Departamento de Sistemas de una entidad académica, para la identificación las vulnerabilidades con la herramienta VEGA que es p= ropi del sistema operativo Linux.

 

Metodología=

Adaptación y aplicaci&= oacute;n de la metodología MAGERIT

Debido a que se necesita evaluar el nivel de riesgo e= n las Tecnologías de la Información y adoptar medidas apropiadas pa= ra el control, la metodología presentada se basó en MAGERIT, una= de las más utilizadas en Latinoamérica ya que contempla má= ;s ampliamente los parámetros de la evaluación y existe soporte = en español, su esquema metódico se presenta en la Figura 1.

 

<= span lang=3DES> 3D"Resultado

 

Figura 1= :  Metodología MAGERIT para determinar el riesgo

 

Fuente: http://polux.unipiloto.edu.co:8080/= 00004420.pdf

=  

= Definir del alcance. Se realizaron= las pruebas para identificar los riesgos y sus posibles soluciones a los servic= ios Web de la Institución Educativa.

 

I= dentificar de Activos.

Los recursos que pertenecen a l= os sistemas de información para facilitar el funcionamiento de la organización en cumplimiento de sus objetivos, se los denominó activos (Aguilera, 2010, pág. 9).&n= bsp; Es necesario realizar el estudio para la identificación de los activos ya que estos guardan relación entre ellos y si ocurre da&nti= lde;o en uno puede afectar a otros, el administrador del Departamento de Computac= ión fue quien los identificó a través de un inventario donde cons= tan activos físicos, hardware y software, los de información tecnológicos de la organización se presentan.

Activos

·      =    URLs. Servicios Web

·      =    Equipos Informáticos

·      =    Soport= es de información (medios de backup)

·      =    Instal= aciones

·      =    Person= al

I= dentificar de Amenazas.

Para la identificación d= e las amenazas se consideraron las que pudieran causar cualquier tipo de evento q= ue produciría un daño sobre los elementos de un sistema de información. Desde el punto de vista de la entidad que maneja los da= tos, existen amenazas de origen interno y externo como: agresiones técnic= as, naturales o humanos (Erb, 2014), como menciona = la Norma 27001, de acuerdo a las condiciones geográficas del lugar se planteó un check li= st con las posibles amenazas. A continuación, se presenta la encuesta realizada al administrador de TICs.<= /span>

Amenazas

·      =    Ca&iac= ute;da de energía

·      =    Aver&i= acute;a de origen físico o lógica

·      =    Acceso= no autorizado

·      =    Errore= s de los usuarios

·      =    Errore= s del Administrador

·      =    Errore= s de configuración

·      =    Errore= s de mantenimiento

·      =    Manipu= lación de la configuración

·      =    Hackin= g

·      =    P&eacu= te;rdida de datos

 

I= dentificar de Salvaguardas. 

Se consideró como salvag= uarda a los mecanismos de protección que reducen la frecuencia de las amenaz= as, limitan el daño causado por estas y permiten mantener la triada de seguridad informática CID: Confidencialidad, Integridad y Disponibilidad.  Donde la confidencialidad busca que solamente la persona o recurso autorizado tenga acceso a información= o servicio específico, la integridad asegura que la información no haya = sido alterada desde su origen al destino y la disponibilidad permite que la información y/o servicios estén disponibles.  Existen diferentes aspectos que pu= ede actuar como salvaguarda para alcanzar los objetivos de mitigar el riesgo.  En vista de que se requieren procedimientos para la operación de salvaguardas preventivas, gestión de incidencias y recuperación tras las mismas, se solicitó al administrador un inventario de seguros de todos los acti= vos de la organización para el levantamiento de la información de salvaguardas.

I= dentificar de Impacto.

Del inventario de los activos c= on su respectivo costo monetario, se realizó un análisis del impacto que tendría una amenaza sobre el activo sí llegara a material= izarse, la identificación de los impactos se desarrollara con repercusiones a las dimensiones de valoración de Disponibilidad, Integridad, Confiabilidad, Autenticidad de la información, estas dimensiones hac= en valioso al activo y la valoración de esta dimensión, es la me= dida del perjuicio para la organización.=   La escala de valoración que se implementa es Alto para un daño grave, Medio para un daño importante, Bajo para un daño menor.

I= dentificar de Vulnerabilidades. =

Las vulnerabilidades está= ;n directamente interrelacionadas con las amenazas, si no existe una amenaza tampoco existe la vulnerabilidad porque no se puede ocasionar un dañ= o. Entonces la capacidad, condiciones y características del sistema que= lo pueden hacer susceptible a amenazas y sufrir algún daño se co= nsidera una vulnerabilidad.  Dependien= do del contexto de la institución, se puede agrupar las vulnerabilidades en grupos característicos: ambiental, física, económica, = social, educativo, institucional y política. (Erb, 2014)

En la tabla 3., se presentan los servicios web identificados de la organización académica, con= una descripción y estados del mismo, sobre los cuales se realizaran los análisis de vulnerabilidades, para este análisis se utilizó la herramienta Vega de código libre, escrito en Java basado en GUI y multiplataforma, incluye un escáner automatizado para pruebas rápidas, un proxy de interceptación para inspección táctica, XSS (cross-site scripting), inyección de SQL y otras vulnerabilidades (Kali Tools, 2014), se puede ampliar su funcionalidad usando una poderosa API en lenguaje Java script para realizar: escáner automatizado de rastreadores y vulnerabilidades, interfaz de usuario coherente, crawl= er del sitio web, proxy de interceptación, SSL MITM, análisis del contenido, alertas personalizables, base de datos y modelo de datos compart= idos.

Servicios web

 

·      =    Posgra= do

·      =    Ingres= o de Calificaciones

·      =    Eva-Do= cente

·      =    Campus= Virtual

·      =    Bienes= tar

·      =    Recurs= os

 

I= dentificar de Riego

Para que exista un riesgo debe = existir tanto una vulnerabilidad como una amenaza, por lo que para el desarrollo de este punto se utilizó toda la información recolectada mediant= e el uso documentación bibliográfica, entrevistas al administrador= del departamento de TICs, pruebas y análisis= con VEGA (Aguilera, 2010).  La valoraci= ón del nivel de riesgo existente sobre los activos, se asignó de 1 a 5,= donde 5 es el más alto y se refiere un daño crítico a la organización, 4 un daño muy alto, 3 daño grave, 2 daño importante, 1 daño menor, 0 daño irrelevante.

Resultados

Identificar de activos relevantes.  Se determinaron los activos que permitieron identificar las amenazas a las que se encuentran expuestos, en la Tabla 1.,= se enumeran los activos relevantes pero con igual g= rado de importancia como resultado del análisis de ventajas y desventajas= de los mismos.

 

 

 

 

 

Tabla 1. Activos relevantes

 

No.

Activos de Información

1

2

3

4

5

6

7

8

9

10

11

UPS

Planta de energía

Procesador 1 (Servidor 1)

Procesador 2 (Servidor 2)

Procesador 3 (Servidor 3)

Procesador 4 (Servidor 4)

Memoria 1 (Servidor 1)=

Memoria 2 (Servidor 2)=

Memoria 3 (Servidor 3)=

Memoria 4 (Servidor 4)=

Storage

 

 

 

 

 

 

 

 

 

 

 

Identificar de Amenazas.  En la Tabla 2., se presenta un listado de d= iez amenazas que pueden producir daños a los activos de la institución.

 

Tabla 2. Identificación de Amenazas

 

No.

Amenazas<= /p>

1

2

3

4

5

6

7

8

9

10

Caída de energía

Avería = de origen físico o lógica

Acceso no auto= rizado

Errores de los usuarios

Errores del Administrador

Errores de configuración

Errores de mantenimiento

Manipulaci&oac= ute;n de la configuración

Hacking

Pérdida= de datos

 

Identificar de salvaguardas.  Los procedimientos y dispositivos que ayudan a reduci= r los riesgos como mecanismos de salvaguarda de los activos observados, se muestr= an en la Tabla 3.

 =

Tabla 3. Identificación de Salvaguar= das

=  

Activos de información

Salvaguarda

Dimensió= ;n

UPS

Protección del equipo dentro de la organización

Disponibilidad

Planta de energía

Protección del equipo dentro de la organización=

Disponibilidad

Servidor 1

Claves

Protección del equipo dentro de la organización

Disponibilidad

Integridad

Confidencialidad

Servidor 2

Claves

Protección del equipo dentro de la organización=

Disponibilidad

Integridad

Confidencialidad

Servidor 3

Claves

Protección del equipo dentro de la organización

Disponibilidad

Integridad

Confidencialidad

Servidor 4

Claves

Protección del equipo dentro de la organización=

Disponibilidad

Integridad

Confidencialidad

Memoria 1

Protección del equipo dentro de la organización

Disponibilidad

Integridad

Confidencialidad

Memoria 2

Protección del equipo dentro de la organización=

Disponibilidad

Integridad

Confidencialidad

Memoria 3

Protección del equipo dentro de la organización

Disponibilidad

Integridad

Confidencialidad

Memoria 4

Protección del equipo dentro de la organización=

Disponibilidad

Integridad

Confidencialidad

Storage

Protección del equipo dentro de la organización

Disponibilidad

Integridad

Confidencialidad

Servicios Web

Protección del servicio dentro de la organización

Disponibilidad

Integridad

Confidencialidad

Personal

Plan de contingencia

Disponibilidad

Integridad

Confidencialidad

=  

Identificar de Vulnerabilidades. En la Tabla 4., en forma de resumen se muestra el resultado del análisis de vulnerabilidades realizado sobre seis de las aplicaciones web con la herramienta VEGA, como se puede observar la aplicación con mayor número de vulnerabilidades de grado alto recae sobre campus virtual = y de igual manera el mayor en los de grado bajo, también se presenta una grave vulnerabilidad que consiste en envío de claves en texto plano = en los servicios de campus virtual, académico y recursos.

 

 

 

 

Tabla 4. Resultados de las pruebas realizad= as

 

Nombre

Grado

Posgrados=

Ingreso de Calificaciones=

Eva-Docente

Campus Virtual

Bienestar

Recursos

Total

No.

No.

No.

No.

No.

No.

No.

Clear Password over HTTP

Alto

1

0

3

3

0

1

8

Cross Site Scripting=

Alto

0

2

0

0

0

7

9

Page Fingerprint Differential Detected

Alto

5

0

0

0

0

2

7

Shell Injection

Alto

0

0

4

82

0

0

86

SQL Injection=

Alto

6

2

9

33<= /o:p>

0

0

50<= /o:p>

HTTP Trace Support <= span class=3DSpellE>Detected

Medio

0

0

1

1

1

0

3

Local Filesystem Paths Found =

Medio

0

1

62<= /o:p>

4

1

0

68<= /o:p>

PHP Error Detected

Medio

0

0

61

 

0

0

61

Possible Source Code Disclosure

Medio

0

0

0

31<= /o:p>

0

0

31<= /o:p>

Possible XML Injection=

Medio

0

0

3

0

0

0

3

URL Injection=

Medio

0

6

0

0

0

3

9

ASP/ASPX Error Detected

Bajo

0

0

0

1

0

0

1

Directory<= span lang=3DES-SV style=3D'font-size:9.0pt;line-height:115%;color:black;mso-an= si-language: ES-SV'> Listing Detected=

Bajo

89<= /o:p>

0

66<= /o:p>

680=

2

3

840=

From Password Field with Autocomplete Enabled

Bajo

0

1

0

0

0

1

2

Total

 

101=

12<= /o:p>

209=

835=

4

17<= /o:p>

1178

 

Modelo de gestión para reducción de riesgos de seguridad informática en servicios web.  El análisis ejecutado a la organización= educativa donde se realizó el estudio presenta vulnerabilidades que podr&iacut= e;an poner en riesgo sus servicios web, por lo que en la Tabla 5., se presenta la propuesta para brindar posibles soluciones en las diferentes vulnerabilidad= es encontradas que en coordinación con los objetivos, estrategias y políticas de TICs, las actividades de gestión de riesgos, permiten elaborar un plan de seguridad que implantado y operado satisfaga los objetivos propuestos con un nivel de rie= sgo inferior al del análisis preliminar.

 

Tabla 5.  Propuesta de solución

 

Vulnerabilidad

Popuesta de Solució= n

U= RL Injection

1.=         El desarrollador debe examinar la etiqueta y determinar las posibles implicaciones de seguridad de la utilización de un URI suministrad= o de forma remota.

Directory Listing Detected

<= span lang=3DES style=3D'font-size:9.0pt;line-height:115%;color:black'>1.=         Para= Apache, realizar una de las siguientes opciones: añadir "IndexIgnore " para archivo .htaccess del directorio, o bien eliminar "Índices" de la lí= ;nea "Opciones Todos los índices FollowSymLin= ks MultiView" en su archivo de configuraci&= oacute;n de Apache.

Cleartext Password over HTTP

1.=       Las contraseñas NO deben ser enviadas a través de texto plano.

2.=       Elaborar contraseñas fuertes y cifrarlas.=

3.=       Una contraseña fuerte debe contener mínimo 8 caracteres: 2 caracteres especiales, 2 números, 2 letras mayúsculas y 2 minúsculas.

SQ= L Injection

<= span lang=3DES-SV style=3D'font-size:10.0pt;line-height:115%;color:black;mso-a= nsi-language: ES-SV'>1.       La mejor defensa contra las vulnerabilidades de = SQL Injection es utilizar instrucciones con parámetros.

<= span lang=3DES-SV style=3D'font-size:10.0pt;line-height:115%;color:black;mso-a= nsi-language: ES-SV'>2.       Las variables de tipos de cadenas deben ser filtrados, y tipos numéricos deben ser evaluados para verificar que son válidos.

<= span lang=3DES-SV style=3D'font-size:10.0pt;line-height:115%;color:black;mso-a= nsi-language: ES-SV'>3.       El uso de procedimientos almacenados puede simplificar consultas complejas y permitir la configuración de con= trol de acceso más estricto.

<= span lang=3DES-SV style=3D'font-size:10.0pt;line-height:115%;color:black;mso-a= nsi-language: ES-SV'>4.       Configuración de los controles de acceso = de base de datos puede limitar el impacto de las vulnerabilidades explotadas= .

L= ocal Filesystem Paths

Found

1.        Cuando se obtenga una salida de error que contie= ne información confidencial, como rutas de sistema absolutos no debería ser enviada a los clientes remotos en servidores de producción.

2.        Esta salida debe ser enviada a otra log de salida, como un registro de errores.

Fr= om Password Field with Autocomplete Enable<= o:p>

1.        El valor del atributo de autocomplete en el formulario debe tener el valor "OFF".

2.        No generar autocomplete.

P= age Fingerprint Differential Detected

1.=         Para= evitar este tipo de vulnerabilidad, el desarrollador debe predeterminar el camin= o de cualquier recurso del sistema de archivos que tiene una trayectoria compu= esta de entrada suministrada externamente y luego realizar una comprobaci&oacu= te;n de autorización previa para el acceso.

2.=         Cuan= do se desarrolle en PHP, Perl y Python se debe utilizar la función realpath (), cuando se utilice aplicaciones ASP.NET= se debe utilizar la función GetFullPath (= ), cuando se utiliza en código Java se utilizar la función getCanonicalPath () estas funciones devuelven la ru= ta predeterminada así se evita este tipo de vulnerabilidad.

3.=         Prot= ección adicional contra el acceso no autorizado al sistema de ficheros de recurs= os se puede obtener mediante el uso de chroot ()= o mecanismos similares para limitar el acceso del sistema de archivos para = el proceso de servidor de aplicaciones web y http, aunque esto puede ser difícil de manejar.

Sh= ell Injection

1.=         Los desarrolladores deben examinar el código correspondiente a la página en detalle para determinar si existe la vulnerabilidad.

2.=         La ejecución de comandos de sistema a través de un intérprete de comandos, como por ejemplo con el system (), debe ser evitado.

3.=         El desarrollador debe validar las entradas antes de que se pasa al intérprete.

H= TTP Trace Support Detected

1.=         Para= los servidores basados en Apache, la función Trac= eEnable () se puede utilizar para desactivar el soporte para HTTP TRACE.

2.=         Para= los servidores basados en IIS, la función EnableT= raceMethod () se puede utilizar para desactivar el soporte para HTTP TRACE.

Possible XML Injection<= /o:p>

1.=         Los desarrolladores deben investigar el código para verificar manualme= nte que existe una vulnerabilidad de XML injection.

2.=         Cara= cteres que se pueden interpretar como XML deben ser filtrados como por ejemplo &= gt;, <, ‘ , ”, etc.

C= ross Site Scripting

1.=         No c= onfiar nunca en datos que se obtenga de los usuarios o de cualquier fuente de da= tos externa.

2.=         Filt= rar datos poco confiables que son generados por el cliente.=

2.=         Esta= regla es la única que tenemos que seguir para prevenir los ataques XSS. = Para evitar ataques XSS, se debe llevar a cabo la validación de datos, = el saneamiento y escapar lo que se va a mostrar

=  

=  

Aplicació= n del modelo.  Al aplicar el modelo es necesario determina= r el efecto sobre las vulnerabilidades, por lo que se detalla a continuaci&oacut= e;n las vulnerabilidades de los servicios web activos.  En la Tabla 6., se observa las vulnerabilidades encontradas en el servicio web después de aplicar la propuesta de solución para la reducción de riesgos de segurid= ad informática.  A pesar d= e la sugerencia de aplicar en su totalidad la propuesta de solución, se p= uede observar que disminuyeron casi toda la vulnerabilidad alta excepto Cleartext Password over HTTP debido a una decisión propia del administrador, pero en las de bajo impacto hubo una disminución cons= iderable.

 

Tabla 6.&n= bsp; Total de vulnerabilidades

 

Nombre

 

Grado

 

Posgrados=

 

Ingreso de Calificaciones=

Eva-Docente

 

Campus Virtual

 

Bienestar

 

Recursos

 

Total

No.

No.

No.

No.

No.

No.

No.

Clear Password over HTTP

Alto

1

0

0

0

0

1

2

Cross Site Scripting=

Alto

0

1

0

0

0

0

1

Page Fingerprint Differential Detected

Alto

1

0

0

0

0

2

3

Shell Injection

Alto

0

0

2

22

0

0

24

SQL Injection=

Alto

1

2

2

13<= /o:p>

0

0

18<= /o:p>

HTTP Trace Support <= span class=3DSpellE>Detected

Medio

0

0

0

0

0

0

0

Local Filesystem Paths Found =

Medio

0

1

12<= /o:p>

4

0

0

17<= /o:p>

PHP Error Detected

Medio

0

0

9

0

0

9

Possible Source Code Disclosure

Medio

0

0

0

3

0

0

3

Possible XML Injection=

Medio

0

0

0

0

0

0

0

URL Injection=

Medio

0

1

0

0

0

0

1

ASP/ASPX Error Detected

Bajo

0

0

0

0

0

0

0

Directory<= span lang=3DES-SV style=3D'font-size:9.0pt;line-height:115%;color:black;mso-an= si-language: ES-SV'> Listing Detected=

Bajo

8

0

2

52<= /o:p>

0

3

65<= /o:p>

From Password Field with Autocomplete Enabled

Bajo

0

0

0

0

0

0

0

Total

 

11<= /o:p>

5

27<= /o:p>

94<= /o:p>

0

6

143=

En la Tabla 7., se observa las vulnerabilidades encon= tradas en los servicio web, antes y  después de aplicar la propuesta de solución para la reducción de riesgos de segurid= ad informática.  Por lo qu= e se visualiza que el administrador consideró de relevancia mitigar la vu= lnerabilidad de.=

=  

Tabla 7.  Total de vulnerabilidades

=  

Total, de vulnerabilidades

Total

%

Antes=

1178

100%

Despu&= eacute;s

143=

12.13%

Eliminadas

1035<= /p>

87.87%

=  

 

Identificaci&oac= ute;n de Impactos. Com= o resultado del análisis en la Tabla 8., indica las dimensiones con sus criterio= s de valoración del impacto del análisis, para conocer el da&ntild= e;o producido sobre los activos del dominio como consecuencia de la materialización de las amenazas.

 

Tabla 8.&n= bsp; Identificación de Impactos

 

Dimensión

Valoración

Disponibilidad

Alto

Integridad

Alto

Autenticidad

Alto

Confidencialidad

Medio

 

 

Identificaci&oac= ute;n del Riego.  La Tabla 9., muestra la escala de dañ= ;o para identificar los riesgos como resultado del análisis de los activos, amenazas, salvaguardas existentes y la identificación de vulnerabilidades e impactos, como se puede observar el mayor riesgo se presentaría en la disponibilidad de los activos.

 

Tabla 9: Identificación de Riesgos

=  

Activos

Dimensiones

Disponibilidad

Integridad

Confidencialidad

Autenticidad

UPS

3

0

0

0

Planta de energía

4

0

0

0

Procesador 1 (Servidor 1)

5

4

2

4

Procesador 2 (Servidor 2)

5

4

2

4

Procesador 3 (Servidor 3)

4

4

2

4

Procesador 4 (Servidor 4)

4

3

2

4

Memoria 1 (Servidor 1)

5

4

3

4

Memoria 2 (Servidor 2)

5

4

3

4

Memoria 3 (Servidor 3)

5

4

3

4

Memoria 4 (Servidor 4)

5

4

3

4

Storage

5

5

2

5

Personal

3

1

3

0

 =

Conclusiones.

 

= ·      =    Del análisis realizado se identific&oacu= te; 14 tipos de vulnerabilidades en los servicios web, los tres más frecuen= tes son: SQL Injection, PHP Error Detected y Directory Listing= Detected, por lo que al plantear propuestas de mejora= para un servicio web se debe replicar la solución en los demás par= a reducirlas o eliminarlas, enfocándose principalmente desde las vulnerabilidades= de nivel alto (High) que implican un mayor riesgo e impacto para su funcionamiento.

= ·      =    Con la aplicación de MAGERIT para reducción de riesgos en servicios Web se redujo en un 87,87% las vulnerabilidades encontradas en el análisis.

= ·      =    A pesar de que existen un sin número de Metodologías se escogieron MAGERIT, debido a que es la más ut= ilizada a nivel de Latinoamérica y permite tener una referencia de trabajo estándar que facilita la gestión de riesgos de una organización, que en lo posterior ayudara a reducir el impacto de las vulnerabilidades existentes en los servicios web.

= ·      =    La herramienta VEGA permitió realizar un escaneo de vulnerabilidades de páginas web permitiendo determinar las debilidades y proponer alternativas de solución, debido a que es multiplataforma, gratuita, de código abierto y sobre todo puede ser adaptable a las necesidades del usuario u organización.

 

 

Referencias Bibliográficas

 

Aguilera, P.; Informá= tica y comunicaciones. Madrid: Editex S.A, (2010).=

= <= span lang=3DES-EC style=3D'font-family:"Times New Roman",serif;font-style:norma= l'>Castillo, J., Cisneros, S., Mendez, P., & Jác= ome, D. (2018). Modelo para la reducción de riesgos de seguridad informática en servicios web. Cumbres.

= Desogles, J. X; Ayudantes técnicos de Informática. Madrid: Editorial <= span class=3DSpellE>Mad S.L, (2010).

<= span class=3DSpellE>Erb, M.; Gestión de Riesgo en la Seguridad Informática. Obtenido de https://protejete.wordpress.com/gdr_principal/amenazas_vulnerab= ilidades/, (2014).

<= span lang=3DES-EC style=3D'font-style:normal;mso-bidi-font-style:italic'>Eterovi= c, E., y G. Pagliari; Metodología de Análi= sis de Riesgos Informáticos. Technical note, 10, (2010).

<= span lang=3DES-EC style=3D'font-style:normal;mso-bidi-font-style:italic'>Freitas= , V. D.; Análisis y evaluación del riesgo de la información: ca= so de estudio Universidad Simón Bolívar. Información T= ecnológica, Scielo, 6, 13-22 (2009).

<= span lang=3DEN-US style=3D'mso-ansi-language:EN-US;font-style:normal;mso-bidi-fo= nt-style: italic'>Khari, M., y N. Singh; Web Services Vulnerability Testing Using Open Source. International Journal of Advanced Engineering and Global Technology, 790-799 (2014).

<= span lang=3DEN-GB style=3D'mso-ansi-language:EN-GB;font-style:normal;mso-bidi-fo= nt-style: italic'>Kwan, T., y H.  Leung;= A Risk Management Methodology for Project Risk Dependencies. IEEE Transactions on Software Engineering, 635-648 IEEE. (2010).

<= span lang=3DEN-US style=3D'mso-ansi-language:EN-US;font-style:normal;mso-bidi-fo= nt-style: italic'>Kyushu, F., Y. Hori y K. Sakurai; Comparison of Risk Analysis Methods: Mehari, Magerit, NIST= 800-30 and Microsoft's Security Management Guide. Availab= ility, Reliability and Security, 2009. ARES '09, 726-731 IEEE (2009).

<= span lang=3DES-EC style=3D'font-style:normal;mso-bidi-font-style:italic'>Monteve= rde, W. A., y R. Campiolo; Estudo<= /span> e Analise de Vulnerabilidades Web. Obtenido de http://es.slideshare.net/wamverde/estudo-e-anlise-de-vulnerabilidades-web, = (2014).

<= span lang=3DES-EC style=3D'font-style:normal;mso-bidi-font-style:italic'>Reyes, = J.; MAGERIT. Obtenido de https://seguridadinformaticaufps.wikispaces.com/MAGERIT, (2015)= .

<= span class=3DSpellE>Shirey, R.; Internet Security Glossary. RFC 2828 (Informational). Obsoleted by RFC = 4949, (2015).

<= span lang=3DEN-US style=3D'mso-ansi-language:EN-US;font-style:normal;mso-bidi-fo= nt-style: italic'>Vicente, E. y A. Jimenez; Risk analysis in information systems: A fuzzification of the MAGERIT methodology. Elsevier, = 1-12 (2014)= .

<= span class=3DSpellE>Voutssas, J.; Documentary, digital and security information. Sci= ELO, 24, 7 (2010).

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[1] Universidad Técnica de Cotopaxi, diego.jacome@utc.edu.ec,= ORCID: https://orcid.org/0000-0001-7681-5386

[2] Universidad Técnica de Cotopaxi, jessica.castillo@utc.edu= .ec, ORCID: https://orcid.org/0000-0002-3120-7229

[3] Escuela Superior Politecnica de Chim= borazo, carmen.mantilla@espoch.edu.ec, ORCID: https://orcid.org/0000-0001-5422-7073

[4] Escuela Superior Politecnica de Chim= borazo, bvacab@espoch.edu.ec, ORCID: https://orcid.org/0000-0002-3622-0668

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ISSN: 2773-7330 &nb= sp;                  =             &nb= sp;            =             &nb= sp;            =     Vol. 3, 2.2, p. 66-82

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Educación        =             &nb= sp;            =             &nb= sp;            =             <= /span>     &n= bsp;            = ;            &n= bsp;            = ;            = Página 50

 

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