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.
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Recherche de CVE id, CWE id, CAPEC id, vendeur ou mots clés dans les CVE
An issue was discovered in Liferay Portal CE 7.1.2 GA3. An attacker can use Liferay's Groovy script console to execute OS commands. Commands can be executed via a [command].execute() call, as demonstrated by "def cmd =" in the ServerAdminPortlet_script value to group/control_panel/manage. Valid credentials for an application administrator user account are required. NOTE: The developer disputes this as a vulnerability since it is a feature for administrators to run groovy scripts and therefore not a design flaw
Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection') The product constructs all or part of an OS command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended OS command when it is sent to a downstream component.
Métriques
Métriques
Score
Gravité
CVSS Vecteur
Source
V3.0
7.2
HIGH
CVSS:3.0/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H
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.
High
The attacker is authorized with (i.e. requires) privileges that provide significant (e.g. administrative) control over the vulnerable component that could affect component-wide settings and files.
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.
High
There is total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact. For example, an attacker steals the administrator's password, or private encryption keys of a web server.
Integrity Impact
This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information.
High
There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the impacted component.
Availability Impact
This metric measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability.
High
There is total loss of availability, resulting in the attacker being able to fully deny access to resources in the impacted component; this loss is either sustained (while the attacker continues to deliver the attack) or persistent (the condition persists even after the attack has completed). Alternatively, the attacker has the ability to deny some availability, but the loss of availability presents a direct, serious consequence to the impacted component (e.g., the attacker cannot disrupt existing connections, but can prevent new connections; the attacker can repeatedly exploit a vulnerability that, in each instance of a successful attack, leaks a only small amount of memory, but after repeated exploitation causes a service to become completely unavailable).
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
9
AV:N/AC:L/Au:S/C:C/I:C/A:C
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)
2021-04-18
3.63%
–
–
–
–
2021-09-05
–
3.63%
–
–
–
2022-01-09
–
3.63%
–
–
–
2022-02-06
–
–
26.47%
–
–
2022-04-03
–
–
7.31%
–
–
2023-02-26
–
–
7.31%
–
–
2023-03-12
–
–
–
5.88%
–
2023-09-03
–
–
–
6.15%
–
2023-10-22
–
–
–
5.88%
–
2023-12-24
–
–
–
5.72%
–
2024-02-11
–
–
–
5.29%
–
2024-03-17
–
–
–
5.19%
–
2024-06-02
–
–
–
5.32%
–
2024-06-09
–
–
–
4.49%
–
2024-06-23
–
–
–
4.49%
–
2024-08-04
–
–
–
4.49%
–
2024-08-11
–
–
–
4.49%
–
2024-09-15
–
–
–
4.43%
–
2024-12-22
–
–
–
4.25%
–
2025-02-09
–
–
–
3.81%
–
2025-01-19
–
–
–
4.25%
–
2025-02-16
–
–
–
3.81%
–
2025-03-18
–
–
–
–
45.82%
2025-03-18
–
–
–
–
45.82,%
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.
