CVE-2025-11226:詳細資料

CVE-2025-11226

7
/
高危
0.07%V4
2025-10-01
07h26 +00:00
A03-Injection
Local
2026-06-25
16h04 +00:00
指定 CVE 通知
掌握特定 CVE 的任何變更。
管理通知

CVE 描述

Conditional processing of logback.xml configuration file, in conjuction with Spring Framework and Janino

ACE vulnerability in conditional configuration file processing by QOS.CH logback-core up to and including version 1.5.18 in Java applications, allows an attacker to execute arbitrary code by compromising an existing logback configuration file or by injecting an environment variable before program execution. A successful attack requires the presence of Janino library and Spring Framework to be present on the user's class path. In addition, the attacker must  have write access to a configuration file. Alternatively, the attacker could inject a malicious environment variable pointing to a malicious configuration file. In both cases, the attack requires existing privilege.

CVE 解決方案

Remove Janino from the Java classpath or update to logack version 1.5.19 or later.

CVE 資訊

相關弱點

CWE-ID 弱點名稱 來源
CWE-20 Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.

指標

指標 評分 嚴重程度 CVSS 向量 來源
V4.0 7 HIGH CVSS:4.0/AV:L/AC:L/AT:P/PR:H/UI:N/VC:H/VI:H/VA:N/SC:L/SI:L/SA:N/S:P/AU:N/RE:M/U:Green

Base: Exploitabilty Metrics

The Exploitability metrics reflect the characteristics of the “thing that is vulnerable”, which we refer to formally as the vulnerable system.

Attack Vector

This metric reflects the context by which vulnerability exploitation is possible.

Local

The vulnerable system is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Either: the attacker exploits the vulnerability by accessing the target system locally (e.g., keyboard, console), or through terminal emulation (e.g., SSH); or the attacker relies on User Interaction by another person to perform actions required to exploit the vulnerability (e.g., using social engineering techniques to trick a legitimate user into opening a malicious document).

Attack Complexity

This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit.

Low

The attacker must take no measurable action to exploit the vulnerability. The attack requires no target-specific circumvention to exploit the vulnerability. An attacker can expect repeatable success against the vulnerable system.

Attack Requirements

This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack.

Present

The successful attack depends on the presence of specific deployment and execution conditions of the vulnerable system that enable the attack. These include: A race condition must be won to successfully exploit the vulnerability. The successfulness of the attack is conditioned on execution conditions that are not under full control of the attacker. The attack may need to be launched multiple times against a single target before being successful. Network injection. The attacker must inject themselves into the logical network path between the target and the resource requested by the victim (e.g. vulnerabilities requiring an on-path attacker).

Privileges Required

This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability.

High

The attacker requires privileges that provide significant (e.g., administrative) control over the vulnerable system allowing full access to the vulnerable system’s settings and files.

User Interaction

This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system.

None

The vulnerable system can be exploited without interaction from any human user, other than the attacker. Examples include: a remote attacker is able to send packets to a target system a locally authenticated attacker executes code to elevate privileges

Base: Impact Metrics

The Impact metrics capture the effects of a successfully exploited vulnerability. Analysts should constrain impacts to a reasonable, final outcome which they are confident an attacker is able to achieve.

Confidentiality Impact

This metric measures the impact to the confidentiality of the information managed by the system due to a successfully exploited vulnerability.

High

There is a total loss of confidentiality, resulting in all information within the Vulnerable System 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.

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 Vulnerable System. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to the Vulnerable System.

Availability Impact

This metric measures the impact to the availability of the impacted system resulting from a successfully exploited vulnerability.

None

There is no impact to availability within the Vulnerable System.

Sub Confidentiality Impact

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 limited. The information disclosure does not cause a direct, serious loss to the Subsequent System.

Sub Integrity Impact

Low

Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact to the Subsequent System.

Sub Availability Impact

None

There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.

Threat Metrics

The Threat metrics measure the current state of exploit techniques or code availability for a vulnerability.

Environmental Metrics

These metrics enable the consumer analyst to customize the resulting score depending on the importance of the affected IT asset to a user’s organization, measured in terms of complementary/alternative security controls in place, Confidentiality, Integrity, and Availability. The metrics are the modified equivalent of Base metrics and are assigned values based on the system placement within organizational infrastructure.

Supplemental Metrics

Supplemental metric group provides new metrics that describe and measure additional extrinsic attributes of a vulnerability. While the assessment of Supplemental metrics is provisioned by the provider, the usage and response plan of each metric within the Supplemental metric group is determined by the consumer.

Automatable

The “Automatable” metric captures the answer to the question ”Can an attacker automate exploitation events for this vulnerability across multiple targets?” based on steps 1-4 of the kill chain2 [Hutchins et al., 2011]. These steps are reconnaissance, weaponization, delivery, and exploitation. If evaluated, the metric can take the values no or yes.

No

Attackers cannot reliably automate all 4 steps of the kill chain for this vulnerability for some reason. These steps are reconnaissance, weaponization, delivery, and exploitation.

Safety

Like all Supplemental Metrics, providing a value for Safety is completely optional. Suppliers and vendors (AKA: scoring providers) may or may not provide Safety as a Supplemental Metric as they see fit.

Present

Consequences of the vulnerability meet definition of IEC 61508 consequence categories of 'marginal', 'critical', or 'catastrophic'.

Vulnerability Response Effort

The intention of the Vulnerability Response Effort metric is to provide supplemental information on how difficult it is for consumers to provide an initial response to the impact of vulnerabilities for deployed products and services in their infrastructure.

Moderate

The actions required to respond to a vulnerability require some effort on behalf of the consumer and could cause minimal service impact to implement. Examples include: simple remote update, disabling of a subsystem, or a low-touch software upgrade such as a driver update.

Provider Urgency

Many vendors currently provide supplemental severity ratings to consumers via product security advisories.

Green

Provider has assessed the impact of this vulnerability as having a reduced urgency.

EPSS

EPSS 是一種預測漏洞被利用可能性的評分模型。

EPSS 評分

EPSS 模型產生介於 0 到 1(0% 到 100%)之間的概率分數。分數越高,漏洞被利用的概率越大。

EPSS 百分位數

百分位數用於根據 EPSS 分數對 CVE 進行排名。例如,EPSS 評分在第 95 百分位的 CVE 比 95% 的其他 CVE 更有可能被利用。因此,百分位數用於比較某 CVE 的 EPSS 分數與其他 CVE 的相對位置。

參考資料