CVE-2025-64502:詳細資料

CVE-2025-64502

6.9
/
中危
0.12%V4
2025-11-10
21h40 +00:00
A01-Broken Access Control
Network
2025-11-12
20h14 +00:00
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CVE 描述

Parse Server allows public `explain` queries which may expose sensitive database performance information and schema details

Parse Server is an open source backend that can be deployed to any infrastructure that can run Node.js. The MongoDB `explain()` method provides detailed information about query execution plans, including index usage, collection scanning behavior, and performance metrics. Prior to version 8.5.0-alpha.5, Parse Server permits any client to execute explain queries without requiring the master key. This exposes database schema structure and field names, index configurations and query optimization details, query execution statistics and performance metrics, and potential attack vectors for database performance exploitation. In version 8.5.0-alpha.5, a new `databaseOptions.allowPublicExplain` configuration option has been introduced that allows to restrict `explain` queries to the master key. The option defaults to `true` for now to avoid a breaking change in production systems that depends on public `explain` availability. In addition, a security warning is logged when the option is not explicitly set, or set to `true`. In a future major release of Parse Server, the default will change to `false`. As a workaround, implement middleware to block explain queries from non-master-key requests, or monitor and alert on explain query usage in production environments.

CVE 資訊

相關弱點

CWE-ID 弱點名稱 來源
CWE-201 Insertion of Sensitive Information Into Sent Data
The code transmits data to another actor, but a portion of the data includes sensitive information that should not be accessible to that actor.

指標

指標 評分 嚴重程度 CVSS 向量 來源
V4.0 6.9 MEDIUM CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:N/SC:L/SI:N/SA:N

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.

Network

The vulnerable system is bound to the network stack and the set of possible attackers extends beyond the other options listed below, up to and including the entire Internet. Such a vulnerability is often termed “remotely exploitable” and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).

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.

None

The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.

Privileges Required

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

None

The attacker is unauthenticated prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.

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.

None

There is no loss of confidentiality within the Vulnerable System.

Integrity Impact

This metric measures the impact to integrity of a successfully exploited vulnerability.

None

There is no loss of integrity within 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

None

There is no loss of integrity within the Subsequent System or all integrity impact is constrained to the Vulnerable 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.

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