CVE-2024-22169 : 詳細

CVE-2024-22169

7.1
/
高
0.1%V4
2024-08-02
18h31 +00:00
Code Injection
A03-Injection
Local
2024-08-05
18h55 +00:00
特定のCVEの通知
特定のCVEの変更情報をいち早くお届けします。
通知を管理する

CVE の説明

Misconfiguration in node.js causing a code execution in WD Discovery

WD Discovery versions prior to 5.0.589 contain a misconfiguration in the Node.js environment settings that could allow code execution by utilizing the 'ELECTRON_RUN_AS_NODE' environment variable. Any malicious application operating with standard user permissions can exploit this vulnerability, enabling code execution within WD Discovery application's context. WD Discovery version 5.0.589 addresses this issue by disabling certain features and fuses in Electron. The attack vector for this issue requires the victim to have the WD Discovery app installed on their device.

CVE の解決策

Users can download the latest version from the WD Discovery Downloads page or by following the instructions on the WD Discovery: Online User Guide https://support-en.wd.com/app/answers/detailweb/a_id/20465

CVE の情報

関連する弱点

CWE-ID 弱点名 出典
CWE-94 Improper Control of Generation of Code
The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

メトリクス

メトリクス スコア 深刻度 CVSS ベクター 出典
V4.0 7.1 HIGH CVSS:4.0/AV:L/AC:L/AT:P/PR:N/UI:P/VC:N/VI:H/VA:N/SC:H/SI:H/SA:H

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.

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.

Passive

Successful exploitation of this vulnerability requires limited interaction by the targeted user with the vulnerable system and the attacker’s payload. These interactions would be considered involuntary and do not require that the user actively subvert protections built into the vulnerable system. Examples include: utilizing a website that has been modified to display malicious content when the page is rendered (most stored XSS or CSRF) running an application that calls a malicious binary that has been planted on the system using an application which generates traffic over an untrusted or compromised network (vulnerabilities requiring an on-path attacker)

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.

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

High

There is a total loss of confidentiality, resulting in all resources within the Subsequent 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.

Sub Integrity Impact

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

Sub Availability Impact

High

There is a total loss of availability, resulting in the attacker being able to fully deny access to resources in the Subsequent System; 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 Subsequent System (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).

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は脆弱性が悪用される可能性を予測するスコアリングモデルです。

EPSSスコア

EPSSモデルは0から1(0〜100%)の確率スコアを算出します。スコアが高いほど、脆弱性が悪用される可能性が高いことを示します。

EPSSパーセンタイル

パーセンタイルはCVEをEPSSスコアで順位付けするために使用されます。例えば、EPSSスコアで95パーセンタイルにあるCVEは、他の95%のCVEよりも悪用される可能性が高いことを意味します。パーセンタイルはCVEのEPSSスコアを他のCVEと比較するために使用されます。

参考資料