CVE-2025-24362 : 상세 정보

CVE-2025-24362

7.1
/
높음
0.29%V4
2025-01-24
18h04 +00:00
A09-Security Log./Monit. Failures
Network
2025-03-31
13h47 +00:00
CVE.org
NVD
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CVE 설명

CodeQL GitHub Action failed workflow writes GitHub PAT to debug artifacts

In some circumstances, debug artifacts uploaded by the CodeQL Action after a failed code scanning workflow run may contain the environment variables from the workflow run, including any secrets that were exposed as environment variables to the workflow. Users with read access to the repository would be able to access this artifact, containing any secrets from the environment. This vulnerability is patched in CodeQL Action version 3.28.3 or later, or CodeQL CLI version 2.20.3 or later. For some affected workflow runs, the exposed environment variables in the debug artifacts included a valid `GITHUB_TOKEN` for the workflow run, which has access to the repository in which the workflow ran, and all the permissions specified in the workflow or job. The `GITHUB_TOKEN` is valid until the job completes or 24 hours has elapsed, whichever comes first. Environment variables are exposed only from workflow runs that satisfy all of the following conditions: - Code scanning workflow configured to scan the Java/Kotlin languages. - Running in a repository containing Kotlin source code. - Running with debug artifacts enabled. - Using CodeQL Action versions <= 3.28.2, and CodeQL CLI versions >= 2.9.2 (May 2022) and <= 2.20.2. - The workflow run fails before the CodeQL database is finalized within the `github/codeql-action/analyze` step. - Running in any GitHub environment: GitHub.com, GitHub Enterprise Cloud, and GitHub Enterprise Server. Note: artifacts are only accessible to users within the same GitHub environment with access to the scanned repo. The `GITHUB_TOKEN` exposed in this way would only have been valid for workflow runs that satisfy all of the following conditions, in addition to the conditions above: - Using CodeQL Action versions >= 3.26.11 (October 2024) and <= 3.28.2, or >= 2.26.11 and < 3. - Running in GitHub.com or GitHub Enterprise Cloud only (not valid on GitHub Enterprise Server). In rare cases during advanced setup, logging of environment variables may also occur during database creation of Java, Swift, and C/C++. Please read the corresponding CodeQL CLI advisory GHSA-gqh3-9prg-j95m for more details. In CodeQL CLI versions >= 2.9.2 and <= 2.20.2, the CodeQL Kotlin extractor logs all environment variables by default into an intermediate file during the process of creating a CodeQL database for Kotlin code. This is a part of the CodeQL CLI and is invoked by the CodeQL Action for analyzing Kotlin repositories. On Actions, the environment variables logged include GITHUB_TOKEN, which grants permissions to the repository being scanned. The intermediate file containing environment variables is deleted when finalizing the database, so it is not included in a successfully created database. It is, however, included in the debug artifact that is uploaded on a failed analysis run if the CodeQL Action was invoked in debug mode. Therefore, under these specific circumstances (incomplete database creation using the CodeQL Action in debug mode) an attacker with access to the debug artifact would gain unauthorized access to repository secrets from the environment, including both the `GITHUB_TOKEN` and any user-configured secrets made available via environment variables. The impact of the `GITHUB_TOKEN` leaked in this environment is limited: - For workflows on GitHub.com and GitHub Enterprise Cloud using CodeQL Action versions >= 3.26.11 and <= 3.28.2, or >= 2.26.11 and < 3, which in turn use the `actions/artifacts v4` library, the debug artifact is uploaded before the workflow job completes. During this time the `GITHUB_TOKEN` is still valid, providing an opportunity for attackers to gain access to the repository. - For all other workflows, the debug artifact is uploaded after the workflow job completes, at which point the leaked `GITHUB_TOKEN` has been revoked and cannot be used to access the repository.

CVE 정보

관련 약점

CWE-ID 약점 이름 출처
CWE-532 Insertion of Sensitive Information into Log File
The product writes sensitive information to a log file.

메트릭

메트릭 점수 심각도 CVSS 벡터 출처
V4.0 7.1 HIGH CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/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.

Low

The attacker requires privileges that provide basic capabilities that are typically limited to settings and resources owned by a single low-privileged user. Alternatively, an attacker with Low privileges has the ability to access only non-sensitive resources.

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.

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

Negligible

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

EPSS는 취약점이 악용될 가능성을 예측하는 점수 모델입니다.

EPSS 점수

EPSS 모델은 0과 1(0~100%) 사이의 확률 점수를 생성합니다. 점수가 높을수록 취약점이 악용될 가능성이 높습니다.

EPSS 백분위수

백분위수는 EPSS 점수에 따라 CVE의 순위를 매기는 데 사용됩니다. 예를 들어 EPSS 점수 기준 95번째 백분위수의 CVE는 다른 CVE의 95%보다 악용될 가능성이 높습니다.
EPSS First.org

참고 자료

CVE Find에 제시된 정보는 엄선된 여러 참고 소스에서 가져옵니다. CVE 데이터는 MITRE Corporation과 국가 취약점 데이터베이스(NVD)에서 제공됩니다. KEV 카탈로그는 CISA에서 가져오며, EPSS 점수는 FIRST.org에서 제공됩니다. CWE 및 CAPEC 데이터는 MITRE Corporation에서 관리하며, CPE 정보는 NVD에서 제공됩니다.